diff --git a/modules/embeddings.js b/modules/embeddings.js
new file mode 100644
index 0000000000000000000000000000000000000000..956e6679ffc3b04bdbcbe81ac12737a91d3cacf7
--- /dev/null
+++ b/modules/embeddings.js
@@ -0,0 +1,33 @@
+import { convertToFloat32 } from './faqData.js';
+
+
+/** import embeddings from JSON files in file system */
+async function loadJsonData(filePath) {
+  try {
+    const response = await fetch(filePath);
+    if (!response.ok) return null;
+    const jsonData = JSON.parse(await response.text());
+    return convertToFloat32(jsonData);
+  } catch (err) {
+    return null;
+  }
+}
+
+/** check if embeddings are presenet in local storage. If not, try getting them from JSON file */
+export async function loadEmbedding(key, filePath) {
+  const retrievedEmb = JSON.parse(localStorage.getItem(key));
+  if (retrievedEmb && Object.keys(retrievedEmb).length > 0) {
+    return convertToFloat32(retrievedEmb);
+  } else {
+    return await loadJsonData(filePath) || {};
+  }
+}
+
+/** get rid of old embeddings */
+export function removeOutdatedEntries(stack, validKeys) {
+  Object.keys(stack).forEach(key => {
+    if (!validKeys.has(key)) {
+      delete stack[key];
+    }
+  });
+}
diff --git a/modules/faqData.js b/modules/faqData.js
new file mode 100644
index 0000000000000000000000000000000000000000..4b1df7693427a82fb62cd5ee29ce0e5d19fd229d
--- /dev/null
+++ b/modules/faqData.js
@@ -0,0 +1,49 @@
+import { tokenizeText } from './semanticSearch.js';
+
+
+/** import the questions, answers and panel Ids from HHU FAQ site */
+/** panel Ids needed for locating and highlighting chat response */
+export async function extractFAQfromHTML(url) {
+  
+  const response = await fetch(url);
+  const htmlText = await response.text();
+  const parser = new DOMParser();
+  const doc = parser.parseFromString(htmlText, "text/html");
+
+  const result = [];
+  const akkordeonGroup = doc.querySelectorAll('.panel-group');
+
+  akkordeonGroup.forEach(group => {
+    const akkordeonId = group.id;
+    const panels = group.querySelectorAll('.panel');
+    panels.forEach(panel => {
+      const questionButton = panel.querySelector('button');
+      const panelBody = panel.querySelector('.panel-body');
+      if (questionButton && panelBody) {
+        const buttonId = questionButton.id;
+        /** extracting the relevant parts */
+        const questionText = questionButton.querySelector('.text-box')?.textContent.trim();
+        const answerText = panelBody.querySelector('.ce-bodytext')?.textContent.trim() || "";
+
+        result.push({
+          akkordeonId,
+          buttonId,
+          question: questionText,
+          answer: answerText,
+          qPlusA: questionText + " " + answerText,
+          tokens: tokenizeText(answerText)
+        });
+      }
+    });
+  });
+  return result;
+}
+
+/** conversion is needed for storage of embeddings */
+export function convertToFloat32(inputEmbeddings) {
+  const convertedEmbeddings = {};
+  for (const [key, value] of Object.entries(inputEmbeddings)) {
+    convertedEmbeddings[key] = new Float32Array(Object.values(value));
+  }
+  return convertedEmbeddings;
+}
\ No newline at end of file
diff --git a/modules/feedback.js b/modules/feedback.js
new file mode 100644
index 0000000000000000000000000000000000000000..9ec47b47fa039820e8d96cbb4ccbc06709fbb114
--- /dev/null
+++ b/modules/feedback.js
@@ -0,0 +1,42 @@
+
+
+
+/** open mail client of user with prewritten message and stats */
+export function submitFeedback(query, bestToken, feedback) {
+
+  /** temporary mail adress, adjust if needed */
+  const feedbackAdress = 'huepfen-richtlinie.7r@icloud.com';
+  const timestamp = new Date().toISOString();
+  let subject = '';
+  let message = '';
+
+
+  
+  if (feedback === 'up') {
+    subject = 'Positive Feedback: FAQ Search Feature';
+    message = `Hello,
+    \nI used your FAQ search feature and was pleased with the result. Details below:
+    \nQuery: ${query}\nBest Token: ${bestToken}\nFeedback: ${feedback}\nTimestamp: ${timestamp}
+    \nI also have some additional suggestions: 
+    \nKeep it up!
+    \nBest regards`;
+
+  } else if (feedback === 'down') {
+    subject = 'Negative Feedback: FAQ Search Feature';
+    message = `Hello,
+    \nI tried used FAQ search feature, and unfortunately, I was not satisfied with this result. Detail below:
+    \nQuery: ${query}\nBest Token: ${bestToken}\nFeedback: ${feedback}\nTimestamp: ${timestamp}
+    \nI also have some additional suggestions: 
+    \nI hope this feedback lets you improve the experience.
+    \nBest regards`;
+  }
+
+  
+  const newSubject = encodeURIComponent(subject);
+  const body = encodeURIComponent(message);
+  const mailtoLink = `mailto:${feedbackAdress}?subject=${newSubject}&body=${body}`;
+
+  window.location.href = mailtoLink;
+}
+
+
diff --git a/modules/highlightText.js b/modules/highlightText.js
new file mode 100644
index 0000000000000000000000000000000000000000..2aa941ba0ffcb67ce92e379bcb24faa77df2a941
--- /dev/null
+++ b/modules/highlightText.js
@@ -0,0 +1,20 @@
+
+
+/** URL highlights stay in DOM until refresh of page; not ideal */
+/** might leave it out */
+export function highlightText(textToHighlight) {
+  const text = encodeURIComponent(textToHighlight);
+  
+  let windows = window;
+  while (windows !== windows.parent) {
+    windows = windows.parent;
+  }
+  
+  const currentUrl = windows.location.origin + windows.location.pathname + windows.location.search;
+  const newUrl = currentUrl + '#:~:text=' + text;
+  windows.location.href = newUrl;
+}
+
+
+
+
diff --git a/modules/semanticSearch.js b/modules/semanticSearch.js
new file mode 100644
index 0000000000000000000000000000000000000000..5d1fd4309708e49bb91f5f0dc93b92be6cff5702
--- /dev/null
+++ b/modules/semanticSearch.js
@@ -0,0 +1,180 @@
+import { pipeline, env } from './transformers.js';
+
+
+/** set transformers.js variables so that nothing is loaded externally */
+env.allowRemoteModels = false; 
+env.useBrowserCache = true;
+env.localModelPath = './models/';
+env.backends.onnx.wasm.wasmPaths = './wasm/'
+
+
+
+
+let embedder;
+let embeddingCache = {};
+let tokenEmbeddingCache = {};
+let queryEmbeddingCache = {};
+
+
+/** getting extraction model ready */
+export async function initializeModel() {
+
+  embedder = await pipeline(
+        'feature-extraction', 
+        'Xenova/all-MiniLM-L6-v2'
+  );
+
+}
+
+/** cosine similarity works out of the box */
+/** https://www.restack.io/p/similarity-search-answer-javascript-cosine-similarity-cat-ai */
+export function cosineSimilarity(vectorA, vectorB) {
+
+  const dotProduct = vectorA.reduce((sum, value, index) => sum + value * vectorB[index], 0);
+  const magnitudeA = Math.sqrt(vectorA.reduce((sum, value) => sum + value * value, 0));
+  const magnitudeB = Math.sqrt(vectorB.reduce((sum, value) => sum + value * value, 0));
+  return dotProduct / (magnitudeA * magnitudeB);
+
+}
+
+
+
+/** various function to calculate the right embeddings */
+/** -------------------------------------------------- */
+function roundEmbedding(embedding) {
+  return embedding.data.map(v => Number(v.toFixed(3)));
+}
+
+export async function getAndRoundEmbedding(text) {
+
+  const embedding = await embedder(text, { 
+                        pooling: 'mean', 
+                        normalize: true 
+                    });
+
+  return roundEmbedding(embedding);
+}
+
+export async function computeEmbedding(text) {
+  return getCachedEmbedding(text, embeddingCache);
+}
+
+export async function computeTokenEmbedding(text) {
+  return getCachedEmbedding(text, tokenEmbeddingCache);
+}
+
+export async function computeQueryEmbedding(text) {
+  return getCachedEmbedding(text, queryEmbeddingCache);
+}
+
+export async function calcFAQEmbeddings(textData, type) {
+  return Promise.all(textData.map(item => computeEmbedding(item[type])));
+}
+
+export async function getEmbedding(text) {
+
+  const result = await embedder(text, { 
+                    pooling: 'mean',
+                    normalize: true 
+                  });
+
+  return result.data;
+}
+/** -------------------------------------------------- */
+
+/** checking if embedding already exists, if not calulate it */
+export async function getCachedEmbedding(text, cache) {
+
+  if (cache[text]) {
+    return cache[text];
+  }
+
+  const emb = await getAndRoundEmbedding(text);
+  cache[text] = emb;
+
+  return emb;
+}
+
+export function getEmbeddingCache() {
+  return embeddingCache;
+}
+
+export function getTokenEmbeddingCache() {
+  return tokenEmbeddingCache;
+}
+
+
+export function setCaches(newEmbeddingCache, newTokenEmbeddingCache) {
+
+  embeddingCache = newEmbeddingCache;
+  tokenEmbeddingCache = newTokenEmbeddingCache;
+
+}
+
+
+/** turn a given text snippet in to tokens */
+/** this could still be optimized with more elaborate regular expessions; good for now */
+export function tokenizeText(text) {
+
+  const tokens = [];
+  const sentences = text.split(/(?<=[.!?])\s+/).filter(s => s.length > 0);
+  let buffer = "";
+  for (let i = 0; i < sentences.length; i++) {
+    buffer = buffer ? buffer + " " + sentences[i] : sentences[i];
+    if (buffer.length >= 10 || i === sentences.length - 1) {
+      tokens.push(buffer);
+      buffer = "";
+    }
+  }
+  return tokens;
+}
+
+/** getting token embeddings ready for later use in realtime search */
+export async function precalcTokenEmbeddings(textData) {
+
+  const allTokens = textData.flatMap(item => tokenizeText(item.answer));
+  const uniqueTokens = Array.from(new Set(allTokens));
+  await Promise.all(uniqueTokens.map(token => computeTokenEmbedding(token)));
+
+}
+
+
+/** give each FAQ entry a score on how similiar it is to the given query */
+/** return only the three most similiar */
+export async function semanticSearch(query, textData, faqEmbeddings, topK = 3) {
+  
+  const queryEmbedding = await computeQueryEmbedding(query);
+
+  return faqEmbeddings
+    .map((emb, index) => ({
+      question: textData[index].question,
+      answer: textData[index].answer,
+      buttonId: textData[index].buttonId,
+      akkordeonId: textData[index].akkordeonId,
+      qPlusA: textData[index].qPlusA,
+      token: textData[index].token,
+      score: cosineSimilarity(queryEmbedding, emb),
+    }))
+    .sort((a, b) => b.score - a.score)
+    .slice(0, topK);
+}
+
+
+export async function findBestToken(query, text) {
+  
+  const tokens = tokenizeText(text);
+  const queryEmbedding = await computeQueryEmbedding(query);
+  let bestToken = null;
+  let bestScore = -Infinity;
+
+  for (const token of tokens) {
+    const tokenEmb = await computeTokenEmbedding(token);
+    const score = cosineSimilarity(queryEmbedding, tokenEmb);
+    if (score > bestScore) {
+      bestScore = score;
+      bestToken = token;
+    }
+  }
+  return { bestToken };
+}
+
diff --git a/modules/transformers.js b/modules/transformers.js
new file mode 100644
index 0000000000000000000000000000000000000000..951a408172022874204cf0bfad0ab1bf9d7f8725
--- /dev/null
+++ b/modules/transformers.js
@@ -0,0 +1,107 @@
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r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){if("object"!=typeof e||null===e)return"object expected";if(null!=e.name&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(null!=e.refAttrName&&e.hasOwnProperty("refAttrName")&&!c.isString(e.refAttrName))return"refAttrName: string expected";if(null!=e.docString&&e.hasOwnProperty("docString")&&!c.isString(e.docString))return"docString: string expected";if(null!=e.type&&e.hasOwnProperty("type"))switch(e.type){default:return"type: enum value expected";case 0:case 1:case 2:case 3:case 4:case 5:case 6:case 7:case 8:case 9:case 10:}if(null!=e.f&&e.hasOwnProperty("f")&&"number"!=typeof e.f)return"f: number expected";if(null!=e.i&&e.hasOwnProperty("i")&&!(c.isInteger(e.i)||e.i&&c.isInteger(e.i.low)&&c.isInteger(e.i.high)))return"i: integer|Long expected";if(null!=e.s&&e.hasOwnProperty("s")&&!(e.s&&"number"==typeof 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8:t.type=8;break;case"TENSORS":case 9:t.type=9;break;case"GRAPHS":case 10:t.type=10}if(null!=e.f&&(t.f=Number(e.f)),null!=e.i&&(c.Long?(t.i=c.Long.fromValue(e.i)).unsigned=!1:"string"==typeof e.i?t.i=parseInt(e.i,10):"number"==typeof e.i?t.i=e.i:"object"==typeof e.i&&(t.i=new c.LongBits(e.i.low>>>0,e.i.high>>>0).toNumber())),null!=e.s&&("string"==typeof e.s?c.base64.decode(e.s,t.s=c.newBuffer(c.base64.length(e.s)),0):e.s.length&&(t.s=e.s)),null!=e.t){if("object"!=typeof e.t)throw TypeError(".onnx.AttributeProto.t: object expected");t.t=u.onnx.TensorProto.fromObject(e.t)}if(null!=e.g){if("object"!=typeof e.g)throw TypeError(".onnx.AttributeProto.g: object expected");t.g=u.onnx.GraphProto.fromObject(e.g)}if(e.floats){if(!Array.isArray(e.floats))throw TypeError(".onnx.AttributeProto.floats: array expected");t.floats=[];for(var n=0;n<e.floats.length;++n)t.floats[n]=Number(e.floats[n])}if(e.ints){if(!Array.isArray(e.ints))throw TypeError(".onnx.AttributeProto.ints: array 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TypeError(".onnx.AttributeProto.graphs: array expected");for(t.graphs=[],n=0;n<e.graphs.length;++n){if("object"!=typeof e.graphs[n])throw TypeError(".onnx.AttributeProto.graphs: object expected");t.graphs[n]=u.onnx.GraphProto.fromObject(e.graphs[n])}}return t},e.toObject=function(e,t){t||(t={});var n={};if((t.arrays||t.defaults)&&(n.floats=[],n.ints=[],n.strings=[],n.tensors=[],n.graphs=[]),t.defaults){if(n.name="",n.f=0,c.Long){var r=new c.Long(0,0,!1);n.i=t.longs===String?r.toString():t.longs===Number?r.toNumber():r}else n.i=t.longs===String?"0":0;t.bytes===String?n.s="":(n.s=[],t.bytes!==Array&&(n.s=c.newBuffer(n.s))),n.t=null,n.g=null,n.docString="",n.type=t.enums===String?"UNDEFINED":0,n.refAttrName=""}if(null!=e.name&&e.hasOwnProperty("name")&&(n.name=e.name),null!=e.f&&e.hasOwnProperty("f")&&(n.f=t.json&&!isFinite(e.f)?String(e.f):e.f),null!=e.i&&e.hasOwnProperty("i")&&("number"==typeof e.i?n.i=t.longs===String?String(e.i):e.i:n.i=t.longs===String?c.Long.prototype.toString.call(e.i):t.longs===Number?new c.LongBits(e.i.low>>>0,e.i.high>>>0).toNumber():e.i),null!=e.s&&e.hasOwnProperty("s")&&(n.s=t.bytes===String?c.base64.encode(e.s,0,e.s.length):t.bytes===Array?Array.prototype.slice.call(e.s):e.s),null!=e.t&&e.hasOwnProperty("t")&&(n.t=u.onnx.TensorProto.toObject(e.t,t)),null!=e.g&&e.hasOwnProperty("g")&&(n.g=u.onnx.GraphProto.toObject(e.g,t)),e.floats&&e.floats.length){n.floats=[];for(var o=0;o<e.floats.length;++o)n.floats[o]=t.json&&!isFinite(e.floats[o])?String(e.floats[o]):e.floats[o]}if(e.ints&&e.ints.length)for(n.ints=[],o=0;o<e.ints.length;++o)"number"==typeof e.ints[o]?n.ints[o]=t.longs===String?String(e.ints[o]):e.ints[o]:n.ints[o]=t.longs===String?c.Long.prototype.toString.call(e.ints[o]):t.longs===Number?new c.LongBits(e.ints[o].low>>>0,e.ints[o].high>>>0).toNumber():e.ints[o];if(e.strings&&e.strings.length)for(n.strings=[],o=0;o<e.strings.length;++o)n.strings[o]=t.bytes===String?c.base64.encode(e.strings[o],0,e.strings[o].length):t.bytes===Array?Array.prototype.slice.call(e.strings[o]):e.strings[o];if(e.tensors&&e.tensors.length)for(n.tensors=[],o=0;o<e.tensors.length;++o)n.tensors[o]=u.onnx.TensorProto.toObject(e.tensors[o],t);if(e.graphs&&e.graphs.length)for(n.graphs=[],o=0;o<e.graphs.length;++o)n.graphs[o]=u.onnx.GraphProto.toObject(e.graphs[o],t);return null!=e.docString&&e.hasOwnProperty("docString")&&(n.docString=e.docString),null!=e.type&&e.hasOwnProperty("type")&&(n.type=t.enums===String?u.onnx.AttributeProto.AttributeType[e.type]:e.type),null!=e.refAttrName&&e.hasOwnProperty("refAttrName")&&(n.refAttrName=e.refAttrName),n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e.AttributeType=function(){var e={},t=Object.create(e);return t[e[0]="UNDEFINED"]=0,t[e[1]="FLOAT"]=1,t[e[2]="INT"]=2,t[e[3]="STRING"]=3,t[e[4]="TENSOR"]=4,t[e[5]="GRAPH"]=5,t[e[6]="FLOATS"]=6,t[e[7]="INTS"]=7,t[e[8]="STRINGS"]=8,t[e[9]="TENSORS"]=9,t[e[10]="GRAPHS"]=10,t}(),e}(),i.ValueInfoProto=function(){function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}return e.prototype.name="",e.prototype.type=null,e.prototype.docString="",e.create=function(t){return new e(t)},e.encode=function(e,t){return t||(t=l.create()),null!=e.name&&e.hasOwnProperty("name")&&t.uint32(10).string(e.name),null!=e.type&&e.hasOwnProperty("type")&&u.onnx.TypeProto.encode(e.type,t.uint32(18).fork()).ldelim(),null!=e.docString&&e.hasOwnProperty("docString")&&t.uint32(26).string(e.docString),t},e.encodeDelimited=function(e,t){return this.encode(e,t).ldelim()},e.decode=function(e,t){e instanceof a||(e=a.create(e));for(var n=void 0===t?e.len:e.pos+t,r=new u.onnx.ValueInfoProto;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:r.name=e.string();break;case 2:r.type=u.onnx.TypeProto.decode(e,e.uint32());break;case 3:r.docString=e.string();break;default:e.skipType(7&o)}}return r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){if("object"!=typeof e||null===e)return"object expected";if(null!=e.name&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(null!=e.type&&e.hasOwnProperty("type")){var t=u.onnx.TypeProto.verify(e.type);if(t)return"type."+t}return null!=e.docString&&e.hasOwnProperty("docString")&&!c.isString(e.docString)?"docString: string expected":null},e.fromObject=function(e){if(e instanceof u.onnx.ValueInfoProto)return e;var t=new u.onnx.ValueInfoProto;if(null!=e.name&&(t.name=String(e.name)),null!=e.type){if("object"!=typeof e.type)throw TypeError(".onnx.ValueInfoProto.type: object expected");t.type=u.onnx.TypeProto.fromObject(e.type)}return null!=e.docString&&(t.docString=String(e.docString)),t},e.toObject=function(e,t){t||(t={});var n={};return t.defaults&&(n.name="",n.type=null,n.docString=""),null!=e.name&&e.hasOwnProperty("name")&&(n.name=e.name),null!=e.type&&e.hasOwnProperty("type")&&(n.type=u.onnx.TypeProto.toObject(e.type,t)),null!=e.docString&&e.hasOwnProperty("docString")&&(n.docString=e.docString),n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),i.NodeProto=function(){function e(e){if(this.input=[],this.output=[],this.attribute=[],e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}return e.prototype.input=c.emptyArray,e.prototype.output=c.emptyArray,e.prototype.name="",e.prototype.opType="",e.prototype.domain="",e.prototype.attribute=c.emptyArray,e.prototype.docString="",e.create=function(t){return new e(t)},e.encode=function(e,t){if(t||(t=l.create()),null!=e.input&&e.input.length)for(var n=0;n<e.input.length;++n)t.uint32(10).string(e.input[n]);if(null!=e.output&&e.output.length)for(n=0;n<e.output.length;++n)t.uint32(18).string(e.output[n]);if(null!=e.name&&e.hasOwnProperty("name")&&t.uint32(26).string(e.name),null!=e.opType&&e.hasOwnProperty("opType")&&t.uint32(34).string(e.opType),null!=e.attribute&&e.attribute.length)for(n=0;n<e.attribute.length;++n)u.onnx.AttributeProto.encode(e.attribute[n],t.uint32(42).fork()).ldelim();return null!=e.docString&&e.hasOwnProperty("docString")&&t.uint32(50).string(e.docString),null!=e.domain&&e.hasOwnProperty("domain")&&t.uint32(58).string(e.domain),t},e.encodeDelimited=function(e,t){return this.encode(e,t).ldelim()},e.decode=function(e,t){e instanceof a||(e=a.create(e));for(var n=void 0===t?e.len:e.pos+t,r=new u.onnx.NodeProto;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:r.input&&r.input.length||(r.input=[]),r.input.push(e.string());break;case 2:r.output&&r.output.length||(r.output=[]),r.output.push(e.string());break;case 3:r.name=e.string();break;case 4:r.opType=e.string();break;case 7:r.domain=e.string();break;case 5:r.attribute&&r.attribute.length||(r.attribute=[]),r.attribute.push(u.onnx.AttributeProto.decode(e,e.uint32()));break;case 6:r.docString=e.string();break;default:e.skipType(7&o)}}return r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){if("object"!=typeof e||null===e)return"object expected";if(null!=e.input&&e.hasOwnProperty("input")){if(!Array.isArray(e.input))return"input: array expected";for(var t=0;t<e.input.length;++t)if(!c.isString(e.input[t]))return"input: string[] expected"}if(null!=e.output&&e.hasOwnProperty("output")){if(!Array.isArray(e.output))return"output: array expected";for(t=0;t<e.output.length;++t)if(!c.isString(e.output[t]))return"output: string[] expected"}if(null!=e.name&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(null!=e.opType&&e.hasOwnProperty("opType")&&!c.isString(e.opType))return"opType: string expected";if(null!=e.domain&&e.hasOwnProperty("domain")&&!c.isString(e.domain))return"domain: string expected";if(null!=e.attribute&&e.hasOwnProperty("attribute")){if(!Array.isArray(e.attribute))return"attribute: array expected";for(t=0;t<e.attribute.length;++t){var n=u.onnx.AttributeProto.verify(e.attribute[t]);if(n)return"attribute."+n}}return null!=e.docString&&e.hasOwnProperty("docString")&&!c.isString(e.docString)?"docString: string expected":null},e.fromObject=function(e){if(e instanceof u.onnx.NodeProto)return e;var t=new u.onnx.NodeProto;if(e.input){if(!Array.isArray(e.input))throw TypeError(".onnx.NodeProto.input: array expected");t.input=[];for(var n=0;n<e.input.length;++n)t.input[n]=String(e.input[n])}if(e.output){if(!Array.isArray(e.output))throw TypeError(".onnx.NodeProto.output: array expected");for(t.output=[],n=0;n<e.output.length;++n)t.output[n]=String(e.output[n])}if(null!=e.name&&(t.name=String(e.name)),null!=e.opType&&(t.opType=String(e.opType)),null!=e.domain&&(t.domain=String(e.domain)),e.attribute){if(!Array.isArray(e.attribute))throw TypeError(".onnx.NodeProto.attribute: array expected");for(t.attribute=[],n=0;n<e.attribute.length;++n){if("object"!=typeof e.attribute[n])throw TypeError(".onnx.NodeProto.attribute: object expected");t.attribute[n]=u.onnx.AttributeProto.fromObject(e.attribute[n])}}return null!=e.docString&&(t.docString=String(e.docString)),t},e.toObject=function(e,t){t||(t={});var n={};if((t.arrays||t.defaults)&&(n.input=[],n.output=[],n.attribute=[]),t.defaults&&(n.name="",n.opType="",n.docString="",n.domain=""),e.input&&e.input.length){n.input=[];for(var r=0;r<e.input.length;++r)n.input[r]=e.input[r]}if(e.output&&e.output.length)for(n.output=[],r=0;r<e.output.length;++r)n.output[r]=e.output[r];if(null!=e.name&&e.hasOwnProperty("name")&&(n.name=e.name),null!=e.opType&&e.hasOwnProperty("opType")&&(n.opType=e.opType),e.attribute&&e.attribute.length)for(n.attribute=[],r=0;r<e.attribute.length;++r)n.attribute[r]=u.onnx.AttributeProto.toObject(e.attribute[r],t);return null!=e.docString&&e.hasOwnProperty("docString")&&(n.docString=e.docString),null!=e.domain&&e.hasOwnProperty("domain")&&(n.domain=e.domain),n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),i.ModelProto=function(){function e(e){if(this.opsetImport=[],this.metadataProps=[],e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}return e.prototype.irVersion=c.Long?c.Long.fromBits(0,0,!1):0,e.prototype.opsetImport=c.emptyArray,e.prototype.producerName="",e.prototype.producerVersion="",e.prototype.domain="",e.prototype.modelVersion=c.Long?c.Long.fromBits(0,0,!1):0,e.prototype.docString="",e.prototype.graph=null,e.prototype.metadataProps=c.emptyArray,e.create=function(t){return new e(t)},e.encode=function(e,t){if(t||(t=l.create()),null!=e.irVersion&&e.hasOwnProperty("irVersion")&&t.uint32(8).int64(e.irVersion),null!=e.producerName&&e.hasOwnProperty("producerName")&&t.uint32(18).string(e.producerName),null!=e.producerVersion&&e.hasOwnProperty("producerVersion")&&t.uint32(26).string(e.producerVersion),null!=e.domain&&e.hasOwnProperty("domain")&&t.uint32(34).string(e.domain),null!=e.modelVersion&&e.hasOwnProperty("modelVersion")&&t.uint32(40).int64(e.modelVersion),null!=e.docString&&e.hasOwnProperty("docString")&&t.uint32(50).string(e.docString),null!=e.graph&&e.hasOwnProperty("graph")&&u.onnx.GraphProto.encode(e.graph,t.uint32(58).fork()).ldelim(),null!=e.opsetImport&&e.opsetImport.length)for(var n=0;n<e.opsetImport.length;++n)u.onnx.OperatorSetIdProto.encode(e.opsetImport[n],t.uint32(66).fork()).ldelim();if(null!=e.metadataProps&&e.metadataProps.length)for(n=0;n<e.metadataProps.length;++n)u.onnx.StringStringEntryProto.encode(e.metadataProps[n],t.uint32(114).fork()).ldelim();return t},e.encodeDelimited=function(e,t){return this.encode(e,t).ldelim()},e.decode=function(e,t){e instanceof a||(e=a.create(e));for(var n=void 0===t?e.len:e.pos+t,r=new u.onnx.ModelProto;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:r.irVersion=e.int64();break;case 8:r.opsetImport&&r.opsetImport.length||(r.opsetImport=[]),r.opsetImport.push(u.onnx.OperatorSetIdProto.decode(e,e.uint32()));break;case 2:r.producerName=e.string();break;case 3:r.producerVersion=e.string();break;case 4:r.domain=e.string();break;case 5:r.modelVersion=e.int64();break;case 6:r.docString=e.string();break;case 7:r.graph=u.onnx.GraphProto.decode(e,e.uint32());break;case 14:r.metadataProps&&r.metadataProps.length||(r.metadataProps=[]),r.metadataProps.push(u.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&o)}}return r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){if("object"!=typeof e||null===e)return"object expected";if(null!=e.irVersion&&e.hasOwnProperty("irVersion")&&!(c.isInteger(e.irVersion)||e.irVersion&&c.isInteger(e.irVersion.low)&&c.isInteger(e.irVersion.high)))return"irVersion: integer|Long expected";if(null!=e.opsetImport&&e.hasOwnProperty("opsetImport")){if(!Array.isArray(e.opsetImport))return"opsetImport: array expected";for(var t=0;t<e.opsetImport.length;++t)if(n=u.onnx.OperatorSetIdProto.verify(e.opsetImport[t]))return"opsetImport."+n}if(null!=e.producerName&&e.hasOwnProperty("producerName")&&!c.isString(e.producerName))return"producerName: string expected";if(null!=e.producerVersion&&e.hasOwnProperty("producerVersion")&&!c.isString(e.producerVersion))return"producerVersion: string expected";if(null!=e.domain&&e.hasOwnProperty("domain")&&!c.isString(e.domain))return"domain: string expected";if(null!=e.modelVersion&&e.hasOwnProperty("modelVersion")&&!(c.isInteger(e.modelVersion)||e.modelVersion&&c.isInteger(e.modelVersion.low)&&c.isInteger(e.modelVersion.high)))return"modelVersion: integer|Long expected";if(null!=e.docString&&e.hasOwnProperty("docString")&&!c.isString(e.docString))return"docString: string expected";if(null!=e.graph&&e.hasOwnProperty("graph")&&(n=u.onnx.GraphProto.verify(e.graph)))return"graph."+n;if(null!=e.metadataProps&&e.hasOwnProperty("metadataProps")){if(!Array.isArray(e.metadataProps))return"metadataProps: array expected";for(t=0;t<e.metadataProps.length;++t){var n;if(n=u.onnx.StringStringEntryProto.verify(e.metadataProps[t]))return"metadataProps."+n}}return null},e.fromObject=function(e){if(e instanceof u.onnx.ModelProto)return e;var t=new u.onnx.ModelProto;if(null!=e.irVersion&&(c.Long?(t.irVersion=c.Long.fromValue(e.irVersion)).unsigned=!1:"string"==typeof e.irVersion?t.irVersion=parseInt(e.irVersion,10):"number"==typeof e.irVersion?t.irVersion=e.irVersion:"object"==typeof e.irVersion&&(t.irVersion=new c.LongBits(e.irVersion.low>>>0,e.irVersion.high>>>0).toNumber())),e.opsetImport){if(!Array.isArray(e.opsetImport))throw TypeError(".onnx.ModelProto.opsetImport: array expected");t.opsetImport=[];for(var n=0;n<e.opsetImport.length;++n){if("object"!=typeof e.opsetImport[n])throw TypeError(".onnx.ModelProto.opsetImport: object expected");t.opsetImport[n]=u.onnx.OperatorSetIdProto.fromObject(e.opsetImport[n])}}if(null!=e.producerName&&(t.producerName=String(e.producerName)),null!=e.producerVersion&&(t.producerVersion=String(e.producerVersion)),null!=e.domain&&(t.domain=String(e.domain)),null!=e.modelVersion&&(c.Long?(t.modelVersion=c.Long.fromValue(e.modelVersion)).unsigned=!1:"string"==typeof e.modelVersion?t.modelVersion=parseInt(e.modelVersion,10):"number"==typeof e.modelVersion?t.modelVersion=e.modelVersion:"object"==typeof e.modelVersion&&(t.modelVersion=new c.LongBits(e.modelVersion.low>>>0,e.modelVersion.high>>>0).toNumber())),null!=e.docString&&(t.docString=String(e.docString)),null!=e.graph){if("object"!=typeof e.graph)throw TypeError(".onnx.ModelProto.graph: object expected");t.graph=u.onnx.GraphProto.fromObject(e.graph)}if(e.metadataProps){if(!Array.isArray(e.metadataProps))throw TypeError(".onnx.ModelProto.metadataProps: array expected");for(t.metadataProps=[],n=0;n<e.metadataProps.length;++n){if("object"!=typeof e.metadataProps[n])throw TypeError(".onnx.ModelProto.metadataProps: object expected");t.metadataProps[n]=u.onnx.StringStringEntryProto.fromObject(e.metadataProps[n])}}return t},e.toObject=function(e,t){t||(t={});var n={};if((t.arrays||t.defaults)&&(n.opsetImport=[],n.metadataProps=[]),t.defaults){if(c.Long){var r=new c.Long(0,0,!1);n.irVersion=t.longs===String?r.toString():t.longs===Number?r.toNumber():r}else n.irVersion=t.longs===String?"0":0;n.producerName="",n.producerVersion="",n.domain="",c.Long?(r=new c.Long(0,0,!1),n.modelVersion=t.longs===String?r.toString():t.longs===Number?r.toNumber():r):n.modelVersion=t.longs===String?"0":0,n.docString="",n.graph=null}if(null!=e.irVersion&&e.hasOwnProperty("irVersion")&&("number"==typeof e.irVersion?n.irVersion=t.longs===String?String(e.irVersion):e.irVersion:n.irVersion=t.longs===String?c.Long.prototype.toString.call(e.irVersion):t.longs===Number?new c.LongBits(e.irVersion.low>>>0,e.irVersion.high>>>0).toNumber():e.irVersion),null!=e.producerName&&e.hasOwnProperty("producerName")&&(n.producerName=e.producerName),null!=e.producerVersion&&e.hasOwnProperty("producerVersion")&&(n.producerVersion=e.producerVersion),null!=e.domain&&e.hasOwnProperty("domain")&&(n.domain=e.domain),null!=e.modelVersion&&e.hasOwnProperty("modelVersion")&&("number"==typeof e.modelVersion?n.modelVersion=t.longs===String?String(e.modelVersion):e.modelVersion:n.modelVersion=t.longs===String?c.Long.prototype.toString.call(e.modelVersion):t.longs===Number?new c.LongBits(e.modelVersion.low>>>0,e.modelVersion.high>>>0).toNumber():e.modelVersion),null!=e.docString&&e.hasOwnProperty("docString")&&(n.docString=e.docString),null!=e.graph&&e.hasOwnProperty("graph")&&(n.graph=u.onnx.GraphProto.toObject(e.graph,t)),e.opsetImport&&e.opsetImport.length){n.opsetImport=[];for(var o=0;o<e.opsetImport.length;++o)n.opsetImport[o]=u.onnx.OperatorSetIdProto.toObject(e.opsetImport[o],t)}if(e.metadataProps&&e.metadataProps.length)for(n.metadataProps=[],o=0;o<e.metadataProps.length;++o)n.metadataProps[o]=u.onnx.StringStringEntryProto.toObject(e.metadataProps[o],t);return n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),i.StringStringEntryProto=function(){function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}return e.prototype.key="",e.prototype.value="",e.create=function(t){return new e(t)},e.encode=function(e,t){return t||(t=l.create()),null!=e.key&&e.hasOwnProperty("key")&&t.uint32(10).string(e.key),null!=e.value&&e.hasOwnProperty("value")&&t.uint32(18).string(e.value),t},e.encodeDelimited=function(e,t){return this.encode(e,t).ldelim()},e.decode=function(e,t){e instanceof a||(e=a.create(e));for(var n=void 0===t?e.len:e.pos+t,r=new u.onnx.StringStringEntryProto;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:r.key=e.string();break;case 2:r.value=e.string();break;default:e.skipType(7&o)}}return r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){return"object"!=typeof e||null===e?"object expected":null!=e.key&&e.hasOwnProperty("key")&&!c.isString(e.key)?"key: string expected":null!=e.value&&e.hasOwnProperty("value")&&!c.isString(e.value)?"value: string expected":null},e.fromObject=function(e){if(e instanceof u.onnx.StringStringEntryProto)return e;var t=new u.onnx.StringStringEntryProto;return null!=e.key&&(t.key=String(e.key)),null!=e.value&&(t.value=String(e.value)),t},e.toObject=function(e,t){t||(t={});var n={};return t.defaults&&(n.key="",n.value=""),null!=e.key&&e.hasOwnProperty("key")&&(n.key=e.key),null!=e.value&&e.hasOwnProperty("value")&&(n.value=e.value),n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),i.TensorAnnotation=function(){function e(e){if(this.quantParameterTensorNames=[],e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}return e.prototype.tensorName="",e.prototype.quantParameterTensorNames=c.emptyArray,e.create=function(t){return new e(t)},e.encode=function(e,t){if(t||(t=l.create()),null!=e.tensorName&&e.hasOwnProperty("tensorName")&&t.uint32(10).string(e.tensorName),null!=e.quantParameterTensorNames&&e.quantParameterTensorNames.length)for(var n=0;n<e.quantParameterTensorNames.length;++n)u.onnx.StringStringEntryProto.encode(e.quantParameterTensorNames[n],t.uint32(18).fork()).ldelim();return t},e.encodeDelimited=function(e,t){return this.encode(e,t).ldelim()},e.decode=function(e,t){e instanceof a||(e=a.create(e));for(var n=void 0===t?e.len:e.pos+t,r=new u.onnx.TensorAnnotation;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:r.tensorName=e.string();break;case 2:r.quantParameterTensorNames&&r.quantParameterTensorNames.length||(r.quantParameterTensorNames=[]),r.quantParameterTensorNames.push(u.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&o)}}return r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){if("object"!=typeof e||null===e)return"object expected";if(null!=e.tensorName&&e.hasOwnProperty("tensorName")&&!c.isString(e.tensorName))return"tensorName: string expected";if(null!=e.quantParameterTensorNames&&e.hasOwnProperty("quantParameterTensorNames")){if(!Array.isArray(e.quantParameterTensorNames))return"quantParameterTensorNames: array expected";for(var t=0;t<e.quantParameterTensorNames.length;++t){var n=u.onnx.StringStringEntryProto.verify(e.quantParameterTensorNames[t]);if(n)return"quantParameterTensorNames."+n}}return null},e.fromObject=function(e){if(e instanceof u.onnx.TensorAnnotation)return e;var t=new u.onnx.TensorAnnotation;if(null!=e.tensorName&&(t.tensorName=String(e.tensorName)),e.quantParameterTensorNames){if(!Array.isArray(e.quantParameterTensorNames))throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: array expected");t.quantParameterTensorNames=[];for(var n=0;n<e.quantParameterTensorNames.length;++n){if("object"!=typeof e.quantParameterTensorNames[n])throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: object expected");t.quantParameterTensorNames[n]=u.onnx.StringStringEntryProto.fromObject(e.quantParameterTensorNames[n])}}return t},e.toObject=function(e,t){t||(t={});var n={};if((t.arrays||t.defaults)&&(n.quantParameterTensorNames=[]),t.defaults&&(n.tensorName=""),null!=e.tensorName&&e.hasOwnProperty("tensorName")&&(n.tensorName=e.tensorName),e.quantParameterTensorNames&&e.quantParameterTensorNames.length){n.quantParameterTensorNames=[];for(var r=0;r<e.quantParameterTensorNames.length;++r)n.quantParameterTensorNames[r]=u.onnx.StringStringEntryProto.toObject(e.quantParameterTensorNames[r],t)}return n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),i.GraphProto=function(){function e(e){if(this.node=[],this.initializer=[],this.input=[],this.output=[],this.valueInfo=[],this.quantizationAnnotation=[],e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}return e.prototype.node=c.emptyArray,e.prototype.name="",e.prototype.initializer=c.emptyArray,e.prototype.docString="",e.prototype.input=c.emptyArray,e.prototype.output=c.emptyArray,e.prototype.valueInfo=c.emptyArray,e.prototype.quantizationAnnotation=c.emptyArray,e.create=function(t){return new e(t)},e.encode=function(e,t){if(t||(t=l.create()),null!=e.node&&e.node.length)for(var n=0;n<e.node.length;++n)u.onnx.NodeProto.encode(e.node[n],t.uint32(10).fork()).ldelim();if(null!=e.name&&e.hasOwnProperty("name")&&t.uint32(18).string(e.name),null!=e.initializer&&e.initializer.length)for(n=0;n<e.initializer.length;++n)u.onnx.TensorProto.encode(e.initializer[n],t.uint32(42).fork()).ldelim();if(null!=e.docString&&e.hasOwnProperty("docString")&&t.uint32(82).string(e.docString),null!=e.input&&e.input.length)for(n=0;n<e.input.length;++n)u.onnx.ValueInfoProto.encode(e.input[n],t.uint32(90).fork()).ldelim();if(null!=e.output&&e.output.length)for(n=0;n<e.output.length;++n)u.onnx.ValueInfoProto.encode(e.output[n],t.uint32(98).fork()).ldelim();if(null!=e.valueInfo&&e.valueInfo.length)for(n=0;n<e.valueInfo.length;++n)u.onnx.ValueInfoProto.encode(e.valueInfo[n],t.uint32(106).fork()).ldelim();if(null!=e.quantizationAnnotation&&e.quantizationAnnotation.length)for(n=0;n<e.quantizationAnnotation.length;++n)u.onnx.TensorAnnotation.encode(e.quantizationAnnotation[n],t.uint32(114).fork()).ldelim();return t},e.encodeDelimited=function(e,t){return this.encode(e,t).ldelim()},e.decode=function(e,t){e instanceof a||(e=a.create(e));for(var n=void 0===t?e.len:e.pos+t,r=new u.onnx.GraphProto;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:r.node&&r.node.length||(r.node=[]),r.node.push(u.onnx.NodeProto.decode(e,e.uint32()));break;case 2:r.name=e.string();break;case 5:r.initializer&&r.initializer.length||(r.initializer=[]),r.initializer.push(u.onnx.TensorProto.decode(e,e.uint32()));break;case 10:r.docString=e.string();break;case 11:r.input&&r.input.length||(r.input=[]),r.input.push(u.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 12:r.output&&r.output.length||(r.output=[]),r.output.push(u.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 13:r.valueInfo&&r.valueInfo.length||(r.valueInfo=[]),r.valueInfo.push(u.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 14:r.quantizationAnnotation&&r.quantizationAnnotation.length||(r.quantizationAnnotation=[]),r.quantizationAnnotation.push(u.onnx.TensorAnnotation.decode(e,e.uint32()));break;default:e.skipType(7&o)}}return r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){if("object"!=typeof e||null===e)return"object expected";if(null!=e.node&&e.hasOwnProperty("node")){if(!Array.isArray(e.node))return"node: array expected";for(var t=0;t<e.node.length;++t)if(n=u.onnx.NodeProto.verify(e.node[t]))return"node."+n}if(null!=e.name&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(null!=e.initializer&&e.hasOwnProperty("initializer")){if(!Array.isArray(e.initializer))return"initializer: array expected";for(t=0;t<e.initializer.length;++t)if(n=u.onnx.TensorProto.verify(e.initializer[t]))return"initializer."+n}if(null!=e.docString&&e.hasOwnProperty("docString")&&!c.isString(e.docString))return"docString: string expected";if(null!=e.input&&e.hasOwnProperty("input")){if(!Array.isArray(e.input))return"input: array expected";for(t=0;t<e.input.length;++t)if(n=u.onnx.ValueInfoProto.verify(e.input[t]))return"input."+n}if(null!=e.output&&e.hasOwnProperty("output")){if(!Array.isArray(e.output))return"output: array expected";for(t=0;t<e.output.length;++t)if(n=u.onnx.ValueInfoProto.verify(e.output[t]))return"output."+n}if(null!=e.valueInfo&&e.hasOwnProperty("valueInfo")){if(!Array.isArray(e.valueInfo))return"valueInfo: array expected";for(t=0;t<e.valueInfo.length;++t)if(n=u.onnx.ValueInfoProto.verify(e.valueInfo[t]))return"valueInfo."+n}if(null!=e.quantizationAnnotation&&e.hasOwnProperty("quantizationAnnotation")){if(!Array.isArray(e.quantizationAnnotation))return"quantizationAnnotation: array expected";for(t=0;t<e.quantizationAnnotation.length;++t){var n;if(n=u.onnx.TensorAnnotation.verify(e.quantizationAnnotation[t]))return"quantizationAnnotation."+n}}return null},e.fromObject=function(e){if(e instanceof u.onnx.GraphProto)return e;var t=new u.onnx.GraphProto;if(e.node){if(!Array.isArray(e.node))throw TypeError(".onnx.GraphProto.node: array expected");t.node=[];for(var n=0;n<e.node.length;++n){if("object"!=typeof e.node[n])throw TypeError(".onnx.GraphProto.node: object expected");t.node[n]=u.onnx.NodeProto.fromObject(e.node[n])}}if(null!=e.name&&(t.name=String(e.name)),e.initializer){if(!Array.isArray(e.initializer))throw TypeError(".onnx.GraphProto.initializer: array expected");for(t.initializer=[],n=0;n<e.initializer.length;++n){if("object"!=typeof e.initializer[n])throw TypeError(".onnx.GraphProto.initializer: object expected");t.initializer[n]=u.onnx.TensorProto.fromObject(e.initializer[n])}}if(null!=e.docString&&(t.docString=String(e.docString)),e.input){if(!Array.isArray(e.input))throw TypeError(".onnx.GraphProto.input: array expected");for(t.input=[],n=0;n<e.input.length;++n){if("object"!=typeof e.input[n])throw TypeError(".onnx.GraphProto.input: object 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TypeError(".onnx.GraphProto.quantizationAnnotation: object expected");t.quantizationAnnotation[n]=u.onnx.TensorAnnotation.fromObject(e.quantizationAnnotation[n])}}return t},e.toObject=function(e,t){t||(t={});var n={};if((t.arrays||t.defaults)&&(n.node=[],n.initializer=[],n.input=[],n.output=[],n.valueInfo=[],n.quantizationAnnotation=[]),t.defaults&&(n.name="",n.docString=""),e.node&&e.node.length){n.node=[];for(var r=0;r<e.node.length;++r)n.node[r]=u.onnx.NodeProto.toObject(e.node[r],t)}if(null!=e.name&&e.hasOwnProperty("name")&&(n.name=e.name),e.initializer&&e.initializer.length)for(n.initializer=[],r=0;r<e.initializer.length;++r)n.initializer[r]=u.onnx.TensorProto.toObject(e.initializer[r],t);if(null!=e.docString&&e.hasOwnProperty("docString")&&(n.docString=e.docString),e.input&&e.input.length)for(n.input=[],r=0;r<e.input.length;++r)n.input[r]=u.onnx.ValueInfoProto.toObject(e.input[r],t);if(e.output&&e.output.length)for(n.output=[],r=0;r<e.output.length;++r)n.output[r]=u.onnx.ValueInfoProto.toObject(e.output[r],t);if(e.valueInfo&&e.valueInfo.length)for(n.valueInfo=[],r=0;r<e.valueInfo.length;++r)n.valueInfo[r]=u.onnx.ValueInfoProto.toObject(e.valueInfo[r],t);if(e.quantizationAnnotation&&e.quantizationAnnotation.length)for(n.quantizationAnnotation=[],r=0;r<e.quantizationAnnotation.length;++r)n.quantizationAnnotation[r]=u.onnx.TensorAnnotation.toObject(e.quantizationAnnotation[r],t);return n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),i.TensorProto=function(){function e(e){if(this.dims=[],this.floatData=[],this.int32Data=[],this.stringData=[],this.int64Data=[],this.externalData=[],this.doubleData=[],this.uint64Data=[],e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}return e.prototype.dims=c.emptyArray,e.prototype.dataType=0,e.prototype.segment=null,e.prototype.floatData=c.emptyArray,e.prototype.int32Data=c.emptyArray,e.prototype.stringData=c.emptyArray,e.prototype.int64Data=c.emptyArray,e.prototype.name="",e.prototype.docString="",e.prototype.rawData=c.newBuffer([]),e.prototype.externalData=c.emptyArray,e.prototype.dataLocation=0,e.prototype.doubleData=c.emptyArray,e.prototype.uint64Data=c.emptyArray,e.create=function(t){return new e(t)},e.encode=function(e,t){if(t||(t=l.create()),null!=e.dims&&e.dims.length){t.uint32(10).fork();for(var n=0;n<e.dims.length;++n)t.int64(e.dims[n]);t.ldelim()}if(null!=e.dataType&&e.hasOwnProperty("dataType")&&t.uint32(16).int32(e.dataType),null!=e.segment&&e.hasOwnProperty("segment")&&u.onnx.TensorProto.Segment.encode(e.segment,t.uint32(26).fork()).ldelim(),null!=e.floatData&&e.floatData.length){for(t.uint32(34).fork(),n=0;n<e.floatData.length;++n)t.float(e.floatData[n]);t.ldelim()}if(null!=e.int32Data&&e.int32Data.length){for(t.uint32(42).fork(),n=0;n<e.int32Data.length;++n)t.int32(e.int32Data[n]);t.ldelim()}if(null!=e.stringData&&e.stringData.length)for(n=0;n<e.stringData.length;++n)t.uint32(50).bytes(e.stringData[n]);if(null!=e.int64Data&&e.int64Data.length){for(t.uint32(58).fork(),n=0;n<e.int64Data.length;++n)t.int64(e.int64Data[n]);t.ldelim()}if(null!=e.name&&e.hasOwnProperty("name")&&t.uint32(66).string(e.name),null!=e.rawData&&e.hasOwnProperty("rawData")&&t.uint32(74).bytes(e.rawData),null!=e.doubleData&&e.doubleData.length){for(t.uint32(82).fork(),n=0;n<e.doubleData.length;++n)t.double(e.doubleData[n]);t.ldelim()}if(null!=e.uint64Data&&e.uint64Data.length){for(t.uint32(90).fork(),n=0;n<e.uint64Data.length;++n)t.uint64(e.uint64Data[n]);t.ldelim()}if(null!=e.docString&&e.hasOwnProperty("docString")&&t.uint32(98).string(e.docString),null!=e.externalData&&e.externalData.length)for(n=0;n<e.externalData.length;++n)u.onnx.StringStringEntryProto.encode(e.externalData[n],t.uint32(106).fork()).ldelim();return null!=e.dataLocation&&e.hasOwnProperty("dataLocation")&&t.uint32(112).int32(e.dataLocation),t},e.encodeDelimited=function(e,t){return this.encode(e,t).ldelim()},e.decode=function(e,t){e instanceof a||(e=a.create(e));for(var n=void 0===t?e.len:e.pos+t,r=new u.onnx.TensorProto;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:if(r.dims&&r.dims.length||(r.dims=[]),2==(7&o))for(var i=e.uint32()+e.pos;e.pos<i;)r.dims.push(e.int64());else r.dims.push(e.int64());break;case 2:r.dataType=e.int32();break;case 3:r.segment=u.onnx.TensorProto.Segment.decode(e,e.uint32());break;case 4:if(r.floatData&&r.floatData.length||(r.floatData=[]),2==(7&o))for(i=e.uint32()+e.pos;e.pos<i;)r.floatData.push(e.float());else r.floatData.push(e.float());break;case 5:if(r.int32Data&&r.int32Data.length||(r.int32Data=[]),2==(7&o))for(i=e.uint32()+e.pos;e.pos<i;)r.int32Data.push(e.int32());else r.int32Data.push(e.int32());break;case 6:r.stringData&&r.stringData.length||(r.stringData=[]),r.stringData.push(e.bytes());break;case 7:if(r.int64Data&&r.int64Data.length||(r.int64Data=[]),2==(7&o))for(i=e.uint32()+e.pos;e.pos<i;)r.int64Data.push(e.int64());else r.int64Data.push(e.int64());break;case 8:r.name=e.string();break;case 12:r.docString=e.string();break;case 9:r.rawData=e.bytes();break;case 13:r.externalData&&r.externalData.length||(r.externalData=[]),r.externalData.push(u.onnx.StringStringEntryProto.decode(e,e.uint32()));break;case 14:r.dataLocation=e.int32();break;case 10:if(r.doubleData&&r.doubleData.length||(r.doubleData=[]),2==(7&o))for(i=e.uint32()+e.pos;e.pos<i;)r.doubleData.push(e.double());else r.doubleData.push(e.double());break;case 11:if(r.uint64Data&&r.uint64Data.length||(r.uint64Data=[]),2==(7&o))for(i=e.uint32()+e.pos;e.pos<i;)r.uint64Data.push(e.uint64());else r.uint64Data.push(e.uint64());break;default:e.skipType(7&o)}}return r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){if("object"!=typeof e||null===e)return"object expected";if(null!=e.dims&&e.hasOwnProperty("dims")){if(!Array.isArray(e.dims))return"dims: array expected";for(var t=0;t<e.dims.length;++t)if(!(c.isInteger(e.dims[t])||e.dims[t]&&c.isInteger(e.dims[t].low)&&c.isInteger(e.dims[t].high)))return"dims: integer|Long[] expected"}if(null!=e.dataType&&e.hasOwnProperty("dataType")&&!c.isInteger(e.dataType))return"dataType: integer expected";if(null!=e.segment&&e.hasOwnProperty("segment")&&(n=u.onnx.TensorProto.Segment.verify(e.segment)))return"segment."+n;if(null!=e.floatData&&e.hasOwnProperty("floatData")){if(!Array.isArray(e.floatData))return"floatData: array expected";for(t=0;t<e.floatData.length;++t)if("number"!=typeof e.floatData[t])return"floatData: number[] expected"}if(null!=e.int32Data&&e.hasOwnProperty("int32Data")){if(!Array.isArray(e.int32Data))return"int32Data: array expected";for(t=0;t<e.int32Data.length;++t)if(!c.isInteger(e.int32Data[t]))return"int32Data: integer[] expected"}if(null!=e.stringData&&e.hasOwnProperty("stringData")){if(!Array.isArray(e.stringData))return"stringData: array expected";for(t=0;t<e.stringData.length;++t)if(!(e.stringData[t]&&"number"==typeof e.stringData[t].length||c.isString(e.stringData[t])))return"stringData: buffer[] expected"}if(null!=e.int64Data&&e.hasOwnProperty("int64Data")){if(!Array.isArray(e.int64Data))return"int64Data: array expected";for(t=0;t<e.int64Data.length;++t)if(!(c.isInteger(e.int64Data[t])||e.int64Data[t]&&c.isInteger(e.int64Data[t].low)&&c.isInteger(e.int64Data[t].high)))return"int64Data: integer|Long[] expected"}if(null!=e.name&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(null!=e.docString&&e.hasOwnProperty("docString")&&!c.isString(e.docString))return"docString: string expected";if(null!=e.rawData&&e.hasOwnProperty("rawData")&&!(e.rawData&&"number"==typeof e.rawData.length||c.isString(e.rawData)))return"rawData: buffer expected";if(null!=e.externalData&&e.hasOwnProperty("externalData")){if(!Array.isArray(e.externalData))return"externalData: array expected";for(t=0;t<e.externalData.length;++t){var n;if(n=u.onnx.StringStringEntryProto.verify(e.externalData[t]))return"externalData."+n}}if(null!=e.dataLocation&&e.hasOwnProperty("dataLocation"))switch(e.dataLocation){default:return"dataLocation: enum value expected";case 0:case 1:}if(null!=e.doubleData&&e.hasOwnProperty("doubleData")){if(!Array.isArray(e.doubleData))return"doubleData: array expected";for(t=0;t<e.doubleData.length;++t)if("number"!=typeof e.doubleData[t])return"doubleData: number[] expected"}if(null!=e.uint64Data&&e.hasOwnProperty("uint64Data")){if(!Array.isArray(e.uint64Data))return"uint64Data: array 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t},e.toObject=function(e,t){t||(t={});var n={};if((t.arrays||t.defaults)&&(n.dim=[]),e.dim&&e.dim.length){n.dim=[];for(var r=0;r<e.dim.length;++r)n.dim[r]=u.onnx.TensorShapeProto.Dimension.toObject(e.dim[r],t)}return n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e.Dimension=function(){function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}var t;return e.prototype.dimValue=c.Long?c.Long.fromBits(0,0,!1):0,e.prototype.dimParam="",e.prototype.denotation="",Object.defineProperty(e.prototype,"value",{get:c.oneOfGetter(t=["dimValue","dimParam"]),set:c.oneOfSetter(t)}),e.create=function(t){return new e(t)},e.encode=function(e,t){return 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t.defaults&&(n.denotation=""),null!=e.dimValue&&e.hasOwnProperty("dimValue")&&("number"==typeof e.dimValue?n.dimValue=t.longs===String?String(e.dimValue):e.dimValue:n.dimValue=t.longs===String?c.Long.prototype.toString.call(e.dimValue):t.longs===Number?new c.LongBits(e.dimValue.low>>>0,e.dimValue.high>>>0).toNumber():e.dimValue,t.oneofs&&(n.value="dimValue")),null!=e.dimParam&&e.hasOwnProperty("dimParam")&&(n.dimParam=e.dimParam,t.oneofs&&(n.value="dimParam")),null!=e.denotation&&e.hasOwnProperty("denotation")&&(n.denotation=e.denotation),n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),e}(),i.TypeProto=function(){function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}var t;return e.prototype.tensorType=null,e.prototype.denotation="",Object.defineProperty(e.prototype,"value",{get:c.oneOfGetter(t=["tensorType"]),set:c.oneOfSetter(t)}),e.create=function(t){return new e(t)},e.encode=function(e,t){return t||(t=l.create()),null!=e.tensorType&&e.hasOwnProperty("tensorType")&&u.onnx.TypeProto.Tensor.encode(e.tensorType,t.uint32(10).fork()).ldelim(),null!=e.denotation&&e.hasOwnProperty("denotation")&&t.uint32(50).string(e.denotation),t},e.encodeDelimited=function(e,t){return this.encode(e,t).ldelim()},e.decode=function(e,t){e instanceof a||(e=a.create(e));for(var n=void 0===t?e.len:e.pos+t,r=new u.onnx.TypeProto;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:r.tensorType=u.onnx.TypeProto.Tensor.decode(e,e.uint32());break;case 6:r.denotation=e.string();break;default:e.skipType(7&o)}}return r},e.decodeDelimited=function(e){return e instanceof a||(e=new a(e)),this.decode(e,e.uint32())},e.verify=function(e){if("object"!=typeof e||null===e)return"object expected";if(null!=e.tensorType&&e.hasOwnProperty("tensorType")){var t=u.onnx.TypeProto.Tensor.verify(e.tensorType);if(t)return"tensorType."+t}return null!=e.denotation&&e.hasOwnProperty("denotation")&&!c.isString(e.denotation)?"denotation: string expected":null},e.fromObject=function(e){if(e instanceof u.onnx.TypeProto)return e;var t=new u.onnx.TypeProto;if(null!=e.tensorType){if("object"!=typeof e.tensorType)throw TypeError(".onnx.TypeProto.tensorType: object expected");t.tensorType=u.onnx.TypeProto.Tensor.fromObject(e.tensorType)}return null!=e.denotation&&(t.denotation=String(e.denotation)),t},e.toObject=function(e,t){t||(t={});var n={};return t.defaults&&(n.denotation=""),null!=e.tensorType&&e.hasOwnProperty("tensorType")&&(n.tensorType=u.onnx.TypeProto.Tensor.toObject(e.tensorType,t),t.oneofs&&(n.value="tensorType")),null!=e.denotation&&e.hasOwnProperty("denotation")&&(n.denotation=e.denotation),n},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e.Tensor=function(){function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t[n]]&&(this[t[n]]=e[t[n]])}return 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r.onnx.AttributeProto.AttributeType.FLOAT:return"float";case r.onnx.AttributeProto.AttributeType.INT:return"int";case r.onnx.AttributeProto.AttributeType.STRING:return"string";case r.onnx.AttributeProto.AttributeType.TENSOR:return"tensor";case r.onnx.AttributeProto.AttributeType.FLOATS:return"floats";case r.onnx.AttributeProto.AttributeType.INTS:return"ints";case r.onnx.AttributeProto.AttributeType.STRINGS:return"strings";case r.onnx.AttributeProto.AttributeType.TENSORS:return"tensors";default:throw new Error(`attribute type is not supported yet: ${r.onnx.AttributeProto.AttributeType[t]}`)}}static getValue(e){const t=e instanceof r.onnx.AttributeProto?e.type:e.type();if(t===r.onnx.AttributeProto.AttributeType.GRAPH||t===r.onnx.AttributeProto.AttributeType.GRAPHS)throw new Error("graph attribute is not supported yet");const n=this.getValueNoCheck(e);if(t===r.onnx.AttributeProto.AttributeType.INT&&s.LongUtil.isLong(n))return s.LongUtil.longToNumber(n);if(t===r.onnx.AttributeProto.AttributeType.INTS){const e=n,t=new Array(e.length);for(let n=0;n<e.length;n++){const r=e[n];t[n]=s.LongUtil.longToNumber(r)}return t}if(t===r.onnx.AttributeProto.AttributeType.TENSOR)return e instanceof r.onnx.AttributeProto?i.Tensor.fromProto(n):i.Tensor.fromOrtTensor(n);if(t===r.onnx.AttributeProto.AttributeType.TENSORS){if(e instanceof r.onnx.AttributeProto)return n.map((e=>i.Tensor.fromProto(e)));if(e instanceof a.Attribute)return n.map((e=>i.Tensor.fromOrtTensor(e)))}if(t===r.onnx.AttributeProto.AttributeType.STRING&&e instanceof r.onnx.AttributeProto){const e=n;return(0,s.decodeUtf8String)(e)}return t===r.onnx.AttributeProto.AttributeType.STRINGS&&e instanceof r.onnx.AttributeProto?n.map(s.decodeUtf8String):n}static getValueNoCheck(e){return e instanceof r.onnx.AttributeProto?this.getValueNoCheckFromOnnxFormat(e):this.getValueNoCheckFromOrtFormat(e)}static getValueNoCheckFromOnnxFormat(e){switch(e.type){case r.onnx.AttributeProto.AttributeType.FLOAT:return e.f;case r.onnx.AttributeProto.AttributeType.INT:return e.i;case r.onnx.AttributeProto.AttributeType.STRING:return e.s;case r.onnx.AttributeProto.AttributeType.TENSOR:return e.t;case r.onnx.AttributeProto.AttributeType.GRAPH:return e.g;case r.onnx.AttributeProto.AttributeType.FLOATS:return e.floats;case r.onnx.AttributeProto.AttributeType.INTS:return e.ints;case r.onnx.AttributeProto.AttributeType.STRINGS:return e.strings;case r.onnx.AttributeProto.AttributeType.TENSORS:return e.tensors;case r.onnx.AttributeProto.AttributeType.GRAPHS:return e.graphs;default:throw new Error(`unsupported attribute type: ${r.onnx.AttributeProto.AttributeType[e.type]}`)}}static getValueNoCheckFromOrtFormat(e){switch(e.type()){case a.AttributeType.FLOAT:return e.f();case a.AttributeType.INT:return e.i();case a.AttributeType.STRING:return e.s();case a.AttributeType.TENSOR:return e.t();case a.AttributeType.GRAPH:return e.g();case a.AttributeType.FLOATS:return e.floatsArray();case a.AttributeType.INTS:{const t=[];for(let n=0;n<e.intsLength();n++)t.push(e.ints(n));return t}case a.AttributeType.STRINGS:{const t=[];for(let n=0;n<e.stringsLength();n++)t.push(e.strings(n));return t}case a.AttributeType.TENSORS:{const t=[];for(let n=0;n<e.tensorsLength();n++)t.push(e.tensors(n));return t}default:throw new Error(`unsupported attribute type: ${a.AttributeType[e.type()]}`)}}}t.Attribute=l},7091:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.resolveBackend=t.backend=void 0;const r=n(5038),o=new Map;async function i(e){const n=t.backend;if(void 0!==n[e]&&function(e){const t=e;return"initialize"in t&&"function"==typeof t.initialize&&"createSessionHandler"in t&&"function"==typeof t.createSessionHandler&&"dispose"in t&&"function"==typeof t.dispose}(n[e])){const t=n[e];let r=t.initialize();if("object"==typeof r&&"then"in r&&(r=await r),r)return o.set(e,t),t}}t.backend={webgl:new r.WebGLBackend},t.resolveBackend=async function 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Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.offsetToCoords()),this.coordsToOffset()),this.toVec()),this.valueFrom()),this.getCommonUtilFuncs()),this.getInputsSamplingSnippets()),this.getOutputSamplingSnippet())}getCustomTypes(){return{}}offsetToCoords(){return{offsetToCoords:new o.GlslLibRoutine("\n      vec2 offsetToCoords(int offset, int width, int height) {\n        int t = offset / width;\n        int s = offset - t*width;\n        vec2 coords = (vec2(s,t) + vec2(0.5,0.5)) / vec2(width, height);\n        return coords;\n      }\n      ")}}coordsToOffset(){return{coordsToOffset:new o.GlslLibRoutine("\n      int coordsToOffset(vec2 coords, int width, int height) {\n        float s = coords.s * float(width);\n        float t = coords.t * float(height);\n        int offset = int(t) * width + int(s);\n        return offset;\n      }\n      ")}}getOutputSamplingSnippet(){const e=this.context.outputTextureLayout;return e.isPacked?this.getPackedOutputSamplingSnippet(e):this.getUnpackedOutputSamplingSnippet(e)}getPackedOutputSamplingSnippet(e){const t=e.unpackedShape,n=[e.width,e.height],r={},s="getOutputCoords";switch(t.length){case 0:r[s]=this.getOutputScalarCoords();break;case 1:r[s]=this.getOutputPacked1DCoords(t,n);break;case 2:r[s]=this.getOutputPacked2DCoords(t,n);break;case 3:r[s]=this.getOutputPacked3DCoords(t,n);break;default:r[s]=this.getOutputPackedNDCoords(t,n)}const a=`\n      void setOutput(vec4 val) {\n        ${(0,i.getGlsl)(this.context.glContext.version).output} = val;\n      }\n    `;return r.floatTextureSetRGBA=new o.GlslLibRoutine(a),r}getUnpackedOutputSamplingSnippet(e){const t=e.unpackedShape,n=[e.width,e.height],r={},s="getOutputCoords";switch(t.length){case 0:r[s]=this.getOutputScalarCoords();break;case 1:r[s]=this.getOutputUnpacked1DCoords(t,n);break;case 2:r[s]=this.getOutputUnpacked2DCoords(t,n);break;case 3:r[s]=this.getOutputUnpacked3DCoords(t,n);break;case 4:r[s]=this.getOutputUnpacked4DCoords(t,n);break;case 5:r[s]=this.getOutputUnpacked5DCoords(t,n);break;case 6:r[s]=this.getOutputUnpacked6DCoords(t,n);break;default:throw new Error(`Unsupported output dimensionality: ${t.length}`)}const a=`\n        void setOutput(float val) {\n          ${(0,i.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0);\n        }\n    `;return r.floatTextureSetR=new o.GlslLibRoutine(a),r}getOutputScalarCoords(){return new o.GlslLibRoutine("\n      int getOutputCoords() {\n        return 0;\n      }\n    ")}getOutputPacked1DCoords(e,t){const n=t;let r="";return 1===n[0]?(r=`\n          int getOutputCoords() {\n            return 2 * int(TexCoords.y * ${n[1]}.0);\n          }\n        `,new o.GlslLibRoutine(r)):1===n[1]?(r=`\n          int getOutputCoords() {\n            return 2 * int(TexCoords.x * ${n[0]}.0);\n          }\n        `,new o.GlslLibRoutine(r)):(r=`\n        int getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                 vec2(${n[0]}, ${n[1]}));\n          return 2 * (resTexRC.y * ${n[0]} + resTexRC.x);\n        }\n      `,new o.GlslLibRoutine(r))}getOutputPacked2DCoords(e,t){let n="";if(r.ArrayUtil.arraysEqual(e,t))return n=`\n        ivec2 getOutputCoords() {\n          return 2 * ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]}));\n        }\n      `,new o.GlslLibRoutine(n);const i=t,s=Math.ceil(e[1]/2);return n=`\n        ivec2 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${i[0]}, ${i[1]}));\n\n          int index = resTexRC.y * ${i[0]} + resTexRC.x;\n\n          // reverse r and c order for packed texture\n          int r = imod(index, ${s}) * 2;\n          int c = 2 * (index / ${s});\n\n          return ivec2(r, c);\n        }\n      `,new o.GlslLibRoutine(n)}getOutputPacked3DCoords(e,t){const n=[t[0],t[1]],r=Math.ceil(e[2]/2),i=r*Math.ceil(e[1]/2),s=`\n        ivec3 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${n[0]}, ${n[1]}));\n          int index = resTexRC.y * ${n[0]} + resTexRC.x;\n\n          int b = index / ${i};\n          index -= b * ${i};\n\n          // reverse r and c order for packed texture\n          int r = imod(index, ${r}) * 2;\n          int c = 2 * (index / ${r});\n\n          return ivec3(b, r, c);\n        }\n      `;return new o.GlslLibRoutine(s)}getOutputPackedNDCoords(e,t){const n=[t[0],t[1]],r=Math.ceil(e[e.length-1]/2),i=r*Math.ceil(e[e.length-2]/2);let s=i,a="",l="b, r, c";for(let t=2;t<e.length-1;t++)s*=e[e.length-t-1],a=`\n      int b${t} = index / ${s};\n      index -= b${t} * ${s};\n    `+a,l=`b${t}, `+l;const c=`\n      ivec${e.length} getOutputCoords() {\n        ivec2 resTexRC = ivec2(TexCoords.xy *\n                              vec2(${n[0]}, ${n[1]}));\n        int index = resTexRC.y * ${n[0]} + resTexRC.x;\n\n        ${a}\n\n        int b = index / ${i};\n        index -= b * ${i};\n\n        // reverse r and c order for packed texture\n        int r = imod(index, ${r}) * 2;\n        int c = 2 * (index / ${r});\n\n        return ivec${e.length}(${l});\n      }\n    `;return new o.GlslLibRoutine(c)}getOutputUnpacked1DCoords(e,t){const n=`\n        int getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${t[0]}, ${t[1]}));\n          return resTexRC.y * ${t[0]} + resTexRC.x;\n        }\n      `;return new o.GlslLibRoutine(n)}getOutputUnpacked2DCoords(e,t){const n=`\n        ivec2 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${t[0]}, ${t[1]}));\n          int index = resTexRC.y * ${t[0]} + resTexRC.x;\n          int r = index / ${e[1]};\n          int c = index - r * ${e[1]};\n          return ivec2(r, c);\n        }\n      `;return new o.GlslLibRoutine(n)}getOutputUnpacked3DCoords(e,t){let n="";const r=e.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=e[r-1];for(let t=r-3;t>=0;--t)i[t]=i[t+1]*e[t+1];const s=["r","c","d"],a=i.map(((e,t)=>`int ${s[t]} = index / ${e}; ${t===i.length-1?`int ${s[t+1]} = index - ${s[t]} * ${e}`:`index -= ${s[t]} * ${e}`};`)).join("");return n=`\n        ivec3 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${t[0]}, ${t[1]}));\n          int index = resTexRC.y * ${t[0]} + resTexRC.x;\n          ${a}\n          return ivec3(r, c, d);\n        }\n      `,new o.GlslLibRoutine(n)}getOutputUnpacked4DCoords(e,t){let n="";const r=e.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=e[r-1];for(let t=r-3;t>=0;--t)i[t]=i[t+1]*e[t+1];const s=["r","c","d","d2"],a=i.map(((e,t)=>`int ${s[t]} = index / ${e}; ${t===i.length-1?`int ${s[t+1]} = index - ${s[t]} * ${e}`:`index -= ${s[t]} * ${e}`};`)).join("");return n=`\n      ivec4 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${t[0]}, ${t[1]}));\n          int index = resTexRC.y * ${t[0]} + resTexRC.x;\n          ${a}\n          return ivec4(r, c, d, d2);\n        }\n      `,new o.GlslLibRoutine(n)}getOutputUnpacked5DCoords(e,t){let n="";const r=e.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=e[r-1];for(let t=r-3;t>=0;--t)i[t]=i[t+1]*e[t+1];const s=["r","c","d","d2","d3"],a=i.map(((e,t)=>`int ${s[t]} = index / ${e}; ${t===i.length-1?`int ${s[t+1]} = index - ${s[t]} * ${e}`:`index -= ${s[t]} * ${e}`};`)).join("");return n=`\n      ivec5 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${t[0]}, ${t[1]}));\n          int index = resTexRC.y * ${t[0]} + resTexRC.x;\n          ${a}\n          return ivec5(r, c, d, d2, d3);\n        }\n      `,new o.GlslLibRoutine(n)}getOutputUnpacked6DCoords(e,t){let n="";const r=e.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=e[r-1];for(let t=r-3;t>=0;--t)i[t]=i[t+1]*e[t+1];const s=["r","c","d","d2","d3","d4"],a=i.map(((e,t)=>`int ${s[t]} = index / ${e}; ${t===i.length-1?`int ${s[t+1]} = index - ${s[t]} * ${e}`:`index -= ${s[t]} * ${e}`};`)).join("");return n=`\n     ivec6 getOutputCoords() {\n         ivec2 resTexRC = ivec2(TexCoords.xy *\n                               vec2(${t[0]}, ${t[1]}));\n         int index = resTexRC.y * ${t[0]} + resTexRC.x;\n         ${a}\n         return ivec6(r, c, d, d2, d3, d4);\n       }\n     `,new o.GlslLibRoutine(n)}getCommonUtilFuncs(){const e={};let t="uvFromFlat";e[t]=new o.GlslLibRoutine("\n    vec2 uvFromFlat(int texNumR, int texNumC, int index) {\n      int texC = index / texNumR;\n      int texR = index - texC * texNumR;\n      // TODO: swap texR, texC order in following function so row is corresponding to u and column is corresponding to\n      //       v.\n      return (vec2(texR, texC) + halfCR) / vec2(texNumR, texNumC);\n    }\n    "),t="packedUVfrom1D",e[t]=new o.GlslLibRoutine("\n      vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n        int texelIndex = index / 2;\n        int texR = texelIndex / texNumC;\n        int texC = texelIndex - texR * texNumC;\n        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n      }\n      "),t="packedUVfrom2D",e[t]=new o.GlslLibRoutine("\n      vec2 packedUVfrom2D(int texNumR, int texNumC, int texelsInLogicalRow, int row, int col) {\n        int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n        int texR = texelIndex / texNumC;\n        int texC = texelIndex - texR * texNumC;\n        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n      }\n      "),t="packedUVfrom3D",e[t]=new o.GlslLibRoutine("\n      vec2 packedUVfrom3D(int texNumR, int texNumC,\n          int texelsInBatch, int texelsInLogicalRow, int b,\n          int row, int col) {\n        int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n        int texR = index / texNumC;\n        int texC = index - texR * texNumC;\n        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n      }\n      "),t="sampleTexture";const n=(0,i.getGlsl)(this.context.glContext.version);return e[t]=new o.GlslLibRoutine(`\n        float sampleTexture(sampler2D textureSampler, vec2 uv) {\n            return ${n.texture2D}(textureSampler, uv).r;\n        }`),e}getInputsSamplingSnippets(){const e={},t=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach(((n,r)=>{const o=this.context.inputTextureLayouts[r],i=(0,a.generateShaderFuncNameFromInputSamplerName)(n);o.isPacked?e[i]=this.getPackedSamplerFromInput(i,n,o):e[i]=this.getUnpackedSamplerFromInput(i,n,o);const s=(0,a.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(n);o.unpackedShape.length<=t.unpackedShape.length&&(o.isPacked?e[s]=this.getPackedSamplerAtOutputCoords(s,o,t,n):e[s]=this.getUnpackedSamplerAtOutputCoords(s,o,t,n))})),e}getPackedSamplerAtOutputCoords(e,t,n,i){const s=t.unpackedShape,l=n.unpackedShape,c=i,u=(0,a.generateShaderFuncNameFromInputSamplerName)(c),p=s.length,d=l.length,_=r.BroadcastUtil.getBroadcastDims(s,l),h=(0,a.getCoordsDataType)(d),f=d-p;let m;const g=(0,a.getGlChannels)();m=0===p?"":d<2&&_.length>=1?"coords = 0;":_.map((e=>`coords.${g[e+f]} = 0;`)).join("\n");let b="";b=d<2&&p>0?"coords":s.map(((e,t)=>`coords.${g[t+f]}`)).join(", ");let w="return outputValue;";const x=1===r.ShapeUtil.size(s),y=1===r.ShapeUtil.size(l);if(1!==p||x||y){if(x&&!y)w=1===d?"\n          return vec4(outputValue.x, outputValue.x, 0., 0.);\n        ":"\n          return vec4(outputValue.x);\n        ";else if(_.length){const e=p-2,t=p-1;_.indexOf(e)>-1&&_.indexOf(t)>-1?w="return vec4(outputValue.x);":_.indexOf(e)>-1?w="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":_.indexOf(t)>-1&&(w="return vec4(outputValue.xx, outputValue.zz);")}}else w="\n        return vec4(outputValue.xy, outputValue.xy);\n      ";const T=`\n      vec4 ${e}() {\n        ${h} coords = getOutputCoords();\n        \n        int lastDim = coords.${g[d-1]};\n        coords.${g[d-1]} = coords.${g[d-2]};\n        coords.${g[d-2]} = lastDim;\n      \n        ${m}\n        vec4 outputValue = ${u}(${b});\n        ${w}\n      }\n    `;return new o.GlslLibRoutine(T,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(e,t,n,i){const s=[n.width,n.height],l=[t.width,t.height],c=t.unpackedShape.length,u=n.unpackedShape.length,p=t.unpackedShape,d=n.unpackedShape,_=(0,a.generateShaderFuncNameFromInputSamplerName)(i);if(c===u&&r.ArrayUtil.arraysEqual(l,s)){const t=`\n          float ${e}() {\n            return sampleTexture(${i}, TexCoords);\n          }\n        `;return new o.GlslLibRoutine(t,["coordinates.sampleTexture"])}const h=(0,a.getCoordsDataType)(u),f=r.BroadcastUtil.getBroadcastDims(p,d),m=u-c;let g;const b=(0,a.getGlChannels)();g=0===c?"":u<2&&f.length>=1?"coords = 0;":f.map((e=>`coords.${b[e+m]} = 0;`)).join("\n");let w="";w=u<2&&c>0?"coords":t.unpackedShape.map(((e,t)=>`coords.${b[t+m]}`)).join(", ");const x=`\n        float ${e}() {\n          ${h} coords = getOutputCoords();\n          ${g}\n          return ${_}(${w});\n        }\n      `;return new o.GlslLibRoutine(x,["coordinates.getOutputCoords"])}getPackedSamplerFromInput(e,t,n){switch(n.unpackedShape.length){case 0:return this.getPackedSamplerScalar(e,t);case 1:return this.getPackedSampler1D(e,t,n);case 2:return this.getPackedSampler2D(e,t,n);case 3:return this.getPackedSampler3D(e,t,n);default:return this.getPackedSamplerND(e,t,n)}}getUnpackedSamplerFromInput(e,t,n){const r=n.unpackedShape;switch(r.length){case 0:return this.getUnpackedSamplerScalar(e,t,n);case 1:return this.getUnpackedSampler1D(e,t,n);case 2:return this.getUnpackedSampler2D(e,t,n);case 3:return this.getUnpackedSampler3D(e,t,n);case 4:return this.getUnpackedSampler4D(e,t,n);case 5:return this.getUnpackedSampler5D(e,t,n);case 6:return this.getUnpackedSampler6D(e,t,n);default:throw new Error(`Unsupported dimension ${r.length}-D`)}}getPackedSamplerScalar(e,t){const n=`\n          vec4 ${e}() {\n            return ${(0,i.getGlsl)(this.context.glContext.version).texture2D}(${t}, halfCR);\n          }\n        `;return new o.GlslLibRoutine(n)}getPackedSampler1D(e,t,n){const r=[n.width,n.height],s=[r[1],r[0]],a=(0,i.getGlsl)(this.context.glContext.version),l=`vec4 ${e}(int index) {\n      vec2 uv = packedUVfrom1D(\n      ${s[0]}, ${s[1]}, index);\n      return ${a.texture2D}(${t}, uv);\n    }`;return new o.GlslLibRoutine(l,["coordinates.packedUVfrom1D"])}getPackedSampler2D(e,t,n){const s=n.unpackedShape,a=[n.width,n.height],l=(0,i.getGlsl)(this.context.glContext.version),c=a[0],u=a[1];if(null!=a&&r.ArrayUtil.arraysEqual(s,a)){const n=`vec4 ${e}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${u}.0, ${c}.0);\n        return ${l.texture2D}(${t}, uv);\n      }`;return new o.GlslLibRoutine(n)}const p=a,d=Math.ceil(s[1]/2),_=`vec4 ${e}(int row, int col) {\n      vec2 uv = packedUVfrom2D(${p[1]}, ${p[0]}, ${d}, row, col);\n      return ${l.texture2D}(${t}, uv);\n    }`;return new o.GlslLibRoutine(_,["coordinates.packedUVfrom2D"])}getPackedSampler3D(e,t,n){const r=n.unpackedShape,s=[n.width,n.height],l=[s[0],s[1]],c=(0,i.getGlsl)(this.context.glContext.version);if(1===r[0]){const i=r.slice(1),s=[1,2],l=(0,a.squeezeInputShape)(r,i),c=["b","row","col"],u=JSON.parse(JSON.stringify(n));u.unpackedShape=l;const p=this.getPackedSamplerFromInput(e,t,u),d=`${p.routineBody}\n      vec4 ${e}(int b, int row, int col) {\n        return ${e}(${(0,a.getSqueezedParams)(c,s)});\n      } `;return new o.GlslLibRoutine(d,p.dependencies)}const u=l[0],p=l[1],d=Math.ceil(r[2]/2),_=`vec4 ${e}(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        ${p}, ${u}, ${d*Math.ceil(r[1]/2)}, ${d}, b, row, col);\n      return ${c.texture2D}(${t}, uv);}`;return new o.GlslLibRoutine(_,["coordinates.packedUVfrom3D"])}getPackedSamplerND(e,t,n){const r=n.unpackedShape,s=r.length,a=[n.width,n.height],l=(0,i.getGlsl)(this.context.glContext.version),c=[a[0],a[1]],u=c[1],p=c[0],d=Math.ceil(r[s-1]/2);let _=d*Math.ceil(r[s-2]/2),h="int b, int row, int col",f=`b * ${_} + (row / 2) * ${d} + (col / 2)`;for(let e=2;e<s-1;e++)h=`int b${e}, `+h,_*=r[s-e-1],f=`b${e} * ${_} + `+f;const m=`vec4 ${e}(${h}) {\n      int index = ${f};\n      int texR = index / ${p};\n      int texC = index - texR * ${p};\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}, ${u});\n      return ${l.texture2D}(${t}, uv);\n    }`;return new o.GlslLibRoutine(m)}getUnpackedSamplerScalar(e,t,n){const[r,i]=[n.width,n.height];if(1===r&&1===i){const n=`\n          float ${e}() {\n            return sampleTexture(${t}, halfCR);\n          }\n        `;return new o.GlslLibRoutine(n,["coordinates.sampleTexture"])}const s=`\n        float ${e}() {\n          int offset_${t} = coordsToOffset(TexCoords, ${r}, ${i});\n          vec2 uv = uvFromFlat(${r}, ${i}, offset_${t});\n          return sampleTexture(${t}, uv);\n        }\n      `;return new o.GlslLibRoutine(s,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler1D(e,t,n){const r=n.width,i=n.height;if(1===i&&1===r){const n=`\n        float ${e}(int index) {\n          return sampleTexture(${t}, halfCR);\n        }\n      `;return new o.GlslLibRoutine(n,["coordinates.sampleTexture"])}if(1===i){const n=`\n          float ${e}(int index) {\n            vec2 uv = vec2((float(index) + 0.5) / ${r}.0, 0.5);\n            return sampleTexture(${t}, uv);\n          }\n        `;return new o.GlslLibRoutine(n,["coordinates.sampleTexture"])}if(1===r){const n=`\n          float ${e}(int index) {\n            vec2 uv = vec2(0.5, (float(index) + 0.5) / ${i}.0);\n            return sampleTexture(${t}, uv);\n          }\n        `;return new o.GlslLibRoutine(n,["coordinates.sampleTexture"])}const s=`\n        float ${e}(int index) {\n          vec2 uv = uvFromFlat(${r}, ${i}, index);\n          return sampleTexture(${t}, uv);\n        }\n      `;return new o.GlslLibRoutine(s,["coordinates.uvFromFlat","coordinates.sampleTexture"])}getUnpackedSampler2D(e,t,n){const i=n.unpackedShape,l=[n.height,n.width];if(null!=l&&r.ArrayUtil.arraysEqual(i,l)){const n=`\n          float ${e}(int row, int col) {\n            vec2 uv = (vec2(row, col) + halfCR) / vec2(${l[1]}.0, ${l[0]}.0);\n            return sampleTexture(${t}, uv);\n          }\n        `;return new o.GlslLibRoutine(n,["coordinates.sampleTexture"])}const{newShape:c,keptDims:u}=(0,s.squeezeShape)(i),p=c;if(p.length<i.length){const r=(0,a.squeezeInputShape)(i,p),s=JSON.parse(JSON.stringify(n));s.unpackedShape=r;const l=["col","row"],c=`\n          ${this.getUnpackedSamplerFromInput(e,t,s).routineBody}\n          float ${e}(int row, int col) {\n            return ${e}(${(0,a.getSqueezedParams)(l,u)});\n          }\n        `;return new o.GlslLibRoutine(c,["coordinates.sampleTexture"])}const d=l[1],_=l[0];if(1===_){const n=`\n          float ${e}(int row, int col) {\n            int offset_${t} = coordsToOffset(TexCoords, ${d}, ${_});\n            float index = dot(vec3(row, col, offset_${t}), vec3(${i[1]}, 1, 1));\n            vec2 uv = vec2(0.5, (index + 0.5) / ${d}.0);\n            return sampleTexture(${t}, uv);\n          }\n        `;return new o.GlslLibRoutine(n,["coordinates.sampleTexture","coordinates.coordsToOffset"])}if(1===d){const n=`\n          float ${e}(int row, int col) {\n            int offset_${t} = coordsToOffset(TexCoords, ${d}, ${_});\n            float index = dot(vec3(row, col, offset_${t}), vec3(${i[1]}, 1, 1));\n            vec2 uv = vec2((index + 0.5) / ${_}.0, 0.5);\n            return sampleTexture(${t}, uv);\n          }\n        `;return new o.GlslLibRoutine(n,["coordinates.sampleTexture","coordinates.coordsToOffset"])}const h=`\n        float ${e}(int row, int col) {\n          int index = col * ${i[1]} + row;\n          vec2 uv = uvFromFlat(${d}, ${_}, index);\n          return sampleTexture(${t}, uv);\n        }\n      `;return new o.GlslLibRoutine(h,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler3D(e,t,n){const r=n.unpackedShape,i=r[1]*r[2],l=r[2],{newShape:c,keptDims:u}=(0,s.squeezeShape)(r),p=c;if(p.length<r.length){const i=(0,a.squeezeInputShape)(r,p),s=["batch","col","row"],l=JSON.parse(JSON.stringify(n));l.unpackedShape=i;const c=this.getUnpackedSamplerFromInput(e,t,l),d=u.reverse(),_=`\n          ${c.routineBody}\n          float ${e}(int batch, int row, int col) {\n            return ${e}(${(0,a.getSqueezedParams)(s,d)});\n          }\n        `;return new o.GlslLibRoutine(_,c.dependencies)}const d=`\n          float ${e}(int depth, int row, int col) {\n            // Explicitly use integer operations as dot() only works on floats.\n            int index = depth * ${i} + col * ${l} + row;\n            vec2 uv = uvFromFlat(${n.width}, ${n.height}, index);\n            return sampleTexture(${t}, uv);\n          }\n      `;return new o.GlslLibRoutine(d,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler4D(e,t,n){const r=n.unpackedShape,i=r[3],s=r[2]*i,a=`\n        float ${e}(int row, int col, int depth, int depth2) {\n          int index = row * ${r[1]*s} + col * ${s} +\n              depth2 * ${i} + depth;\n          vec2 uv = uvFromFlat(${n.width}, ${n.height}, index);\n          return sampleTexture(${t}, uv);\n        }\n      `;return new o.GlslLibRoutine(a,["coordinates.uvFromFlat","coordinates.sampleTexture"])}getUnpackedSampler5D(e,t,n){const r=n.unpackedShape,i=r[4],l=r[3]*i,c=r[2]*l,u=r[1]*c,{newShape:p,keptDims:d}=(0,s.squeezeShape)(r);if(p.length<r.length){const i=(0,a.squeezeInputShape)(r,p),s=["row","col","depth","depth2","depth3"],l=JSON.parse(JSON.stringify(n));l.unpackedShape=i;const c=`\n          ${this.getUnpackedSamplerFromInput(e,t,l).routineBody}\n          float ${e}(int row, int col, int depth, int depth2, int depth3) {\n            return ${e}(${(0,a.getSqueezedParams)(s,d)});\n          }\n        `;return new o.GlslLibRoutine(c,["coordinates.sampleTexture","coordinates.uvFromFlat"])}const _=`\n        float ${e}(int row, int col, int depth, int depth2, int depth3) {\n          int index = row * ${u} + col * ${c} + depth * ${l} +\n          depth3 * ${i} + depth2;\n          vec2 uv = uvFromFlat(${n.width}, ${n.height}, index);\n          return sampleTexture(${t}, uv);\n        }\n      `;return new o.GlslLibRoutine(_,["coordinates.sampleTexture","coordinates.uvFromFlat"])}getUnpackedSampler6D(e,t,n){const r=n.unpackedShape,i=r[5],l=r[4]*i,c=r[3]*l,u=r[2]*c,p=r[1]*u,{newShape:d,keptDims:_}=(0,s.squeezeShape)(r);if(d.length<r.length){const i=(0,a.squeezeInputShape)(r,d),s=["row","col","depth","depth2","depth3","depth4"],l=JSON.parse(JSON.stringify(n));l.unpackedShape=i;const c=`\n            ${this.getUnpackedSamplerFromInput(e,t,l).routineBody}\n            float ${e}(int row, int col, int depth,\n              int depth2, int depth3, int depth4) {\n              return ${e}(${(0,a.getSqueezedParams)(s,_)});\n            }\n          `;return new o.GlslLibRoutine(c,["coordinates.sampleTexture","coordinates.uvFromFlat"])}const h=`\n          float ${e}(int row, int col, int depth,\n            int depth2, int depth3, int depth4) {\n            int index = row * ${p} + col * ${u} + depth * ${c} +\n            depth2 * ${l} + depth3 * ${i} + depth4;\n            vec2 uv = uvFromFlat(${n.width}, ${n.height}, index);\n            return sampleTexture(${t}, uv);\n          }\n        `;return new o.GlslLibRoutine(h,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}toVec(){const e=this.context.outputTextureLayout,t=e.shape.length,n=e.strides,r=e.width,i=e.height,s=[];for(let e=0;e<t-1;++e)s.push(`\n        c[${e}] = offset / ${n[e]};`),s.push(`\n        offset -= c[${e}] * ${n[e]};`);s.push(`\n        c[${t-1}] = offset;`);const a=`\n      void toVec(vec2 texCoords, out int c[${t}]) {\n        int offset = coordsToOffset(texCoords, ${r}, ${i});\n        ${s.join("")}\n      }\n      void toVec(int offset, out int c[${t}]) {\n        ${s.join("")}\n      }\n    `;return{toVec:new o.GlslLibRoutine(a,["coordinates.coordsToOffset"])}}valueFrom(){const e={};return this.context.programInfo.inputNames.forEach(((t,n)=>{const r=this.context.inputTextureLayouts[n],i=(r.unpackedShape.length>0?r.unpackedShape:r.shape).length;let s=`_${t}`;e[s]=new o.GlslLibRoutine(this.getValueFromSingle(t,i,r.width,r.height,!1),[`shapeUtils.indicesToOffset${s}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"]),s+="_T",e[s]=new o.GlslLibRoutine(this.getValueFromSingle(t,i,r.width,r.height,!0),[`shapeUtils.indicesToOffset${s}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"])})),e}getValueFromSingle(e,t,n,r,o){let s=`_${e}`;return o&&(s+="_T"),`\n        float ${s}(int m[${t}]) {\n          int offset = indicesToOffset${s}(m);\n          vec2 coords = offsetToCoords(offset, ${n}, ${r});\n          float value = getColorAsFloat(${(0,i.getGlsl)(this.context.glContext.version).texture2D}(${e}, coords));\n          return value;\n        }\n        `}getPackedValueFrom(e,t,n,r,o){let s=`_${e}_Pack`;return o&&(s+="_T"),`\n        vec4 ${s}(int m[${t}]) {\n          int offset = indicesToOffset_${e}(m);\n          vec2 coords = offsetToCoords(offset, ${n}, ${r});\n          return ${(0,i.getGlsl)(this.context.glContext.version).texture2D}(${e}, coords);\n        }\n        `}}t.CoordsGlslLib=l},8520:(e,t)=>{var n;Object.defineProperty(t,"__esModule",{value:!0}),t.TopologicalSortGlslRoutines=t.GlslLibRoutineNode=t.GlslLibRoutine=t.GlslLib=t.GlslContext=t.FunctionType=void 0,(n=t.FunctionType||(t.FunctionType={}))[n.ValueBased=0]="ValueBased",n[n.Positional=1]="Positional",t.GlslContext=class{constructor(e,t,n,r){this.glContext=e,this.programInfo=t,this.inputTextureLayouts=n,this.outputTextureLayout=r}},t.GlslLib=class{constructor(e){this.context=e}},t.GlslLibRoutine=class{constructor(e,t){this.routineBody=e,this.dependencies=t}},t.GlslLibRoutineNode=class{constructor(e,t,n){this.name=e,this.dependencies=n||[],t&&(this.routineBody=t)}addDependency(e){e&&this.dependencies.push(e)}},t.TopologicalSortGlslRoutines=class{static returnOrderedNodes(e){if(!e||0===e.length)return[];if(1===e.length)return e;const t=new Set,n=new Set,r=new Array;return this.createOrderedNodes(e,t,n,r),r}static createOrderedNodes(e,t,n,r){for(let o=0;o<e.length;++o)this.dfsTraverse(e[o],t,n,r)}static dfsTraverse(e,t,n,r){if(!e||n.has(e.name))return;if(t.has(e.name))throw new Error("Cyclic dependency detected. Can't topologically sort routines needed for shader.");t.add(e.name);const o=e.dependencies;if(o&&o.length>0)for(let e=0;e<o.length;++e)this.dfsTraverse(o[e],t,n,r);r.push(e),n.add(e.name),t.delete(e.name)}}},7341:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.EncodingGlslLib=void 0;const r=n(8520);class o extends r.GlslLib{constructor(e){super(e)}getFunctions(){return Object.assign(Object.assign({},this.encodeFloat32()),this.decodeFloat32())}getCustomTypes(){return{}}encodeFloat32(){return{encode:new r.GlslLibRoutine("highp vec4 encode(highp float f) {\n        return vec4(f, 0.0, 0.0, 0.0);\n      }\n        ")}}decodeFloat32(){return{decode:new r.GlslLibRoutine("highp float decode(highp vec4 rgba) {\n        return rgba.r;\n      }\n        ")}}encodeUint8(){const e=o.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{encode:new r.GlslLibRoutine(`\n      highp vec4 encode(highp float f) {\n        highp float F = abs(f);\n        highp float Sign = step(0.0,-f);\n        highp float Exponent = floor(log2(F));\n        highp float Mantissa = (exp2(- Exponent) * F);\n        Exponent = floor(log2(F) + 127.0) + floor(log2(Mantissa));\n        highp vec4 rgba;\n        rgba[0] = 128.0 * Sign  + floor(Exponent*exp2(-1.0));\n        rgba[1] = 128.0 * mod(Exponent,2.0) + mod(floor(Mantissa*128.0),128.0);\n        rgba[2] = floor(mod(floor(Mantissa*exp2(23.0 -8.0)),exp2(8.0)));\n        rgba[3] = floor(exp2(23.0)*mod(Mantissa,exp2(-15.0)));\n        ${e}\n        rgba = rgba / 255.0; // values need to be normalized to [0,1]\n        return rgba;\n    }\n        `)}}decodeUint8(){const e=o.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{decode:new r.GlslLibRoutine(`\n        highp float decode(highp vec4 rgba) {\n          rgba = rgba * 255.0; // values need to be de-normalized from [0,1] to [0,255]\n          ${e}\n          highp float Sign = 1.0 - step(128.0,rgba[0])*2.0;\n          highp float Exponent = 2.0 * mod(rgba[0],128.0) + step(128.0,rgba[1]) - 127.0;\n          highp float Mantissa = mod(rgba[1],128.0)*65536.0 + rgba[2]*256.0 +rgba[3] + float(0x800000);\n          highp float Result =  Sign * exp2(Exponent) * (Mantissa * exp2(-23.0 ));\n          return Result;\n      }\n        `)}}static isLittleEndian(){const e=new ArrayBuffer(4),t=new Uint32Array(e),n=new Uint8Array(e);if(t[0]=3735928559,239===n[0])return!0;if(222===n[0])return!1;throw new Error("unknown endianness")}}t.EncodingGlslLib=o},9894:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.FragColorGlslLib=void 0;const r=n(8520),o=n(5060);class i extends r.GlslLib{constructor(e){super(e)}getFunctions(){return Object.assign(Object.assign({},this.setFragColor()),this.getColorAsFloat())}getCustomTypes(){return{}}setFragColor(){const e=(0,o.getGlsl)(this.context.glContext.version);return{setFragColor:new r.GlslLibRoutine(`\n        void setFragColor(float value) {\n            ${e.output} = encode(value);\n        }\n        `,["encoding.encode"])}}getColorAsFloat(){return{getColorAsFloat:new r.GlslLibRoutine("\n        float getColorAsFloat(vec4 color) {\n            return decode(color);\n        }\n        ",["encoding.decode"])}}}t.FragColorGlslLib=i},2848:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.replaceInlines=void 0;const n=/@inline[\s\n\r]+(\w+)[\s\n\r]+([0-9a-zA-Z_]+)\s*\(([^)]*)\)\s*{(([^}]|[\n\r])*)}/gm;t.replaceInlines=function(e){const t={};let r;for(;null!==(r=n.exec(e));){const e=r[3].split(",").map((e=>{const t=e.trim().split(" ");return t&&2===t.length?{type:t[0],name:t[1]}:null})).filter((e=>null!==e));t[r[2]]={params:e,body:r[4]}}for(const n in t){const o="(\\w+)?\\s+([_0-9a-zA-Z]+)\\s+=\\s+__FUNC__\\((.*)\\)\\s*;".replace("__FUNC__",n),i=new RegExp(o,"gm");for(;null!==(r=i.exec(e));){const o=r[1],i=r[2],s=r[3].split(","),a=o?`${o} ${i};`:"";let l=t[n].body,c="";t[n].params.forEach(((e,t)=>{e&&(c+=`${e.type} ${e.name} = ${s[t]};\n`)})),l=`${c}\n 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t=e.shaderSource;return this.context.programInfo.hasMain||(t=`${t}\n      ${(0,s.getDefaultFragShaderMain)(this.context.glContext.version,this.context.outputTextureLayout.shape.length)}`),t=(0,o.replaceInlines)(t),`${(0,s.getFragShaderPreamble)(this.context.glContext.version)}\n    ${this.getUniforms(e.inputNames,e.variables)}\n    ${this.getImports(t)}\n    ${t}`}getImports(e){const t=this.selectGlslLibRoutinesToBeIncluded(e);if(0===t.length)return"";let n="";for(let e=0;e<t.length;++e){if(!t[e].routineBody)throw new Error(`Missing body for the Glsl Library routine: ${t[e].name}`);n+=t[e].routineBody+"\n"}return n}selectGlslLibRoutinesToBeIncluded(e){const t=[];return Object.keys(this.glslLibRoutineDependencyGraph).forEach((n=>{const r=n.split(".")[1];-1!==e.indexOf(r)&&t.push(this.glslLibRoutineDependencyGraph[n])})),r.TopologicalSortGlslRoutines.returnOrderedNodes(t)}getUniforms(e,t){const n=[];if(e)for(const t of e)n.push(`uniform sampler2D ${t};`);if(t)for(const e of t)n.push(`uniform ${e.type} ${e.name}${e.arrayLength?`[${e.arrayLength}]`:""};`);return n.join("\n")}}},5483:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.glslRegistry=void 0;const r=n(5107),o=n(7341),i=n(9894),s=n(2655),a=n(3891);t.glslRegistry={encoding:o.EncodingGlslLib,fragcolor:i.FragColorGlslLib,vec:a.VecGlslLib,shapeUtils:s.ShapeUtilsGlslLib,coordinates:r.CoordsGlslLib}},2655:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ShapeUtilsGlslLib=void 0;const r=n(8520);class o extends r.GlslLib{constructor(e){super(e)}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.bcastIndex()),this.bcastMatmulIndex()),this.offsetToIndices()),this.indicesToOffset()),this.incrementIndices())}getCustomTypes(){return{}}bcastIndex(){const e=this.context.outputTextureLayout.shape.length,t={};return this.context.programInfo.inputNames.forEach(((n,o)=>{const i=this.context.inputTextureLayouts[o].unpackedShape;if(i.length<=e){const o=i.length,s=e-o,a=`bcastIndices_${n}`;let l="";for(let e=0;e<o;++e)l+=`\n          realIndices[${e}] = int( mod(float(bcastedIndices[${s+e}]), ${i[e]}.0) );\n          `;const c=`\n        void ${a} (int bcastedIndices[${e}], out int realIndices[${o}]) {\n          ${l}\n        }\n        `;t[a]=new r.GlslLibRoutine(c)}})),t}bcastMatmulIndex(){const e=this.context.outputTextureLayout.shape.length,t={};return this.context.programInfo.inputNames.forEach(((n,o)=>{const i=this.context.inputTextureLayouts[o].shape;if(!(i.length<2||i.length>e)){const o=i.length,s=e-o,a=`bcastMatmulIndices_${n}`;let l="";for(let e=0;e<o-2;++e)l+=`\n          realIndices[${e}] = int( mod(float(bcastedIndices[${s+e}]), ${i[e]}.0) );\n          `;const c=`\n        void ${a}(int bcastedIndices[${e}], out int realIndices[${o}]) {\n          ${l}\n          realIndices[${o-1}] = bcastedIndices[${e-1}];\n          realIndices[${o-2}] = bcastedIndices[${e-2}];\n        }\n        `;t[a]=new r.GlslLibRoutine(c)}})),t}indicesToOffset(){const e={};return this.context.programInfo.inputNames.forEach(((t,n)=>{const i=this.context.inputTextureLayouts[n].shape,s=this.context.inputTextureLayouts[n].strides,a=i.length;let l=`indicesToOffset_${t}`;e[l]=new r.GlslLibRoutine(o.indexToOffsetSingle(l,a,s)),l=`indicesToOffset_${t}_T`,e[l]=new r.GlslLibRoutine(o.indexToOffsetSingle(l,a,s.slice().reverse()))})),e}static indexToOffsetSingle(e,t,n){let r="";for(let e=t-1;e>=0;--e)r+=`\n        offset += indices[${e}] * ${n[e]};\n        `;return`\n      int ${e}(int indices[${t}]) {\n        int offset = 0;\n        ${r}\n        return offset;\n      }\n      `}offsetToIndices(){const e={};return this.context.programInfo.inputNames.forEach(((t,n)=>{const i=this.context.inputTextureLayouts[n].shape,s=this.context.inputTextureLayouts[n].strides,a=i.length;let l=`offsetToIndices_${t}`;e[l]=new r.GlslLibRoutine(o.offsetToIndicesSingle(l,a,s)),l=`offsetToIndices_${t}_T`,e[l]=new r.GlslLibRoutine(o.offsetToIndicesSingle(l,a,s.slice().reverse()))})),e}static offsetToIndicesSingle(e,t,n){const r=[];for(let e=0;e<t-1;++e)r.push(`\n      indices[${e}] = offset / ${n[e]};`),r.push(`\n        offset -= indices[${e}] * ${n[e]};`);return r.push(`\n      indices[${t-1}] = offset;`),`\n      void ${e}(int offset, out int indices[${t}]) {\n        ${r.join("")}\n      }\n      `}incrementIndices(){const e={};return this.context.programInfo.inputNames.forEach(((t,n)=>{const o=this.context.inputTextureLayouts[n].shape,i=o.length,s=`incrementIndices_${t}`;let a="";for(let e=0;e<i;++e)a+=`\n        shape[${e}] = ${o[e]};`;const l=`\n        void ${s}(int axis, out int indices[${i}]) {\n          int shape[${i}];\n          ${a};\n          for(int i = ${i} -1 ; i >= 0; --i) {\n            if(i > axis) continue;\n            indices[i] += 1;\n            if(indices[i] < shape[i]) {\n              break;\n            }\n            indices[i] = 0;\n          }\n        }\n        `;e[s]=new r.GlslLibRoutine(l)})),e}}t.ShapeUtilsGlslLib=o},5060:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.getDefaultFragShaderMain=t.getFragShaderPreamble=t.getVertexShaderSource=t.getGlsl=void 0;const n={version:"",attribute:"attribute",varyingVertex:"varying",varyingFrag:"varying",texture2D:"texture2D",output:"gl_FragColor",outputDeclaration:""},r={version:"#version 300 es",attribute:"in",varyingVertex:"out",varyingFrag:"in",texture2D:"texture",output:"outputColor",outputDeclaration:"out vec4 outputColor;"};function o(e){return 1===e?n:r}t.getGlsl=o,t.getVertexShaderSource=function(e){const t=o(e);return`${t.version}\n      precision highp float;\n      ${t.attribute} vec3 position;\n      ${t.attribute} vec2 textureCoord;\n\n      ${t.varyingVertex} vec2 TexCoords;\n\n      void main()\n      {\n          gl_Position = vec4(position, 1.0);\n          TexCoords = textureCoord;\n      }`},t.getFragShaderPreamble=function(e){const t=o(e);return`${t.version}\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    ${t.varyingFrag} vec2 TexCoords;\n    ${t.outputDeclaration}\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    // Custom vector types to handle higher dimenalities.\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    `},t.getDefaultFragShaderMain=function(e,t){return`\n  void main() {\n    int indices[${t}];\n    toVec(TexCoords, indices);\n    vec4 result = vec4(process(indices));\n    ${o(e).output} = result;\n  }\n  `}},3891:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.VecGlslLib=void 0;const r=n(8520);class o extends r.GlslLib{constructor(e){super(e)}getCustomTypes(){return{}}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign({},this.binaryVecFunctions()),this.copyVec()),this.setVecItem()),this.getVecItem())}binaryVecFunctions(){const e=this.context.outputTextureLayout.shape.length,t={add:"+=",sub:"-=",mul:"*=",div:"/="},n={};for(const o in t){const i=`${o}Vec`;let s="";for(let n=0;n<e;++n)s+=`\n          dest[${n}] ${t[o]} src[${n}];\n          `;const a=`\n        void ${i}(int src[${e}], out int dest[${e}]) {\n          ${s}\n        }\n        `;n[i]=new r.GlslLibRoutine(a)}return n}copyVec(){const e=this.context.outputTextureLayout.shape.length;let t="";for(let n=0;n<e;++n)t+=`\n        dest[${n}] = src[${n}];\n        `;const n=`\n      void copyVec(int src[${e}], out int dest[${e}]) {\n        ${t}\n      }\n      `;return{copyVec:new r.GlslLibRoutine(n)}}setVecItem(){const e=this.context.outputTextureLayout.shape.length;let t=`\n        if(index < 0)\n            index =${e} + index;\n        if (index == 0)\n            m[0] = value;\n        `;for(let n=1;n<e-1;++n)t+=`\n        else if (index == ${n})\n            m[${n}] = value;\n            `;t+=`\n        else\n            m[${e-1}] = value;\n        `;const n=`\n      void setVecItem(out int m[${e}], int index, int value) {\n        ${t}\n      }\n        `;return{setVecItem:new r.GlslLibRoutine(n)}}getVecItem(){const e=this.context.outputTextureLayout.shape.length;let t=`\n        if(index < 0)\n            index = ${e} + index;\n        if (index == 0)\n            return m[0];\n      `;for(let n=1;n<e-1;++n)t+=`\n        else if (index == ${n})\n            return m[${n}];\n      `;t+=`\n        else\n            return m[${e-1}];\n        `;const n=`\n      int getVecItem(int m[${e}], int index) {\n        ${t}\n      }\n    `;return{getVecItem:new r.GlslLibRoutine(n)}}}t.VecGlslLib=o},8316:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.WebGLInferenceHandler=void 0;const r=n(6231),o=n(9162),i=n(2517),s=n(2403),a=n(7019),l=n(8710),c=n(5611),u=n(4057),p=n(2039);t.WebGLInferenceHandler=class{constructor(e){this.session=e,this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new Map}calculateTextureWidthAndHeight(e,t){return(0,u.calculateTextureWidthAndHeight)(this.session.layoutStrategy,e,t)}executeProgram(e,t){if(t.length<e.inputNames.length)throw new Error(`Input size mustn't be less than ${e.inputNames.length}.`);if(e.inputNames.length!==e.inputTypes.length)throw new Error("input names size does not match input types");const n=[];for(let r=0;r<e.inputNames.length;++r)n[r]=this.getOrCreateTextureData(t[r],e.inputTypes[r]);const r=((e,t)=>{const n=t.map((e=>`${e.unpackedShape.join(",")};${e.width}x${e.height}`)).join("_");let r=e.name;return e.cacheHint&&(r+="["+e.cacheHint+"]"),r+=":"+n,r})(e,n);let o=this.session.programManager.getArtifact(r);const i=o?o.programInfo:"function"==typeof e.get?e.get():e,s=(0,u.createTextureLayoutFromTextureType)(this.session.layoutStrategy,i.output.dims,i.output.textureType),a=this.createTextureData(s,i.output.type);return o||(o=this.session.programManager.build(i,n,a),this.session.programManager.setArtifact(r,o)),this.runProgram(o,n,a),a}run(e,t){return this.executeProgram(e,t).tensor}runProgram(e,t,n){for(let n=0;n<t.length;++n)if(!!t[n].isPacked!=(e.programInfo.inputTypes[n]===p.TextureType.packed))throw new Error(`input[${n}] property packed inconsistent`);if(!!n.isPacked!=(e.programInfo.output.textureType===p.TextureType.packed))throw new Error("output property packed inconsistent");this.session.programManager.run(e,t,n)}getOrCreateTextureData(e,t){let n=this.getTextureData(e.dataId,t===p.TextureType.packed);if(!n&&(n=this.getTextureData(e.dataId,t!==p.TextureType.packed),n))return t===p.TextureType.packed?this.pack(n):this.unpack(n);if(!n){const r=(0,u.createTextureLayoutFromTextureType)(this.session.layoutStrategy,e.dims,t);if(t===p.TextureType.packedLastDimension){const n=1,r=4,o=e.dims;if(4===o.length){const i=[o[0],Math.ceil(o[1]*o[2]*o[3]/r)],s=(0,u.createTextureLayoutFromTextureType)(this.session.layoutStrategy,i,t);let a=e.numberData;if(o[1]*o[2]*o[3]%r!=0){const t=o[0],i=o[1]*o[2]*o[3],s=Math.ceil(i*n/r)*r;a=new Float32Array(t*s);for(let r=0;r<t;++r){const t=r*i,o=r*s+r%n*i;a.set(e.numberData.subarray(t,t+i),o)}}return this.createTextureData(s,e.type,a,e,1)}}if(t===p.TextureType.packed){const t=(0,u.createTextureLayoutFromShape)(this.session.layoutStrategy,e.dims,1,[],{reverseWH:!0}),r=this.createTextureData(t,e.type,e.numberData,e,1);n=this.pack(r)}else n=this.createTextureData(r,e.type,e.numberData,e,1)}return n}createTextureDataFromLayoutBindTensor(e,t,n,r){return this.createTextureData(e,t,n,r,1)}createTextureData(e,t,n,o,i){r.Logger.verbose("InferenceHandler",`Creating TextureData: layout:[${JSON.stringify(e)}]`);const s=this.session.textureManager.createTextureFromLayout(t,e,n,i);return this.createTextureDataFromTexture(e,t,s,o)}reshapeUnpacked(e,t){const n=this.getOrCreateTextureData(e,p.TextureType.unpacked),r={channels:n.channels,height:n.height,width:n.width,shape:0!==t.length?t:[1],strides:i.ShapeUtil.computeStrides(t),unpackedShape:t};return this.createTextureDataFromTexture(r,e.type,n.texture).tensor}reshapePacked(e,t){const n=this.getOrCreateTextureData(e,p.TextureType.packed);if((0,a.isReshapeCheap)(e.dims,t)){const r={channels:n.channels,height:n.height,width:n.width,shape:0!==t.length?t:[1],strides:i.ShapeUtil.computeStrides(t),unpackedShape:t,isPacked:!0};return this.createTextureDataFromTexture(r,e.type,n.texture).tensor}const r=(0,a.processDims3D)(e.dims),o=(0,a.processDims3D)(t),s=this.reshapePacked(e,r),l=this.run((0,a.createPackedReshape3DProgramInfoLoader)(this,s,o),[s]);return this.reshapePacked(l,t)}cast(e,t){const n=this.getOrCreateTextureData(e,p.TextureType.unpacked);return this.createTextureDataFromTexture(n,t,n.texture).tensor}createTextureDataFromTexture(e,t,n,r,i){const s=Object.assign(Object.assign({},e),{tensor:r||new o.Tensor(e.unpackedShape,t,(e=>this.readTexture(s)),(async e=>this.readTextureAsync(s)),void 0,i),texture:n});return this.setTextureData(s.tensor.dataId,s,e.isPacked),s}getTextureData(e,t=!1){return this.session.isInitializer(e)?this.session.getTextureData(e,t):t?this.packedTextureDataCache.get(e):this.unpackedTextureDataCache.get(e)}setTextureData(e,t,n=!1){this.session.isInitializer(e)?this.session.setTextureData(e,t,n):(n?this.packedTextureDataCache:this.unpackedTextureDataCache).set(e,t)}isTextureLayoutCached(e,t=!1){return!!this.getTextureData(e.dataId,t)}dispose(){this.session.textureManager.clearActiveTextures(),this.packedTextureDataCache.forEach((e=>this.session.textureManager.releaseTexture(e))),this.packedTextureDataCache=new 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0;const r=n(246),o=n(5060),i=n(2039),s={name:"BatchNormalization",inputNames:["A","Scale","B","Mean","Variance"],inputTypes:[i.TextureType.unpacked,i.TextureType.unpacked,i.TextureType.unpacked,i.TextureType.unpacked,i.TextureType.unpacked]};t.batchNormalization=(e,t,n)=>(l(t),[e.run(Object.assign(Object.assign({},s),{cacheHint:n.cacheKey,get:()=>a(e,t,n)}),t)]),t.parseBatchNormalizationAttributes=e=>{const t=e.attributes.getFloat("epsilon",1e-5),n=e.attributes.getFloat("momentum",.9),o=e.attributes.getInt("spatial",1);return(0,r.createAttributeWithCacheKey)({epsilon:t,momentum:n,spatial:o})};const a=(e,t,n)=>{const r=(0,o.getGlsl)(e.session.backend.glContext.version),a=t[0].dims.length,[l,c]=e.calculateTextureWidthAndHeight(t[1].dims,i.TextureType.unpacked),u=`\n  float process(int[${a}] indices) {\n    vec2 position = offsetToCoords(indices[1], ${l}, ${c});\n    float scale = getColorAsFloat(${r.texture2D}(Scale, position));\n    float mean = getColorAsFloat(${r.texture2D}(Mean, 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e="sub_";return{body:`\n  float ${e}(float a, float b) {\n    return a - b;\n  }\n  vec4 ${e}(vec4 v1, vec4 v2) {\n    return v1 - v2;\n  }\n  `,name:e,type:o.FunctionType.ValueBased}}function p(){const e="equal_";return{body:`\n  float ${e}(float a, float b) {\n    return float(a == b);\n  }\n  vec4 ${e}(vec4 v1, vec4 v2) {\n    return vec4(equal(v1, v2));\n  }\n  `,name:e,type:o.FunctionType.ValueBased}}function d(){const e="greater_";return{body:`\n  float ${e}(float a, float b) {\n    return float(a > b);\n  }\n  vec4 ${e}(vec4 v1, vec4 v2) {\n    return vec4( v1.r > v2.r ,\n      v1.g > v2.g,\n      v1.b > v2.b,\n      v1.a > v2.a );\n  }\n  `,name:e,type:o.FunctionType.ValueBased}}function _(){const e="less_";return{body:`\n  float ${e}(float a, float b) {\n    return float(a < b);\n  }\n  vec4 ${e}(vec4 v1, vec4 v2) {\n    return vec4( v1.r < v2.r ,\n                v1.g < v2.g,\n                v1.b < v2.b,\n                v1.a < v2.a );\n  }\n  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bvec4 b2 = bvec4(v2);\n    return vec4( b1.r ^^ b2.r ,\n                b1.g ^^ b2.g,\n                b1.b ^^ b2.b,\n                b1.a ^^ b2.a );\n  }\n  `,name:e,type:o.FunctionType.ValueBased}}function g(){return function(e){const t=`${e}_`;return{body:`\n  float ${t}(float a, float b) {\n    return ${e}(a, b);\n  }\n  vec4 ${t}(vec4 v1, vec4 v2) {\n    return ${e}(v1, v2);\n  }\n  `,name:t,type:o.FunctionType.ValueBased}}("pow")}function b(){const e="prelu_";return{body:`\n  float ${e}(float a, float b) {\n    return a < 0.0 ? a * b: a;\n  }\n  vec4 ${e}(vec4 v1, vec4 v2) {\n    return vec4(\n      v1.r < 0.0 ? v1.r * v2.r: v1.r,\n      v1.g < 0.0 ? v1.g * v2.g: v1.g,\n      v1.b < 0.0 ? v1.b * v2.b: v1.b,\n      v1.a < 0.0 ? v1.a * v2.a: v1.a\n      );\n  }\n  `,name:e,type:o.FunctionType.ValueBased}}t.glslAdd=a,t.glslDiv=l,t.glslMul=c,t.glslSub=u,t.glslEqual=p,t.glslGreater=d,t.glslLess=_,t.glslAnd=h,t.glslOr=f,t.glslXor=m,t.glslPow=g,t.glslPRelu=b;const w=(e,t,n,r=t[0].type,o)=>{const i=e.session.pack?s.TextureType.packed:s.TextureType.unpacked;return{name:n.name,inputNames:["A","B"],inputTypes:[i,i],cacheHint:o,get:()=>x(e,t,n,r)}},x=(e,t,n,o=t[0].type)=>{const a=e.session.pack?s.TextureType.packed:s.TextureType.unpacked,l=!r.ShapeUtil.areEqual(t[0].dims,t[1].dims);let c=t[0].dims;const u=e.session.pack;if(l){const s=r.BroadcastUtil.calcShape(t[0].dims,t[1].dims,!1);if(!s)throw new Error("Can't perform binary op on the given tensors");c=s;const l=c.length,p=0!==t[0].dims.length?t[0].dims.length:1,d=0!==t[1].dims.length?t[1].dims.length:1,_=0!==t[0].dims.length?"bcastIndices_A(indices, aindices);":"aindices[0] = 0;",h=0!==t[1].dims.length?"bcastIndices_B(indices, bindices);":"bindices[0] = 0;",f=(0,i.getGlsl)(e.session.backend.glContext.version),m=u?`\n      ${n.body}\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n        vec4 result = ${n.name}(a, b);\n        ${f.output} = result;\n   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r=n(246),o=n(2039),i=n(1163);t.concat=(e,t,n)=>(p(t),e.session.pack&&t[0].dims.length>1?[e.run((0,i.createPackedConcatProgramInfoLoader)(e,t,n),t)]:[e.run(s(e,t,n),t)]);const s=(e,t,n)=>{const r=(i=t.length,s=n.cacheKey,{name:"Concat",inputNames:Array.from({length:i},((e,t)=>`X${t}`)),inputTypes:Array(i).fill(o.TextureType.unpacked),cacheHint:s});var i,s;return Object.assign(Object.assign({},r),{get:()=>((e,t,n,r)=>{const i=n[0].dims.slice();if(r>=i.length||r<-1*i.length)throw new Error("axis specified for concat doesn't match input dimensionality");r<0&&(r=i.length+r);const s=i.slice(0);for(let e=1;e<n.length;e++){const t=n[e].dims.slice();for(let e=0;e<i.length;e++)if(e===r)s[r]+=t[e];else if(i[e]!==t[e])throw new Error("non concat dimensions must match")}const p=s.length,d=new Array(n.length);let _=0;for(let e=0;e<d.length;++e)_+=n[e].dims[r],d[e]=_;let h="";h=n.length<5?a(d):l(d);const f=`\n        ${c(n.length,p)}\n        ${u(d)}\n        ${h}\n        float process(int indices[${p}]) {\n          int textureIndex = getTextureWhereDataResides (indices[${r}]);\n\n          if(textureIndex != 0) {\n            indices[${r}] = indices[${r}] - int(getSizeInConcatAxisValueFromIndex(textureIndex-int(1)));\n          }\n\n          return fetchDataFromCorrectTexture(textureIndex, indices);\n        }`;return Object.assign(Object.assign({},t),{output:{dims:s,type:n[0].type,textureType:o.TextureType.unpacked},shaderSource:f})})(0,r,t,n.axis)})},a=e=>`int getTextureWhereDataResides(int index) {\n      ${e.map(((e,t)=>`if(index<${e}) {return ${t};}\n`)).join("")}\n    }`,l=e=>a(e),c=(e,t)=>{const n=[`float fetchDataFromCorrectTexture(int textureIndex, int indices[${t}]) {`];for(let t=0;t<e;++t)0===t?n.push(`\tif (textureIndex == ${t}) { return _X${t}(indices); }`):t===e-1?n.push(`\telse { return _X${t}(indices); }`):n.push(`\telse if (textureIndex == ${t}) { return _X${t}(indices); }`);return n.push("\t}"),n.join("\n")},u=e=>{const t=["int getSizeInConcatAxisValueFromIndex(int index) {"];for(let n=0;n<e.length;++n)0===n?t.push(`\tif (index == ${n}) { return ${e[n]}; }`):n===e.length-1?t.push(`\telse { return ${e[n]}; }`):t.push(`\telse if (index == ${n}) { return ${e[n]}; }`);return t.push("\t}"),t.join("\n")};t.parseConcatAttributes=e=>(0,r.createAttributeWithCacheKey)({axis:e.attributes.getInt("axis")});const p=e=>{if(!e||e.length<1)throw new Error("too few inputs");const t=e[0].type,n=e[0].dims.length;if("string"===t)throw new Error("string tensor is not supported yet");for(const r of e){if(r.type!==t)throw new Error("input tensors should be one type");if(r.dims.length!==n)throw new Error("input tensors should have the same shape")}}},4770:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createUnpackedGroupedConvProgramInfoLoader=void 0;const r=n(6231),o=n(5060),i=n(2039),s=n(8138),a=n(2823);t.createUnpackedGroupedConvProgramInfoLoader=(e,t,n)=>{const l=(c=t.length>2,u=n.cacheKey,{name:"GroupedConv",inputNames:c?["X","W","Bias"]:["X","W"],inputTypes:c?[i.TextureType.unpacked,i.TextureType.unpacked,i.TextureType.unpacked]:[i.TextureType.unpacked,i.TextureType.unpacked],cacheHint:u});var c,u;return Object.assign(Object.assign({},l),{get:()=>((e,t,n,l)=>{const c=t.length>2?"value += getBias(output_channel);":"",u=t[0].dims.slice(),p=t[1].dims.slice(),d=p[0]/l.group;r.Logger.verbose("GroupedConv",`autpPad:${l.autoPad}, dilations:${l.dilations}, group:${l.group}, kernelShape:${l.kernelShape}, pads:${l.pads}, strides:${l.strides}`);const _=(0,s.calculateOutputShape)(u,p,l.dilations,l.pads,l.strides),h=(0,o.getGlsl)(e.session.backend.glContext.version),{activationFunction:f,applyActivation:m}=(0,a.getActivationSnippet)(l),g=`\n  const ivec2 strides = ivec2(${l.strides[0]}, ${l.strides[1]});\n  const ivec2 pads = ivec2(${l.pads[0]}, ${l.pads[1]});\n  ${f}\n  void main() {\n    ivec4 coords = getOutputCoords();\n    int batch = coords.x;\n    int output_channel = coords.y;\n    ivec2 xRCCorner = coords.zw * strides - pads;\n    int group_id = output_channel / ${d};\n\n    float value = 0.0;\n    for (int wInChannel = 0; wInChannel < ${p[1]}; wInChannel++) {\n      int input_channel = group_id * ${p[1]} + wInChannel;\n      for (int wHeight = 0; wHeight < ${p[2]}; wHeight++) {\n        int xHeight = xRCCorner.x + wHeight * ${l.dilations[0]};\n\n        if (xHeight < 0 || xHeight >= ${u[2]}) {\n          continue;\n        }\n\n        for (int wWidth = 0; wWidth < ${p[3]}; wWidth++) {\n          int xWidth = xRCCorner.y + wWidth * ${l.dilations[1]};\n          if (xWidth < 0 || xWidth >= ${u[3]}) {\n            continue;\n          }\n\n          float xVal = getX(batch, input_channel, xWidth, xHeight);\n          float wVal = getW(output_channel, wInChannel, wWidth, wHeight);\n          value += xVal*wVal;\n        }\n      }\n    }\n    ${c}\n    ${m}\n    ${h.output} = vec4(value, .0, .0, .0);\n  }\n`;return Object.assign(Object.assign({},n),{output:{dims:_,type:t[0].type,textureType:i.TextureType.unpacked},shaderSource:g,hasMain:!0})})(e,t,l,n)})}},1386:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.conv2DPacked=t.conv2DPackedPointwise=void 0;const r=n(8138),o=n(8555),i=n(708);t.conv2DPackedPointwise=(e,t,n)=>{const o=t[0].dims,s=t[1].dims,a=(0,r.calculateOutputShape)(o,s,n.dilations,n.pads,n.strides),l=e.reshapePacked(t[0],[o[1],o[2]*o[3]]),c=e.reshapePacked(t[1],[s[0],s[1]]),u=t.length>2?[c,l,t[2]]:[c,l],p=e.run((0,i.createPackedMatmulProgramInfoLoader)(e,u,n),u);return e.reshapePacked(p,a)},t.conv2DPacked=(e,t,n)=>{const s=t[0].dims,a=t[1].dims,l=(0,r.calculateOutputShape)(s,a,n.dilations,n.pads,n.strides),c=e.run((0,o.createPackedIm2ColProgramInfoLoader)(e,t[0],t[1],l,n),[t[0]]),u=e.reshapePacked(t[1],[a[0],a[1]*a[2]*a[3]]),p=3===t.length?[u,c,t[2]]:[u,c],d=e.run((0,i.createPackedMatmulProgramInfoLoader)(e,p,n),p);return e.reshapePacked(d,l)}},9663:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseConvTransposeAttributes=t.convTranspose=void 0;const r=n(246),o=n(5060),i=n(2039),s=n(2823),a=(e,t,n,r,o,i)=>(e-1)*t+n+(r-1)*o+1-i,l=(e,t,n,r,o)=>{const i=Math.floor(e/2);"SAME_UPPER"===t?(n[r]=i,n[o]=e-i):"SAME_LOWER"===t&&(n[r]=e-i,n[o]=i)};t.convTranspose=(e,t,n)=>(d(t,n),c(e,t,n));const c=(e,t,n)=>{const r=p(n,t);return[u(e,t,r)]},u=(e,t,n)=>e.run(((e,t,n)=>{const r=(a=t.length>2,l=n.cacheKey,{name:"ConvTranspose",inputNames:a?["X","W","B"]:["X","W"],inputTypes:a?[i.TextureType.unpacked,i.TextureType.unpacked,i.TextureType.unpacked]:[i.TextureType.unpacked,i.TextureType.unpacked],cacheHint:l});var a,l;return Object.assign(Object.assign({},r),{get:()=>((e,t,n,r)=>{const a=t.length>2?"getB(output_channel)":"0.0",l=t[0].dims,c=t[1].dims,u=c[1],p=c[0]/r.group,d=[t[0].dims[0],t[1].dims[1]*r.group,...r.outputShape],_=(0,o.getGlsl)(e.session.backend.glContext.version),{activationFunction:h,applyActivation:f}=(0,s.getActivationSnippet)(r),m=`\n  const ivec2 strides = ivec2(${r.strides[0]}, ${r.strides[1]});\n  const ivec2 pads = ivec2(${r.pads[0]}, ${r.pads[1]});\n  ${h}\n  void main() {\n    ivec4 coords = getOutputCoords();\n    int batch = coords.x;\n    int output_channel = coords.y;\n\n    ivec2 loc = coords.zw + pads;\n\n    int group_id = output_channel / ${u};\n    int wOutChannel = output_channel - group_id * ${u};\n\n    float value = ${a};\n    for (int inChannelOffset = 0; inChannelOffset < ${p}; inChannelOffset++) {\n      int input_channel = group_id * ${p} + inChannelOffset;\n      for (int wWOff = 0; wWOff < ${c[2]}; wWOff++) {\n        for (int wHOff = 0; wHOff < ${c[3]}; wHOff++) {\n          ivec2 wOff = ivec2(wWOff * ${r.dilations[0]}, wHOff * ${r.dilations[1]});\n          ivec2 wLoc = loc - wOff;\n          ivec2 wLocIn = wLoc / strides;\n          if (\n            wLocIn * strides == wLoc &&\n            wLocIn.x >= 0 && wLocIn.x < ${l[2]} &&\n            wLocIn.y >= 0 && wLocIn.y < ${l[3]}\n          ) {\n            float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x);\n            float wVal = getW(input_channel, wOutChannel, wHOff, wWOff);\n            value += xVal * wVal;\n          }\n        }\n      }\n    }\n    ${f}\n    ${_.output} = vec4(value, .0, .0, .0);\n  }\n`;return Object.assign(Object.assign({},n),{output:{dims:d,type:t[0].type,textureType:i.TextureType.unpacked},shaderSource:m,hasMain:!0})})(e,t,r,n)})})(e,t,n),t),p=(e,t)=>{const n=e.kernelShape.slice();if(0===e.kernelShape.length)for(let e=2;e<t[1].dims.length;++e)n.push(t[1].dims[e]);const r=e.pads.slice(),o=e.outputShape.slice();((e,t,n,r,o,i,s,c)=>{const u=e.length-2,p=0===c.length;for(let d=0;d<u;++d){const _=p?e[d+2]*i[d]:c[d],h=a(e[d+2],i[d],o[d],t[d],n[d],_);l(h,r,o,d,d+u),p&&c.push(i[d]*(e[d+2]-1)+s[d]+(t[d]-1)*n[d]+1-o[d]-o[d+u])}})(t[0].dims,n,e.dilations,e.autoPad,r,e.strides,e.outputPadding,o);const i=Object.assign({},e);return Object.assign(i,{kernelShape:n,pads:r,outputShape:o,cacheKey:e.cacheKey}),i};t.parseConvTransposeAttributes=e=>{const t=e.attributes,n=(0,s.parseInternalActivationAttributes)(t),o=t.getString("auto_pad","NOTSET"),i=t.getInts("dilations",[1,1]),a=t.getInt("group",1),l=t.getInts("kernel_shape",[]),c=t.getInts("output_padding",[0,0]),u=t.getInts("output_shape",[]),p=t.getInts("pads",[0,0,0,0]),d=t.getInts("strides",[1,1]);return(0,r.createAttributeWithCacheKey)(Object.assign({autoPad:o,dilations:i,group:a,kernelShape:l,outputPadding:c,outputShape:u,pads:p,strides:d},n))};const d=(e,t)=>{if(!e||2!==e.length&&3!==e.length)throw new Error("Conv requires 2 or 3 inputs");if(4!==e[0].dims.length||4!==e[1].dims.length)throw new Error("currently only support 2-dimensional conv");if(e[0].dims[1]!==e[1].dims[0])throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");const n=e[1].dims[1]*t.group;if(3===e.length&&(1!==e[2].dims.length||e[2].dims[0]!==n))throw new Error("invalid bias");const r=e[0].dims.length-2;if(t.dilations.length!==r)throw new Error(`dilations should be ${r}D`);if(t.strides.length!==r)throw new Error(`strides should be ${r}D`);if(t.pads.length!==2*r)throw new Error(`pads should be ${2*r}D`);if(t.outputPadding.length!==r)throw new Error(`output_padding should be ${r}D`);if(0!==t.kernelShape.length&&t.kernelShape.length!==e[1].dims.length-2)throw new Error("invalid kernel shape");if(0!==t.outputShape.length&&t.outputShape.length!==e[0].dims.length-2)throw new Error("invalid output shape");if("float32"!==e[0].type||"float32"!==e[1].type)throw new Error("ConvTranspose input(X,W) should be float tensor");if(3===e.length&&"float32"!==e[2].type)throw new Error("ConvTranspose input(bias) should be float tensor")}},8138:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseConvAttributes=t.conv=t.calculateOutputShape=void 0;const r=n(246),o=n(2517),i=n(4770),s=n(1386),a=n(9828),l=n(2823),c=n(3248),u=n(5623);t.calculateOutputShape=(e,t,n,r,o)=>{const i=e[0],s=e.slice(2),a=s.length,l=t[0],c=t.slice(2).map(((e,t)=>e+(e-1)*(n[t]-1))),u=s.map(((e,t)=>e+r[t]+r[t+a])).map(((e,t)=>Math.floor((e-c[t]+o[t])/o[t])));return[i,l].concat(...u)},t.conv=(e,t,n)=>(f(t,n),p(e,t,n));const p=(e,t,n)=>{const r=h(n,t),o=e.session.pack,a=1===r.kernelShape[0]&&1===r.kernelShape[1];return r.group>1?[e.run((0,i.createUnpackedGroupedConvProgramInfoLoader)(e,t,r),t)]:a&&o?[d(e,t,r)]:o&&4===t[0].dims.length&&1===t[0].dims[0]&&!a?[(0,s.conv2DPacked)(e,t,r)]:[_(e,t,r)]},d=(e,n,r)=>{const o=n[0].dims,i=n[1].dims,s=(0,t.calculateOutputShape)(o,i,r.dilations,r.pads,r.strides),a=e.reshapeUnpacked(n[0],[o[1],o[2]*o[3]]),l=e.reshapeUnpacked(n[1],[i[0],i[1]]),c=n.length>2?[l,a,n[2]]:[l,a],p=e.run((0,u.createMatmulProgramInfoLoader)(c,r),c);return e.reshapeUnpacked(p,s)},_=(e,n,r)=>{const o=n[0].dims,i=n[1].dims,s=(0,t.calculateOutputShape)(o,i,r.dilations,r.pads,r.strides),l=e.run((0,c.createIm2ColProgramInfoLoader)(e,n[0],n[1],s,r),[n[0]]),u=3===n.length?[l,n[1],n[2]]:[l,n[1]];return e.run((0,a.createDotProductProgramInfoLoader)(e,n,s,r),u)},h=(e,t)=>{const n=e.kernelShape.slice();if(0===e.kernelShape.length)for(let e=2;e<t[1].dims.length;++e)n.push(t[1].dims[e]);const r=e.pads.slice();o.PoolConvUtil.adjustPadsBasedOnAutoPad(t[0].dims,e.strides,e.dilations,n,r,e.autoPad);const i=Object.assign({},e);return Object.assign(i,{kernelShape:n,pads:r,cacheKey:e.cacheKey}),i};t.parseConvAttributes=e=>{const t=e.attributes,n=(0,l.parseInternalActivationAttributes)(t),o=t.getString("auto_pad","NOTSET"),i=t.getInts("dilations",[1,1]),s=t.getInt("group",1),a=t.getInts("kernel_shape",[]),c=t.getInts("pads",[0,0,0,0]),u=t.getInts("strides",[1,1]);return(0,r.createAttributeWithCacheKey)(Object.assign({autoPad:o,dilations:i,group:s,kernelShape:a,pads:c,strides:u},n))};const f=(e,t)=>{if(!e||2!==e.length&&3!==e.length)throw new Error("Conv requires 2 or 3 inputs");if(4!==e[0].dims.length||4!==e[1].dims.length)throw new Error("currently only support 2-dimensional conv");if(e[0].dims[1]!==e[1].dims[1]*t.group)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(3===e.length&&(1!==e[2].dims.length||e[1].dims[0]!==e[2].dims[0]))throw new Error("invalid bias");const n=e[0].dims.length-2;if(t.dilations.length!==n)throw new Error(`dilations should be ${n}D`);if(t.strides.length!==n)throw new Error(`strides should be ${n}D`);if(t.pads.length!==2*n)throw new Error(`pads should be ${2*n}D`);if(0!==t.kernelShape.length&&t.kernelShape.length!==e[1].dims.length-2)throw new Error("invalid kernel shape");if("float32"!==e[0].type||"float32"!==e[1].type)throw new Error("Conv input(X,W) should be float tensor");if(3===e.length&&"float32"!==e[2].type)throw new Error("Conv input(bias) should be float tensor")}},5193:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseDepthToSpaceAttributes=t.depthToSpace=void 0;const r=n(3738);t.depthToSpace=(e,t,n)=>{o(t);const i=n.blocksize,s=i*i,a="DCR"===n.mode?[0,3,4,1,5,2]:[0,1,4,2,5,3],l="DCR"===n.mode?[t[0].dims[0],i,i,t[0].dims[1]/s,t[0].dims[2],t[0].dims[3]]:[t[0].dims[0],t[0].dims[1]/s,i,i,t[0].dims[2],t[0].dims[3]],c=e.reshapeUnpacked(t[0],l),u={perm:a,cacheKey:`${a}`},[p]=(0,r.transpose)(e,[c],u),d=[t[0].dims[0],t[0].dims[1]/s,t[0].dims[2]*i,t[0].dims[3]*i];return[e.reshapeUnpacked(p,d)]},t.parseDepthToSpaceAttributes=e=>{const t=e.attributes.getInt("blocksize");if(t<1)throw new Error(`blocksize must be >= 1, but got : ${t} for DepthToSpace`);const n=e.attributes.getString("mode","DCR");if("DCR"!==n&&"CRD"!==n)throw new Error(`unrecognized mode: ${n} for DepthToSpace`);return{mode:n,blocksize:t}};const o=e=>{if(1!==e.length)throw new Error(`DepthToSpace expect 1 inputs, but got ${e.length}`);if("string"===e[0].type||4!==e[0].dims.length)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}},9828:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createDotProductProgramInfoLoader=void 0;const r=n(2517),o=n(5060),i=n(2039),s=n(2823),a=n(3248);t.createDotProductProgramInfoLoader=(e,t,n,l)=>{const c=((e,t)=>({name:"ConvDotProduct",inputNames:e?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:e?[i.TextureType.unpacked,i.TextureType.packedLastDimension,i.TextureType.unpacked]:[i.TextureType.unpacked,i.TextureType.packedLastDimension],cacheKey:t.activationCacheKey}))(t.length>2,l);return Object.assign(Object.assign({},c),{get:()=>((e,t,n,l,c)=>{const u=n[0].dims,p=n[1].dims,d=[p[0],Math.ceil(u[1]*p[2]*p[3]/4)],_=(0,a.calculateIm2ColDims)(u,p,l),[h,f]=e.calculateTextureWidthAndHeight(d,i.TextureType.packedLastDimension),m=r.ShapeUtil.computeStrides(_),[g,b]=e.calculateTextureWidthAndHeight(_,i.TextureType.packedLastDimension),w=l.length,x=n.length<3?"0.0":"_B(b)",y=Math.ceil(u[1]*p[2]*p[3]/4),{activationFunction:T,applyActivation:v}=(0,s.getActivationSnippet)(c),k=(0,o.getGlsl)(e.session.backend.glContext.version),M=`\n${T}\nfloat process(int indices[${w}]) {\n  int b[1];\n  b[0] = indices[1];\n  int im2col[4];\n  im2col[0] = indices[0];\n  im2col[1] = indices[2];\n  im2col[2] = indices[3];\n  int im2colOffset = im2col[0] * ${m[0]} + im2col[1] * ${m[1]} + im2col[2] * ${m[2]};\n  int kernelOffset = indices[1] * ${d[1]};\n  float value = ${x};\n  for (int i = 0; i < ${y}; ++i) {\n    vec2 im2colCoords = offsetToCoords(im2colOffset, ${g}, ${b});\n    vec2 kernelCoords = offsetToCoords(kernelOffset, ${h}, ${f});\n    value += dot(${k.texture2D}(Im2Col, im2colCoords), ${k.texture2D}(K, kernelCoords));\n    ++im2colOffset;\n    ++kernelOffset;\n  }\n  ${v}\n  return value;\n}`;return Object.assign(Object.assign({},t),{output:{dims:l,type:n[0].type,textureType:i.TextureType.unpacked},shaderSource:M})})(e,c,t,n,l)})}},7992:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseFlattenAttributes=t.flatten=void 0;const r=n(2517);t.flatten=(e,t,n)=>{o(t,n);const i=r.ShapeUtil.flattenShape(t[0].dims,n);return[e.reshapeUnpacked(t[0],i)]},t.parseFlattenAttributes=e=>e.attributes.getInt("axis",1);const o=(e,t)=>{if(!e||1!==e.length)throw new Error("Flatten requires 1 input.");const n=e[0].dims.length;if(0===n)throw new Error("scalar tensor is not supported.");if(t<-n||t>n)throw new Error("Invalid axis");if("string"===e[0].type)throw new Error("string tensor is not supported.")}},2823:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseInternalActivationAttributes=t.getActivationSnippet=void 0;const r=n(2517),o=n(4909);t.getActivationSnippet=function(e){let t;switch(e.activation){case"Relu":t=(0,o.glslRelu)();break;case"Sigmoid":t=(0,o.glslSigmoid)();break;case"Clip":t=(0,o.glslClip)(e.clipMin,e.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const n=t.name;return{activationFunction:t.body,applyActivation:`value = ${n}_(value);`}},t.parseInternalActivationAttributes=e=>{const t=e.getString("activation","");if("Clip"===t){const[n,o]=e.getFloats("activation_params",[r.MIN_CLIP,r.MAX_CLIP]);return{activation:t,clipMax:o,clipMin:n,activationCacheKey:`${t}:${n},${o}`}}return{activation:t,activationCacheKey:t}}},1253:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseGatherAttributes=t.gather=void 0;const r=n(246),o=n(782),i=n(2517),s=n(2039);t.gather=(e,t,n)=>(c(t,n.axis),[e.run(l(e,t,n),t)]),t.parseGatherAttributes=e=>(0,r.createAttributeWithCacheKey)({axis:e.attributes.getInt("axis",0)});const a={name:"Gather",inputNames:["A","B"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked]},l=(e,t,n)=>{const r=Object.assign(Object.assign({},a),{cacheHint:n.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((e,t,n,r)=>{const o=n[0].dims.slice(),a=n[1].dims.slice(),l=new Array(o.length+a.length-1);r=i.ShapeUtil.normalizeAxis(r,o.length);const c=[];for(let e=0;e<l.length;e++)e<r?(l[e]=o[e],c.push(`inputIdx[${e}] = outputIdx[${e}];`)):e<r+a.length?(l[e]=a[e-r],c.push(`indexDataIdx[${e-r}] = outputIdx[${e}];`)):(l[e]=o[e-a.length+1],c.push(`inputIdx[${e-a.length+1}] = outputIdx[${e}];`));const u=`\n      float process(int outputIdx[${l.length||1}]) {\n        int inputIdx[${o.length}];\n        int indexDataIdx[${a.length||1}];\n        indexDataIdx[0] = 0;\n        ${c.join("\n        ")}\n        int idx = int(_B(indexDataIdx));\n        inputIdx[${r}] = idx < 0 ? idx + ${o[r]} : idx;\n        return _A(inputIdx);\n      }`;return Object.assign(Object.assign({},t),{output:{dims:l,type:n[0].type,textureType:s.TextureType.unpacked},shaderSource:u})})(0,r,t,n.axis)})},c=(e,t)=>{if(!e||2!==e.length)throw new Error("Gather requires 2 inputs.");const n=e[0].dims.length;if(n<1)throw new Error("Invalid input shape.");if(t<-n||t>n-1)throw new Error("Invalid axis.");if(-1===o.NUMBER_TYPES.indexOf(e[0].type))throw new Error("Invaid input type.");if("int32"!==e[1].type&&"int16"!==e[1].type)throw new Error("Invaid input type.")}},4776:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseGemmAttributesV11=t.parseGemmAttributesV7=t.gemm=void 0;const r=n(246),o=n(2517),i=n(2039);t.gemm=(e,t,n)=>(c(t,n),[e.run(a(t,n),t)]);const s=(e,t)=>{const n=0!==e.attributes.getInt("transA",0),o=0!==e.attributes.getInt("transB",0),i=e.attributes.getFloat("alpha",1),s=e.attributes.getFloat("beta",1);return(0,r.createAttributeWithCacheKey)({transA:n,transB:o,alpha:i,beta:s,isOptionalC:t})};t.parseGemmAttributesV7=e=>s(e,!1),t.parseGemmAttributesV11=e=>s(e,!0);const a=(e,t)=>{const n={name:"Gemm",inputNames:3===e.length?["A","B","C"]:["A","B"],inputTypes:3===e.length?[i.TextureType.unpacked,i.TextureType.unpacked,i.TextureType.unpacked]:[i.TextureType.unpacked,i.TextureType.unpacked],key:t.cacheKey};return Object.assign(Object.assign({},n),{get:()=>l(n,e,t)})},l=(e,t,n)=>{const r=t[0].dims.slice(),s=t[1].dims.slice(),[a,l]=o.GemmUtil.getShapeOfGemmResult(r,n.transA,s,n.transB,3===t.length?t[2].dims:void 0),c=[a,l];if(!c)throw new Error("Can't use gemm on the given tensors");let u=r[r.length-1],p="";n.transA&&(u=r[0]),n.transA&&n.transB?p="value += _A_T(a) * _B_T(b);":n.transA&&!n.transB?p="value += _A_T(a) * _B(b);":!n.transA&&n.transB?p="value += _A(a) * _B_T(b);":n.transA||n.transB||(p="value += _A(a) * _B(b);");const d=c.length,_=`\n      float process(int indices[${d}]) {\n          int a[${d}];\n          int b[${d}];\n          ${3===t.length?`int c[${t[2].dims.length}];`:""}\n\n          copyVec(indices, a);\n          copyVec(indices, b);\n          ${3===t.length?"bcastIndices_C(indices, c);":""}\n\n          float value = 0.0;\n          for (int k=0; k<${u}; ++k) {\n              a[${d-1}] = k;\n              b[${d-2}] = k;\n              ${p}\n          }\n\n          value = value * alpha;\n          ${3===t.length?"value += beta * _C(c);":""}\n          return value;\n      }`;return Object.assign(Object.assign({},e),{output:{dims:c,type:t[0].type,textureType:i.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:n.alpha},{name:"beta",type:"float",data:n.beta}],shaderSource:_})},c=(e,t)=>{if(!e)throw new Error("Input is missing");if(t.isOptionalC&&(e.length<2||e.length>3))throw new Error("Invaid input shape.");if(!t.isOptionalC&&3!==e.length)throw new Error("Gemm requires 3 inputs");if(3===e.length&&1!==e[2].dims.length&&2!==e[2].dims.length)throw new Error("Invalid input shape of C");if("float32"!==e[0].type&&"float64"!==e[0].type||"float32"!==e[1].type&&"float64"!==e[1].type||3===e.length&&"float32"!==e[2].type&&"float64"!==e[2].type)throw new Error("Invalid input type.");if(e[0].type!==e[1].type||3===e.length&&e[0].type!==e[2].type)throw new Error("Input types are mismatched")}},8555:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createPackedIm2ColProgramInfoLoader=void 0;const r=n(5060),o=n(2039),i=n(2827);t.createPackedIm2ColProgramInfoLoader=(e,t,n,s,a)=>{const l=(c=a.cacheKey,{name:"Im2Col (packed)",inputNames:["A"],inputTypes:[o.TextureType.packed],cacheHint:c});var c;return Object.assign(Object.assign({},l),{get:()=>((e,t,n,s,a,l)=>{const c=n.dims,u=s.dims,p=a.length,d=[u[1]*u[2]*u[3],a[2]*a[3]],_=u[2]*u[3],h=(0,i.unpackFromChannel)(),f=(0,r.getGlsl)(e.session.backend.glContext.version);let m="";for(let e=0;e<=1;e++)for(let t=0;t<=1;t++)m+=`\n            blockIndex = rc.x + ${t};\n            pos = rc.y + ${e};\n\n            if(blockIndex < ${d[1]} && pos < ${d[0]}) {\n              offsetY = int(blockIndex / (${a[p-1]})) * ${l.strides[0]} -\n                ${l.pads[0]};\n              d0 = offsetY + ${l.dilations[0]} * (imod(pos, ${_}) / ${u[2]});\n\n              if(d0 < ${c[2]} && d0 >= 0) {\n                offsetX = imod(blockIndex, ${a[p-1]}) * ${l.strides[1]} -\n                  ${l.pads[1]};\n                d1 = offsetX + ${l.dilations[1]} * imod(imod(pos, ${_}), ${u[2]});\n\n                if(d1 < ${c[3]} && d1 >= 0) {\n\n                  ch = int(float(pos)/ ${_}.);\n                    innerDims = vec2(d0, d1);\n                    result[${2*e+t}] = getChannel(\n                      getA(0, ch, int(innerDims.x),\n                      int(innerDims.y)), innerDims);\n                }\n              }\n            }\n\n          `;const g=`\n      ${h}\n\n      void main() {\n        ivec2 rc = getOutputCoords();\n          vec4 result = vec4(0.0);\n          int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n          vec2 innerDims;\n          ${m}\n          ${f.output} = result;\n      }\n            `;return Object.assign(Object.assign({},t),{output:{dims:d,type:n.type,textureType:o.TextureType.packed},shaderSource:g,hasMain:!0})})(e,l,t,n,s,a)})}},3248:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.calculateIm2ColDims=t.createIm2ColProgramInfoLoader=void 0;const r=n(2039);t.createIm2ColProgramInfoLoader=(e,n,o,i,s)=>{const a=(l=s.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[r.TextureType.unpacked],cacheHint:l});var l;return Object.assign(Object.assign({},a),{get:()=>((e,n,o,i,s,a)=>{const l=o.dims,c=i.dims,u=s.length,p=(0,t.calculateIm2ColDims)(l,c,s,4),d=`\n        const int XC = ${l[1]};\n        const int XH = ${l[2]};\n        const int XW = ${l[3]};\n        const int KH = ${a.kernelShape[0]};\n        const int KW = ${a.kernelShape[1]};\n        const int dilationH = ${a.dilations[0]};\n        const int dilationW = ${a.dilations[1]};\n        const int strideH = ${a.strides[0]};\n        const int strideW = ${a.strides[1]};\n        const int padH = ${a.pads[0]};\n        const int padW = ${a.pads[1]};\n        const int KHKW = KH*KW;\n        const int XCKHKW = XC * KHKW;\n        const int outputChannels = 4;\n        vec4 process(int indices[${u}]) {\n          int b  = indices[0]; // batch size\n          int oh = indices[1] * strideH - padH; //output height\n          int ow = indices[2] * strideW - padW; //output width\n          int p = indices[3] * outputChannels; //patch\n          vec4 value = vec4(0.0);\n          for(int i=0; i < outputChannels; ++i) {\n            if(p < XCKHKW) {\n              int patchC = p / KHKW;\n              int patchH = (p - patchC*KHKW) / KW;\n              int patchW = (p - patchC*KHKW) - patchH * KW;\n              int xh2 = oh + patchH * dilationH;\n              int xw2 = ow + patchW * dilationW;\n              int x[${l.length}];\n              x[0] = b;\n              x[1] = patchC;\n              x[2] = xh2;\n              x[3] = xw2;\n              if(xh2 >= 0 &&\n                  xh2 < XH &&\n                  xw2 >= 0 &&\n                  xw2 < XW) {\n                value[i] = _X(x);\n              }\n            }\n            ++p;\n          }\n          return value;\n        }\n        `;return Object.assign(Object.assign({},n),{output:{dims:p,type:o.type,textureType:r.TextureType.packedLastDimension},shaderSource:d})})(0,a,n,o,i,s)})},t.calculateIm2ColDims=(e,t,n,r=4)=>[n[0],n[2],n[3],Math.ceil(e[1]*t[2]*t[3]/r)]},6572:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseImageScalerAttributes=t.imageScaler=void 0;const r=n(246),o=n(2039);t.imageScaler=(e,t,n)=>(l(t),[e.run(s(e,t,n),t)]),t.parseImageScalerAttributes=e=>{const t=e.attributes.getFloat("scale"),n=e.attributes.getFloats("bias");return(0,r.createAttributeWithCacheKey)({scale:t,bias:n})};const i={name:"ImageScaler",inputNames:["X"],inputTypes:[o.TextureType.unpacked]},s=(e,t,n)=>{const r=Object.assign(Object.assign({},i),{cacheHint:n.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((e,t,n,r)=>{const i=n[0].dims.slice(),s=i.length,l=`\n      ${a(r.bias.length)}\n      float process(int indices[${s}]) {\n        return _X(indices) * scale + getBias(bias, indices[1]);\n      }`;return Object.assign(Object.assign({},t),{output:{dims:i,type:n[0].type,textureType:o.TextureType.unpacked},variables:[{name:"bias",type:"float",arrayLength:r.bias.length,data:r.bias},{name:"scale",type:"float",data:r.scale}],shaderSource:l})})(0,r,t,n)})},a=e=>{const t=[`float getBias(float bias[${e}], int channel) {`];for(let n=0;n<e;++n)0===n?t.push(`\tif (channel == ${n}) { return bias[${n}]; }`):n===e-1?t.push(`\telse { return bias[${n}]; }`):t.push(`\telse if (channel == ${n}) { return bias[${n}]; }`);return t.push("\t}"),t.join("\n")},l=e=>{if(!e||1!==e.length)throw new Error("ImageScaler requires 1 input.");if(4!==e[0].dims.length)throw new Error("Invalid input shape.");if("float32"!==e[0].type&&"float64"!==e[0].type)throw new Error("Invalid input type.")}},3346:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseInstanceNormalizationAttributes=t.instanceNormalization=void 0;const r=n(5060),o=n(2039);t.instanceNormalization=(e,t,n)=>{c(t);const r=e.run(s(t[0]),t);return[e.run(l(e,t[0],n,r.dims),[t[0],r,t[1],t[2]])]},t.parseInstanceNormalizationAttributes=e=>e.attributes.getFloat("epsilon",1e-5);const i={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[o.TextureType.unpacked]},s=e=>Object.assign(Object.assign({},i),{get:()=>((e,t)=>{const n=t.dims.slice(),r=n[1],i=n[2]*n[3],s=[n[0],r],a=`\n      vec4 process(int[2] indices) {\n        vec4 v = vec4(0.0);\n        int a[4];\n        a[0] = indices[0];\n        a[1] = indices[1];\n        float temp = 0.0;\n        for(int a2=0; a2<${n[2]}; a2++) {\n          a[2] = a2;\n          for(int a3=0; a3<${n[3]}; a3++) {\n            a[3] = a3;\n            float x = _X(a);\n            temp += x;\n          }\n        }\n        float mean = temp / float(${i});\n        temp = 0.0;\n        for(int a2=0; a2<${n[2]}; a2++) {\n          a[2] = a2;\n          for(int a3=0; a3<${n[3]}; a3++) {\n            a[3] = a3;\n            float x = _X(a);\n            temp += (x - mean) * (x - mean);\n          }\n        }\n        v.r = mean;\n        v.g = temp / float(${i});\n\n        return v;\n      }`;return Object.assign(Object.assign({},e),{output:{dims:s,type:t.type,textureType:o.TextureType.packedLastDimension},shaderSource:a})})(i,e)}),a={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[o.TextureType.unpacked,o.TextureType.packedLastDimension,o.TextureType.unpacked,o.TextureType.unpacked]},l=(e,t,n,i)=>{const s=Object.assign(Object.assign({},a),{cacheHint:`${n}`});return Object.assign(Object.assign({},s),{get:()=>((e,t,n,i,s)=>{const a=(0,r.getGlsl)(e.session.backend.glContext.version),[l,c]=e.calculateTextureWidthAndHeight(s,o.TextureType.packedLastDimension),[u,p]=[l/4,c],d=`\n      vec4 get_MeanAndVariance(int[2] mv) {\n        int offset = indicesToOffset_MeanAndVariance(mv);\n        vec2 coords = offsetToCoords(offset, ${u}, ${p});\n        return ${a.texture2D}(MeanAndVariance, coords);\n      }\n\n      float process(int[4] indices) {\n        int mv[2];\n        mv[0] = indices[0];\n        mv[1] = indices[1];\n        vec4 mean_and_variance = get_MeanAndVariance(mv);\n        float mean = mean_and_variance.r;\n        float variance = mean_and_variance.g;\n\n        int sb[1];\n        sb[0] = indices[1];\n        float scale = _Scale(sb);\n        float b = _B(sb);\n\n        return scale * (_X(indices) - mean) / sqrt(variance + epsilon) + b;\n      }`;return Object.assign(Object.assign({},t),{output:{dims:n.dims,type:n.type,textureType:o.TextureType.unpacked},variables:[{name:"epsilon",type:"float",data:i}],shaderSource:d})})(e,s,t,n,i)})},c=e=>{if(!e||3!==e.length)throw new Error("InstanceNormalization requires 3 inputs.");const t=e[0],n=e[1],r=e[2];if(t.dims.length<3||1!==n.dims.length||1!==r.dims.length)throw new Error("Invalid input shape.");if(n.dims[0]!==t.dims[1]||r.dims[0]!==t.dims[1])throw new Error("Input shapes are mismatched.");if("float32"!==t.type&&"float64"!==t.type||"float32"!==n.type&&"float64"!==n.type||"float32"!==r.type&&"float64"!==r.type)throw new Error("Invalid input type.");if(4!==e[0].dims.length)throw new Error("Only support 4-D input shape.")}},708:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createPackedMatmulProgramInfoLoader=void 0;const r=n(2517),o=n(5060),i=n(2039),s=n(9390),a=n(2823),l=n(5623);t.createPackedMatmulProgramInfoLoader=(e,t,n)=>{const c=(u=t.length>2,p=n.activationCacheKey,{name:"MatMul (packed)",inputNames:u?["A","B","Bias"]:["A","B"],inputTypes:u?[i.TextureType.packed,i.TextureType.packed,i.TextureType.packed]:[i.TextureType.packed,i.TextureType.packed],cacheHint:p});var u,p;return Object.assign(Object.assign({},c),{get:()=>((e,t,n,c)=>{const u=n.length>2,p=u?"value += getBiasForMatmul();":"",d=n[0].dims,_=n[1].dims,h=r.BroadcastUtil.calcShape(d,_,!0),f=!r.ShapeUtil.areEqual(n[0].dims,n[1].dims);if(!h)throw new Error("Can't use matmul on the given tensors");const m=d[d.length-1],g=Math.ceil(m/2),b=d.length,w=_.length,x=(0,o.getGlsl)(e.session.backend.glContext.version),y=(0,s.getCoordsDataType)(h.length),T=h.length,v=(0,s.getGlChannels)(),{activationFunction:k,applyActivation:M}=(0,a.getActivationSnippet)(c),S=u?`${(0,l.getBiasForMatmul)(y,v,n[2].dims,h,!0)}`:"",P=f?`${function(e,t,n,o){let i=[],s=[];const a=n[0].dims,l=n[1].dims,c=a.length,u=l.length,p=o.length,d=p-c,_=p-u;i=a.map(((e,n)=>`coords.${t[n+d]}`)),i[c-1]="i*2",i.join(", "),s=l.map(((e,n)=>`coords.${t[n+_]}`)),s[u-2]="i*2",s.join(", ");const h=r.BroadcastUtil.getBroadcastDims(a,o),f=r.BroadcastUtil.getBroadcastDims(l,o),m=h.map((e=>`coords.${t[e+d]} = 0;`)).join("\n"),g=f.map((e=>`coords.${t[e+_]} = 0;`)).join("\n"),b=`int lastDim = coords.${t[p-1]};\n  coords.${t[p-1]} = coords.${t[p-2]};\n  coords.${t[p-2]} = lastDim;`;return`\nvec4 getAAtOutCoordsMatmul(int i) {\n  ${e} coords = getOutputCoords();\n  ${b}\n  ${m}\n  vec4 outputValue = getA(${i});\n  return outputValue;\n}\n\nvec4 getBAtOutCoordsMatmul(int i) {\n  ${e} coords = getOutputCoords();\n  ${b}\n  ${g}\n  vec4 outputValue = getB(${s});\n  return outputValue;\n}`}(y,v,n,h)}`:"",A=f?"getAAtOutCoordsMatmul(i)":`getA(${function(e,t){let n="";for(let r=0;r<t-2;r++)n+=`rc.${e[r]}, `;return n+=`rc.${e[t-2]}, i*2`,n}(v,b)})`,F=f?"getBAtOutCoordsMatmul(i)":`getB(${function(e,t){let n="";for(let r=0;r<t-2;r++)n+=`rc.${e[r]}, `;return n+=`i*2, rc.${e[t-1]}`,n}(v,w)})`,C=`\n            ${P}\n            ${S}\n            ${k}\n            void main() {\n              ${f?"":`${y} rc =\n          getOutputCoords(); int lastDim = rc.${v[T-1]}; rc.${v[T-1]} =\n          rc.${v[T-2]}; rc.${v[T-2]} = lastDim;\n      `}\n\n              vec4 value = vec4(0);\n              for (int i = 0; i < ${g}; i++) {\n                vec4 a = ${A};\n                vec4 b = ${F};\n\n                value += (a.rrbb * b.rgrg);\n                value += (a.ggaa * b.baba);\n              }\n              ${p}\n              ${M}\n              ${x.output} = value;\n            }`;return Object.assign(Object.assign({},t),{output:{dims:h,type:n[0].type,textureType:i.TextureType.packed},shaderSource:C,hasMain:!0})})(e,c,t,n)})}},5623:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.getBiasForMatmul=t.createMatmulProgramInfoLoader=t.parseMatMulAttributes=t.matMul=void 0;const r=n(2517),o=n(2039),i=n(9390),s=n(2823),a=n(708);function l(e,t){const n=(a=e.length>2,l=t.activationCacheKey,{name:"MatMul",inputNames:a?["A","B","Bias"]:["A","B"],inputTypes:a?[o.TextureType.unpacked,o.TextureType.unpacked,o.TextureType.unpacked]:[o.TextureType.unpacked,o.TextureType.unpacked],cacheHint:l});var a,l;return Object.assign(Object.assign({},n),{get:()=>function(e,t,n){const a=t[0].dims,l=t[1].dims,c=r.BroadcastUtil.calcShape(a,l,!0);if(!c)throw new Error("Can't use matmul on the given tensors");const p=(0,i.getCoordsDataType)(c.length),d=(0,i.getGlChannels)(),{activationFunction:_,applyActivation:h}=(0,s.getActivationSnippet)(n),f=t.length>2,m=f?"value += getBiasForMatmul();":"",g=f?`${u(p,d,t[2].dims,c,!1)}`:"",b=c.length,w=a.length,x=l.length,y=`\n    ${_}\n    ${g}\n    float process(int indices[${b}]) {\n        int a[${w}];\n        int b[${x}];\n        bcastMatmulIndices_A(indices, a);\n        bcastMatmulIndices_B(indices, b);\n\n        float value;\n        for (int k=0; k<${a[a.length-1]}; ++k) {\n            a[${w-1}] = k;\n            b[${x-2}] = k;\n            value += _A(a) * _B(b);\n        }\n        ${m}\n        ${h}\n        return value;\n    }`;return Object.assign(Object.assign({},e),{output:{dims:c,type:t[0].type,textureType:o.TextureType.unpacked},shaderSource:y})}(n,e,t)})}t.matMul=(e,t,n)=>(c(t),e.session.pack?[e.run((0,a.createPackedMatmulProgramInfoLoader)(e,t,n),t)]:[e.run(l(t,n),t)]),t.parseMatMulAttributes=e=>(0,s.parseInternalActivationAttributes)(e.attributes),t.createMatmulProgramInfoLoader=l;const c=e=>{if(!e||2!==e.length)throw new Error("MatMul requires 2 inputs.");if(e[0].dims[e[0].dims.length-1]!==e[1].dims[e[1].dims.length-2])throw new Error("shared dimension does not match.");if("float32"!==e[0].type&&"float64"!==e[0].type||"float32"!==e[1].type&&"float64"!==e[1].type)throw new Error("inputs should be float type");if(e[0].type!==e[1].type)throw new Error("inputs types should match")};function u(e,t,n,o,i){let s="";const a=n.length,l=o.length,c=l-a;s=l<2&&a>0?"coords":n.map(((e,n)=>`coords.${t[n+c]}`)).join(", ");const u=r.BroadcastUtil.getBroadcastDims(n,o).map((e=>`coords.${t[e+c]} = 0;`)).join("\n");let p="vec4(outputValue.xx, outputValue.yy)";return 1===r.ShapeUtil.size(n)&&(p="vec4(outputValue.x)"),i?`\nvec4 getBiasForMatmul() {\n  ${e} coords = getOutputCoords();\n  ${u}\n  vec4 outputValue = getBias(${s});\n  return ${p};\n}`:`\nfloat getBiasForMatmul() {\n  ${e} coords = getOutputCoords();\n  ${u}\n  return getBias(coords.x);\n}`}t.getBiasForMatmul=u},2403:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createPackProgramInfoLoader=void 0;const r=n(5060),o=n(2039),i=n(9390),s=n(2827),a={name:"pack",inputNames:["A"],inputTypes:[o.TextureType.unpackedReversed]};t.createPackProgramInfoLoader=(e,t)=>Object.assign(Object.assign({},a),{get:()=>((e,t)=>{const n=(0,r.getGlsl)(e.session.backend.glContext.version),l=t.dims,c=l.length,u=t.dims.length,p=(0,i.getCoordsDataType)(u),d=(0,s.getChannels)("rc",u),_=(h=u,f=d,m=l[l.length-2],g=l[l.length-1],0===h||1===h?"":`\n    int r = ${f[h-2]};\n    int c = ${f[h-1]};\n    int rp1 = ${f[h-2]} + 1;\n    int cp1 = ${f[h-1]} + 1;\n    bool rEdge = rp1 >= ${g};\n    bool cEdge = cp1 >= ${m};\n    `);var h,f,m,g;let b;b=0===c?[1,1]:1===c?[l[0],1]:[l[u-1],l[u-2]];const w=function(e,t,n){if(0===e)return"false";if(1===e)return`rc > ${t[0]}`;let r="";for(let o=e-2;o<e;o++)r+=`${n[o]} >= ${t[o-e+2]}`,o<e-1&&(r+="||");return r}(u,b,d),x=function(e,t){const n=e.length;if(0===n)return"getA(), 0, 0, 0";if(1===n)return`getA(rc),\n            rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),\n            0, 0`;let r="";if(n>2)for(let e=0;e<n-2;++e)r+=`${t[e]},`;return`getA(${r}r, c),\n          rEdge ? 0. : getA(${r}rp1, c),\n          cEdge ? 0. : getA(${r}r, cp1),\n          rEdge || cEdge ? 0. : getA(${r}rp1, cp1)`}(l,d),y=`\n        void main() {\n          ${p} rc = getOutputCoords();\n\n          if(${w}) {\n            ${n.output} = vec4(0);\n          } else {\n            ${_}\n\n            ${n.output} = vec4(${x});\n          }\n        }\n      `;return Object.assign(Object.assign({},a),{hasMain:!0,output:{dims:t.dims,type:t.type,textureType:o.TextureType.packed},shaderSource:y})})(e,t)})},2827:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.unpackFromChannel=t.getChannels=t.getVecChannels=void 0;const r=n(9390);function o(e,t){return(0,r.getGlChannels)(t).map((t=>`${e}.${t}`))}t.getVecChannels=o,t.getChannels=function(e,t){return 1===t?[e]:o(e,t)},t.unpackFromChannel=function(){return"\n    float getChannel(vec4 frag, int dim) {\n      int modCoord = imod(dim, 2);\n      return modCoord == 0 ? frag.r : frag.g;\n    }\n\n    float getChannel(vec4 frag, vec2 innerDims) {\n      vec2 modCoord = mod(innerDims, 2.);\n      return modCoord.x == 0. ?\n        (modCoord.y == 0. ? frag.r : frag.g) :\n        (modCoord.y == 0. ? frag.b : frag.a);\n    }\n  "}},2870:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parsePadAttributesV11=t.padV11=t.parsePadAttributesV2=t.padV2=void 0;const r=n(246),o=n(2517),i=n(5060),s=n(2039),a={name:"Pad",inputNames:["A"],inputTypes:[s.TextureType.unpacked]};t.padV2=(e,t,n)=>(u(t),[e.run(Object.assign(Object.assign({},a),{cacheHint:n.cacheKey,get:()=>c(e,t[0],n)}),t)]),t.parsePadAttributesV2=e=>{const t=e.attributes.getString("mode","constant"),n=e.attributes.getFloat("value",0),o=e.attributes.getInts("pads");return(0,r.createAttributeWithCacheKey)({mode:t,value:n,pads:o})},t.padV11=(e,n,r)=>{p(n);const o=l(e,n,r);return(0,t.padV2)(e,[n[0]],o)},t.parsePadAttributesV11=e=>e.attributes.getString("mode","constant");const l=(e,t,n)=>{if(!e.session.isInitializer(t[1].dataId)||t.length>=3&&!e.session.isInitializer(t[2].dataId))throw new Error("dynamic pad attributes are not allowed");const o=Array.from(t[1].integerData),i=t.length>=3?t[2].floatData[0]:0;return(0,r.createAttributeWithCacheKey)({mode:n,pads:o,value:i})},c=(e,t,n)=>{const r=o.ShapeUtil.padShape(t.dims.slice(),n.pads),i=r.length,a=`\n      ${d(e,t,n)}\n      float process(int[${i}] indices) {\n          return padA(indices);\n      }`;return{name:"Pad",inputNames:["A"],inputTypes:[s.TextureType.unpacked],output:{dims:r,type:t.type,textureType:s.TextureType.unpacked},shaderSource:a}},u=e=>{if(!e||1!==e.length)throw new Error("Pad requires 1 input");if("float32"!==e[0].type&&"float64"!==e[0].type)throw new Error("Invalid input type.")},p=e=>{if(!e||2!==e.length&&3!==e.length)throw new Error("Pad requires 2 or 3 inputs");if("int32"!==e[1].type)throw new Error("Invalid input type.");if(e.length>=3&&"string"===e[2].type)throw new Error("Invalid input type.")},d=(e,t,n)=>{const r=(0,i.getGlsl)(e.session.backend.glContext.version),[a,l]=e.calculateTextureWidthAndHeight(t.dims,s.TextureType.unpacked),c=o.ShapeUtil.computeStrides(t.dims);switch(n.mode){case"constant":return _(r,t.dims,c,a,l,n.pads,n.value);case"reflect":return h(r,t.dims,c,a,l,n.pads);case"edge":return f(r,t.dims,c,a,l,n.pads);default:throw new Error("Invalid mode")}},_=(e,t,n,r,o,i,s)=>{const a=t.length;let l="";for(let e=a-1;e>=0;--e)l+=`\n        k = m[${e}] - ${i[e]};\n        if (k < 0)  return constant;\n        if (k >= ${t[e]}) return constant;\n        offset += k * ${n[e]};\n        `;return`\n      float padA(int m[${a}]) {\n        const float constant = float(${s});\n        int offset = 0;\n        int k = 0;\n        ${l}\n        vec2 coords = offsetToCoords(offset, ${r}, ${o});\n        float value = getColorAsFloat(${e.texture2D}(A, coords));\n        return value;\n      }\n      `},h=(e,t,n,r,o,i)=>{const s=t.length;let a="";for(let e=s-1;e>=0;--e)a+=`\n        k = m[${e}] - ${i[e]};\n        if (k < 0) { k = -k; }\n        {\n          const int _2n_1 = ${2*(t[e]-1)};\n          k = int( mod( float(k), float(_2n_1) ) ) ;\n          if(k >= ${t[e]}) { k = _2n_1 - k; }\n        }\n        offset += k * ${n[e]};\n        `;return`\n      float padA(int m[${s}]) {\n        int offset = 0;\n        int k = 0;\n        ${a}\n        vec2 coords = offsetToCoords(offset, ${r}, ${o});\n        float value = getColorAsFloat(${e.texture2D}(A, coords));\n        return value;\n      }\n      `},f=(e,t,n,r,o,i)=>{const s=t.length;let a="";for(let e=s-1;e>=0;--e)a+=`\n        k = m[${e}] - ${i[e]};\n        if (k < 0)  k = 0;\n        if (k >= ${t[e]}) k = ${t[e]-1};\n        offset += k * ${n[e]};\n      `;return`\n      float padA(int m[${s}]) {\n        int offset = 0;\n        int k = 0;\n        ${a}\n        vec2 coords = offsetToCoords(offset, ${r}, ${o});\n        float value = getColorAsFloat(${e.texture2D}(A, coords));\n        return value;\n      }\n      `}},2143:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.globalMaxPool=t.parseMaxPoolAttributes=t.maxPool=t.parseGlobalAveragePoolAttributes=t.globalAveragePool=t.parseAveragePoolAttributes=t.averagePool=void 0;const r=n(246),o=n(2517),i=n(2039);t.averagePool=(e,t,n)=>{p(t);const r={name:"AveragePool",inputNames:["X"],inputTypes:[i.TextureType.unpacked],cacheHint:n.cacheKey};return[e.run(Object.assign(Object.assign({},r),{get:()=>s(t,r,!1,n)}),t)]},t.parseAveragePoolAttributes=e=>{const t=e.attributes.getString("auto_pad","NOTSET"),n=e.attributes.getInt("ceil_mode",0),o=0!==e.attributes.getInt("count_include_pad",0),i=e.attributes.getInts("kernel_shape"),s=e.attributes.getInts("strides",[]),a=e.attributes.getInts("pads",[]);if(0!==n)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,r.createAttributeWithCacheKey)({autoPad:t,ceilMode:n,countIncludePad:o,kernelShape:i,strides:s,pads:a})};const s=(e,t,n,r)=>{const[s,a]=l(e,r,n),c=o.ShapeUtil.size(s.kernelShape);let u="";s.countIncludePad?u+=`value /= float(${c});`:u+=`value /= float(${c} - pad);`;const p=`\n        ${d(e[0].dims,s,"value += _X(x);",u,"0.0")}\n      `;return Object.assign(Object.assign({},t),{output:{dims:a,type:e[0].type,textureType:i.TextureType.unpacked},shaderSource:p})};t.globalAveragePool=(e,t,n)=>{p(t);const r={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[i.TextureType.unpacked],cacheHint:`${n.countIncludePad}`};return[e.run(Object.assign(Object.assign({},r),{get:()=>s(t,r,!0,n)}),t)]},t.parseGlobalAveragePoolAttributes=e=>{const t=0!==e.attributes.getInt("count_include_pad",0);return(0,r.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:t,kernelShape:[],strides:[],pads:[]})},t.maxPool=(e,t,n)=>{p(t);const r={name:"MaxPool",inputNames:["X"],inputTypes:[i.TextureType.unpacked],cacheHint:n.cacheKey};return[e.run(Object.assign(Object.assign({},r),{get:()=>a(t,r,!1,n)}),t)]},t.parseMaxPoolAttributes=e=>{const t=e.attributes.getString("auto_pad","NOTSET"),n=e.attributes.getInt("ceil_mode",0),o=e.attributes.getInts("kernel_shape"),i=e.attributes.getInts("strides",[]),s=e.attributes.getInts("pads",[]),a=e.attributes.getInt("storage_order",0),l=e.attributes.getInts("dilations",[]);if(0!==a)throw new Error("column major storage order is not yet supported for MaxPool");if(0!==n)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return(0,r.createAttributeWithCacheKey)({autoPad:t,ceilMode:n,countIncludePad:!1,kernelShape:o,strides:i,pads:s,storageOrder:a,dilations:l})};const a=(e,t,n,r)=>{const[o,s]=l(e,r,n),a=`\n      ${d(e[0].dims,o,"\n      value = max(_X(x), value);\n    ","","-1e5")}\n    `;return Object.assign(Object.assign({},t),{output:{dims:s,type:e[0].type,textureType:i.TextureType.unpacked},shaderSource:a})},l=(e,t,n)=>{const r=e[0].dims.slice(),i=Object.hasOwnProperty.call(t,"dilations"),s=t.kernelShape.slice(),a=t.strides.slice(),l=i?t.dilations.slice():[],c=t.pads.slice();o.PoolConvUtil.adjustPoolAttributes(n,r,s,a,l,c);const u=o.PoolConvUtil.computePoolOutputShape(n,r,a,l,s,c,t.autoPad),p=Object.assign({},t);return i?Object.assign(p,{kernelShape:s,strides:a,pads:c,dilations:l,cacheKey:t.cacheKey}):Object.assign(p,{kernelShape:s,strides:a,pads:c,cacheKey:t.cacheKey}),[p,u]},c={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},u={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[i.TextureType.unpacked]};t.globalMaxPool=(e,t)=>(p(t),[e.run(Object.assign(Object.assign({},u),{get:()=>a(t,u,!0,c)}),t)]);const p=e=>{if(!e||1!==e.length)throw new Error("Pool ops requires 1 input.");if("float32"!==e[0].type&&"float64"!==e[0].type)throw new Error("Invalid input type.")},d=(e,t,n,r,i)=>{const s=e.length;if(t.kernelShape.length<=2){const o=t.kernelShape[t.kernelShape.length-1],a=t.strides[t.strides.length-1],l=t.pads[t.pads.length/2-1],c=t.pads[t.pads.length-1],u=e[s-1];let p="",d="",_="";if(p=l+c!==0?`\n          for (int i = 0; i < ${o}; i++) {\n            x[${s} - 1] = indices[${s} - 1] * ${a} - ${l} + i;\n            if (x[${s} - 1] < 0 || x[${s} - 1] >= ${u}) {\n              pad++;\n              continue;\n            }\n            ${n}\n          }`:`\n          for (int i = 0; i < ${o}; i++) {\n            x[${s} - 1] = indices[${s} - 1] * ${a} - ${l} + i;\n            ${n}\n          }`,2===t.kernelShape.length){const n=t.kernelShape[t.kernelShape.length-2],r=t.strides[t.strides.length-2],i=t.pads[t.pads.length/2-2],a=t.pads[t.pads.length-2],l=e[s-2];d=i+a!==0?`\n            for (int j = 0; j < ${n}; j++) {\n              x[${s} - 2] = indices[${s} - 2] * ${r} - ${i} + j;\n              if (x[${s} - 2] < 0 || x[${s} - 2] >= ${l}) {\n                pad+= ${o};\n                continue;\n              }\n          `:`\n            for (int j = 0; j < ${n}; j++) {\n              x[${s} - 2] = indices[${s} - 2] * ${r} - ${i} + j;\n            `,_="\n          }\n        "}return`\n        float process(int indices[${s}]) {\n          int x[${s}];\n          copyVec(indices, x);\n\n          float value = ${i};\n          int pad = 0;\n          ${d}\n          ${p}\n          ${_}\n          ${r}\n          return value;\n        }\n      `}{const a=o.ShapeUtil.size(t.kernelShape),l=o.ShapeUtil.computeStrides(t.kernelShape),c=l.length,u=t.pads.length,p=h(c),d=_(e,"inputDims"),f=_(t.pads,"pads"),m=_(l,"kernelStrides"),g=_(t.strides,"strides");let b="";return b=t.pads.reduce(((e,t)=>e+t))?`\n            if (x[j] >= inputDims[j] || x[j] < 0) {\n              pad++;\n              isPad = true;\n              break;\n            }\n          }\n          if (!isPad) {\n            ${n}\n          }`:`\n          }\n          ${n}\n        `,`\n        ${p}\n        float process(int indices[${s}]) {\n          int x[${s}];\n          copyVec(indices, x);\n          int offset[${c}];\n          int pads[${u}];\n          int inputDims[${s}];\n          int kernelStrides[${c}];\n          int strides[${c}];\n          ${f}\n          ${d}\n          ${g}\n          ${m}\n\n          float value = ${i};\n          int pad = 0;\n          bool isPad = false;\n          for (int i = 0; i < ${a}; i++) {\n            offsetToIndices(i, kernelStrides, offset);\n            isPad = false;\n            for (int j = ${s} - ${c}; j < ${s}; j++) {\n              x[j] = indices[j] * strides[j - ${s} + ${c}]\n                + offset[j - ${s} + ${c}] - pads[j - 2];\n              ${b}\n          }\n          ${r}\n\n          return value;\n        }\n      `}},_=(e,t)=>{let n="";for(let r=0;r<e.length;r++)n+=`\n      ${t}[${r}] = ${e[r]};\n    `;return n},h=e=>`\n  void offsetToIndices(int offset, int[${e}] strides, out int[${e}] indices) {\n    if (${e} == 0) {\n      return;\n    }\n    for (int i = 0; i < ${e} - 1; ++i) {\n      indices[i] = offset / strides[i];\n      offset -= indices[i] * strides[i];\n    }\n    indices[${e} - 1] = offset;\n  }`},4939:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.reduceLogSumSquare=t.reduceLogSum=t.reduceProd=t.reduceMin=t.reduceMax=t.reduceMean=t.reduceSum=t.parseReduceAttributes=void 0;const r=n(246),o=n(782),i=n(2517),s=n(2039),a=(e,t,n,r,o)=>{c(t);const i={name:r,inputNames:["A"],inputTypes:[s.TextureType.unpacked]};return[e.run(Object.assign(Object.assign({},i),{cacheHint:n.cacheKey,get:()=>l(e,t,n,r,o,i)}),t)]};t.parseReduceAttributes=e=>{const t=e.attributes.getInts("axes",[]),n=1===e.attributes.getInt("keepdims",1);return(0,r.createAttributeWithCacheKey)({axes:t,keepDims:n})};const l=(e,t,n,r,o,a)=>{const l=[],c=t[0].dims.length||1,u=[],p=i.ShapeUtil.normalizeAxes(n.axes,t[0].dims.length),d=o(t,p);let _=d[1];for(let e=0;e<t[0].dims.length;e++)p.indexOf(e)>=0||0===p.length?(n.keepDims&&l.push(1),_=`\n          for(int j${e} = 0; j${e} < ${t[0].dims[e]}; j${e}++) {\n            inputIdx[${e}] = j${e};\n            ${_}\n          }`):(u.push(`inputIdx[${e}] = outputIdx[${l.length}];`),l.push(t[0].dims[e]));const h=`\n      float process(int outputIdx[${l.length||1}]) {\n        float value;                 // final result\n        int inputIdx[${c}];      // addressing input data\n        ${u.join("\n")}\n        ${d[0]}       // init ops for reduce max/min\n        ${_}\n        ${d[2]}       // final computation for reduce mean\n        return value;\n      }`;return Object.assign(Object.assign({},a),{output:{dims:l,type:t[0].type,textureType:s.TextureType.unpacked},shaderSource:h})},c=e=>{if(!e||1!==e.length)throw new Error("Reduce op requires 1 input.");if(-1===o.NUMBER_TYPES.indexOf(e[0].type))throw new Error("Invalid input type.")};t.reduceSum=(e,t,n)=>a(e,t,n,"ReduceSum",(()=>["value = 0.0;","value += _A(inputIdx);",""])),t.reduceMean=(e,t,n)=>a(e,t,n,"ReduceMean",((e,t)=>{let n=1;for(let r=0;r<e[0].dims.length;r++)(t.indexOf(r)>=0||0===t.length)&&(n*=e[0].dims[r]);return["value = 0.0;","value += _A(inputIdx);",`value /= ${n}.;`]})),t.reduceMax=(e,t,n)=>a(e,t,n,"ReduceMax",((e,t)=>{const n=[];for(let r=0;r<e[0].dims.length;r++)(t.indexOf(r)>=0||0===t.length)&&n.push(`inputIdx[${r}] = 0;`);return[`${n.join("\n")}\nvalue = _A(inputIdx);`,"value = max(value, _A(inputIdx));",""]})),t.reduceMin=(e,t,n)=>a(e,t,n,"ReduceMin",((e,t)=>{const n=[];for(let r=0;r<e[0].dims.length;r++)(t.indexOf(r)>=0||0===t.length)&&n.push(`inputIdx[${r}] = 0;`);return[`${n.join("\n")}\nvalue = _A(inputIdx);`,"value = min(value, _A(inputIdx));",""]})),t.reduceProd=(e,t,n)=>a(e,t,n,"ReduceProd",(()=>["value = 1.0;","value *= _A(inputIdx);",""])),t.reduceLogSum=(e,t,n)=>a(e,t,n,"ReduceLogSum",(()=>["value = 0.0;","value += _A(inputIdx);","value = log(value);"])),t.reduceLogSumSquare=(e,t,n)=>a(e,t,n,"ReduceLogSumSquare",(()=>["float t; value = 0.0;","t = _A(inputIdx); value += t * t;",""]))},7019:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.isReshapeCheap=t.processDims3D=t.createPackedReshape3DProgramInfoLoader=void 0;const r=n(2517),o=n(5060),i=n(2039),s=n(2827);t.createPackedReshape3DProgramInfoLoader=(e,t,n)=>{const a=(e=>({name:"Reshape (packed)",inputTypes:[i.TextureType.packed],inputNames:["A"],cacheHint:`${e}`}))(n);return Object.assign(Object.assign({},a),{get:()=>((e,t,n,a)=>{const l=t.dims,c=a;let u="";for(let e=0;e<4;e++){let t="";switch(e){case 0:t="outputCoords = rc;";break;case 1:t="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:t="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:t="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}u+=`\n        ${t}\n        ${e>0?"if(outputCoords.y < rows && outputCoords.z < cols){":""}\n          int flattenedIndex = getFlattenedIndex(outputCoords);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex);\n          vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result[${e}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims);\n\n        ${e>0?"}":""}\n      `}const p=(0,o.getGlsl)(e.session.backend.glContext.version),d=`\n      ${function(e){const t=r.ShapeUtil.computeStrides(e),n=["b","r","c"],o="index";return`\n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      ${t.map(((e,r)=>`int ${n[r]} = ${o} / ${e}; ${r===t.length-1?`int ${n[r+1]} = ${o} - ${n[r]} * ${e}`:`index -= ${n[r]} * ${e}`};`)).join("")}\n      return ivec3(b, r, c);\n    }\n  `}(l)}\n      ${function(e){const t=r.ShapeUtil.computeStrides(e);return`\n  int getFlattenedIndex(ivec3 coords) {\n    // reverse y, z order\n    return coords.x * ${t[0]} + coords.z * ${t[1]} + coords.y;\n  }\n`}(c)}\n      ${(0,s.unpackFromChannel)()}\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.0);\n\n        ivec3 outputCoords;\n        int rows = ${c[2]};\n        int cols = ${c[1]};\n\n        ${u}\n        ${p.output} = result;\n      }\n    `;return Object.assign(Object.assign({},n),{output:{dims:c,type:t.type,textureType:i.TextureType.packed},shaderSource:d,hasMain:!0})})(e,t,a,n)})},t.processDims3D=function(e){if(0===e.length)return[1,1,1];let t=1;for(let n=0;n<e.length-2;++n)t*=e[n];return[t,e.length>1?e[e.length-2]:1,e[e.length-1]]},t.isReshapeCheap=function(e,t){let n=!1;return n=0===e.length||0===t.length||(e.length<2||t.length<2?e[e.length-1]===t[t.length-1]:e[e.length-1]===t[t.length-1]&&e[e.length-2]===t[t.length-2]),n}},718:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.reshape=void 0;const r=n(2517);t.reshape=(e,t)=>{const n=r.ShapeUtil.calculateReshapedDims(t[0].dims,t[1].integerData);return e.session.pack?[e.reshapePacked(t[0],n)]:[e.reshapeUnpacked(t[0],n)]}},2268:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseResizeAttributesV11=t.parseResizeAttributesV10=t.resize=void 0;const r=n(5060),o=n(2039),i=n(9390),s=n(2827),a=n(9793),l={name:"Resize",inputNames:["A"],inputTypes:[o.TextureType.packed]};t.resize=(e,t,n)=>((0,a.validateInputs)(t,n),[e.run(Object.assign(Object.assign({},l),{cacheHint:n.cacheKey,get:()=>c(e,t,n)}),t)]),t.parseResizeAttributesV10=e=>(0,a.parseUpsampleAttributes)(e,10),t.parseResizeAttributesV11=e=>(0,a.parseUpsampleAttributes)(e,11);const c=(e,t,n)=>{const a=(0,r.getGlsl)(e.session.backend.glContext.version),[c,p]=u(t,n);if(c.every((e=>1===e))&&"tf_crop_and_resize"!==n.coordinateTransformMode)return Object.assign(Object.assign({},l),{output:{dims:p,type:t[0].type,textureType:o.TextureType.packed},hasMain:!0,shaderSource:`void main() {\n                    vec4 v = ${a.texture2D}(X, TexCoords);\n                    ${a.output} = v;\n                }`});const d=p.length;if(d<2)throw new Error(`output dimension should be at least 2, but got ${d}`);const _=p[d-2],h=p[d-1],f=t[0].dims;if(d!==f.length)throw new Error(`output dimension should match input ${f.length}, but got ${d}`);const m=f[d-2],g=f[d-1],b=c[d-2],w=c[d-1];let x="";if("linear"!==n.mode)throw new Error(`resize (packed) does not support mode: '${n.mode}'`);switch(n.coordinateTransformMode){case"asymmetric":x="\n                    vec4 getSourceFracIndex(ivec4 coords) {\n                        return vec4(coords) / scaleWHWH;\n                    }\n                ";break;case"half_pixel":x="\n                    vec4 getSourceFracIndex(ivec4 coords) {\n                        return (vec4(coords) + 0.5) / scaleWHWH - 0.5;\n                    }\n                ";break;case"pytorch_half_pixel":x=`\n                    vec4 getSourceFracIndex(ivec4 coords) {\n                        vec4 fcoords = vec4(coords);\n                        return vec4(\n                            ${h}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0,\n                            ${_}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0,\n                            ${h}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0,\n                            ${_}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0\n                          );\n                    }\n                `;break;case"align_corners":x=`\n                    vec4 getSourceFracIndex(ivec4 coords) {\n                        vec4 resized = vec4(${h}.0 - 1.0, ${_}.0 - 1.0, ${h}.0 - 1.0,\n                            ${_}.0 - 1.0);\n                        vec4 original = vec4(${g}.0 - 1.0, ${m}.0 - 1.0, ${g}.0 - 1.0,\n                            ${m}.0 - 1.0);\n                        vec4 new_scale = original / resized;\n                        return vec4(coords) * new_scale;\n                    }\n                `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode:                                 '${n.coordinateTransformMode}'`)}const y=(0,i.getCoordsDataType)(d),T=`\n            const vec2 inputWH = vec2(${m}.0, ${g}.0);\n            const vec4 scaleWHWH = vec4(float(${b}), float(${w}), float(${b}), float(${w}));\n            ${(0,s.unpackFromChannel)()}\n            ${x}\n            float getAValue(int x10, int r, int c, int d) {\n                return getChannel(getA(x10, r, c, d), vec2(c, d));\n            }\n            void main() {\n                ${y} rc = getOutputCoords();\n\n                int batch = rc[0];\n                int depth = rc[1];\n\n                // retrieve the 4 coordinates that is used in the 4 packed output values.\n                ivec4 coords = ivec4(rc.wz, rc.w + 1, rc.z + 1);\n\n                // calculate the source index in fraction\n                vec4 sourceFrac = getSourceFracIndex(coords);\n\n                // get the lower and upper bound of the 4 values that will be packed into one texel.\n                ivec4 x00 = ivec4(max(sourceFrac.xy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xy)));\n                ivec4 x01 = ivec4(max(sourceFrac.xw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xw)));\n                ivec4 x10 = ivec4(max(sourceFrac.zy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zy)));\n                ivec4 x11 = ivec4(max(sourceFrac.zw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zw)));\n\n                bool hasNextRow = rc.w < ${_-1};\n                bool hasNextCol = rc.z < ${h-1};\n\n                // pack x00, x01, x10, x11's top-left corner into one vec4 structure\n                vec4 topLeft = vec4(\n                    getAValue(batch, depth, x00.x, x00.y),\n                    hasNextCol ? getAValue(batch, depth, x01.x, x01.y) : 0.0,\n                    hasNextRow ? getAValue(batch, depth, x10.x, x10.y) : 0.0,\n                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.y) : 0.0);\n\n                // pack x00, x01, x10, x11's top-right corner into one vec4 structure\n                vec4 topRight = vec4(\n                    getAValue(batch, depth, x00.x, x00.w),\n                    hasNextCol ? getAValue(batch, depth, x01.x, x01.w) : 0.0,\n                    hasNextRow ? getAValue(batch, depth, x10.x, x10.w) : 0.0,\n                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.w) : 0.0);\n\n                // pack x00, x01, x10, x11's bottom-left corner into one vec4 structure\n                vec4 bottomLeft = vec4(\n                    getAValue(batch, depth, x00.z, x00.y),\n                    hasNextCol ? getAValue(batch, depth, x01.z, x01.y) : 0.0,\n                    hasNextRow ? getAValue(batch, depth, x10.z, x10.y) : 0.0,\n                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.y) : 0.0);\n\n                // pack x00, x01, x10, x11's bottom-right corner into one vec4 structure\n                vec4 bottomRight = vec4(\n                    getAValue(batch, depth, x00.z, x00.w),\n                    hasNextCol ? getAValue(batch, depth, x01.z, x01.w) : 0.0,\n                    hasNextRow ? getAValue(batch, depth, x10.z, x10.w) : 0.0,\n                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.w) : 0.0);\n\n                // calculate the interpolation fraction on u and v direction\n                vec4 frac = vec4(sourceFrac) - floor(sourceFrac);\n                vec4 clampFrac = clamp(frac, vec4(0.0), vec4(1.0));\n\n                vec4 top = mix(topLeft, topRight, clampFrac.ywyw);\n                vec4 bottom = mix(bottomLeft, bottomRight, clampFrac.ywyw);\n                vec4 newValue = mix(top, bottom, clampFrac.xxzz);\n\n                ${a.output} = vec4(newValue);\n            }\n        `;return Object.assign(Object.assign({},l),{output:{dims:p,type:t[0].type,textureType:o.TextureType.packed},hasMain:!0,shaderSource:T})},u=(e,t)=>{const n=e[0].dims;let r,o=t.scales;if(0===o.length){const i=e[t.scalesInputIdx];if(i&&0!==i.size){if(e[t.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");o=p(i,t.mode,t.isResize)}else{const i=e[t.sizesInputIdx];if(!i||0===i.size)throw new Error("Either scales or sizes MUST be provided as input.");r=Array.from(i.integerData),o=d(r,n,t.mode,t.isResize)}}else if(e[t.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");const i=r||n.map(((e,t)=>Math.floor(e*o[t])));return[o,i]},p=(e,t,n)=>{const r=Array.from(e.floatData);return(0,a.scalesValidation)(r,t,n),r},d=(e,t,n,r)=>{const o=t.length,i=new Array(o);for(let n=0,r=o;n<r;n++)if(0===t[n]){if(0!==e[n])throw new Error("Input dim is zero but required output dim is non-zero.");i[n]=1}else i[n]=e[n]/t[n];return(0,a.scalesValidation)(i,n,r),i}},8117:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.shape=void 0;const r=n(9162);t.shape=(e,t)=>(o(t),[new r.Tensor([t[0].dims.length],"int32",void 0,void 0,new Int32Array(t[0].dims))]);const o=e=>{if(!e||1!==e.length)throw new Error("Shape requires 1 input.")}},2278:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.sliceV10=t.parseSliceAttributes=t.slice=void 0;const r=n(246),o=n(782),i=n(2517),s=n(2039),a={name:"Slice",inputNames:["A"],inputTypes:[s.TextureType.unpacked]};t.slice=(e,t,n)=>(c(t),[e.run(Object.assign(Object.assign({},a),{cacheHint:n.cacheKey,get:()=>l(e,t[0],n)}),t)]),t.parseSliceAttributes=e=>{const t=e.attributes.getInts("starts"),n=e.attributes.getInts("ends"),o=e.attributes.getInts("axes",[]);return(0,r.createAttributeWithCacheKey)({starts:t,ends:n,axes:o})};const l=(e,t,n)=>{const r=0===n.axes.length?t.dims.slice(0).map(((e,t)=>t)):n.axes,o=i.ShapeUtil.normalizeAxes(r,t.dims.length),l=n.starts.map(((e,n)=>e>t.dims[o[n]]-1?t.dims[o[n]]:i.ShapeUtil.normalizeAxis(e,t.dims[o[n]]))),c=n.ends.map(((e,n)=>e>t.dims[o[n]]-1?t.dims[o[n]]:i.ShapeUtil.normalizeAxis(e,t.dims[o[n]]))),u=t.dims.slice(),p=[];for(let e=0;e<o.length;e++)u[o[e]]=c[e]-l[e],l[e]>0&&p.push(`outputIdx[${o[e]}] += ${l[e]};`);const d=`\n      float process(int outputIdx[${u.length}]) {\n        ${p.join("\n      ")}\n        return _A(outputIdx);\n      }`;return Object.assign(Object.assign({},a),{output:{dims:u,type:t.type,textureType:s.TextureType.unpacked},shaderSource:d})},c=e=>{if(!e||1!==e.length)throw new Error("Slice requires 1 input.");if(-1===o.NUMBER_TYPES.indexOf(e[0].type))throw new Error("Invalid input type.")};t.sliceV10=(e,t)=>{p(t);const n=u(e,t);return[e.run(Object.assign(Object.assign({},a),{cacheHint:n.cacheKey,get:()=>l(e,t[0],n)}),[t[0]])]};const u=(e,t)=>{if(!e.session.isInitializer(t[1].dataId)||!e.session.isInitializer(t[2].dataId)||t.length>=4&&!e.session.isInitializer(t[3].dataId)||t.length>=5&&!e.session.isInitializer(t[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(t.length>=5&&t[4].integerData.some((e=>1!==e)))throw new Error("currently non-1 steps is not supported for Slice");const n=Array.from(t[1].integerData),r=Array.from(t[2].integerData),o=t.length>=4?Array.from(t[3].integerData):[];return{starts:n,ends:r,axes:o,cacheKey:`${o};${n};${r}`}},p=e=>{if(!e||e.length<3||e.length>5)throw new Error("Invalid input number.");if("int32"!==e[1].type||1!==e[1].dims.length)throw new Error("Invalid input type.");if("int32"!==e[2].type||1!==e[2].dims.length)throw new Error("Invalid input type.");if(e.length>=4&&("int32"!==e[3].type||1!==e[3].dims.length))throw new Error("Invalid input type.");if(e.length>=5&&("int32"!==e[4].type||1!==e[4].dims.length))throw new Error("Invalid input type.")}},5524:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.softmaxV13=t.parseSoftmaxAttributesV13=t.parseSoftmaxAttributes=t.softmax=void 0;const r=n(246),o=n(2517),i=n(5060),s=n(2039),a=n(3738),l={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[s.TextureType.unpacked]},c={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked]},u={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked,s.TextureType.unpacked]};t.softmax=(e,t,n)=>{f(t);const r=t[0].dims.slice(),i=o.ShapeUtil.normalizeAxis(n.axis,r.length),s=o.ShapeUtil.sizeToDimension(r,i),a=o.ShapeUtil.sizeFromDimension(r,i);return p(e,t,n,s,a)},t.parseSoftmaxAttributes=e=>(0,r.createAttributeWithCacheKey)({axis:e.attributes.getInt("axis",1)}),t.parseSoftmaxAttributesV13=e=>(0,r.createAttributeWithCacheKey)({axis:e.attributes.getInt("axis",-1)}),t.softmaxV13=(e,t,n)=>{f(t);const i=t[0].dims.slice(),s=o.ShapeUtil.normalizeAxis(n.axis,i.length),l=i.length,c=s!==l-1,u=[];let d,_=[],h=[];c&&(_=Array.from({length:l}).map(((e,t)=>t)),_[s]=l-1,_[l-1]=s,_.map((e=>u.push(i[e]))),d=(0,r.createAttributeWithCacheKey)({perm:_}),h=(0,a.transpose)(e,t,d));const m=c?o.ShapeUtil.sizeToDimension(u,l-1):o.ShapeUtil.sizeToDimension(i,l-1),g=c?o.ShapeUtil.sizeFromDimension(u,l-1):o.ShapeUtil.sizeFromDimension(i,l-1),b=p(e,c?h:t,n,m,g);return c?(0,a.transpose)(e,b,d):b};const p=(e,t,n,r,o)=>{const i=d(e,t[0],r,o,[r]),s=e.run(Object.assign(Object.assign({},l),{cacheHint:n.cacheKey,get:()=>i}),t),a=_(e,t[0],r,o,i.output.dims,[r]),p=e.run(Object.assign(Object.assign({},c),{cacheHint:n.cacheKey,get:()=>a}),[t[0],s]),f=h(e,t[0],r,o,i.output.dims,a.output.dims);return[e.run(Object.assign(Object.assign({},u),{cacheHint:n.cacheKey,get:()=>f}),[t[0],s,p])]},d=(e,t,n,r,o)=>{const[a,c]=e.calculateTextureWidthAndHeight(t.dims,s.TextureType.unpacked),u=o.length;if(n<1||r<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(1!==o.length)throw new Error("Dimensionality of the output should be 1");if(o[0]!==n)throw new Error("Shape of the output should be equal to logical row count");const p=(0,i.getGlsl)(e.session.backend.glContext.version),d=`\n      float process(int[${u}] indices) {\n        int logical_row_start_offset = indices[0] * ${r};\n\n        float max = getColorAsFloat(${p.texture2D}(A, offsetToCoords(logical_row_start_offset, ${a},\n        ${c} )));\n        for(int i=1; i<${r}; ++i)\n        {\n          float current = getColorAsFloat(${p.texture2D}(A, offsetToCoords(logical_row_start_offset + i,\n            ${a}, ${c})));\n          if(current > max)\n          max = current;\n        }\n\n        return max;\n      }`;return Object.assign(Object.assign({},l),{output:{dims:o,type:t.type,textureType:s.TextureType.unpacked},shaderSource:d})},_=(e,t,n,r,o,a)=>{const[l,u]=e.calculateTextureWidthAndHeight(t.dims,s.TextureType.unpacked),p=a.length;if(n<1||r<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(1!==a.length)throw new Error("Dimensionality of the output should be 1");if(a[0]!==n)throw new Error("Shape of the output should be equal to logical row count");if(1!==o.length)throw new Error("Dimensionality of the intermediate results should be 1");if(o[0]!==n)throw new Error("Shape of the intermediate results should be equal to logical row count");const d=`\n      float process(int[${p}] indices) {\n        int logical_row_start_offset = indices[0] * ${r};\n\n        float norm_factor = 0.0;\n        float max = _Max(indices);\n        for(int i=0; i<${r}; ++i)\n        {\n          norm_factor += exp(getColorAsFloat(${(0,i.getGlsl)(e.session.backend.glContext.version).texture2D}(A, offsetToCoords(logical_row_start_offset + i,\n            ${l}, ${u}))) - max);\n        }\n\n        return norm_factor;\n      }`;return Object.assign(Object.assign({},c),{output:{dims:a,type:t.type,textureType:s.TextureType.unpacked},shaderSource:d})},h=(e,t,n,r,o,i)=>{const[a,l]=e.calculateTextureWidthAndHeight(t.dims,s.TextureType.unpacked),c=t.dims.length;if(n<1||r<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(1!==o.length||1!==i.length)throw new Error("Dimensionality of the intermediate results should be 1");if(o[0]!==n||i[0]!==n)throw new Error("Shape of the intermediate results should be equal to logical 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type")}},5975:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseSplitAttributes=t.split=void 0;const r=n(246),o=n(2517),i=n(2039),s={name:"Split",inputNames:["A"],inputTypes:[i.TextureType.unpacked]};t.split=(e,t,n)=>{c(t);const r=o.ShapeUtil.normalizeAxis(n.axis,t[0].dims.length),i=a(e,t,r,n),u=[];for(let o=0;o<i;++o)u.push(e.run(Object.assign(Object.assign({},s),{cacheHint:`${n.cacheKey};${o}`,get:()=>l(e,t[0],n,r,o)}),t));return u},t.parseSplitAttributes=e=>{const t=e.attributes.getInt("axis",0),n=e.attributes.getInts("split",[]),o=e.outputs.length;return(0,r.createAttributeWithCacheKey)({axis:t,split:n,numOutputs:o})};const a=(e,t,n,r)=>{const[,i]=o.SplitUtil.splitShape(t[0].dims,n,r.split,r.numOutputs);return i.length},l=(e,t,n,r,a)=>{const[l,c]=o.SplitUtil.splitShape(t.dims,r,n.split,n.numOutputs),u=c[a],p=l[a],d=`\n      float process(int indices[${p.length}]) {\n        indices[${r}] += ${u};\n        return _A(indices);\n      }\n    `;return Object.assign(Object.assign({},s),{cacheHint:`${n.cacheKey}:${a}`,output:{dims:p,type:t.type,textureType:i.TextureType.unpacked},shaderSource:d})},c=e=>{if(!e||1!==e.length)throw new Error("Split requires one input.");if("int8"!==e[0].type&&"uint8"!==e[0].type&&"int16"!==e[0].type&&"uint16"!==e[0].type&&"int32"!==e[0].type&&"uint32"!==e[0].type&&"float32"!==e[0].type&&"float64"!==e[0].type&&"bool"!==e[0].type)throw new Error("Invalid input type.")}},3933:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseSqueezeAttributes=t.squeezeV13=t.squeeze=void 0;const r=n(2517);t.squeeze=(e,t,n)=>{o(t);const i=r.ShapeUtil.squeezeShape(t[0].dims,n);return[e.reshapeUnpacked(t[0],i)]},t.squeezeV13=(e,n)=>(i(n),(0,t.squeeze)(e,[n[0]],Array.from(n[1].integerData))),t.parseSqueezeAttributes=e=>e.attributes.getInts("axes");const o=e=>{if(!e||1!==e.length)throw new Error("Squeeze requires 1 input.");if("string"===e[0].type)throw new Error("invalid input tensor types.")},i=e=>{if(!e||2!==e.length)throw new Error("Squeeze requires 2 inputs.");if("int32"!==e[1].type)throw new Error("Invalid input type.")}},6558:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.sum=void 0;const r=n(5060),o=n(2039);t.sum=(e,t)=>{s(t);const n={name:"Sum",inputNames:t.map(((e,t)=>`X${t}`)),inputTypes:new Array(t.length).fill(o.TextureType.unpacked)};return[e.run(Object.assign(Object.assign({},n),{get:()=>i(e,t,n)}),t)]};const i=(e,t,n)=>{const i=(0,r.getGlsl)(e.session.backend.glContext.version),s=t[0].dims.slice(),a=`\n      void main() {\n        vec4 result = ${t.map(((e,t)=>`${i.texture2D}(X${t},TexCoords)`)).join(" + ")};\n        ${i.output} = result;\n      }\n    `;return Object.assign(Object.assign({},n),{output:{dims:s,type:t[0].type,textureType:o.TextureType.unpacked},hasMain:!0,shaderSource:a})},s=e=>{if(!e||0===e.length)throw new Error("Sum requires inputs.");const t=e[0].dims.length;for(let n=1;n<e.length;n++){if(t!==e[n].dims.length)throw new Error("Input shapes are mismatched.");for(let r=0;r<t;r++)if(e[0].dims[r]!==e[n].dims[r])throw new Error("Input shapes are not matched.")}if("float32"!==e[0].type&&"float64"!==e[0].type)throw new Error("Invalid input type.");for(let t=1;t<e.length;t++)if(e[0].type!==e[t].type)throw new Error("Input types are not matched.")}},5723:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.tile=void 0;const r=n(782),o=n(2039);t.tile=(e,t)=>{s(t);const n={name:"Tile",inputNames:["A"],inputTypes:[o.TextureType.unpacked]};return[e.run(Object.assign(Object.assign({},n),{get:()=>i(e,t,n)}),t)]};const i=(e,t,n)=>{const r=t[0].dims.slice(),i=new Array(r.length),s=[];for(let e=0;e<r.length;e++)i[e]=r[e]*t[1].numberData[e],s.push(`inputIdx[${e}] = int(mod(float(outputIdx[${e}]), ${r[e]}.));`);const a=i.length,l=`\n      float process(int outputIdx[${a}]) {\n        int inputIdx[${a}];\n        ${s.join("\n")}\n        return _A(inputIdx);\n      }\n    `;return Object.assign(Object.assign({},n),{output:{dims:i,type:t[0].type,textureType:o.TextureType.unpacked},shaderSource:l})},s=e=>{if(!e||2!==e.length)throw new Error("Tile requires 2 input.");if(1!==e[1].dims.length)throw new Error("The second input shape must 1 dimension.");if(e[1].dims[0]!==e[0].dims.length)throw new Error("Invalid input shape.");if(-1===r.NUMBER_TYPES.indexOf(e[0].type))throw new Error("Invalid input type.");if("int32"!==e[1].type&&"int16"!==e[1].type)throw new Error("Invalid repeat type.")}},3738:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseTransposeAttributes=t.transpose=void 0;const r=n(246),o=n(2517),i=n(2039),s={name:"Transpose",inputNames:["A"],inputTypes:[i.TextureType.unpacked]};t.transpose=(e,t,n)=>(p(t),[e.run(Object.assign(Object.assign({},s),{cacheHint:n.cacheKey,get:()=>a(e,t[0],n.perm)}),t)]),t.parseTransposeAttributes=e=>(0,r.createAttributeWithCacheKey)({perm:e.attributes.getInts("perm",[])});const a=(e,t,n)=>{const r=t.dims;n=l(r,n);const o=c(r,n),a=r.length,p=`\n      ${u("perm",n,a)}\n      float process(int indices[${a}]) {\n        int a[${a}];\n        perm(a, indices);\n        return _A(a);\n      }`;return Object.assign(Object.assign({},s),{output:{dims:o,type:t.type,textureType:i.TextureType.unpacked},shaderSource:p})},l=(e,t)=>(t&&t.length!==e.length&&(t=[...e.keys()].reverse()),t),c=(e,t)=>(t=l(e,t),o.ShapeUtil.sortBasedOnPerm(e,t)),u=(e,t,n)=>{const r=[];r.push(`void ${e}(out int a[${n}], int src[${n}]) {`);for(let e=0;e<n;++e)r.push(`\ta[${t[e]}]=src[${e}];`);return r.push("\t}"),r.join("\n")},p=e=>{if(!e||1!==e.length)throw new Error("Transpose requires 1 input.");if("float32"!==e[0].type&&"float64"!==e[0].type)throw new Error("input should be float tensor")}},8710:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.encodeAsUint8=void 0;const r=n(5060),o=n(2039);t.encodeAsUint8=(e,t)=>{const n=t.shape,i=(0,r.getGlsl)(e.session.backend.glContext.version),s=`\n    const float FLOAT_MAX = 1.70141184e38;\n    const float FLOAT_MIN = 1.17549435e-38;\n\n    bool isNaN(float val) {\n      return (val < 1.0 || 0.0 < val || val == 0.0) ? false : true;\n    }\n\n    highp vec4 encodeAsUint8(highp float v) {\n      if (isNaN(v)) {\n        return vec4(255, 255, 255, 255);\n      }\n\n      highp float av = abs(v);\n\n      if(av < FLOAT_MIN) {\n        return vec4(0.0, 0.0, 0.0, 0.0);\n      } else if(v > FLOAT_MAX) {\n        return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;\n      } else if(v < -FLOAT_MAX) {\n        return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;\n      }\n\n      highp vec4 c = vec4(0,0,0,0);\n\n      highp float e = floor(log2(av));\n      highp float m = exp2(fract(log2(av))) - 1.0;\n\n      c[2] = floor(128.0 * m);\n      m -= c[2] / 128.0;\n      c[1] = floor(32768.0 * m);\n      m -= c[1] / 32768.0;\n      c[0] = floor(8388608.0 * m);\n\n      highp float ebias = e + 127.0;\n      c[3] = floor(ebias / 2.0);\n      ebias -= c[3] * 2.0;\n      c[2] += floor(ebias) * 128.0;\n\n      c[3] += 128.0 * step(0.0, -v);\n\n      return c / 255.0;\n    }\n\n    void main() {\n      float value = ${i.texture2D}(X,TexCoords).r;\n      ${i.output} = encodeAsUint8(value);\n    }`,a={name:"Uint8Encode",inputTypes:[o.TextureType.unpacked],inputNames:["X"],output:{dims:n,type:t.tensor.type,textureType:o.TextureType.downloadUint8AsFloat},shaderSource:s,hasMain:!0};return e.executeProgram(a,[t.tensor])}},4909:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.tanh=t.tan=t.sqrt=t.sin=t.sigmoid=t.relu=t.not=t.neg=t.log=t.parseLeakyReluAttributes=t.leakyRelu=t.identity=t.floor=t.exp=t.parseEluAttributes=t.elu=t.cos=t.ceil=t.clipV11=t.parseClipAttributes=t.clip=t.atan=t.asin=t.acos=t.abs=t.glslTanh=t.glslTan=t.glslSqrt=t.glslSigmoid=t.glslRelu=t.glslSin=t.glslNot=t.glslNeg=t.glslLog=t.glslLeakyRelu=t.glslIdentity=t.glslClip=t.glslFloor=t.glslExp=t.glslElu=t.glslCos=t.glslCeil=t.glslAtan=t.glslAsin=t.glslAcos=t.glslAbs=void 0;const r=n(246),o=n(2517),i=n(8520),s=n(5060),a=n(2039);function l(){return F("abs")}function c(){return F("acos")}function u(){return F("asin")}function p(){return F("atan")}function d(){return F("ceil")}function _(){return F("cos")}function h(e){const t="elu";return{body:`\n  const float alpha = float(${e});\n\n  float ${t}_(float a) {\n    return a >= 0.0 ? a: (exp(a) - 1.0) * alpha;\n  }\n  vec4 ${t}_(vec4 v) {\n    return vec4(${t}_(v.x), ${t}_(v.y), ${t}_(v.z), ${t}_(v.w));\n  }\n  `,name:t,type:i.FunctionType.ValueBased}}function f(){return F("exp")}function m(){return F("floor")}function g(e,t){const n="clip";return{body:`\n  const float min = float(${e});\n  const float max = float(${t});\n\n  float ${n}_(float a) {\n    return clamp(a, min, max);\n  }\n  vec4 ${n}_(vec4 v) {\n    return clamp(v, min, max);\n  }\n  `,name:n,type:i.FunctionType.ValueBased}}function b(){const e="indentity";return{body:`\n  float ${e}_(float a) {\n    return a;\n  }\n  vec4 ${e}_(vec4 v) {\n    return v;\n  }\n  `,name:e,type:i.FunctionType.ValueBased}}function w(e){const t="leakyRelu";return{body:`\n  const float alpha = float(${e});\n\n  float ${t}_(float a) {\n    return a < 0.0 ? a * alpha : a;\n  }\n  vec4 ${t}_(vec4 v) {\n    return vec4(${t}_(v.x), ${t}_(v.y), ${t}_(v.z), ${t}_(v.w));\n  }\n  `,name:t,type:i.FunctionType.ValueBased}}function x(){return F("log")}function y(){const e="neg";return{body:`\n  float ${e}_(float a) {\n    return -a;\n  }\n  vec4 ${e}_(vec4 v) {\n    return -v;\n  }\n  `,name:e,type:i.FunctionType.ValueBased}}function T(){const e="not";return{body:`\n  float ${e}_(float a) {\n    return float( ! bool(a) );\n  }\n  bool ${e}_(bool a) {\n    return !a;\n  }\n  vec4 ${e}_(vec4 v) {\n    return vec4(!bool(v.x), !bool(v.y), !bool(v.z), !bool(v.w));\n  }\n  bvec4 ${e}_(bvec4 v) {\n    return bvec4(!v.x, !v.y, !v.z, !v.w);\n  }\n  `,name:e,type:i.FunctionType.ValueBased}}function v(){return F("sin")}function k(){const e="relu";return{body:`\n  float ${e}_(float a) {\n    return max( a, 0.0 );\n  }\n  vec4 ${e}_(vec4 v) {\n    return max( v, 0.0 );\n  }\n  `,name:e,type:i.FunctionType.ValueBased}}function M(){const e="sigmoid";return{body:`\n  float ${e}_(float a) {\n    return 1.0 / (1.0 + exp(-a));\n  }\n  vec4 ${e}_(vec4 v) {\n    return 1.0 / (1.0 + exp(-v));\n  }\n  `,name:e,type:i.FunctionType.ValueBased}}function S(){return F("sqrt")}function P(){return F("tan")}function A(){const e="tanh";return{body:`\n  float ${e}_(float a) {\n    a = clamp(a, -10., 10.);\n    a = exp(2.*a);\n    return (a - 1.) / (a + 1.);\n  }\n  vec4 ${e}_(vec4 v) {\n    v = clamp(v, -10., 10.);\n    v = exp(2.*v);\n    return (v - 1.) / (v + 1.);\n  }\n  `,name:e,type:i.FunctionType.ValueBased}}function F(e){return{body:`\n  float ${e}_(float a) {\n    return ${e}(a);\n  }\n  vec4 ${e}_(vec4 v) {\n    return ${e}(v);\n  }\n  `,name:e,type:i.FunctionType.ValueBased}}t.glslAbs=l,t.glslAcos=c,t.glslAsin=u,t.glslAtan=p,t.glslCeil=d,t.glslCos=_,t.glslElu=h,t.glslExp=f,t.glslFloor=m,t.glslClip=g,t.glslIdentity=b,t.glslLeakyRelu=w,t.glslLog=x,t.glslNeg=y,t.glslNot=T,t.glslSin=v,t.glslRelu=k,t.glslSigmoid=M,t.glslSqrt=S,t.glslTan=P,t.glslTanh=A;const C=(e,t,n,r)=>{const o=e.session.pack?a.TextureType.packed:a.TextureType.unpacked,i={name:n.name,inputTypes:[o],inputNames:["A"],cacheHint:r};return Object.assign(Object.assign({},i),{get:()=>((e,t,n,r)=>{const o=e.session.pack?a.TextureType.packed:a.TextureType.unpacked,i=(0,s.getGlsl)(e.session.backend.glContext.version);return Object.assign(Object.assign({},t),{output:{dims:n.dims,type:n.type,textureType:o},shaderSource:`\n     ${r.body}\n     void main() {\n       vec4 v = ${i.texture2D}(A, TexCoords);\n       v = ${r.name}_(v);\n       ${i.output} = v;\n     }\n     `,hasMain:!0})})(e,i,t,n)})};t.abs=(e,t)=>[e.run(C(e,t[0],l()),t)],t.acos=(e,t)=>[e.run(C(e,t[0],c()),t)],t.asin=(e,t)=>[e.run(C(e,t[0],u()),t)],t.atan=(e,t)=>[e.run(C(e,t[0],p()),t)],t.clip=(e,t,n)=>[e.run(C(e,t[0],g(n.min,n.max),n.cacheKey),t)],t.parseClipAttributes=e=>(0,r.createAttributeWithCacheKey)({min:e.attributes.getFloat("min",o.MIN_CLIP),max:e.attributes.getFloat("max",o.MAX_CLIP)}),t.clipV11=(e,n)=>{const r=E(e,n);return(0,t.clip)(e,[n[0]],r)};const E=(e,t)=>{if(t.length>=3&&(!e.session.isInitializer(t[1].dataId)||!e.session.isInitializer(t[2].dataId)))throw new Error("dynamic clip attributes are not allowed");const n=t.length>=3?t[1].numberData[0]:o.MIN_CLIP,i=t.length>=3?t[2].numberData[0]:o.MAX_CLIP;return(0,r.createAttributeWithCacheKey)({min:n,max:i})};t.ceil=(e,t)=>[e.run(C(e,t[0],d()),t)],t.cos=(e,t)=>[e.run(C(e,t[0],_()),t)],t.elu=(e,t,n)=>[e.run(C(e,t[0],h(n.alpha),n.cacheKey),t)],t.parseEluAttributes=e=>(0,r.createAttributeWithCacheKey)({alpha:e.attributes.getFloat("alpha",1)}),t.exp=(e,t)=>[e.run(C(e,t[0],f()),t)],t.floor=(e,t)=>[e.run(C(e,t[0],m()),t)],t.identity=(e,t)=>[e.run(C(e,t[0],b()),t)],t.leakyRelu=(e,t,n)=>[e.run(C(e,t[0],w(n.alpha),n.cacheKey),t)],t.parseLeakyReluAttributes=e=>(0,r.createAttributeWithCacheKey)({alpha:e.attributes.getFloat("alpha",.01)}),t.log=(e,t)=>[e.run(C(e,t[0],x()),t)],t.neg=(e,t)=>[e.run(C(e,t[0],y()),t)],t.not=(e,t)=>[e.run(C(e,t[0],T()),t)],t.relu=(e,t)=>[e.run(C(e,t[0],k()),t)],t.sigmoid=(e,t)=>[e.run(C(e,t[0],M()),t)],t.sin=(e,t)=>[e.run(C(e,t[0],v()),t)],t.sqrt=(e,t)=>[e.run(C(e,t[0],S()),t)],t.tan=(e,t)=>[e.run(C(e,t[0],P()),t)],t.tanh=(e,t)=>[e.run(C(e,t[0],A()),t)]},5611:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createUnpackProgramInfoLoader=t.createUnpackProgramInfo=void 0;const r=n(5060),o=n(2039),i=n(9390),s=n(2827),a={name:"unpack",inputNames:["A"],inputTypes:[o.TextureType.packed]};t.createUnpackProgramInfo=(e,t)=>{const n=t.dims.length,l=(0,s.getChannels)("rc",n),c=l.slice(-2),u=(0,i.getCoordsDataType)(n),p=(0,s.unpackFromChannel)(),d=0===t.dims.length?"":function(e,t){if(1===e)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}(n,l),_=n<=1?"rc":`vec2(${c.join(",")})`,h=`\n    ${p}\n    void main() {\n      ${u} rc = getOutputCoords();\n\n       // Sample the texture with the coords to get the rgba channel value.\n       vec4 packedInput = getA(${d});\n\n       ${(0,r.getGlsl)(e.session.backend.glContext.version).output} = vec4(getChannel(packedInput, ${_}), 0, 0, 0);\n     }\n   `;return Object.assign(Object.assign({},a),{hasMain:!0,output:{dims:t.dims,type:t.type,textureType:o.TextureType.unpacked},shaderSource:h})},t.createUnpackProgramInfoLoader=(e,n)=>Object.assign(Object.assign({},a),{get:()=>(0,t.createUnpackProgramInfo)(e,n)})},8428:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseUnsqueezeAttributes=t.unsqueezeV13=t.unsqueeze=void 0;const r=n(2517);t.unsqueeze=(e,t,n)=>{o(t);const i=r.ShapeUtil.unsqueezeShape(t[0].dims,n);return[e.reshapeUnpacked(t[0],i)]},t.unsqueezeV13=(e,n)=>(i(n),(0,t.unsqueeze)(e,[n[0]],Array.from(n[1].integerData))),t.parseUnsqueezeAttributes=e=>e.attributes.getInts("axes");const o=e=>{if(!e||1!==e.length)throw new Error("Unsqueeze requires 1 input.");if("string"===e[0].type)throw new Error("invalid input tensor types.")},i=e=>{if(!e||2!==e.length)throw new Error("Unsqueeze requires 2 inputs.");if("int32"!==e[1].type)throw new Error("Invalid input type.")}},9793:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.scalesValidation=t.validateInputs=t.parseUpsampleAttributes=t.parseUpsampleAttributesV9=t.parseUpsampleAttributesV7=t.upsample=void 0;const r=n(246),o=n(5060),i=n(2039),s={name:"Upsample",inputNames:["X"],inputTypes:[i.TextureType.unpacked]};t.upsample=(e,n,r)=>((0,t.validateInputs)(n,r),[e.run(Object.assign(Object.assign({},s),{cacheHint:r.cacheKey,get:()=>a(e,n,r)}),n)]),t.parseUpsampleAttributesV7=e=>(0,t.parseUpsampleAttributes)(e,7),t.parseUpsampleAttributesV9=e=>(0,t.parseUpsampleAttributes)(e,9),t.parseUpsampleAttributes=(e,n)=>{const o=n>=10,i=e.attributes.getString("mode","nearest");if("nearest"!==i&&"linear"!==i&&(n<11||"cubic"!==i))throw new Error(`unrecognized mode: ${i}`);let s=[];n<9&&(s=e.attributes.getFloats("scales"),(0,t.scalesValidation)(s,i,o));const a=e.attributes.getFloat("extrapolation_value",0),l=n>10?e.attributes.getString("coordinate_transformation_mode","half_pixel"):"asymmetric";if(-1===["asymmetric","pytorch_half_pixel","tf_half_pixel_for_nn","align_corners","tf_crop_and_resize","half_pixel"].indexOf(l))throw new Error(`coordinate_transform_mode '${l}' is not supported`);const c="tf_crop_and_resize"===l,u=c,p="nearest"===i&&n>=11?e.attributes.getString("nearest_mode","round_prefer_floor"):"";if(-1===["round_prefer_floor","round_prefer_ceil","floor","ceil",""].indexOf(p))throw new Error(`nearest_mode '${p}' is not supported`);const d=e.attributes.getFloat("cubic_coeff_a",-.75),_=0!==e.attributes.getInt("exclude_outside",0);if(_&&"cubic"!==i)throw new Error("exclude_outside can be set to 1 only when mode is CUBIC.");const h=n<11||"nearest"===i&&"asymmetric"===l&&"floor"===p;let f=0,m=0,g=0;return n>10?e.inputs.length>2?(f=1,m=2,g=3):(m=1,g=2):9===n&&(m=1),(0,r.createAttributeWithCacheKey)({opset:n,isResize:o,mode:i,scales:s,extrapolationValue:a,coordinateTransformMode:l,useExtrapolation:u,needRoiInput:c,nearestMode:p,cubicCoefficientA:d,excludeOutside:_,useNearest2xOptimization:h,roiInputIdx:f,scalesInputIdx:m,sizesInputIdx:g})};const a=(e,t,n)=>{const r=(0,o.getGlsl)(e.session.backend.glContext.version),[a,l]=e.calculateTextureWidthAndHeight(t[0].dims,i.TextureType.unpacked),c=t[0].dims.map(((e,t)=>Math.floor(e*n.scales[t]))),[u,p]=e.calculateTextureWidthAndHeight(c,i.TextureType.unpacked),d=c.length,_=new Array(d),h=new Array(d);let f=`\n      int output_pitches[${d}];\n      int input_pitches[${d}];\n      `;for(let e=d-1;e>=0;e--)_[e]=e===d-1?1:_[e+1]*c[e+1],h[e]=e===d-1?1:h[e+1]*t[0].dims[e+1],f+=`\n        output_pitches[${e}] = ${_[e]};\n        input_pitches[${e}] = ${h[e]};\n        `;const m=`\n      float getInputFloat(int index) {\n        vec2 coords = offsetToCoords(index, ${a}, ${l});\n        float value = getColorAsFloat(${r.texture2D}(X, coords));\n        return value;\n      }\n      `,g="nearest"===n.mode?`\n    ${m}\n    float process(int indices[${d}]) {\n      int input_index = 0;\n      int output_index = coordsToOffset(TexCoords, ${u}, ${p});\n\n      ${f}\n\n      int d, m;\n      for (int dim = 0; dim < ${d}; ++dim) {\n        d = output_index / output_pitches[dim];\n        m = output_index - d * output_pitches[dim];\n        output_index = m;\n\n        if (scales[dim] != 1 && d > 0) {\n          int d2 = d / scales[dim];\n          m = d - d2 * scales[dim];\n          d = d2;\n        }\n        input_index += input_pitches[dim] * d;\n      }\n\n      return getInputFloat(input_index);\n    }`:4===d?`\n    ${m}\n    float process(int indices[4]) {\n      int input_index = 0;\n      int output_index = coordsToOffset(TexCoords, ${u}, ${p});\n\n      ${f}\n\n      int m;\n      int index_of_dim0, index_of_dim1, index_of_dim2, index_of_dim3;\n      index_of_dim0 = output_index / output_pitches[0];\n      m = output_index - index_of_dim0 * output_pitches[0];\n      index_of_dim1 = m / output_pitches[1];\n      m = m - index_of_dim1 * output_pitches[1];\n      index_of_dim2 = m / output_pitches[2];\n      m = m - index_of_dim2 * output_pitches[2];\n      index_of_dim3 = m;\n\n      int index_of_input_dim2, index_of_input_dim3, x_offset, y_offset;\n      index_of_input_dim2 = index_of_dim2 / scales[2];\n      y_offset = index_of_dim2 - index_of_input_dim2 * scales[2];\n      index_of_input_dim3 = index_of_dim3 / scales[3];\n      x_offset = index_of_dim3 - index_of_input_dim3 * scales[3];\n\n      input_index = index_of_dim0 * input_pitches[0] +\n            index_of_dim1 * input_pitches[1] +\n            index_of_input_dim2 * input_pitches[2] +\n            index_of_input_dim3;\n\n      float x00 = getInputFloat(input_index);\n      float x10, x01, x11;\n\n      bool end_of_dim2 = false;\n      if (index_of_input_dim2 == (${t[0].dims[2]} - 1)) {\n        // It's the end in dimension 2\n        x01 = x00;\n        end_of_dim2 = true;\n      } else {\n        x01 = getInputFloat(input_index + input_pitches[2]);\n      }\n\n      if (index_of_input_dim3 == (input_pitches[2] - 1)) {\n        // It's the end in dimension 3\n        x10 = x00;\n        x11 = x01;\n      }\n      else {\n        x10 = getInputFloat(input_index + 1);\n        x11 = end_of_dim2 ? x10 : getInputFloat(input_index + input_pitches[2] + 1);\n      }\n\n      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[2]);\n      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[2]);\n      return y0 + float(x_offset) * (y1 - y0) / float(scales[3]);\n    }`:`\n    ${m}\n    float process(int indices[2]) {\n      int input_index = 0;\n      int output_index = coordsToOffset(TexCoords, ${u}, ${p});\n\n      ${f}\n\n      int m;\n      int index_of_dim0, index_of_dim1;\n      index_of_dim0 = output_index / output_pitches[0];\n      m = output_index - index_of_dim0 * output_pitches[0];\n      index_of_dim1 = m;\n\n      int index_of_input_dim0, index_of_input_dim1, x_offset, y_offset;\n      index_of_input_dim0 = index_of_dim0 / scales[0];\n      y_offset = index_of_dim0 - index_of_input_dim0 * scales[0];\n      index_of_input_dim1 = index_of_dim1 / scales[1];\n      x_offset = index_of_dim1 - index_of_input_dim1 * scales[1];\n\n      input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1;\n\n      float x00 = getInputFloat(input_index);\n      float x10, x01, x11;\n\n      bool end_of_dim0 = false;\n      if (index_of_input_dim0 == (${t[0].dims[0]} - 1)) {\n        // It's the end in dimension 0\n        x01 = x00;\n        end_of_dim0 = true;\n      } else {\n        x01 = getInputFloat(input_index + input_pitches[0]);\n      }\n\n      if (index_of_input_dim1 == (input_pitches[0] - 1)) {\n        // It's the end in dimension 1\n        x10 = x00;\n    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Map,this.unpackedTextureDataCache.forEach((e=>this.textureManager.releaseTexture(e,!0))),this.unpackedTextureDataCache=new Map}resolve(e,t,n){const r=(0,o.resolveOperator)(e,t,s.WEBGL_OP_RESOLVE_RULES);return{impl:r.opImpl,context:r.opInit?r.opInit(e,n):e}}}},7769:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.Uint8DataEncoder=t.RGBAFloatDataEncoder=t.RedFloat32DataEncoder=void 0;const r=n(6231);t.RedFloat32DataEncoder=class{constructor(e,t=1){if(1===t)this.internalFormat=e.R32F,this.format=e.RED,this.textureType=e.FLOAT,this.channelSize=t;else{if(4!==t)throw new Error(`Invalid number of channels: ${t}`);this.internalFormat=e.RGBA32F,this.format=e.RGBA,this.textureType=e.FLOAT,this.channelSize=t}}encode(e,t){let n,o;return e.constructor!==Float32Array&&(r.Logger.warning("Encoder","data was not of type Float32; creating new Float32Array"),o=new Float32Array(e)),t*this.channelSize>e.length?(r.Logger.warning("Encoder","Source data too small. 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n=t.breakAxis>=e.length?1:e.slice(t.breakAxis).reduce(((e,t)=>e*t)),i=t.breakAxis<=0?1:e.slice(0,t.breakAxis).reduce(((e,t)=>e*t));if(!(n>o||i>o))return[n,i];r.Logger.verbose("TextureLayout",`Given width/height preferences were unattainable: shape:${e}, breakAxis:${t.breakAxis}`)}let s=e.slice(0);if(n&&(o*=2,s=s.map(((e,t)=>t>=s.length-2?s[t]%2==0?s[t]:s[t]+1:s[t])),1===s.length&&(s=[2,s[0]])),2!==s.length){const e=i(s);s=e.newShape}const a=l(s);return s.length<=1&&a<=o?[1,a]:2===s.length&&s[0]<=o&&s[1]<=o?s:3===s.length&&s[0]*s[1]<=o&&s[2]<=o?[s[0]*s[1],s[2]]:3===s.length&&s[0]<=o&&s[1]*s[2]<=o?[s[0],s[1]*s[2]]:4===s.length&&s[0]*s[1]*s[2]<=o&&s[3]<=o?[s[0]*s[1]*s[2],s[3]]:4===s.length&&s[0]<=o&&s[1]*s[2]*s[3]<=o?[s[0],s[1]*s[2]*s[3]]:n?c(a/4).map((e=>2*e)):c(a)}},t.squeezeShape=i,t.parseAxisParam=s,t.isInt=a,t.sizeFromShape=l,t.getRowsCols=function(e){if(0===e.length)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]},t.sizeToSquarishShape=c,t.getBatchDim=function(e,t=2){return l(e.slice(0,e.length-t))}},4057:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createTextureLayoutFromShape=t.calculateTextureWidthAndHeight=t.createTextureLayoutFromTextureType=void 0;const r=n(2517),o=n(2039);t.createTextureLayoutFromTextureType=(e,n,r)=>{const i=r===o.TextureType.unpacked||r===o.TextureType.unpackedReversed?1:4,s=r===o.TextureType.packed,a=r===o.TextureType.unpackedReversed||r===o.TextureType.packed,l=r===o.TextureType.packedLastDimension?n.length-1:void 0,c=r===o.TextureType.packedLastDimension?n.map(((e,t)=>t===n.length-1?4*e:e)):void 0;return(0,t.createTextureLayoutFromShape)(e,n,i,c,{isPacked:s,reverseWH:a,breakAxis:l})},t.calculateTextureWidthAndHeight=(e,n,r)=>{const o=(0,t.createTextureLayoutFromTextureType)(e,n,r);return[o.width,o.height]},t.createTextureLayoutFromShape=(e,t,n=1,o,i)=>{const s=!(!i||!i.isPacked),[a,l]=e.computeTextureWH(s&&o||t,i),c=t.length;let u=t.slice(0);if(0===c&&(u=[1]),1===n)o=t;else if(s){if(4!==n)throw new Error("a packed texture must be 4-channel");o=t,c>0&&(u[c-1]=Math.ceil(u[c-1]/2)),c>1&&(u[c-2]=Math.ceil(u[c-2]/2))}else if(!o)throw new Error("Unpacked shape is needed when using channels > 1");return{width:a,height:l,channels:n,isPacked:s,shape:u,strides:r.ShapeUtil.computeStrides(u),unpackedShape:o,reversedWH:i&&i.reverseWH}}},5702:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.TextureManager=void 0;const r=n(6231);t.TextureManager=class{constructor(e,t,n,r){this.glContext=e,this.layoutStrategy=t,this.profiler=n,this.config=r,this.pendingRead=new Map,r.reuseTextures&&(this.inUseTextures=new Map,this.idleTextures=new Map,this.textureLookup=new Map)}createTextureFromLayout(e,t,n,o){const i=this.toEncoderType(e),s=this.glContext.getEncoder(i,t.channels||1,o);if(t.isPacked&&1===o)throw new Error("not implemented");const a=t.width,l=t.height;let c,u;if(this.config.reuseTextures){c=`${a}x${l}_${s.format}_${s.internalFormat}_${s.textureType}`,u=this.inUseTextures.get(c),u||(u=[],this.inUseTextures.set(c,u));const t=this.idleTextures.get(c);if(t&&t.length>0){const r=t.pop();return u.push(r),1===o&&this.glContext.updateTexture(r,a,l,s,this.toTextureData(e,n)),r}}r.Logger.verbose("TextureManager",`Creating new texture of size ${t.width}x${t.height}`);const p=this.glContext.allocateTexture(a,l,s,this.toTextureData(e,n));return this.config.reuseTextures&&(u.push(p),this.textureLookup.set(p,c)),p}readTexture(e,t,n){return n||(n=1),this.profiler.event("backend","TextureManager.readTexture",(()=>{const r=e.shape.reduce(((e,t)=>e*t))*n,o=this.glContext.readTexture(e.texture,e.width,e.height,r,this.toEncoderType(t),n);return this.toTensorData(t,o)}))}async readTextureAsync(e,t,n){const r=e.tensor.dataId;if(n||(n=1),this.pendingRead.has(r)){const e=this.pendingRead.get(r);return new Promise((t=>null==e?void 0:e.push(t)))}return this.profiler.event("backend","TextureManager.readTextureAsync",(async()=>{this.pendingRead.set(r,[]);const o=e.shape.reduce(((e,t)=>e*t))*n;await this.glContext.createAndWaitForFence();const i=this.glContext.readTexture(e.texture,e.width,e.height,o,this.toEncoderType(t),n),s=this.toTensorData(t,i),a=this.pendingRead.get(r);return this.pendingRead.delete(r),null==a||a.forEach((e=>e(s))),s}))}readUint8TextureAsFloat(e){return this.profiler.event("backend","TextureManager.readUint8TextureAsFloat",(()=>{const t=e.shape.reduce(((e,t)=>e*t)),n=this.glContext.readTexture(e.texture,e.width,e.height,4*t,"byte",4);return new Float32Array(n.buffer,n.byteOffset,t)}))}releaseTexture(e,t){let n;if(this.config.reuseTextures&&(n=this.textureLookup.get(e.texture),n)){t&&this.textureLookup.delete(n);const r=this.inUseTextures.get(n);if(r){const t=r.indexOf(e.texture);if(-1!==t){r.splice(t,1);let o=this.idleTextures.get(n);o||(o=[],this.idleTextures.set(n,o)),o.push(e.texture)}}}n&&!t||(r.Logger.verbose("TextureManager",`Deleting texture of size ${e.width}x${e.height}`),this.glContext.deleteTexture(e.texture))}toTensorData(e,t){switch(e){case"int16":return t instanceof Int16Array?t:Int16Array.from(t);case"int32":return t instanceof Int32Array?t:Int32Array.from(t);case"int8":return t instanceof Int8Array?t:Int8Array.from(t);case"uint16":return t instanceof Uint16Array?t:Uint16Array.from(t);case"uint32":return t instanceof Uint32Array?t:Uint32Array.from(t);case"uint8":case"bool":return t instanceof Uint8Array?t:Uint8Array.from(t);case"float32":return t instanceof Float32Array?t:Float32Array.from(t);case"float64":return t instanceof Float64Array?t:Float64Array.from(t);default:throw new Error(`TensorData type ${e} is not supported`)}}toTextureData(e,t){if(t)return t instanceof Float32Array?t:new Float32Array(t)}toEncoderType(e){return"float"}clearActiveTextures(){this.glContext.clearActiveTextures()}}},2039:(e,t)=>{var n;Object.defineProperty(t,"__esModule",{value:!0}),t.TextureType=void 0,(n=t.TextureType||(t.TextureType={}))[n.unpacked=0]="unpacked",n[n.unpackedReversed=1]="unpackedReversed",n[n.packed=2]="packed",n[n.downloadUint8AsFloat=3]="downloadUint8AsFloat",n[n.packedLastDimension=4]="packedLastDimension"},9390:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.getGlChannels=t.getCoordsDataType=t.getSqueezedParams=t.squeezeInputShape=t.generateShaderFuncNameFromInputSamplerNameAtOutCoords=t.generateShaderFuncNameFromInputSamplerName=t.repeatedTry=t.getPackedShape=void 0;const r=n(2517);t.getPackedShape=function(e){const t=e.length;return e.slice(0,t-1).concat(e[t-1]/4)},t.repeatedTry=async function(e,t=(e=>0),n){return new Promise(((r,o)=>{let i=0;const s=()=>{if(e())return void r();i++;const a=t(i);null!=n&&i>=n?o():setTimeout(s,a)};s()}))},t.generateShaderFuncNameFromInputSamplerName=function(e){return(0,r.assert)(void 0!==e&&0!==e.length,(()=>"empty string found for sampler name")),"get"+e.charAt(0).toUpperCase()+e.slice(1)},t.generateShaderFuncNameFromInputSamplerNameAtOutCoords=function(e){return(0,r.assert)(void 0!==e&&0!==e.length,(()=>"empty string found for sampler name")),"get"+e.charAt(0).toUpperCase()+e.slice(1)+"AtOutCoords"},t.squeezeInputShape=function(e,t){let n=JSON.parse(JSON.stringify(e));return n=t,n},t.getSqueezedParams=function(e,t){return t.map((t=>e[t])).join(", ")},t.getCoordsDataType=function(e){if(e<=1)return"int";if(2===e)return"ivec2";if(3===e)return"ivec3";if(4===e)return"ivec4";if(5===e)return"ivec5";if(6===e)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)},t.getGlChannels=function(e=6){return["x","y","z","w","u","v"].slice(0,e)}},7305:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createNewWebGLContext=t.createWebGLContext=void 0;const r=n(6231),o=n(1713),i={};function s(e){const t=function(){if("undefined"==typeof document){if("undefined"==typeof OffscreenCanvas)throw new TypeError("failed to create canvas: OffscreenCanvas is not supported");return new OffscreenCanvas(1,1)}const e=document.createElement("canvas");return e.width=1,e.height=1,e}();let n;const i={alpha:!1,depth:!1,antialias:!1,stencil:!1,preserveDrawingBuffer:!1,premultipliedAlpha:!1,failIfMajorPerformanceCaveat:!1};if((!e||"webgl2"===e)&&(n=t.getContext("webgl2",i),n))try{return new o.WebGLContext(n,2)}catch(e){r.Logger.warning("GlContextFactory",`failed to create WebGLContext using contextId 'webgl2'. 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Error: ${e}`)}throw new Error("WebGL is not supported")}t.createWebGLContext=function e(t){let n;t&&"webgl2"!==t||!("webgl2"in i)?t&&"webgl"!==t||!("webgl"in i)||(n=i.webgl):n=i.webgl2,n=n||s(t),t=t||1===n.version?"webgl":"webgl2";const r=n.gl;return i[t]=n,r.isContextLost()?(delete i[t],e(t)):(r.disable(r.DEPTH_TEST),r.disable(r.STENCIL_TEST),r.disable(r.BLEND),r.disable(r.DITHER),r.disable(r.POLYGON_OFFSET_FILL),r.disable(r.SAMPLE_COVERAGE),r.enable(r.SCISSOR_TEST),r.enable(r.CULL_FACE),r.cullFace(r.BACK),n)},t.createNewWebGLContext=s},1713:function(e,t,n){var r=this&&this.__createBinding||(Object.create?function(e,t,n,r){void 0===r&&(r=n);var o=Object.getOwnPropertyDescriptor(t,n);o&&!("get"in o?!t.__esModule:o.writable||o.configurable)||(o={enumerable:!0,get:function(){return t[n]}}),Object.defineProperty(e,r,o)}:function(e,t,n,r){void 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o=this.gl,i=o.createTexture();o.bindTexture(o.TEXTURE_2D,i),o.texParameteri(o.TEXTURE_2D,o.TEXTURE_MIN_FILTER,o.NEAREST),o.texParameteri(o.TEXTURE_2D,o.TEXTURE_MAG_FILTER,o.NEAREST),o.texParameteri(o.TEXTURE_2D,o.TEXTURE_WRAP_S,o.CLAMP_TO_EDGE),o.texParameteri(o.TEXTURE_2D,o.TEXTURE_WRAP_T,o.CLAMP_TO_EDGE);const s=r?n.encode(r,e*t):null;return o.texImage2D(o.TEXTURE_2D,0,n.internalFormat,e,t,0,n.format,n.textureType,s),this.checkError(),i}updateTexture(e,t,n,r,o){const i=this.gl;i.bindTexture(i.TEXTURE_2D,e);const s=r.encode(o,t*n);i.texSubImage2D(i.TEXTURE_2D,0,0,0,t,n,r.format,r.textureType,s),this.checkError()}attachFramebuffer(e,t,n){const r=this.gl;r.bindTexture(r.TEXTURE_2D,e),r.bindFramebuffer(r.FRAMEBUFFER,this.framebuffer),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,e,0),this.checkError(),r.viewport(0,0,t,n),r.scissor(0,0,t,n)}readTexture(e,t,n,r,o,i){const s=this.gl;i||(i=1),this.frameBufferBound||this.attachFramebuffer(e,t,n);const a=this.getEncoder(o,i),l=a.allocate(t*n);return s.bindTexture(s.TEXTURE_2D,e),s.framebufferTexture2D(s.FRAMEBUFFER,s.COLOR_ATTACHMENT0,s.TEXTURE_2D,e,0),s.readPixels(0,0,t,n,s.RGBA,a.textureType,l),this.checkError(),a.decode(l,r)}isFramebufferReady(){return!0}getActiveTexture(){const e=this.gl;return"TEXTURE"+(e.getParameter(this.gl.ACTIVE_TEXTURE)-e.TEXTURE0)}getTextureBinding(){return this.gl.getParameter(this.gl.TEXTURE_BINDING_2D)}getFramebufferBinding(){return this.gl.getParameter(this.gl.FRAMEBUFFER_BINDING)}setVertexAttributes(e,t){const n=this.gl;n.vertexAttribPointer(e,3,n.FLOAT,!1,20,0),n.enableVertexAttribArray(e),-1!==t&&(n.vertexAttribPointer(t,2,n.FLOAT,!1,20,12),n.enableVertexAttribArray(t)),this.checkError()}createProgram(e,t){const n=this.gl,r=n.createProgram();return n.attachShader(r,e),n.attachShader(r,t),n.linkProgram(r),r}compileShader(e,t){const n=this.gl,r=n.createShader(t);if(!r)throw new Error(`createShader() returned null with type ${t}`);if(n.shaderSource(r,e),n.compileShader(r),!1===n.getShaderParameter(r,n.COMPILE_STATUS))throw new Error(`Failed to compile shader: ${n.getShaderInfoLog(r)}\nShader source:\n${e}`);return r}deleteShader(e){this.gl.deleteShader(e)}bindTextureToUniform(e,t,n){const r=this.gl;r.activeTexture(r.TEXTURE0+t),this.checkError(),r.bindTexture(r.TEXTURE_2D,e),this.checkError(),r.uniform1i(n,t),this.checkError()}draw(){this.gl.drawArrays(this.gl.TRIANGLE_STRIP,0,4),this.checkError()}checkError(){if(s.env.debug){const e=this.gl,t=e.getError();let n="";switch(t){case e.NO_ERROR:return;case e.INVALID_ENUM:n="INVALID_ENUM";break;case e.INVALID_VALUE:n="INVALID_VALUE";break;case e.INVALID_OPERATION:n="INVALID_OPERATION";break;case e.INVALID_FRAMEBUFFER_OPERATION:n="INVALID_FRAMEBUFFER_OPERATION";break;case e.OUT_OF_MEMORY:n="OUT_OF_MEMORY";break;case e.CONTEXT_LOST_WEBGL:n="CONTEXT_LOST_WEBGL";break;default:n=`Unknown WebGL Error: ${t.toString(16)}`}throw new Error(n)}}deleteTexture(e){this.gl.deleteTexture(e)}deleteProgram(e){this.gl.deleteProgram(e)}getEncoder(e,t,n=0){if(2===this.version)return new a.RedFloat32DataEncoder(this.gl,t);switch(e){case"float":return 1===n||this.isRenderFloat32Supported?new a.RGBAFloatDataEncoder(this.gl,t):new a.RGBAFloatDataEncoder(this.gl,t,this.textureHalfFloatExtension.HALF_FLOAT_OES);case"int":throw new Error("not implemented");case"byte":return new a.Uint8DataEncoder(this.gl,t);default:throw new Error(`Invalid dataType: ${e}`)}}clearActiveTextures(){const e=this.gl;for(let t=0;t<this.maxTextureImageUnits;++t)e.activeTexture(e.TEXTURE0+t),e.bindTexture(e.TEXTURE_2D,null)}dispose(){if(this.disposed)return;const e=this.gl;e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteFramebuffer(this.framebuffer),e.bindBuffer(e.ARRAY_BUFFER,null),e.deleteBuffer(this.vertexbuffer),e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null),e.finish(),this.disposed=!0}createDefaultGeometry(){return new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0])}createVertexbuffer(){const e=this.gl,t=e.createBuffer();if(!t)throw new Error("createBuffer() returned null");const n=this.createDefaultGeometry();return e.bindBuffer(e.ARRAY_BUFFER,t),e.bufferData(e.ARRAY_BUFFER,n,e.STATIC_DRAW),this.checkError(),t}createFramebuffer(){const e=this.gl.createFramebuffer();if(!e)throw new Error("createFramebuffer returned null");return e}queryVitalParameters(){const e=this.gl;if(this.isFloatTextureAttachableToFrameBuffer=this.checkFloatTextureAttachableToFrameBuffer(),this.isRenderFloat32Supported=this.checkRenderFloat32(),this.isFloat32DownloadSupported=this.checkFloat32Download(),1===this.version&&!this.textureHalfFloatExtension&&!this.isRenderFloat32Supported)throw new Error("both float32 and float16 TextureType are not supported");this.isBlendSupported=!this.isRenderFloat32Supported||this.checkFloat32Blend(),this.maxTextureSize=e.getParameter(e.MAX_TEXTURE_SIZE),this.maxTextureImageUnits=e.getParameter(e.MAX_TEXTURE_IMAGE_UNITS),this.version}getExtensions(){2===this.version?(this.colorBufferFloatExtension=this.gl.getExtension("EXT_color_buffer_float"),this.disjointTimerQueryWebgl2Extension=this.gl.getExtension("EXT_disjoint_timer_query_webgl2")):(this.textureFloatExtension=this.gl.getExtension("OES_texture_float"),this.textureHalfFloatExtension=this.gl.getExtension("OES_texture_half_float"))}checkFloatTextureAttachableToFrameBuffer(){const e=this.gl,t=e.createTexture();e.bindTexture(e.TEXTURE_2D,t);const n=2===this.version?e.RGBA32F:e.RGBA;e.texImage2D(e.TEXTURE_2D,0,n,1,1,0,e.RGBA,e.FLOAT,null);const r=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,r),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0);const o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(t),e.deleteFramebuffer(r),o}checkRenderFloat32(){if(2===this.version){if(!this.colorBufferFloatExtension)return!1}else if(!this.textureFloatExtension)return!1;return this.isFloatTextureAttachableToFrameBuffer}checkFloat32Download(){if(2===this.version){if(!this.colorBufferFloatExtension)return!1}else{if(!this.textureFloatExtension)return!1;if(!this.gl.getExtension("WEBGL_color_buffer_float"))return!1}return this.isFloatTextureAttachableToFrameBuffer}checkFloat32Blend(){const e=this.gl;let t,n,r,o,i;try{t=e.createTexture(),n=e.createFramebuffer(),e.bindTexture(e.TEXTURE_2D,t);const s=2===this.version?e.RGBA32F:e.RGBA;return e.texImage2D(e.TEXTURE_2D,0,s,1,1,0,e.RGBA,e.FLOAT,null),e.bindFramebuffer(e.FRAMEBUFFER,n),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),e.enable(e.BLEND),r=e.createShader(e.VERTEX_SHADER),!!r&&(e.shaderSource(r,"void main(){}"),e.compileShader(r),o=e.createShader(e.FRAGMENT_SHADER),!!o&&(e.shaderSource(o,"precision highp float;void main(){gl_FragColor=vec4(0.5);}"),e.compileShader(o),i=e.createProgram(),!!i&&(e.attachShader(i,r),e.attachShader(i,o),e.linkProgram(i),e.useProgram(i),e.drawArrays(e.POINTS,0,1),e.getError()===e.NO_ERROR)))}finally{e.disable(e.BLEND),i&&e.deleteProgram(i),r&&e.deleteShader(r),o&&e.deleteShader(o),n&&(e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteFramebuffer(n)),t&&(e.bindTexture(e.TEXTURE_2D,null),e.deleteTexture(t))}}beginTimer(){if(2===this.version&&this.disjointTimerQueryWebgl2Extension){const e=this.gl,t=this.disjointTimerQueryWebgl2Extension,n=e.createQuery();return e.beginQuery(t.TIME_ELAPSED_EXT,n),n}throw new Error("WebGL1 profiling currently not supported.")}endTimer(){if(2!==this.version||!this.disjointTimerQueryWebgl2Extension)throw new Error("WebGL1 profiling currently not supported");{const e=this.gl,t=this.disjointTimerQueryWebgl2Extension;e.endQuery(t.TIME_ELAPSED_EXT)}}isTimerResultAvailable(e){let t=!1,n=!1;if(2!==this.version||!this.disjointTimerQueryWebgl2Extension)throw new Error("WebGL1 profiling currently not supported");{const r=this.gl,o=this.disjointTimerQueryWebgl2Extension;t=r.getQueryParameter(e,r.QUERY_RESULT_AVAILABLE),n=r.getParameter(o.GPU_DISJOINT_EXT)}return t&&!n}getTimerResult(e){let t=0;if(2!==this.version)throw new Error("WebGL1 profiling currently not supported");{const n=this.gl;t=n.getQueryParameter(e,n.QUERY_RESULT),n.deleteQuery(e)}return t/1e6}async waitForQueryAndGetTime(e){return await(0,l.repeatedTry)((()=>this.isTimerResultAvailable(e))),this.getTimerResult(e)}async createAndWaitForFence(){const e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t;const n=e,r=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);return e.flush(),t=null===r?()=>!0:()=>{const e=n.clientWaitSync(r,0,0);return e===n.ALREADY_SIGNALED||e===n.CONDITION_SATISFIED},{query:r,isFencePassed:t}}async pollFence(e){return new Promise((t=>{this.addItemToPoll((()=>e.isFencePassed()),(()=>t()))}))}pollItems(){const e=c(this.itemsToPoll.map((e=>e.isDoneFn)));for(let t=0;t<=e;++t){const{resolveFn:e}=this.itemsToPoll[t];e()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}async addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1||await(0,l.repeatedTry)((()=>(this.pollItems(),0===this.itemsToPoll.length)))}}},1036:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ExecutionPlan=void 0;const r=n(6231);class o{constructor(e,t){this.op=e,this.node=t}}t.ExecutionPlan=class{constructor(e,t,n){this.graph=e,this.profiler=n,this.initialize(t)}initialize(e){this.profiler.event("session","ExecutionPlan.initialize",(()=>{const t=this.graph.getNodes();if(t.length!==e.length)throw new Error("The size of nodes and OPs do not match.");this._ops=e.map(((e,n)=>new o(e,t[n]))),this.reset(),this._starter=[],this._ops.forEach(((e,t)=>{let n=!0;for(const t of e.node.inputs)if(!this._values[t]&&-1===this.graph.getInputIndices().indexOf(t)){n=!1;break}n&&this._starter.push(t)}))}))}reset(){this._values=this.graph.getValues().map((e=>e.tensor))}async execute(e,t){return this.profiler.event("session","ExecutionPlan.execute",(async()=>{this.reset();const n=e.createInferenceHandler(),o=this.graph.getInputIndices();if(t.length!==o.length)throw new Error(`number of input tensors don't match the number of inputs to the model: actual: ${t.length} expected: ${o.length}`);t.forEach(((e,t)=>{const n=o[t];this._values[n]=e}));const i=this._starter.slice(0),s=this.graph.getValues(),a=this.graph.getNodes();let l=0;for(;l<i.length;){const e=i[l++],t=this._ops[e],o=t.node.inputs.map((e=>this._values[e]));if(-1!==o.indexOf(void 0))throw new Error(`unresolved input detected: op: ${t.node}`);const c=o;r.Logger.verbose("ExecPlan",`Runing op:${t.node.name} (${c.map(((e,n)=>`'${t.node.inputs[n]}': ${e.type}[${e.dims.join(",")}]`)).join(", ")})`);const u=await this.profiler.event("node",t.node.name,(async()=>t.op.impl(n,c,t.op.context)));if(u.length!==t.node.outputs.length)throw new Error("the size of output does not match model definition.");u.forEach(((e,n)=>{const r=t.node.outputs[n];if(this._values[r])throw new Error(`output [${r}] already has value: op:${t.node.name}`);this._values[r]=e}));const p=new Set;u.forEach(((e,n)=>{const r=t.node.outputs[n];for(const e of s[r].to){const t=a[e];let n=!0;for(const e of t.inputs)if(!this._values[e]){n=!1;break}n&&p.add(e)}})),i.push(...p)}const c=[];for(let e=0;e<this.graph.getOutputIndices().length;e++){const t=this.graph.getOutputIndices()[e],n=this._values[t];if(void 0===n)throw new Error(`required output [${t}] does not have value`);0===t?await n.getData():n.data,c.push(n)}return r.Logger.verbose("ExecPlan","disposing of inferenceHandler"),n.dispose(),c}))}}},7070:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.Graph=void 0;const r=n(1446),o=n(7778),i=n(9395),s=n(9162),a=n(2517);var l=i.onnxruntime.experimental.fbs;t.Graph={from:(e,t)=>new p(e,t)};class c{constructor(e){this._from=void 0,this._to=[],this.tensor=void 0,this.type=void 0,e&&(this.type=a.ProtoUtil.tensorValueTypeFromProto(e.type.tensorType))}get from(){return this._from}get to(){return this._to}}class u{constructor(e,t){e instanceof r.onnx.NodeProto?(this.name=e.name,this.opType=e.opType,this.attributes=new o.Attribute(e.attribute)):e instanceof l.Node&&(this.name=null!=t?t:e.name(),this.opType=e.opType(),this.attributes=new o.Attribute(a.ProtoUtil.tensorAttributesFromORTFormat(e))),this.inputs=[],this.outputs=[],this.executeNode=!0}}class p{constructor(e,t){if(!e)throw new TypeError("graph is empty");this.buildGraph(e),this.transformGraph(t),this.checkIsAcyclic()}getInputIndices(){return this._allInputIndices}getInputNames(){return this._allInputNames}getOutputIndices(){return this._allOutputIndices}getOutputNames(){return this._allOutputNames}getValues(){return this._allData}getNodes(){return this._nodes}buildGraph(e){if(e instanceof r.onnx.GraphProto)this.buildGraphFromOnnxFormat(e);else{if(!(e instanceof l.Graph))throw new TypeError("Graph type is not supported.");this.buildGraphFromOrtFormat(e)}}buildGraphFromOnnxFormat(e){const t=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const n=new Map;if(!e.input)throw new Error("missing information in graph: input");const r=[];for(const n of e.input){if(t.has(n.name))throw new Error(`duplicated input name: ${n.name}`);const e=this._allData.push(new c(n))-1;t.set(n.name,e),r.push(n.name)}if(!e.initializer)throw new Error("missing information in graph: initializer");for(const n of e.initializer){let e=t.get(n.name);if(void 0===e){const r=new c;r.type={shape:{dims:a.ProtoUtil.tensorDimsFromProto(n.dims)},tensorType:a.ProtoUtil.tensorDataTypeFromProto(n.dataType)},e=this._allData.push(r)-1,t.set(n.name,e)}this._allData[e]._from=-1,this._allData[e].tensor=s.Tensor.fromProto(n)}for(let e=0;e<this._allData.length;e++)this._allData[e].tensor||(this._allInputIndices.push(e),this._allInputNames.push(r[e]));if(!e.output)throw new Error("missing information in graph: output");for(const n of e.output){if(t.has(n.name))throw new Error(`duplicated output name: ${n.name}`);const e=this._allData.push(new c(n))-1;t.set(n.name,e),this._allOutputIndices.push(e),this._allOutputNames.push(n.name)}if(!e.node)throw new Error("missing information in graph: node");for(const t of e.node){if(!t.name)for(let e=0;;e++){const r=`unnamed_${t.opType}_${e}`;if(!n.has(r)){t.name=r;break}}if(n.has(t.name))throw new Error(`duplicated node name: ${t.name}`);const e=this._nodes.push(new u(t))-1;n.set(t.name,e)}for(let n=0;n<this._nodes.length;n++){const r=this._nodes[n],o=e.node[n];if(!o.output)throw new Error(`missing output for node: ${o.name}`);for(const e of o.output){let i=t.get(e);if(void 0===i&&(i=this._allData.push(new c)-1,t.set(e,i)),r.outputs.push(i),void 0!==this._allData[i]._from)throw new Error(`multiple nodes output to one data value: ${i}`);if(this._allData[i]._from=n,"Constant"===o.opType){if(!o.attribute||1!==o.attribute.length||!o.attribute[0].t)throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(!o.output||1!==o.output.length)throw new Error("missing output or incorrect number of outputs for this Constant operator");r.outputs.pop(),r.executeNode=!1,this._allData[i]._from=-1,this._allData[i].tensor=s.Tensor.fromProto(o.attribute[0].t)}}}for(let n=0;n<this._nodes.length;n++){const r=this._nodes[n],o=e.node[n];if(!o.input)throw new Error(`missing input for node: ${o.name}`);for(const e of o.input){const i=t.get(e);if(void 0===i){if(""===e&&3===o.input.length&&"Resize"===o.opType)continue;throw new Error(`unrecognized input '${e}' for node: ${o.name}`)}r.inputs.push(i),this._allData[i]._to.push(n)}}return!0}buildGraphFromOrtFormat(e){var t,n,r;const o=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const i=new Map,p=[];for(let i=0;i<e.inputsLength();i++){const s=e.inputs(i);if(o.has(s))throw new Error(`duplicated input name: ${s}`);for(let i=0;i<e.nodeArgsLength();i++)if((null===(t=e.nodeArgs(i))||void 0===t?void 0:t.name())===s){const t=new c;if((null===(r=null===(n=e.nodeArgs(i))||void 0===n?void 0:n.type())||void 0===r?void 0:r.valueType())!==l.TypeInfoValue.tensor_type)throw new Error("Unexpected value type for the nodeArg.");const u=e.nodeArgs(i).type().value(new l.TensorTypeAndShape),d=a.ProtoUtil.tensorDataTypeFromProto(u.elemType()),_=u.shape(),h=[];for(let e=0;e<_.dimLength();e++)h.push(a.LongUtil.longToNumber(_.dim(e).value().dimValue()));t.type={shape:{dims:h},tensorType:d};const f=this._allData.push(t)-1;o.set(s,f),p.push(s)}}for(let t=0;t<e.initializersLength();t++){const n=e.initializers(t);let r=o.get(n.name());if(void 0===r){const e=new c,t=a.ProtoUtil.tensorDimsFromORTFormat(n),i=a.ProtoUtil.tensorDataTypeFromProto(n.dataType());e.type={shape:{dims:t},tensorType:i},r=this._allData.push(e)-1,o.set(n.name(),r)}this._allData[r]._from=-1,this._allData[r].tensor=s.Tensor.fromOrtTensor(n)}for(let e=0;e<this._allData.length;e++)this._allData[e].tensor||(this._allInputIndices.push(e),this._allInputNames.push(p[e]));for(let t=0;t<e.outputsLength();t++){const n=e.outputs(t);if(o.has(n))throw new Error(`duplicated output name: ${n}`);const r=this._allData.push(new c)-1;o.set(n,r),this._allOutputIndices.push(r),this._allOutputNames.push(n)}if(!e.nodes)throw new Error("missing information in graph: node");for(let t=0;t<e.nodesLength();t++){const n=e.nodes(t);let r=n.name();if(!r)for(let e=0;r=`unnamed_${n.opType()}_${e}`,i.has(r);e++);if(i.has(r))throw new Error(`duplicated node name: ${r}`);const o=this._nodes.push(new u(n,r))-1;i.set(r,o)}for(let t=0;t<this._nodes.length;t++){const n=this._nodes[t],r=e.nodes(t);if(null==r)throw new Error(`No node exists at index ${t}`);if(0===(null==r?void 0:r.outputsLength()))throw new Error(`missing output for node: ${r.name}`);for(let e=0;e<(null==r?void 0:r.outputsLength());e++){const i=null==r?void 0:r.outputs(e);let a=o.get(i);if(void 0===a&&(a=this._allData.push(new c)-1,o.set(i,a)),n.outputs.push(a),void 0!==this._allData[a]._from)throw new Error(`multiple nodes output to one data value: ${a}`);if(this._allData[a]._from=t,"Constant"===r.opType()){if(1!==r.attributesLength()||!r.attributes(0).t())throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(1!==r.outputsLength())throw new Error("missing output or incorrect number of outputs for this Constant operator");n.outputs.pop(),n.executeNode=!1,this._allData[a]._from=-1,this._allData[a].tensor=s.Tensor.fromOrtTensor(r.attributes(0).t())}}}for(let t=0;t<this._nodes.length;t++){const n=this._nodes[t],r=e.nodes(t);if(0===r.inputsLength())throw new Error(`missing input for node: ${r.name}`);for(let e=0;e<r.inputsLength();e++){const i=r.inputs(e),s=o.get(i);if(void 0===s)throw new Error(`unrecognized input '${i}' for node: ${r.name()}`);n.inputs.push(s),this._allData[s]._to.push(t)}}}checkIsAcyclic(){const e=new Set;this._allInputIndices.forEach((t=>{this._allData[t]._to.forEach((t=>{e.add(t)}))}));const t=Array.from(e),n=new Array(this._nodes.length).fill("white");for(;t.length>0;){const e=t.pop();"gray"===n[e]?n[e]="black":(t.push(e),n[e]="gray",this._nodes[e].outputs.forEach((r=>{const o=this._allData[r];if(void 0!==o.tensor)throw new Error("node outputs should not be initialized");if(o._from!==e)throw new Error("from property of the Value object doesn't match index of Node being processed");o._to.forEach((e=>{if("gray"===n[e])throw new Error("model graph is cyclic");"white"===n[e]&&t.push(e)}))})))}}transformGraph(e){this.removeAllIdentityNodes(),this.removeAllDropoutNodes(),this.fuseConvActivationNodes(),e&&e.transformGraph(this),this.finalizeGraph()}finalizeGraph(){let e=0;for(let t=0;t<this._nodes.length;t++)this._nodes[t].executeNode?e>0&&(this._nodes[t].inputs.forEach((n=>{const r=this._allData[n]._to.indexOf(t+e);-1!==r&&(this._allData[n]._to[r]=t)})),this._nodes[t].outputs.forEach((n=>{this._allData[n]._from&&this._allData[n]._from===t+e&&(this._allData[n]._from=t)}))):(e++,this._nodes[t].outputs.forEach((e=>{this._allData[e]._from=-2})),this._nodes.splice(t,1),t--);e=0;for(let t=0;t<this._allData.length;t++)if(-2!==this._allData[t].from||-1!==this._allOutputIndices.indexOf(t+e)){if(e>0){let n=-1;void 0!==this._allData[t].from&&-1!==this._allData[t].from?(n=this._nodes[this._allData[t].from].outputs.indexOf(t+e),-1!==n&&(this._nodes[this._allData[t].from].outputs[n]=t)):(n=this._allInputIndices.indexOf(t+e),-1!==n&&(this._allInputIndices[n]=t)),this._allData[t].to.forEach((r=>{n=this._nodes[r].inputs.indexOf(t+e),-1!==n&&(this._nodes[r].inputs[n]=t)})),0===this._allData[t].to.length&&(n=this._allOutputIndices.indexOf(t+e),-1!==n&&(this._allOutputIndices[n]=t))}}else e++,this._allData.splice(t,1),t--}deleteNode(e){const t=this._nodes[e];if(t.outputs.length>1)for(let e=1;e<t.outputs.length;e++)if(this._allData[t.outputs[e]].to.length>0)throw new Error("Node deletion with more than one output connected to other nodes is not supported. ");t.executeNode=!1;const n=t.inputs[0],r=t.outputs[0],o=this._allData[r].to,i=this._allData[n].to.indexOf(e);if(-1===i)throw new Error("The Value object doesn't have the current Node in it's 'to' property ");this._allData[n].to.splice(i,1),this._allData[r]._to=[];const s=this._allOutputIndices.indexOf(r);if(-1!==s&&(this._allOutputIndices[s]=n),o&&o.length>0)for(const e of o){const t=this._nodes[e].inputs.indexOf(r);if(-1===t)throw new Error("The Node object doesn't have the output Value in it's 'inputs' property ");this._nodes[e].inputs[t]=n,this._allData[n].to.push(e)}}removeAllDropoutNodes(){let e=0;for(const t of this._nodes){if("Dropout"===t.opType){if(1!==t.inputs.length)throw new Error("Dropout nodes should only contain one input. ");if(1!==t.outputs.length&&2!==t.outputs.length)throw new Error("Dropout nodes should contain either 1 or 2 output(s)");if(2===t.outputs.length&&0!==this._allData[t.outputs[1]]._to.length)throw new Error("Dropout nodes's second output should not be referenced by other nodes");this.deleteNode(e)}e++}}removeAllIdentityNodes(){let e=0;for(const t of this._nodes)"Identity"===t.opType&&this.deleteNode(e),e++}isActivation(e){switch(e.opType){case"Relu":case"Sigmoid":case"Clip":return!0;default:return!1}}fuseConvActivationNodes(){for(const e of this._nodes)if("Conv"===e.opType){const t=this._allData[e.outputs[0]]._to;if(1===t.length&&this.isActivation(this._nodes[t[0]])){const n=this._nodes[t[0]];if("Clip"===n.opType)if(1===n.inputs.length)try{e.attributes.set("activation_params","floats",[n.attributes.getFloat("min"),n.attributes.getFloat("max")])}catch(t){e.attributes.set("activation_params","floats",[a.MIN_CLIP,a.MAX_CLIP])}else{if(!(n.inputs.length>=3&&void 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addMaxNodeIndex(e,t){e.addFieldInt32(3,t,0)}static addNodeEdges(e,t){e.addFieldOffset(4,t,0)}static createNodeEdgesVector(e,t){e.startVector(4,t.length,4);for(let n=t.length-1;n>=0;n--)e.addOffset(t[n]);return e.endVector()}static startNodeEdgesVector(e,t){e.startVector(4,t,4)}static addInputs(e,t){e.addFieldOffset(5,t,0)}static createInputsVector(e,t){e.startVector(4,t.length,4);for(let n=t.length-1;n>=0;n--)e.addOffset(t[n]);return e.endVector()}static startInputsVector(e,t){e.startVector(4,t,4)}static addOutputs(e,t){e.addFieldOffset(6,t,0)}static createOutputsVector(e,t){e.startVector(4,t.length,4);for(let n=t.length-1;n>=0;n--)e.addOffset(t[n]);return e.endVector()}static startOutputsVector(e,t){e.startVector(4,t,4)}static addSparseInitializers(e,t){e.addFieldOffset(7,t,0)}static createSparseInitializersVector(e,t){e.startVector(4,t.length,4);for(let n=t.length-1;n>=0;n--)e.addOffset(t[n]);return e.endVector()}static startSparseInitializersVector(e,t){e.startVector(4,t,4)}static endGraph(e){return e.endObject()}static createGraph(e,t,r,o,i,s,a,l,c){return n.startGraph(e),n.addInitializers(e,t),n.addNodeArgs(e,r),n.addNodes(e,o),n.addMaxNodeIndex(e,i),n.addNodeEdges(e,s),n.addInputs(e,a),n.addOutputs(e,l),n.addSparseInitializers(e,c),n.endGraph(e)}}t.Graph=n}(t.fbs||(t.fbs={}))}(e.experimental||(e.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(e){!function(t){!function(t){class n{constructor(){this.bb=null,this.bb_pos=0}__init(e,t){return this.bb_pos=e,this.bb=t,this}static getRootAsModel(e,t){return(t||new n).__init(e.readInt32(e.position())+e.position(),e)}static getSizePrefixedRootAsModel(e,t){return e.setPosition(e.position()+r.flatbuffers.SIZE_PREFIX_LENGTH),(t||new n).__init(e.readInt32(e.position())+e.position(),e)}irVersion(){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.readInt64(this.bb_pos+e):this.bb.createLong(0,0)}opsetImport(t,n){let r=this.bb.__offset(this.bb_pos,6);return r?(n||new e.experimental.fbs.OperatorSetId).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}opsetImportLength(){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.__vector_len(this.bb_pos+e):0}producerName(e){let t=this.bb.__offset(this.bb_pos,8);return t?this.bb.__string(this.bb_pos+t,e):null}producerVersion(e){let t=this.bb.__offset(this.bb_pos,10);return t?this.bb.__string(this.bb_pos+t,e):null}domain(e){let t=this.bb.__offset(this.bb_pos,12);return t?this.bb.__string(this.bb_pos+t,e):null}modelVersion(){let e=this.bb.__offset(this.bb_pos,14);return e?this.bb.readInt64(this.bb_pos+e):this.bb.createLong(0,0)}docString(e){let t=this.bb.__offset(this.bb_pos,16);return t?this.bb.__string(this.bb_pos+t,e):null}graph(t){let n=this.bb.__offset(this.bb_pos,18);return n?(t||new e.experimental.fbs.Graph).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}graphDocString(e){let t=this.bb.__offset(this.bb_pos,20);return t?this.bb.__string(this.bb_pos+t,e):null}static startModel(e){e.startObject(9)}static addIrVersion(e,t){e.addFieldInt64(0,t,e.createLong(0,0))}static addOpsetImport(e,t){e.addFieldOffset(1,t,0)}static createOpsetImportVector(e,t){e.startVector(4,t.length,4);for(let n=t.length-1;n>=0;n--)e.addOffset(t[n]);return e.endVector()}static startOpsetImportVector(e,t){e.startVector(4,t,4)}static addProducerName(e,t){e.addFieldOffset(2,t,0)}static addProducerVersion(e,t){e.addFieldOffset(3,t,0)}static addDomain(e,t){e.addFieldOffset(4,t,0)}static addModelVersion(e,t){e.addFieldInt64(5,t,e.createLong(0,0))}static addDocString(e,t){e.addFieldOffset(6,t,0)}static addGraph(e,t){e.addFieldOffset(7,t,0)}static addGraphDocString(e,t){e.addFieldOffset(8,t,0)}static endModel(e){return e.endObject()}static createModel(e,t,r,o,i,s,a,l,c,u){return n.startModel(e),n.addIrVersion(e,t),n.addOpsetImport(e,r),n.addProducerName(e,o),n.addProducerVersion(e,i),n.addDomain(e,s),n.addModelVersion(e,a),n.addDocString(e,l),n.addGraph(e,c),n.addGraphDocString(e,u),n.endModel(e)}}t.Model=n}(t.fbs||(t.fbs={}))}(e.experimental||(e.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(e){!function(e){!function(e){class t{constructor(){this.bb=null,this.bb_pos=0}__init(e,t){return this.bb_pos=e,this.bb=t,this}static getRootAsKernelCreateInfos(e,n){return(n||new t).__init(e.readInt32(e.position())+e.position(),e)}static getSizePrefixedRootAsKernelCreateInfos(e,n){return e.setPosition(e.position()+r.flatbuffers.SIZE_PREFIX_LENGTH),(n||new t).__init(e.readInt32(e.position())+e.position(),e)}nodeIndices(e){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readUint32(this.bb.__vector(this.bb_pos+t)+4*e):0}nodeIndicesLength(){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__vector_len(this.bb_pos+e):0}nodeIndicesArray(){let e=this.bb.__offset(this.bb_pos,4);return e?new Uint32Array(this.bb.bytes().buffer,this.bb.bytes().byteOffset+this.bb.__vector(this.bb_pos+e),this.bb.__vector_len(this.bb_pos+e)):null}kernelDefHashes(e){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.readUint64(this.bb.__vector(this.bb_pos+t)+8*e):this.bb.createLong(0,0)}kernelDefHashesLength(){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.__vector_len(this.bb_pos+e):0}static startKernelCreateInfos(e){e.startObject(2)}static addNodeIndices(e,t){e.addFieldOffset(0,t,0)}static createNodeIndicesVector(e,t){e.startVector(4,t.length,4);for(let n=t.length-1;n>=0;n--)e.addInt32(t[n]);return e.endVector()}static startNodeIndicesVector(e,t){e.startVector(4,t,4)}static addKernelDefHashes(e,t){e.addFieldOffset(1,t,0)}static createKernelDefHashesVector(e,t){e.startVector(8,t.length,8);for(let n=t.length-1;n>=0;n--)e.addInt64(t[n]);return e.endVector()}static startKernelDefHashesVector(e,t){e.startVector(8,t,8)}static endKernelCreateInfos(e){return e.endObject()}static createKernelCreateInfos(e,n,r){return t.startKernelCreateInfos(e),t.addNodeIndices(e,n),t.addKernelDefHashes(e,r),t.endKernelCreateInfos(e)}}e.KernelCreateInfos=t}(e.fbs||(e.fbs={}))}(e.experimental||(e.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(e){!function(t){!function(t){class n{constructor(){this.bb=null,this.bb_pos=0}__init(e,t){return this.bb_pos=e,this.bb=t,this}static getRootAsSubGraphSessionState(e,t){return(t||new n).__init(e.readInt32(e.position())+e.position(),e)}static getSizePrefixedRootAsSubGraphSessionState(e,t){return e.setPosition(e.position()+r.flatbuffers.SIZE_PREFIX_LENGTH),(t||new n).__init(e.readInt32(e.position())+e.position(),e)}graphId(e){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.__string(this.bb_pos+t,e):null}sessionState(t){let n=this.bb.__offset(this.bb_pos,6);return n?(t||new e.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}static startSubGraphSessionState(e){e.startObject(2)}static addGraphId(e,t){e.addFieldOffset(0,t,0)}static addSessionState(e,t){e.addFieldOffset(1,t,0)}static endSubGraphSessionState(e){let t=e.endObject();return e.requiredField(t,4),t}static createSubGraphSessionState(e,t,r){return n.startSubGraphSessionState(e),n.addGraphId(e,t),n.addSessionState(e,r),n.endSubGraphSessionState(e)}}t.SubGraphSessionState=n}(t.fbs||(t.fbs={}))}(e.experimental||(e.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(e){!function(t){!function(t){class n{constructor(){this.bb=null,this.bb_pos=0}__init(e,t){return this.bb_pos=e,this.bb=t,this}static getRootAsSessionState(e,t){return(t||new n).__init(e.readInt32(e.position())+e.position(),e)}static getSizePrefixedRootAsSessionState(e,t){return e.setPosition(e.position()+r.flatbuffers.SIZE_PREFIX_LENGTH),(t||new n).__init(e.readInt32(e.position())+e.position(),e)}kernels(t){let n=this.bb.__offset(this.bb_pos,4);return n?(t||new e.experimental.fbs.KernelCreateInfos).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}subGraphSessionStates(t,n){let r=this.bb.__offset(this.bb_pos,6);return r?(n||new e.experimental.fbs.SubGraphSessionState).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}subGraphSessionStatesLength(){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.__vector_len(this.bb_pos+e):0}static startSessionState(e){e.startObject(2)}static addKernels(e,t){e.addFieldOffset(0,t,0)}static addSubGraphSessionStates(e,t){e.addFieldOffset(1,t,0)}static createSubGraphSessionStatesVector(e,t){e.startVector(4,t.length,4);for(let n=t.length-1;n>=0;n--)e.addOffset(t[n]);return e.endVector()}static startSubGraphSessionStatesVector(e,t){e.startVector(4,t,4)}static endSessionState(e){return e.endObject()}static createSessionState(e,t,r){return n.startSessionState(e),n.addKernels(e,t),n.addSubGraphSessionStates(e,r),n.endSessionState(e)}}t.SessionState=n}(t.fbs||(t.fbs={}))}(e.experimental||(e.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(e){!function(t){!function(t){class n{constructor(){this.bb=null,this.bb_pos=0}__init(e,t){return this.bb_pos=e,this.bb=t,this}static getRootAsInferenceSession(e,t){return(t||new n).__init(e.readInt32(e.position())+e.position(),e)}static getSizePrefixedRootAsInferenceSession(e,t){return e.setPosition(e.position()+r.flatbuffers.SIZE_PREFIX_LENGTH),(t||new n).__init(e.readInt32(e.position())+e.position(),e)}static bufferHasIdentifier(e){return e.__has_identifier("ORTM")}ortVersion(e){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.__string(this.bb_pos+t,e):null}model(t){let n=this.bb.__offset(this.bb_pos,6);return n?(t||new e.experimental.fbs.Model).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}sessionState(t){let n=this.bb.__offset(this.bb_pos,8);return n?(t||new e.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}static startInferenceSession(e){e.startObject(3)}static addOrtVersion(e,t){e.addFieldOffset(0,t,0)}static addModel(e,t){e.addFieldOffset(1,t,0)}static addSessionState(e,t){e.addFieldOffset(2,t,0)}static endInferenceSession(e){return e.endObject()}static finishInferenceSessionBuffer(e,t){e.finish(t,"ORTM")}static finishSizePrefixedInferenceSessionBuffer(e,t){e.finish(t,"ORTM",!0)}static createInferenceSession(e,t,r,o){return n.startInferenceSession(e),n.addOrtVersion(e,t),n.addModel(e,r),n.addSessionState(e,o),n.endInferenceSession(e)}}t.InferenceSession=n}(t.fbs||(t.fbs={}))}(e.experimental||(e.experimental={}))}(t.onnxruntime||(t.onnxruntime={}))},7448:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.OnnxjsSessionHandler=void 0;const r=n(1670),o=n(9162);t.OnnxjsSessionHandler=class{constructor(e){this.session=e,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(e,t,n){const i=new Map;for(const t in e)if(Object.hasOwnProperty.call(e,t)){const n=e[t];i.set(t,new o.Tensor(n.dims,n.type,void 0,void 0,n.data))}const s=await this.session.run(i),a={};return s.forEach(((e,t)=>{a[t]=new r.Tensor(e.type,e.data,e.dims)})),a}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(e,t,n)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.Session=void 0;const r=n(7067),o=n(1296),i=n(7091),s=n(1036),a=n(6231),l=n(2644);t.Session=class{constructor(e={}){this._initialized=!1,this.backendHint=e.backendHint,this.profiler=a.Profiler.create(e.profiler),this.context={profiler:this.profiler,graphInputTypes:[],graphInputDims:[]}}get inputNames(){return this._model.graph.getInputNames()}get outputNames(){return this._model.graph.getOutputNames()}startProfiling(){this.profiler.start()}endProfiling(){this.profiler.stop()}async loadModel(e,t,n){await this.profiler.event("session","Session.loadModel",(async()=>{const s=await(0,i.resolveBackend)(this.backendHint);if(this.sessionHandler=s.createSessionHandler(this.context),this._model=new l.Model,"string"==typeof e){const t=e.endsWith(".ort");if("undefined"==typeof fetch){const n=await(0,o.promisify)(r.readFile)(e);this.initialize(n,t)}else{const n=await fetch(e),r=await n.arrayBuffer();this.initialize(new Uint8Array(r),t)}}else if(ArrayBuffer.isView(e))this.initialize(e);else{const r=new Uint8Array(e,t||0,n||e.byteLength);this.initialize(r)}}))}initialize(e,t){if(this._initialized)throw new Error("already initialized");this.profiler.event("session","Session.initialize",(()=>{const n=this.sessionHandler.transformGraph?this.sessionHandler:void 0;this._model.load(e,n,t),this.sessionHandler.onGraphInitialized&&this.sessionHandler.onGraphInitialized(this._model.graph),this.initializeOps(this._model.graph),this._executionPlan=new s.ExecutionPlan(this._model.graph,this._ops,this.profiler)})),this._initialized=!0}async run(e){if(!this._initialized)throw new Error("session not initialized yet");return this.profiler.event("session","Session.run",(async()=>{const t=this.normalizeAndValidateInputs(e),n=await this._executionPlan.execute(this.sessionHandler,t);return this.createOutput(n)}))}normalizeAndValidateInputs(e){const t=this._model.graph.getInputNames();if(Array.isArray(e)){if(e.length!==t.length)throw new Error(`incorrect input array length: expected ${t.length} but got ${e.length}`)}else{if(e.size!==t.length)throw new Error(`incorrect input map size: expected ${t.length} but got ${e.size}`);const n=new Array(e.size);let r=0;for(let o=0;o<t.length;++o){const i=e.get(t[o]);if(!i)throw new Error(`missing input tensor for: '${name}'`);n[r++]=i}e=n}if(this.context.graphInputTypes&&0!==this.context.graphInputTypes.length&&this.context.graphInputDims&&0!==this.context.graphInputDims.length)this.validateInputTensorDims(this.context.graphInputDims,e,!1);else{const t=this._model.graph.getInputIndices(),n=this._model.graph.getValues(),r=new Array(t.length);for(let o=0;o<t.length;++o){const i=n[t[o]];r[o]=i.type.shape.dims,this.context.graphInputTypes.push(i.type.tensorType),this.context.graphInputDims.push(e[o].dims)}this.validateInputTensorDims(r,e,!0)}return this.validateInputTensorTypes(this.context.graphInputTypes,e),e}validateInputTensorTypes(e,t){for(let n=0;n<t.length;n++){const r=e[n],o=t[n].type;if(r!==o)throw new Error(`input tensor[${n}] check failed: expected type '${r}' but got ${o}`)}}validateInputTensorDims(e,t,n){for(let r=0;r<t.length;r++){const o=e[r],i=t[r].dims;if(!this.compareTensorDims(o,i,n))throw new Error(`input tensor[${r}] check failed: expected shape '[${o.join(",")}]' but got [${i.join(",")}]`)}}compareTensorDims(e,t,n){if(e.length!==t.length)return!1;for(let r=0;r<e.length;++r)if(e[r]!==t[r]&&(!n||0!==e[r]))return!1;return!0}createOutput(e){const t=this._model.graph.getOutputNames();if(e.length!==t.length)throw new Error("expected number of outputs do not match number of generated outputs");const n=new Map;for(let r=0;r<t.length;++r)n.set(t[r],e[r]);return n}initializeOps(e){const t=e.getNodes();this._ops=new Array(t.length);for(let n=0;n<t.length;n++)this._ops[n]=this.sessionHandler.resolve(t[n],this._model.opsets,e)}}},9162:function(e,t,n){var r=this&&this.__importDefault||function(e){return e&&e.__esModule?e:{default:e}};Object.defineProperty(t,"__esModule",{value:!0}),t.Tensor=void 0;const o=n(3442),i=r(n(3720)),s=n(1446),a=n(9395),l=n(2517);var c=a.onnxruntime.experimental.fbs;class u{get data(){if(void 0===this.cache){const e=this.dataProvider(this.dataId);if(e.length!==this.size)throw new Error("Length of data provided by the Data Provider is inconsistent with the dims of this Tensor.");this.cache=e}return this.cache}get stringData(){if("string"!==this.type)throw new TypeError("data type is not string");return this.data}get integerData(){switch(this.type){case"uint8":case"int8":case"uint16":case"int16":case"int32":case"uint32":case"bool":return this.data;default:throw new TypeError("data type is not integer (uint8, int8, uint16, int16, int32, uint32, bool)")}}get floatData(){switch(this.type){case"float32":case"float64":return this.data;default:throw new TypeError("data type is not float (float32, float64)")}}get numberData(){if("string"!==this.type)return this.data;throw new TypeError("type cannot be non-number (string)")}get(e){return this.data[l.ShapeUtil.indicesToOffset(e,this.strides)]}set(e,t){this.data[l.ShapeUtil.indicesToOffset(e,this.strides)]=t}async getData(){return void 0===this.cache&&(this.cache=await this.asyncDataProvider(this.dataId)),this.cache}get strides(){return this._strides||(this._strides=l.ShapeUtil.computeStrides(this.dims)),this._strides}constructor(e,t,n,r,i,s=o.Guid.create()){this.dims=e,this.type=t,this.dataProvider=n,this.asyncDataProvider=r,this.cache=i,this.dataId=s,this.size=l.ShapeUtil.validateDimsAndCalcSize(e);const a=this.size,c=void 0===n&&void 0===r&&void 0===i;if(void 0!==i&&i.length!==a)throw new RangeError("Input dims doesn't match data length.");if("string"===t){if(!(void 0===i||Array.isArray(i)&&i.every((e=>"string"==typeof e))))throw new TypeError("cache should be a string array");c&&(this.cache=new Array(a))}else{if(void 0!==i){const e=d(t);if(!(i instanceof e))throw new TypeError(`cache should be type ${e.name}`)}if(c){const e=new ArrayBuffer(a*function(e){switch(e){case"bool":case"int8":case"uint8":return 1;case"int16":case"uint16":return 2;case"int32":case"uint32":case"float32":return 4;case"float64":return 8;default:throw new Error(`cannot calculate sizeof() on type ${e}`)}}(t));this.cache=function(e,t){return new(d(t))(e)}(e,t)}}}static fromProto(e){if(!e)throw new Error("cannot construct Value from an empty tensor");const t=l.ProtoUtil.tensorDataTypeFromProto(e.dataType),n=l.ProtoUtil.tensorDimsFromProto(e.dims),r=new u(n,t);if("string"===t)e.stringData.forEach(((e,t)=>{r.data[t]=(0,l.decodeUtf8String)(e)}));else if(e.rawData&&"number"==typeof e.rawData.byteLength&&e.rawData.byteLength>0){const t=r.data,n=new DataView(e.rawData.buffer,e.rawData.byteOffset,e.rawData.byteLength),o=p(e.dataType),i=e.rawData.byteLength/o;if(e.rawData.byteLength%o!=0)throw new Error("invalid buffer length");if(t.length!==i)throw new Error("buffer length mismatch");for(let r=0;r<i;r++){const i=h(n,e.dataType,r*o);t[r]=i}}else{let t;switch(e.dataType){case s.onnx.TensorProto.DataType.FLOAT:t=e.floatData;break;case s.onnx.TensorProto.DataType.INT32:case s.onnx.TensorProto.DataType.INT16:case s.onnx.TensorProto.DataType.UINT16:case s.onnx.TensorProto.DataType.INT8:case s.onnx.TensorProto.DataType.UINT8:case s.onnx.TensorProto.DataType.BOOL:t=e.int32Data;break;case s.onnx.TensorProto.DataType.INT64:t=e.int64Data;break;case s.onnx.TensorProto.DataType.DOUBLE:t=e.doubleData;break;case s.onnx.TensorProto.DataType.UINT32:case s.onnx.TensorProto.DataType.UINT64:t=e.uint64Data;break;default:throw new Error("unspecific error")}if(null==t)throw new Error("failed to populate data from a tensorproto value");const n=r.data;if(n.length!==t.length)throw new Error("array length mismatch");for(let r=0;r<t.length;r++){const o=t[r];i.default.isLong(o)?n[r]=_(o,e.dataType):n[r]=o}}return r}static fromData(e,t,n){return new u(t,n,void 0,void 0,e)}static fromOrtTensor(e){if(!e)throw new Error("cannot construct Value from an empty tensor");const t=l.ProtoUtil.tensorDimsFromORTFormat(e),n=l.ProtoUtil.tensorDataTypeFromProto(e.dataType()),r=new u(t,n);if("string"===n)for(let t=0;t<e.stringDataLength();t++)r.data[t]=e.stringData(t);else if(e.rawDataArray()&&"number"==typeof e.rawDataLength()&&e.rawDataLength()>0){const t=r.data,n=new DataView(e.rawDataArray().buffer,e.rawDataArray().byteOffset,e.rawDataLength()),o=p(e.dataType()),i=e.rawDataLength()/o;if(e.rawDataLength()%o!=0)throw new Error("invalid buffer length");if(t.length!==i)throw new Error("buffer length mismatch");for(let r=0;r<i;r++){const i=h(n,e.dataType(),r*o);t[r]=i}}return r}}function p(e){switch(e){case s.onnx.TensorProto.DataType.UINT8:case s.onnx.TensorProto.DataType.INT8:case s.onnx.TensorProto.DataType.BOOL:return 1;case s.onnx.TensorProto.DataType.UINT16:case s.onnx.TensorProto.DataType.INT16:return 2;case s.onnx.TensorProto.DataType.FLOAT:case s.onnx.TensorProto.DataType.INT32:case s.onnx.TensorProto.DataType.UINT32:return 4;case s.onnx.TensorProto.DataType.INT64:case s.onnx.TensorProto.DataType.DOUBLE:case s.onnx.TensorProto.DataType.UINT64:return 8;default:throw new Error(`cannot calculate sizeof() on type ${s.onnx.TensorProto.DataType[e]}`)}}function d(e){switch(e){case"bool":case"uint8":return Uint8Array;case"int8":return Int8Array;case"int16":return Int16Array;case"uint16":return Uint16Array;case"int32":return Int32Array;case"uint32":return Uint32Array;case"float32":return Float32Array;case"float64":return Float64Array;default:throw new Error("unspecified error")}}function _(e,t){if(t===s.onnx.TensorProto.DataType.INT64||t===c.TensorDataType.INT64){if(e.greaterThanOrEqual(2147483648)||e.lessThan(-2147483648))throw new TypeError("int64 is not supported")}else{if(t!==s.onnx.TensorProto.DataType.UINT32&&t!==c.TensorDataType.UINT32&&t!==s.onnx.TensorProto.DataType.UINT64&&t!==c.TensorDataType.UINT64)throw new TypeError(`not a LONG type: ${s.onnx.TensorProto.DataType[t]}`);if(e.greaterThanOrEqual(4294967296)||e.lessThan(0))throw new TypeError("uint64 is not supported")}return e.toNumber()}function h(e,t,n){switch(t){case s.onnx.TensorProto.DataType.BOOL:case s.onnx.TensorProto.DataType.UINT8:return e.getUint8(n);case s.onnx.TensorProto.DataType.INT8:return e.getInt8(n);case s.onnx.TensorProto.DataType.UINT16:return e.getUint16(n,!0);case s.onnx.TensorProto.DataType.INT16:return e.getInt16(n,!0);case s.onnx.TensorProto.DataType.FLOAT:return e.getFloat32(n,!0);case s.onnx.TensorProto.DataType.INT32:return e.getInt32(n,!0);case s.onnx.TensorProto.DataType.UINT32:return e.getUint32(n,!0);case s.onnx.TensorProto.DataType.INT64:return _(i.default.fromBits(e.getUint32(n,!0),e.getUint32(n+4,!0),!1),t);case s.onnx.TensorProto.DataType.DOUBLE:return e.getFloat64(n,!0);case s.onnx.TensorProto.DataType.UINT64:return _(i.default.fromBits(e.getUint32(n,!0),e.getUint32(n+4,!0),!0),t);default:throw new Error(`cannot read from DataView for type ${s.onnx.TensorProto.DataType[t]}`)}}t.Tensor=u},2517:function(e,t,n){var r=this&&this.__importDefault||function(e){return e&&e.__esModule?e:{default:e}};Object.defineProperty(t,"__esModule",{value:!0}),t.decodeUtf8String=t.MAX_CLIP=t.MIN_CLIP=t.PoolConvUtil=t.ReduceUtil=t.SplitUtil=t.MathUtil=t.ShapeUtil=t.LongUtil=t.ProtoUtil=t.GemmUtil=t.arrayCopyHelper=t.BroadcastUtil=t.MatMulUtil=t.ArrayUtil=t.assert=t.checkInputsShape=void 0;const o=n(5686),i=r(n(3720)),s=n(1446),a=n(9162);t.checkInputsShape=function(e,...t){if(!e||e.length!==t.length)return!1;for(let n=0;n<e.length;n++)if(!e[n].dims||e[n].dims.length!==t[n])return!1;return!0},t.assert=function(e,t){if(!e)throw new Error("string"==typeof t?t:t())},t.ArrayUtil=class{static arraysEqual(e,t){if(e.length!==t.length)return!1;for(let n=0;n<e.length;n++)if(e[n]!==t[n])return!1;return!0}};class l{static preprocessInputShapes(e,t){return[1===e.length?[1,e[0]]:e,1===t.length?[t[0],1]:t]}static postprocessOutputShape(e,t,n){1===t&&e.splice(e.length-2,1),1===n&&e.pop()}static calcMatMulShape(e,t){return e[1]!==t[0]?void 0:[e[0],t[1]]}}t.MatMulUtil=l;class c{static calcShape(e,t,n=!1){const r=e.length,o=t.length;if(0===r)return t;if(0===o)return e;const i=Math.max(e.length,t.length),s=new Array(i);if(n){if(r<2||o<2)return;const n=l.calcMatMulShape([e[r-2],e[r-1]],[t[o-2],t[o-1]]);if(void 0===n)return;[s[i-2],s[i-1]]=n}for(let a=n?3:1;a<=i;a++){const n=r-a<0?1:e[r-a],l=o-a<0?1:t[o-a];if(n!==l&&n>1&&l>1)return;s[i-a]=Math.max(n,l)}return s}static index(e,t){const n=new Array(t.length);return c.fillIndex(e,t,n),n}static fillIndex(e,t,n){const r=e.length-t.length;for(let o=0;o<t.length;o++)n[o]=e[r+o]%t[o]}static calc(e,t,n,r,o){const i=c.calcShape(e.dims,t.dims);if(i){if(r&&!d.areEqual(i,e.dims))return;const s=d.size(i),l=r?e:new a.Tensor(i,o||e.type);if(0===i.length)l.set([],n(e.get([]),t.get([])));else{const r=new Array(i.length),o=new Array(e.dims.length),a=new Array(t.dims.length);let u,p=0,d=0,_=!1,h=!1;0===e.dims.length&&(p=e.get([]),_=!0),0===t.dims.length&&(d=t.get([]),h=!0);for(let f=0;f<s;f++){u=f;for(let e=i.length-1;e>=0;e--)r[e]=u%i[e],u=Math.floor(u/i[e]);_||(c.fillIndex(r,e.dims,o),p=e.get(o)),h||(c.fillIndex(r,t.dims,a),d=t.get(a)),l.set(r,n(p,d))}}return l}}static isValidBroadcast(e,t){const n=e.length,r=t.length;if(n>r)return!1;for(let o=1;o<=n;o++)if(1!==e[n-o]&&e[n-o]!==t[r-o])return!1;return!0}static getBroadcastDims(e,t){const n=e.length,r=[];for(let o=0;o<n;o++){const i=n-1-o,s=e[i]||1;(t[t.length-1-o]||1)>1&&1===s&&r.unshift(i)}return r}}t.BroadcastUtil=c,t.arrayCopyHelper=function(e,t,n,r,o){if(r<0||r>=t.length)throw new Error("sourceIndex out of bounds");if(n<0||n>=e.length)throw new Error("targetIndex out of bounds");if(r+o>t.length)throw new Error("source indices to be copied are outside bounds");if(n+o>e.length)throw new Error("target array is too small to hold result");for(let i=0;i<o;i++)e[n+i]=t[r+i]},t.GemmUtil=class{static getShapeOfGemmResult(e,t,n,r,o){if(2!==e.length||2!==n.length)throw new Error("shape need to be of size 2");let i,s,a;t?(i=e[1],s=e[0]):(i=e[0],s=e[1]);let l=-1;if(r?(a=n[0],l=1):(a=n[1],l=0),n[l]!==s)throw new Error("dimension mismatch");if(i<=0||a<=0||s<=0)throw new Error("invalid shape specified");if(o&&!c.isValidBroadcast(o,[i,a]))throw new Error("gemm: invalid bias shape for broadcast");return[i,a,s]}};class u{static tensorDataTypeFromProto(e){switch(e){case s.onnx.TensorProto.DataType.INT8:return"int8";case s.onnx.TensorProto.DataType.UINT8:return"uint8";case s.onnx.TensorProto.DataType.BOOL:return"bool";case s.onnx.TensorProto.DataType.INT16:return"int16";case s.onnx.TensorProto.DataType.UINT16:return"uint16";case s.onnx.TensorProto.DataType.INT32:return"int32";case s.onnx.TensorProto.DataType.UINT32:return"uint32";case s.onnx.TensorProto.DataType.FLOAT:return"float32";case s.onnx.TensorProto.DataType.DOUBLE:return"float64";case s.onnx.TensorProto.DataType.STRING:return"string";case s.onnx.TensorProto.DataType.INT64:return"int32";case s.onnx.TensorProto.DataType.UINT64:return"uint32";default:throw new Error(`unsupported data type: ${s.onnx.TensorProto.DataType[e]}`)}}static tensorDataTypeStringToEnum(e){switch(e){case"int8":return s.onnx.TensorProto.DataType.INT8;case"uint8":return s.onnx.TensorProto.DataType.UINT8;case"bool":return s.onnx.TensorProto.DataType.BOOL;case"int16":return s.onnx.TensorProto.DataType.INT16;case"uint16":return s.onnx.TensorProto.DataType.UINT16;case"int32":return s.onnx.TensorProto.DataType.INT32;case"uint32":return s.onnx.TensorProto.DataType.UINT32;case"float32":return s.onnx.TensorProto.DataType.FLOAT;case"float64":return s.onnx.TensorProto.DataType.DOUBLE;case"string":return s.onnx.TensorProto.DataType.STRING;case"int64":return s.onnx.TensorProto.DataType.INT64;case"uint64":return s.onnx.TensorProto.DataType.UINT64;default:throw new Error(`unsupported data type: ${e}`)}}static tensorDimsFromProto(e){return e.map((e=>i.default.isLong(e)?e.toNumber():e))}static tensorValueTypeFromProto(e){return{tensorType:u.tensorDataTypeFromProto(e.elemType),shape:{dims:u.tensorDimsFromProto(e.shape.dim.map((e=>e.dimValue)))}}}static tensorDimsFromORTFormat(e){const t=[];for(let n=0;n<e.dimsLength();n++)t.push(p.longToNumber(e.dims(n)));return t}static tensorAttributesFromORTFormat(e){const t=[];for(let n=0;n<e.attributesLength();n++)t.push(e.attributes(n));return t}}t.ProtoUtil=u;class p{static longToNumber(e,t){return i.default.isLong(e)?e.toNumber():e instanceof o.flatbuffers.Long?i.default.fromValue({low:e.low,high:e.high,unsigned:null!=t&&t}).toNumber():e}static isLong(e){return i.default.isLong(e)||e instanceof o.flatbuffers.Long}}t.LongUtil=p;class d{static size(e){return d.getSizeFromDimensionRange(e,0,e.length)}static sizeFromDimension(e,t){if(t<0||t>e.length)throw new Error(`invalid dimension of ${t} for sizeFromDimension as Tensor has ${e.length} dimensions.`);return d.getSizeFromDimensionRange(e,t,e.length)}static sizeToDimension(e,t){if(t<0||t>e.length)throw new Error(`invalid dimension of ${t} for sizeToDimension as Tensor has ${e.length} dimensions.`);return d.getSizeFromDimensionRange(e,0,t)}static getSizeFromDimensionRange(e,t,n){let r=1;for(let o=t;o<n;o++){if(e[o]<=0)throw new Error("cannot get valid size from specified dimension range. Most likely the range contains 0 or negative values in them.");r*=e[o]}return r}static computeStrides(e){const t=e.length;if(0===t)return[];if(1===t)return[1];const n=new Array(t);n[t-1]=1,n[t-2]=e[t-1];for(let r=t-3;r>=0;--r)n[r]=n[r+1]*e[r+1];return n}static transpose(e){return e.slice().reverse()}static indicesToOffset(e,t,n){void 0===n&&(n=e.length);let r=0;for(let o=0;o<n;++o)r+=t[o]*e[o];return r}static offsetToIndices(e,t){const n=t.length;if(0===n)return[];if(1===n)return[e*t[0]];const r=new Array(t.length);for(let n=0;n<r.length-1;++n)r[n]=Math.floor(e/t[n]),e-=r[n]*t[n];return r[r.length-1]=e,r}static normalizeAxis(e,t){if(e<-t&&e>=t)throw new Error("unsupported axis for this operation.");return e<0?e+t:e}static normalizeAxes(e,t){return e.map((e=>this.normalizeAxis(e,t)))}static incrementIndex(e,t,n){if(0===t.length||0===e.length)throw new Error("Index incrementing unsupported for scalar Tensor");if(void 0===n)n=t.length;else if(n<=0||n>t.length)throw new Error("Incorrect axis to increment on");for(let r=n-1;r>=0&&(e[r]++,!(e[r]<t[r]));--r)e[r]=0}static calculateReshapedDims(e,t){if(0===t.length){if(0===e.length||1===d.size(e))return[];throw new Error("cannot reshape to a scalar Tensor")}const n=t.length,r=new Array(n);let o=-1,i=1;for(let s=0;s<n;s++){if(t[s]<-1)throw new Error("a dimension in shape hints cannot be less than -1");if(-1===t[s]){if(-1!==o)throw new Error("at most one dimension in shape hints can be -1");o=s}else{if(0===t[s]){if(s>=e.length)throw new Error("the dimension with value zero exceeds the dimension size of the input tensor");r[s]=e[s]}else r[s]=t[s];i*=r[s]}}const s=d.size(e);if(-1!==o){if(s%i!=0)throw new Error(`the input tensor cannot be reshaped to the requested shape. Input shape: [${e}] Output shape: [${t}]`);r[o]=s/i}else if(i!==s)throw new Error("reshapedDims and originalDims don't have matching sizes");return r}static sortBasedOnPerm(e,t){return t?t.map((t=>e[t])):e.slice().reverse()}static padShape(e,t){const n=e.length;return e.map(((e,r)=>e+t[r]+t[r+n]))}static areEqual(e,t){return e.length===t.length&&e.every(((e,n)=>e===t[n]))}static validateDimsAndCalcSize(e){if(e.length>6)throw new TypeError("Only rank 0 to 6 is supported for tensor shape.");let t=1;for(const n of e){if(!Number.isInteger(n))throw new TypeError(`Invalid shape: ${n} is not an integer`);if(n<0||n>2147483647)throw new TypeError(`Invalid shape: length ${n} is not allowed`);t*=n}return t}static flattenShape(e,t){t<0&&(t+=e.length);const n=e.reduce(((e,t)=>e*t),1),r=e.slice(t).reduce(((e,t)=>e*t),1);return[n/r,r]}static squeezeShape(e,t){const n=new Array;t=d.normalizeAxes(t,e.length);for(let r=0;r<e.length;r++){const o=t.indexOf(r)>=0;if(o&&1!==e[r])throw new Error("squeeze an axis of size different than 1");(0===t.length&&e[r]>1||t.length>0&&!o)&&n.push(e[r])}return n}static unsqueezeShape(e,t){const n=new Array(e.length+t.length);n.fill(0);for(let e=0;e<t.length;e++){const r=d.normalizeAxis(t[e],n.length);if(r>=n.length)throw new Error("'axes' has an out of range axis");if(0!==n[r])throw new Error("'axes' has a duplicate axis");n[r]=1}let r=0;for(let t=0;t<n.length;t++)0===n[t]&&(n[t]=e[r++]);if(r!==e.length)throw new Error("the unsqueezed dimension could not be established");return n}}t.ShapeUtil=d,t.MathUtil=class{static sqr(e,t,n,r,o){if(r<0||r>=t.length)throw new Error("sourceIndex out of bounds");if(n<0||n>=e.length)throw new Error("targetIndex out of bounds");if(r+o>t.length)throw new Error("source indices to be copied are outside bounds");if(n+o>e.length)throw new Error("target array is too small to hold result");for(let i=0;i<o;i++)e[n+i]+=Math.pow(t[r+i],2)}static axpy(e,t,n,r,o,i){if(r<0||r>=t.length)throw new Error("sourceIndex out of bounds");if(n<0||n>=e.length)throw new Error("targetIndex out of bounds");if(r+o>t.length)throw new Error("source indices to be copied are outside bounds");if(n+o>e.length)throw new Error("target array is too small to hold result");for(let s=0;s<o;s++)e[n+s]+=i*t[r+s]}static powx(e,t,n,r,o,i){if(r<0||r>=t.length)throw new Error("sourceIndex out of bounds");if(n<0||n>=e.length)throw new Error("targetIndex out of bounds");if(r+o>t.length)throw new Error("source indices to be copied are outside bounds");if(n+o>e.length)throw new Error("target array is too small to hold result");for(let s=0;s<o;s++)e[n+s]=Math.pow(t[r+s],i)}static mul(e,t,n,r,o){if(r<0||r>=t.length)throw new Error("sourceIndex out of bounds");if(n<0||n>=e.length)throw new Error("targetIndex out of bounds");if(r+o>t.length)throw new Error("source indices to be copied are outside bounds");if(n+o>e.length)throw new Error("target array is too small to hold result");for(let i=0;i<o;i++)e[n+i]=t[r+i]*e[n+i]}};class _{static splitShape(e,t,n,r){if(0===n.length){if(!r)throw new Error("need to know number of outputs when the 'split' attribute is not specified");_.determineSplit(e[t],r,n)}const o=[],i=[0];for(let r=0;r<n.length;++r){0!==r&&i.push(i[r-1]+n[r-1]);const s=e.slice();s[t]=n[r],o.push(s)}return[o,i]}static determineSplit(e,t,n){if(e%t!=0)throw new Error("cannot split tensor to equal sized parts");for(let r=0;r<t;++r)n.push(e/t)}}t.SplitUtil=_;class h{static calcReduce(e,t,n,r,o){const i=e.dims.slice(0);0===t.length&&i.forEach(((e,n)=>t.push(n)));const s=h.calcReduceShape(i,t,!0),l=d.size(s),u=new a.Tensor(s,e.type),p=d.computeStrides(s),_=d.computeStrides(i),f=new Array(i.length);for(let n=0;n<l;n++){const s=d.offsetToIndices(n,p);c.fillIndex(s,i,f),u.set(s,h.calcReduceByAxis(e.numberData,t,i,0,d.indicesToOffset(f,_),r,o))}return n?u:new a.Tensor(h.calcReduceShape(i,t,n),u.type,void 0,void 0,u.data,u.dataId)}static calcReduceByAxis(e,t,n,r,o,i,s){let a=0;if(r>=t.length)return i(e[o]);const l=t[r],c=l>=n.length?1:d.size(n.slice(l+1));for(let u=0;u<n[l];u++)a=0===u?h.calcReduceByAxis(e,t,n,r+1,o,i,s):s(a,h.calcReduceByAxis(e,t,n,r+1,o,i,s)),o+=c;return a}static calcReduceShape(e,t,n){const r=e.slice();for(let e=0;e<t.length;e++)r[t[e]]=n?1:0;return r.filter((e=>0!==e))}}t.ReduceUtil=h;class f{static adjustPoolAttributes(e,t,n,r,o,i){if(!e&&n.length!==t.length-2)throw new Error("length of specified kernel shapes should be 2 less than length of input dimensions");if(e)for(let e=0;e<t.length-2;e++)e>=n.length?n.push(t[e+2]):n[e]=t[e+2];for(let e=0;e<n.length;e++)if(e<r.length){if(r[e]<0)throw new Error("strides should be greater than or equal to 1")}else r.push(1);for(let e=0;e<n.length;e++)if(e<o.length){if(o[e]<0)throw new Error("dilations should be greater than or equal to 1")}else o.push(1);for(let e=0;e<2*n.length;e++)if(e<i.length){if(i[e]<0)throw new Error("pad should be greater than or equal to 1")}else i.push(0);for(let e=0;e<n.length;e++){if(n[e]<=0)throw new Error("kernel shapes need to be greater than 0");if(i[e]>=n[e]||i[e+n.length]>=n[e])throw new Error("pads should be smaller than kernel")}}static adjustPadsBasedOnAutoPad(e,t,n,r,o,i){if(i){if(o.length!==2*(e.length-2))throw new Error("length of pads should be twice the length of data dimensions");if(t.length!==e.length-2)throw new Error("length of strides should be the length of data dimensions");if(r.length!==e.length-2)throw new Error("length of kernel shapes should be the length of data dimensions");for(let s=0;s<e.length-2;s++)f.adjustPadAndReturnShape(e[s+2],t[s],n[s],r[s],o,s,s+e.length-2,i)}}static computePoolOutputShape(e,t,n,r,o,i,s){if(t.length<=0)throw new Error("input shape must be of size greater than 0");const a=[t[0],t[1]];return f.computeShapeHelper(e,t,a,n,r,o,i,s),a}static computeConvOutputShape(e,t,n,r,o,i,s){if(e.length<=0||t.length<=0)throw new Error("invalid input tensor dims or invalid filter tensor dims");const a=[e[0],t[0]];return f.computeShapeHelper(!1,e,a,n,r,o,i,s),a}static computeShapeHelper(e,t,n,r,o,i,s,a){if(e)for(let e=0;e<t.length-2;e++)n.push(1);else for(let e=0;e<t.length-2;e++)n.push(f.adjustPadAndReturnShape(t[e+2],r[e],o[e],i[e],s,e,e+t.length-2,a))}static adjustPadAndReturnShape(e,t,n,r,o,i,s,a){const l=n*(r-1)+1;if(!a||"NOTSET"===a)return Math.floor((e+o[i]+o[s]-l)/t+1);switch(a){case"VALID":return o[i]=0,o[s]=0,Math.floor((e-l)/t+1);case"SAME_LOWER":case"SAME_UPPER":if(1!==n)throw new Error("Dilation not supported for SAME_UPPER or SAME_LOWER");{const n=((e+t-1)/t-1)*t+r-e;return o[i]="SAME_LOWER"===a?Math.floor((n+1)/2):Math.floor(n/2),o[s]=n-o[i],Math.floor((e+n-r)/t+1)}default:throw new Error("Unsupported AutoPad type")}}}t.PoolConvUtil=f,t.MIN_CLIP=-34028234663852886e22,t.MAX_CLIP=34028234663852886e22,t.decodeUtf8String=function(e){return(new TextDecoder).decode(e)}},7967:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.iterateExtraOptions=void 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L(e,t,n,r,o){let i=[],s=0;for(let n of t){let t,a=n.tolist().map(Number);n.dims=[1,...n.dims],o?(t=o[s],t.dims=[1,...t.dims]):t=S(e,n);let l={input:n,model_input_ids:n,attention_mask:t,prev_model_outputs:null,output_token_ids:a,num_output_tokens:r,done:!1,score:0,id:s++};i.push(l)}return i}async function N(e,t){let n=new BigInt64Array(t.output_token_ids.length).fill(1n),r={input_ids:t.model_input_ids,attention_mask:new a.Tensor("int64",n,[1,n.length]),past_key_values:t.prev_model_outputs?.past_key_values},o=await e.forward(r);return t.prev_model_outputs=o,o}function $(e,t){e.output_token_ids=[...e.output_token_ids,t],e.model_input_ids=new a.Tensor("int64",[BigInt(t)],[1,1])}class B extends o.Callable{main_input_name="input_ids";constructor(e,t){super(),this.config=e,this.session=t;const n=y.get(this.constructor),r=w.get(n);this.can_generate=!1,this._runBeam=null,this._getStartBeams=null,this._updateBeam=null,this._forward=null,r===g?(this.can_generate=!0,this._runBeam=N,this._getStartBeams=L,this._updateBeam=$,this._forward=D):r===f||r===m?(this.can_generate=!0,this._runBeam=E,this._getStartBeams=C,this._updateBeam=O,this._forward=F):this._forward=I}async dispose(){const e=[];for(let t of Object.keys(this)){const n=this[t];n instanceof u&&e.push(n.handler.dispose())}return await Promise.all(e)}static async from_pretrained(e,{quantized:t=!0,progress_callback:n=null,config:o=null,cache_dir:s=null,local_files_only:a=!1,revision:l="main",model_file_name:c=null}={}){let u={quantized:t,progress_callback:n,config:o,cache_dir:s,local_files_only:a,revision:l,model_file_name:c};const p=y.get(this),d=w.get(p);let x;return d===g?x=await Promise.all([r.AutoConfig.from_pretrained(e,u),T(e,u.model_file_name??"decoder_model_merged",u),(0,i.getModelJSON)(e,"generation_config.json",!1,u)]):d===f||d===m?x=await Promise.all([r.AutoConfig.from_pretrained(e,u),T(e,"encoder_model",u),T(e,"decoder_model_merged",u),(0,i.getModelJSON)(e,"generation_config.json",!1,u)]):d===b?x=await Promise.all([r.AutoConfig.from_pretrained(e,u),T(e,"vision_encoder",u),T(e,"prompt_encoder_mask_decoder",u)]):d===h?x=await Promise.all([r.AutoConfig.from_pretrained(e,u),T(e,"encoder_model",u),T(e,"decoder_model_merged",u)]):(d!==_&&console.warn(`Model type for '${p??o?.model_type}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`),x=await Promise.all([r.AutoConfig.from_pretrained(e,u),T(e,u.model_file_name??"model",u)])),new this(...x)}async _call(e){return await this.forward(e)}async forward(e){return await this._forward(this,e)}_get_logits_processor(e,t,n=null){const r=new s.LogitsProcessorList;if(null!==e.repetition_penalty&&1!==e.repetition_penalty&&r.push(new s.RepetitionPenaltyLogitsProcessor(e.repetition_penalty)),null!==e.no_repeat_ngram_size&&e.no_repeat_ngram_size>0&&r.push(new s.NoRepeatNGramLogitsProcessor(e.no_repeat_ngram_size)),null!==e.bad_words_ids&&r.push(new s.NoBadWordsLogitsProcessor(e.bad_words_ids,e.eos_token_id)),null!==e.min_length&&null!==e.eos_token_id&&e.min_length>0&&r.push(new s.MinLengthLogitsProcessor(e.min_length,e.eos_token_id)),null!==e.min_new_tokens&&null!==e.eos_token_id&&e.min_new_tokens>0&&r.push(new s.MinNewTokensLengthLogitsProcessor(t,e.min_new_tokens,e.eos_token_id)),null!==e.forced_bos_token_id&&r.push(new s.ForcedBOSTokenLogitsProcessor(e.forced_bos_token_id)),null!==e.forced_eos_token_id&&r.push(new s.ForcedEOSTokenLogitsProcessor(e.max_length,e.forced_eos_token_id)),null!==e.begin_suppress_tokens){let n=t>1||null===e.forced_bos_token_id?t:t+1;null!==e.forced_decoder_ids&&(n+=e.forced_decoder_ids[e.forced_decoder_ids.length-1][0]),r.push(new s.SuppressTokensAtBeginLogitsProcessor(e.begin_suppress_tokens,n))}return null!==e.forced_decoder_ids&&r.push(new s.ForceTokensLogitsProcessor(e.forced_decoder_ids)),null!==n&&r.extend(n),r}_get_generation_config(e){let t=new s.GenerationConfig(this.config);return"generation_config"in this&&Object.assign(t,this.generation_config),null!==e&&Object.assign(t,e),t}async generate(e,t=null,n=null,{inputs_attention_mask:r=null}={}){if(!this.can_generate){let e=`The current model class (${y.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const t=this.config.model_type,n=Ri.get(t)??zi.get(t)??Di.get(t)??Ui.get(t);throw n&&(e+=` Please use the following class instead: '${n[0]}'`),Error(e)}if(!(e instanceof a.Tensor||(0,o.isTypedArray)(e)||Array.isArray(e)))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${e.constructor.name}".`);let i;if(this.config.is_encoder_decoder)i=0;else if(i=e instanceof a.Tensor?e.dims.at(-1):e.length,0===i)throw Error("Must supply a non-empty array of input token ids.");t=this._get_generation_config(t),n=n??new s.LogitsProcessorList,n=this._get_logits_processor(t,i,n);let l=t.eos_token_id;null===l||Array.isArray(l)||(l=[l]);let c=1;const u=c+(t.max_new_tokens??1/0),p=Number.isInteger(t.max_length)&&null===(t.max_new_tokens??null);let d=s.Sampler.getSampler(t),_=this.getStartBeams(e,t,c,r);for(;_.some((e=>!e.done))&&c<u;){let e=[];for(let r of _){if(r.done){e.push(r);continue}if(p&&r.output_token_ids.length>=t.max_length){r.done=!0,e.push(r);continue}let o=await this.runBeam(r);t.output_attentions&&this.addAttentionsToBeam(r,o),t.output_scores;let i=o.logits.slice(null,-1,null);n(r.output_token_ids,i);let s=d(i);for(let[t,n]of s){let o={...r};this.updateBeam(o,t),o.score+=n,l&&l.includes(t)&&(o.done=!0),e.push(o)}}++c,e=this.groupBeams(e).map((e=>e.sort(((e,t)=>t.score-e.score)).slice(0,t.num_beams))),_=e.flat(),t.callback_function&&t.callback_function(_)}const h=this.groupBeams(_),f=e=>h.map((n=>t.num_return_sequences>1?n.slice(0,t.num_return_sequences).map((t=>t[e])):[n[0][e]])).flat(),m=f("output_token_ids");if(t.return_dict_in_generate){return{sequences:m,decoder_attentions:f("decoder_attentions"),cross_attentions:f("cross_attentions")}}return m}addAttentionsToBeam(e,t){if(this.config.is_encoder_decoder){if(!t.cross_attentions||0===t.cross_attentions.length)throw Error("`output_attentions` is true, but the model did not produce cross-attentions. This is most likely because the model was not exported with `output_attentions=True`.");e.cross_attentions||(e.cross_attentions=[]),e.cross_attentions.push(t.cross_attentions)}if(!t.decoder_attentions||0===t.decoder_attentions.length)throw Error("`output_attentions` is true, but the model did not produce decoder-attentions. This is most likely because the model was not exported with `output_attentions=True`.");e.decoder_attentions||(e.decoder_attentions=[]),e.decoder_attentions.push(t.decoder_attentions)}groupBeams(e){const t=Object.create(null);for(const n of e)void 0===t[n.id]?t[n.id]=[n]:t[n.id].push(n);return Object.values(t)}getPastKeyValues(e,t){const n=Object.create(null);for(const r in e)if(r.startsWith("present")){let o=r.replace("present","past_key_values");t&&r.includes("encoder")?n[o]=t[o]:n[o]=e[r]}return n}getAttentions(e){const t=Object.create(null);for(const n of["cross_attentions","decoder_attentions"]){const r=[];for(const t in e)if(t.startsWith(n)){r[t.split(".").pop()]=e[t]}t[n]=r}return t}addPastKeyValues(e,t){if(t)Object.assign(e,t);else{const t=1;if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??1)){let n=[t,this.num_encoder_heads,0,this.encoder_dim_kv],r=[t,this.num_decoder_heads,0,this.decoder_dim_kv];for(let t=0;t<this.num_decoder_layers;++t)e[`past_key_values.${t}.encoder.key`]=new a.Tensor("float32",[],n),e[`past_key_values.${t}.encoder.value`]=new a.Tensor("float32",[],n),e[`past_key_values.${t}.decoder.key`]=new a.Tensor("float32",[],r),e[`past_key_values.${t}.decoder.value`]=new a.Tensor("float32",[],r)}else if("falcon"===this.config.model_type){let n=[t*this.num_heads,0,this.dim_kv];for(let t=0;t<this.num_layers;++t)e[`past_key_values.${t}.key`]=new a.Tensor("float32",[],n),e[`past_key_values.${t}.value`]=new a.Tensor("float32",[],n)}else if(this.config.multi_query){let n=[t*this.num_heads,0,2*this.dim_kv];for(let t=0;t<this.num_layers;++t)e[`past_key_values.${t}.key_value`]=new a.Tensor("float32",[],n)}else if("bloom"===this.config.model_type){let n=[t*this.num_heads,this.dim_kv,0],r=[t*this.num_heads,0,this.dim_kv];for(let t=0;t<this.num_layers;++t)e[`past_key_values.${t}.key`]=new a.Tensor("float32",[],n),e[`past_key_values.${t}.value`]=new a.Tensor("float32",[],r)}else{let n=[t,this.num_heads,0,this.dim_kv];for(let t=0;t<this.num_layers;++t)e[`past_key_values.${t}.key`]=new a.Tensor("float32",[],n),e[`past_key_values.${t}.value`]=new a.Tensor("float32",[],n)}}}getStartBeams(e,t,n,r){return this._getStartBeams(this,e,t,n,r)}async runBeam(e){return await this._runBeam(this,e)}updateBeam(e,t){return this._updateBeam(e,t)}}class z{}class R extends z{constructor({last_hidden_state:e,hidden_states:t=null,attentions:n=null}){super(),this.last_hidden_state=e,this.hidden_states=t,this.attentions=n}}class j extends B{}class V extends j{}class U extends j{async _call(e){return new $s(await super._call(e))}}class G extends j{async _call(e){return new Ds(await super._call(e))}}class q extends j{async _call(e){return new Ns(await super._call(e))}}class W extends j{async _call(e){return new Bs(await super._call(e))}}class H extends B{}class X extends H{}class Q extends B{}class Y extends Q{}class K extends Q{async _call(e){return new $s(await super._call(e))}}class Z extends Q{async _call(e){return new Ds(await super._call(e))}}class J extends Q{async _call(e){return new Ns(await super._call(e))}}class ee extends Q{async _call(e){return new Bs(await super._call(e))}}class te extends B{}class ne extends te{}class re extends te{async _call(e){return new $s(await super._call(e))}}class oe extends te{async _call(e){return new Ds(await super._call(e))}}class ie extends te{async _call(e){return new Ns(await super._call(e))}}class se extends te{async _call(e){return new Bs(await super._call(e))}}class ae extends B{}class le extends ae{}class ce extends ae{async _call(e){return new $s(await super._call(e))}}class ue extends ae{async _call(e){return new Ds(await super._call(e))}}class pe extends ae{async _call(e){return new Ns(await super._call(e))}}class de extends ae{async _call(e){return new Bs(await super._call(e))}}class _e extends B{}class he extends _e{}class fe extends _e{async _call(e){return new $s(await super._call(e))}}class me extends _e{async _call(e){return new Ds(await super._call(e))}}class ge extends _e{async _call(e){return new Ns(await super._call(e))}}class be extends _e{async _call(e){return new Bs(await super._call(e))}}class we extends B{}class xe extends we{}class ye extends we{async _call(e){return new $s(await super._call(e))}}class Te extends we{async _call(e){return new Ds(await super._call(e))}}class ve extends we{async _call(e){return new Ns(await super._call(e))}}class ke extends we{async _call(e){return new Bs(await super._call(e))}}class Me extends B{}class Se extends Me{}class Pe extends Me{async _call(e){return new $s(await super._call(e))}}class Ae extends Me{async _call(e){return new Ds(await super._call(e))}}class Fe extends Me{async _call(e){return new Ns(await super._call(e))}}class Ce extends Me{async _call(e){return new Bs(await super._call(e))}}class Ee extends B{}class Oe extends Ee{}class Ie extends Ee{async _call(e){return new Ds(await super._call(e))}}class De extends Ee{async _call(e){return new Ns(await super._call(e))}}class Le extends Ee{async _call(e){return new Bs(await super._call(e))}}class Ne extends Ee{async _call(e){return new $s(await super._call(e))}}class $e extends B{}class Be extends $e{}class ze extends $e{async _call(e){return new $s(await super._call(e))}}class Re extends $e{async _call(e){return new Ds(await super._call(e))}}class je extends $e{async _call(e){return new Ns(await super._call(e))}}class Ve extends B{}class Ue extends Ve{}class Ge extends Ve{async _call(e){return new $s(await super._call(e))}}class qe extends Ve{async _call(e){return new Ds(await super._call(e))}}class We extends Ve{async _call(e){return new Bs(await super._call(e))}}class He extends B{}class Xe extends He{}class Qe extends He{async _call(e){return new $s(await super._call(e))}}class Ye extends He{async _call(e){return new Ds(await super._call(e))}}class Ke extends He{async _call(e){return new Ns(await super._call(e))}}class Ze extends He{async _call(e){return new Bs(await super._call(e))}}class Je extends B{}class et extends Je{}class tt extends Je{async _call(e){return new $s(await super._call(e))}}class nt extends Je{async _call(e){return new Ds(await super._call(e))}}class rt extends Je{async _call(e){return new Bs(await super._call(e))}}class ot extends B{}class it extends ot{}class st extends ot{async _call(e){return new Ds(await super._call(e))}}class at extends ot{async _call(e){return new Bs(await super._call(e))}}class lt extends ot{async _call(e){return new $s(await super._call(e))}}class ct extends B{}class ut extends ct{}class pt extends ct{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.num_decoder_layers,this.num_decoder_heads=this.config.num_heads,this.decoder_dim_kv=this.config.d_kv,this.num_encoder_layers=this.config.num_layers,this.num_encoder_heads=this.config.num_heads,this.encoder_dim_kv=this.config.d_kv}}class dt extends B{}class _t extends dt{}class ht extends dt{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.num_decoder_layers,this.num_decoder_heads=this.config.num_heads,this.decoder_dim_kv=this.config.d_kv,this.num_encoder_layers=this.config.num_layers,this.num_encoder_heads=this.config.num_heads,this.encoder_dim_kv=this.config.d_kv}}class ft extends B{}class mt extends ft{}class gt extends ft{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.num_decoder_layers,this.num_decoder_heads=this.config.num_heads,this.decoder_dim_kv=this.config.d_kv,this.num_encoder_layers=this.config.num_layers,this.num_encoder_heads=this.config.num_heads,this.encoder_dim_kv=this.config.d_kv}}class bt extends B{}class wt extends bt{}class xt extends bt{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class yt extends bt{async _call(e){return new Ds(await super._call(e))}}class Tt extends B{}class vt extends Tt{}class kt extends Tt{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class Mt extends Tt{async _call(e){return new Ds(await super._call(e))}}class St extends Tt{constructor(e,t,n){super(e,t),this.generation_config=n,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class Pt extends B{}class At extends Pt{}class Ft extends Pt{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class Ct extends B{}class Et extends Ct{}class Ot extends Ct{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class It extends B{}class Dt extends It{}class Lt extends It{async _call(e){return new $s(await super._call(e))}}class Nt extends It{async _call(e){return new Ds(await super._call(e))}}class $t extends It{async _call(e){return new Ns(await super._call(e))}}class Bt extends It{async _call(e){return new Bs(await super._call(e))}}class zt extends B{}class Rt extends zt{}class jt extends zt{async _call(e){return new $s(await super._call(e))}}class Vt extends zt{async _call(e){return new Ds(await super._call(e))}}class Ut extends zt{async _call(e){return new Ns(await super._call(e))}}class Gt extends zt{async _call(e){return new Bs(await super._call(e))}}class qt extends B{}class Wt extends qt{}class Ht extends qt{async _call(e){return new $s(await super._call(e))}}class Xt extends qt{async _call(e){return new Ds(await super._call(e))}}class Qt extends qt{async _call(e){return new Ns(await super._call(e))}}class Yt extends qt{async _call(e){return new Bs(await super._call(e))}}class Kt extends B{}class Zt extends Kt{}class Jt extends Kt{}class en extends B{}class tn extends en{}class nn extends en{requires_attention_mask=!1;main_input_name="input_features";constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}async generate(e,t=null,n=null){if(t=this._get_generation_config(t),t.return_timestamps??=!1,t.return_timestamps&&(n=[new s.WhisperTimeStampLogitsProcessor(t)]),t.return_token_timestamps&&(t.output_attentions=!0,t.return_dict_in_generate=!0,"translate"===t.task&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),!t.alignment_heads))throw new Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");const r=await super.generate(e,t,n);return t.return_token_timestamps&&t.alignment_heads&&(r.token_timestamps=this._extract_token_timestamps(r,t.alignment_heads,t.num_frames)),r}_extract_token_timestamps(e,t,n=null,r=.02){if(!e.cross_attentions)throw new Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");let i=this.config.median_filter_width;void 0===i&&(console.warn("Model config has no `median_filter_width`, using default value of 7."),i=7);const s=e.cross_attentions.map((e=>{let r=Array.from({length:this.config.decoder_layers},((t,n)=>(0,a.cat)(e.map((e=>e[n])),2))),o=(0,a.stack)(t.map((([e,t])=>n?r[e].slice(null,t,null,[0,n]):r[e].slice(null,t))));o=o.transpose(1,0,2,3);let[s,l]=(0,a.std_mean)(o,-2,0,!0),u=o.clone();for(let e=0;e<u.dims[0];++e){let t=u[e];for(let n=0;n<t.dims[0];++n){let r=t[n];const o=s[e][n][0],a=l[e][n][0];for(let e=0;e<r.dims[0];++e){let t=r[e];for(let e=0;e<t.data.length;++e)t.data[e]=(t.data[e]-a.data[e])/o.data[e];t.data.set((0,c.medianFilter)(t.data,i))}}}return(0,a.mean)(u,1)})),l=[e.sequences.length,e.sequences[0].length],u=new a.Tensor("float32",new Float32Array(l[0]*l[1]),l);for(let e=0;e<l[0];++e){const t=s[e].neg().squeeze_(0);let[n,i]=(0,a.dynamicTimeWarping)(t),l=Array.from({length:n.length-1},((e,t)=>n[t+1]-n[t])),c=(0,o.mergeArrays)([1],l).map((e=>!!e)),p=[];for(let e=0;e<c.length;++e)c[e]&&p.push(i[e]*r);u[e].data.set(p,1)}return u}}class rn extends B{main_input_name="pixel_values";constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r;const o=this.config.encoder,i=this.config.decoder,s=o.model_type;(Ei.get(s)??Oi.get(s))||console.warn(`Model type for encoder '${s}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`);const a=Ri.get(i.model_type);if(!a)throw new Error(`Unable to construct \`VisionEncoderDecoder\` due to unsupported decoder: "${this.config.decoder.model_type}"`);const l=new(0,a[1])(i,n,r);this.add_encoder_pkv="num_decoder_layers"in l,this.add_encoder_pkv?(this.num_decoder_layers=l.num_decoder_layers,this.num_decoder_heads=l.num_decoder_heads,this.decoder_dim_kv=l.decoder_dim_kv,this.num_encoder_layers=l.num_encoder_layers,this.num_encoder_heads=l.num_encoder_heads,this.encoder_dim_kv=l.encoder_dim_kv):(this.num_layers=l.num_layers,this.num_heads=l.num_heads,this.dim_kv=l.dim_kv)}}class on extends B{}class sn extends on{}class an extends on{static async from_pretrained(e,t={}){return t.model_file_name??="text_model",super.from_pretrained(e,t)}}class ln extends on{static async from_pretrained(e,t={}){return t.model_file_name??="vision_model",super.from_pretrained(e,t)}}class cn extends B{}class un extends cn{}class pn extends cn{static async from_pretrained(e,t={}){return t.model_file_name??="text_model",super.from_pretrained(e,t)}}class dn extends on{static async from_pretrained(e,t={}){return t.model_file_name??="vision_model",super.from_pretrained(e,t)}}class _n extends B{}class hn extends _n{}class fn extends B{}class mn extends fn{}class gn extends fn{}class bn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class wn extends bn{}class xn extends bn{}class yn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_heads,this.num_layers=this.config.num_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Tn extends yn{}class vn extends yn{}class kn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Mn extends kn{}class Sn extends kn{}class Pn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class An extends Pn{}class Fn extends Pn{}class Cn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class En extends Cn{}class On extends Cn{}class In extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class Dn extends In{}class Ln extends In{}class Nn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class $n extends Nn{}class Bn extends Nn{}class zn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class Rn extends zn{}class jn extends zn{}class Vn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Un extends Vn{}class Gn extends Vn{}class qn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.hidden_size/this.num_heads}}class Wn extends qn{}class Hn extends qn{}class Xn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_heads,this.num_layers=this.config.n_layers,this.dim_kv=this.config.d_model/this.num_heads}}class Qn extends Xn{}class Yn extends Xn{}class Kn extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Zn extends Kn{}class Jn extends Kn{}class er extends B{}class tr extends er{}class nr extends er{async _call(e){return new Ds(await super._call(e))}}class rr extends B{}class or extends rr{}class ir extends rr{async _call(e){return new Ds(await super._call(e))}}class sr extends B{}class ar extends sr{async _call(e){return new js(await super._call(e))}}class lr extends B{}class cr extends lr{}class ur extends lr{async _call(e){return new Ds(await super._call(e))}}class pr extends B{}class dr extends pr{}class _r extends pr{async _call(e){return new Ds(await super._call(e))}}class hr extends B{}class fr extends hr{}class mr extends hr{}class gr extends B{}class br extends gr{}class wr extends gr{}class xr extends B{}class yr extends xr{}class Tr extends xr{async _call(e){return new Ds(await super._call(e))}}class vr extends B{}class kr extends vr{}class Mr extends vr{async _call(e){return new Pr(await super._call(e))}}class Sr extends vr{async _call(e){return new Ar(await super._call(e))}}class Pr extends z{constructor({logits:e,pred_boxes:t}){super(),this.logits=e,this.pred_boxes=t}}class Ar extends z{constructor({logits:e,pred_boxes:t,pred_masks:n}){super(),this.logits=e,this.pred_boxes=t,this.pred_masks=n}}class Fr extends B{}class Cr extends Fr{}class Er extends Fr{async _call(e){return new Or(await super._call(e))}}class Or extends Pr{}class Ir extends B{}class Dr extends Ir{}class Lr extends Ir{async _call(e){return new Ds(await super._call(e))}}class Nr extends B{}class $r extends Nr{}class Br extends Nr{async _call(e){return new Ds(await super._call(e))}}class zr extends B{}class Rr extends zr{}class jr extends zr{async _call(e){return new Ds(await super._call(e))}}class Vr extends B{}class Ur extends Vr{}class Gr extends Vr{}class qr extends B{}class Wr extends qr{}class Hr extends qr{}class Xr extends B{}class Qr extends Xr{}class Yr extends B{}class Kr extends Yr{}class Zr extends Yr{}class Jr extends B{}class eo extends Jr{}class to extends B{}class no extends to{}class ro extends to{async _call(e){return new Ds(await super._call(e))}}class oo extends B{}class io extends oo{}class so extends oo{async _call(e){return new Ds(await super._call(e))}}class ao extends B{}class lo extends ao{}class co extends ao{async _call(e){return new Ds(await super._call(e))}}class uo extends B{}class po extends uo{}class _o extends uo{async _call(e){return new ho(await super._call(e))}}class ho extends z{constructor({logits:e,pred_boxes:t}){super(),this.logits=e,this.pred_boxes=t}}class fo extends B{}class mo extends fo{constructor(e,t,n){super(e,t),this.prompt_encoder_mask_decoder=n}async get_image_embeddings({pixel_values:e}){return await I(this,{pixel_values:e})}async forward(e){if(e.image_embeddings&&e.image_positional_embeddings||(e={...e,...await this.get_image_embeddings(e)}),!e.input_labels){const t=e.input_points.dims.slice(0,-1),n=t.reduce(((e,t)=>e*t),1);e.input_labels=new a.Tensor("int64",new BigInt64Array(n).fill(1n),t)}return await v(this.prompt_encoder_mask_decoder,{input_points:e.input_points,input_labels:e.input_labels,image_embeddings:e.image_embeddings,image_positional_embeddings:e.image_positional_embeddings})}async _call(e){return new go(await super._call(e))}}class go extends z{constructor({iou_scores:e,pred_masks:t}){super(),this.iou_scores=e,this.pred_masks=t}}class bo extends B{}class wo extends bo{}class xo extends bo{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class yo extends B{}class To extends yo{}class vo extends yo{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class ko extends B{}class Mo extends ko{}class So extends ko{async _call(e){return new zs(await super._call(e))}}class Po extends ko{async _call(e){return new Ds(await super._call(e))}}class Ao extends ko{async _call(e){return new Ns(await super._call(e))}}class Fo extends B{}class Co extends Fo{}class Eo extends Fo{async _call(e){return new zs(await super._call(e))}}class Oo extends Fo{async _call(e){return new Ds(await super._call(e))}}class Io extends B{}class Do extends Io{}class Lo extends Io{async _call(e){return new zs(await super._call(e))}}class No extends Io{async _call(e){return new Ds(await super._call(e))}}class $o extends Io{async _call(e){return new Ns(await super._call(e))}}class Bo extends B{}class zo extends Bo{}class Ro extends Bo{async _call(e){return new zs(await super._call(e))}}class jo extends Bo{async _call(e){return new Ds(await super._call(e))}}class Vo extends B{}class Uo extends ko{}class Go extends ko{async _call(e){return new zs(await super._call(e))}}class qo extends ko{async _call(e){return new Ds(await super._call(e))}}class Wo extends B{}class Ho extends Wo{}class Xo extends Wo{async _call(e){return new zs(await super._call(e))}}class Qo extends Wo{async _call(e){return new Ds(await super._call(e))}}class Yo extends Wo{async _call(e){return new Ls(await super._call(e))}}class Ko extends Wo{async _call(e){return new Ns(await super._call(e))}}class Zo extends B{}class Jo extends Zo{}class ei extends Zo{}class ti extends Zo{constructor(e,t,n,r){super(e,t),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.hidden_size/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.hidden_size/this.num_encoder_heads}async generate_speech(e,t,{threshold:n=.5,minlenratio:r=0,maxlenratio:o=20,vocoder:i=null}={}){const s={input_ids:e},{encoder_outputs:l,encoder_attention_mask:c}=await I(this,s),u=l.dims[1]/this.config.reduction_factor,p=Math.floor(u*o),d=Math.floor(u*r),_=this.config.num_mel_bins;let h=[],f=null,m=null,g=0;for(;;){++g;const e=A(!!m);let r;r=m?m.output_sequence_out:new a.Tensor("float32",new Float32Array(_),[1,1,_]);let o={use_cache_branch:e,output_sequence:r,encoder_attention_mask:c,speaker_embeddings:t,encoder_hidden_states:l};this.addPastKeyValues(o,f),m=await v(this.decoder_merged_session,o),f=this.getPastKeyValues(m,f);const{prob:i,spectrum:s}=m;if(h.push(s),g>=d&&(Array.from(i.data).filter((e=>e>=n)).length>0||g>=p))break}const b=(0,a.cat)(h),{waveform:w}=await v(i.session,{spectrogram:b});return{spectrogram:b,waveform:w}}}class ni extends B{main_input_name="spectrogram"}class ri extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_encoder_layers=this.num_decoder_layers=this.config.decoder_layers,this.num_encoder_heads=this.num_decoder_heads=this.config.decoder_attention_heads,this.encoder_dim_kv=this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads}}class oi extends ri{}class ii extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class si extends ii{}class ai extends ii{}class li extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class ci extends li{}class ui extends li{}class pi extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class di extends pi{}class _i extends pi{}class hi extends B{}class fi extends hi{}class mi extends hi{static async from_pretrained(e,t={}){return t.model_file_name??="text_model",super.from_pretrained(e,t)}}class gi extends hi{static async from_pretrained(e,t={}){return t.model_file_name??="audio_model",super.from_pretrained(e,t)}}class bi extends B{}class wi extends bi{async _call(e){return new Vs(await super._call(e))}}class xi extends B{}class yi extends xi{}class Ti extends xi{}class vi extends xi{}class ki extends B{constructor(e,t,n){super(e,t),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Mi extends ki{}class Si extends ki{}class Pi extends B{}class Ai extends Pi{}class Fi extends Pi{async _call(e){return new Ds(await super._call(e))}}class Ci{static MODEL_CLASS_MAPPINGS=null;static BASE_IF_FAIL=!1;static async from_pretrained(e,{quantized:t=!0,progress_callback:n=null,config:o=null,cache_dir:i=null,local_files_only:s=!1,revision:a="main",model_file_name:l=null}={}){let c={quantized:t,progress_callback:n,config:o,cache_dir:i,local_files_only:s,revision:a,model_file_name:l};if(o=await r.AutoConfig.from_pretrained(e,c),c.config||(c.config=o),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let t of this.MODEL_CLASS_MAPPINGS){const n=t.get(o.model_type);if(n)return await n[1].from_pretrained(e,c)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${o.model_type}", attempting to construct from base class.`),await B.from_pretrained(e,c);throw Error(`Unsupported model type: ${o.model_type}`)}}const Ei=new Map([["bert",["BertModel",V]],["nomic_bert",["NomicBertModel",X]],["roformer",["RoFormerModel",Y]],["electra",["ElectraModel",le]],["esm",["EsmModel",Be]],["convbert",["ConvBertModel",ne]],["camembert",["CamembertModel",he]],["deberta",["DebertaModel",xe]],["deberta-v2",["DebertaV2Model",Se]],["mpnet",["MPNetModel",Xe]],["albert",["AlbertModel",it]],["distilbert",["DistilBertModel",Oe]],["roberta",["RobertaModel",Dt]],["xlm",["XLMModel",Rt]],["xlm-roberta",["XLMRobertaModel",Wt]],["clap",["ClapModel",fi]],["clip",["CLIPModel",sn]],["clipseg",["CLIPSegModel",mn]],["chinese_clip",["ChineseCLIPModel",hn]],["siglip",["SiglipModel",un]],["mobilebert",["MobileBertModel",Ue]],["squeezebert",["SqueezeBertModel",et]],["wav2vec2",["Wav2Vec2Model",Mo]],["wav2vec2-bert",["Wav2Vec2BertModel",zo]],["unispeech",["UniSpeechModel",Co]],["unispeech-sat",["UniSpeechSatModel",Do]],["hubert",["HubertModel",Uo]],["wavlm",["WavLMModel",Ho]],["audio-spectrogram-transformer",["ASTModel",Zt]],["vits",["VitsModel",wi]],["detr",["DetrModel",kr]],["table-transformer",["TableTransformerModel",Cr]],["vit",["ViTModel",tr]],["fastvit",["FastViTModel",or]],["mobilevit",["MobileViTModel",cr]],["mobilevitv2",["MobileViTV2Model",dr]],["owlvit",["OwlViTModel",fr]],["owlv2",["Owlv2Model",br]],["beit",["BeitModel",yr]],["deit",["DeiTModel",Dr]],["convnext",["ConvNextModel",no]],["convnextv2",["ConvNextV2Model",io]],["dinov2",["Dinov2Model",lo]],["resnet",["ResNetModel",$r]],["swin",["SwinModel",Rr]],["swin2sr",["Swin2SRModel",Ur]],["donut-swin",["DonutSwinModel",eo]],["yolos",["YolosModel",po]],["dpt",["DPTModel",Wr]],["glpn",["GLPNModel",Kr]],["hifigan",["SpeechT5HifiGan",ni]],["efficientnet",["EfficientNetModel",Ai]]]),Oi=new Map([["t5",["T5Model",ut]],["longt5",["LongT5Model",_t]],["mt5",["MT5Model",mt]],["bart",["BartModel",wt]],["mbart",["MBartModel",vt]],["marian",["MarianModel",wo]],["whisper",["WhisperModel",tn]],["m2m_100",["M2M100Model",To]],["blenderbot",["BlenderbotModel",At]],["blenderbot-small",["BlenderbotSmallModel",Et]]]),Ii=new Map([["bloom",["BloomModel",Wn]],["gpt2",["GPT2Model",wn]],["gptj",["GPTJModel",An]],["gpt_bigcode",["GPTBigCodeModel",En]],["gpt_neo",["GPTNeoModel",Tn]],["gpt_neox",["GPTNeoXModel",Mn]],["codegen",["CodeGenModel",Dn]],["llama",["LlamaModel",$n]],["qwen2",["Qwen2Model",Rn]],["phi",["PhiModel",Un]],["mpt",["MptModel",Qn]],["opt",["OPTModel",Zn]],["mistral",["MistralModel",si]],["starcoder2",["Starcoder2Model",ci]],["falcon",["FalconModel",di]]]),Di=new Map([["speecht5",["SpeechT5ForSpeechToText",ei]],["whisper",["WhisperForConditionalGeneration",nn]]]),Li=new Map([["speecht5",["SpeechT5ForTextToSpeech",ti]]]),Ni=new Map([["vits",["VitsModel",wi]]]),$i=new Map([["bert",["BertForSequenceClassification",G]],["roformer",["RoFormerForSequenceClassification",Z]],["electra",["ElectraForSequenceClassification",ue]],["esm",["EsmForSequenceClassification",Re]],["convbert",["ConvBertForSequenceClassification",oe]],["camembert",["CamembertForSequenceClassification",me]],["deberta",["DebertaForSequenceClassification",Te]],["deberta-v2",["DebertaV2ForSequenceClassification",Ae]],["mpnet",["MPNetForSequenceClassification",Ye]],["albert",["AlbertForSequenceClassification",st]],["distilbert",["DistilBertForSequenceClassification",Ie]],["roberta",["RobertaForSequenceClassification",Nt]],["xlm",["XLMForSequenceClassification",Vt]],["xlm-roberta",["XLMRobertaForSequenceClassification",Xt]],["bart",["BartForSequenceClassification",yt]],["mbart",["MBartForSequenceClassification",Mt]],["mobilebert",["MobileBertForSequenceClassification",qe]],["squeezebert",["SqueezeBertForSequenceClassification",nt]]]),Bi=new Map([["bert",["BertForTokenClassification",q]],["roformer",["RoFormerForTokenClassification",J]],["electra",["ElectraForTokenClassification",pe]],["esm",["EsmForTokenClassification",je]],["convbert",["ConvBertForTokenClassification",ie]],["camembert",["CamembertForTokenClassification",ge]],["deberta",["DebertaForTokenClassification",ve]],["deberta-v2",["DebertaV2ForTokenClassification",Fe]],["mpnet",["MPNetForTokenClassification",Ke]],["distilbert",["DistilBertForTokenClassification",De]],["roberta",["RobertaForTokenClassification",$t]],["xlm",["XLMForTokenClassification",Ut]],["xlm-roberta",["XLMRobertaForTokenClassification",Qt]]]),zi=new Map([["t5",["T5ForConditionalGeneration",pt]],["longt5",["LongT5ForConditionalGeneration",ht]],["mt5",["MT5ForConditionalGeneration",gt]],["bart",["BartForConditionalGeneration",xt]],["mbart",["MBartForConditionalGeneration",kt]],["marian",["MarianMTModel",xo]],["m2m_100",["M2M100ForConditionalGeneration",vo]],["blenderbot",["BlenderbotForConditionalGeneration",Ft]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",Ot]]]),Ri=new Map([["bloom",["BloomForCausalLM",Hn]],["gpt2",["GPT2LMHeadModel",xn]],["gptj",["GPTJForCausalLM",Fn]],["gpt_bigcode",["GPTBigCodeForCausalLM",On]],["gpt_neo",["GPTNeoForCausalLM",vn]],["gpt_neox",["GPTNeoXForCausalLM",Sn]],["codegen",["CodeGenForCausalLM",Ln]],["llama",["LlamaForCausalLM",Bn]],["qwen2",["Qwen2ForCausalLM",jn]],["phi",["PhiForCausalLM",Gn]],["mpt",["MptForCausalLM",Yn]],["opt",["OPTForCausalLM",Jn]],["mbart",["MBartForCausalLM",St]],["mistral",["MistralForCausalLM",ai]],["starcoder2",["Starcoder2ForCausalLM",ui]],["falcon",["FalconForCausalLM",_i]],["trocr",["TrOCRForCausalLM",oi]],["stablelm",["StableLmForCausalLM",Si]]]),ji=new Map([["bert",["BertForMaskedLM",U]],["roformer",["RoFormerForMaskedLM",K]],["electra",["ElectraForMaskedLM",ce]],["esm",["EsmForMaskedLM",ze]],["convbert",["ConvBertForMaskedLM",re]],["camembert",["CamembertForMaskedLM",fe]],["deberta",["DebertaForMaskedLM",ye]],["deberta-v2",["DebertaV2ForMaskedLM",Pe]],["mpnet",["MPNetForMaskedLM",Qe]],["albert",["AlbertForMaskedLM",lt]],["distilbert",["DistilBertForMaskedLM",Ne]],["roberta",["RobertaForMaskedLM",Lt]],["xlm",["XLMWithLMHeadModel",jt]],["xlm-roberta",["XLMRobertaForMaskedLM",Ht]],["mobilebert",["MobileBertForMaskedLM",Ge]],["squeezebert",["SqueezeBertForMaskedLM",tt]]]),Vi=new Map([["bert",["BertForQuestionAnswering",W]],["roformer",["RoFormerForQuestionAnswering",ee]],["electra",["ElectraForQuestionAnswering",de]],["convbert",["ConvBertForQuestionAnswering",se]],["camembert",["CamembertForQuestionAnswering",be]],["deberta",["DebertaForQuestionAnswering",ke]],["deberta-v2",["DebertaV2ForQuestionAnswering",Ce]],["mpnet",["MPNetForQuestionAnswering",Ze]],["albert",["AlbertForQuestionAnswering",at]],["distilbert",["DistilBertForQuestionAnswering",Le]],["roberta",["RobertaForQuestionAnswering",Bt]],["xlm",["XLMForQuestionAnswering",Gt]],["xlm-roberta",["XLMRobertaForQuestionAnswering",Yt]],["mobilebert",["MobileBertForQuestionAnswering",We]],["squeezebert",["SqueezeBertForQuestionAnswering",rt]]]),Ui=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",rn]]]),Gi=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",rn]]]),qi=new Map([["vit",["ViTForImageClassification",nr]],["fastvit",["FastViTForImageClassification",ir]],["mobilevit",["MobileViTForImageClassification",ur]],["mobilevitv2",["MobileViTV2ForImageClassification",_r]],["beit",["BeitForImageClassification",Tr]],["deit",["DeiTForImageClassification",Lr]],["convnext",["ConvNextForImageClassification",ro]],["convnextv2",["ConvNextV2ForImageClassification",so]],["dinov2",["Dinov2ForImageClassification",co]],["resnet",["ResNetForImageClassification",Br]],["swin",["SwinForImageClassification",jr]],["segformer",["SegformerForImageClassification",Ti]],["efficientnet",["EfficientNetForImageClassification",Fi]]]),Wi=new Map([["detr",["DetrForObjectDetection",Mr]],["table-transformer",["TableTransformerForObjectDetection",Er]],["yolos",["YolosForObjectDetection",_o]]]),Hi=new Map([["owlvit",["OwlViTForObjectDetection",mr]],["owlv2",["Owlv2ForObjectDetection",wr]]]),Xi=new Map([["detr",["DetrForSegmentation",Sr]],["clipseg",["CLIPSegForImageSegmentation",gn]]]),Qi=new Map([["segformer",["SegformerForSemanticSegmentation",vi]]]),Yi=new Map([["sam",["SamModel",mo]]]),Ki=new Map([["wav2vec2",["Wav2Vec2ForCTC",So]],["wav2vec2-bert",["Wav2Vec2BertForCTC",Ro]],["unispeech",["UniSpeechForCTC",Eo]],["unispeech-sat",["UniSpeechSatForCTC",Lo]],["wavlm",["WavLMForCTC",Xo]],["hubert",["HubertForCTC",Go]]]),Zi=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Po]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",jo]],["unispeech",["UniSpeechForSequenceClassification",Oo]],["unispeech-sat",["UniSpeechSatForSequenceClassification",No]],["wavlm",["WavLMForSequenceClassification",Qo]],["hubert",["HubertForSequenceClassification",qo]],["audio-spectrogram-transformer",["ASTForAudioClassification",Jt]]]),Ji=new Map([["wavlm",["WavLMForXVector",Yo]]]),es=new Map([["unispeech-sat",["UniSpeechSatForAudioFrameClassification",$o]],["wavlm",["WavLMForAudioFrameClassification",Ko]],["wav2vec2",["Wav2Vec2ForAudioFrameClassification",Ao]]]),ts=new Map([["vitmatte",["VitMatteForImageMatting",ar]]]),ns=new Map([["swin2sr",["Swin2SRForImageSuperResolution",Gr]]]),rs=new Map([["dpt",["DPTForDepthEstimation",Hr]],["depth_anything",["DepthAnythingForDepthEstimation",Qr]],["glpn",["GLPNForDepthEstimation",Zr]]]),os=new Map([["clip",["CLIPVisionModelWithProjection",ln]],["siglip",["SiglipVisionModel",dn]]]),is=[[Ei,_],[Oi,h],[Ii,g],[$i,_],[Bi,_],[zi,f],[Di,f],[Ri,g],[ji,_],[Vi,_],[Ui,m],[qi,_],[Xi,_],[Qi,_],[ts,_],[ns,_],[rs,_],[Wi,_],[Hi,_],[Yi,b],[Ki,_],[Zi,_],[Li,f],[Ni,_],[Ji,_],[es,_],[os,_]];for(const[e,t]of is)for(const[n,r]of e.values())w.set(n,t),y.set(r,n),x.set(n,r);const ss=[["CLIPTextModelWithProjection",an,_],["SiglipTextModel",pn,_],["ClapTextModelWithProjection",mi,_],["ClapAudioModelWithProjection",gi,_]];for(const[e,t,n]of ss)w.set(e,n),y.set(t,e),x.set(e,t);class as extends Ci{static MODEL_CLASS_MAPPINGS=is.map((e=>e[0]));static BASE_IF_FAIL=!0}class ls extends Ci{static MODEL_CLASS_MAPPINGS=[$i]}class cs extends Ci{static MODEL_CLASS_MAPPINGS=[Bi]}class us extends Ci{static MODEL_CLASS_MAPPINGS=[zi]}class ps extends Ci{static MODEL_CLASS_MAPPINGS=[Di]}class ds extends Ci{static MODEL_CLASS_MAPPINGS=[Li]}class _s extends Ci{static MODEL_CLASS_MAPPINGS=[Ni]}class hs extends Ci{static MODEL_CLASS_MAPPINGS=[Ri]}class fs extends Ci{static MODEL_CLASS_MAPPINGS=[ji]}class ms extends Ci{static MODEL_CLASS_MAPPINGS=[Vi]}class gs extends Ci{static MODEL_CLASS_MAPPINGS=[Ui]}class bs extends Ci{static MODEL_CLASS_MAPPINGS=[qi]}class ws extends Ci{static MODEL_CLASS_MAPPINGS=[Xi]}class xs extends Ci{static MODEL_CLASS_MAPPINGS=[Qi]}class ys extends Ci{static MODEL_CLASS_MAPPINGS=[Wi]}class Ts extends Ci{static MODEL_CLASS_MAPPINGS=[Hi]}class vs extends Ci{static MODEL_CLASS_MAPPINGS=[Yi]}class ks extends Ci{static MODEL_CLASS_MAPPINGS=[Ki]}class Ms extends Ci{static MODEL_CLASS_MAPPINGS=[Zi]}class Ss extends Ci{static MODEL_CLASS_MAPPINGS=[Ji]}class Ps extends Ci{static MODEL_CLASS_MAPPINGS=[es]}class As extends Ci{static MODEL_CLASS_MAPPINGS=[Gi]}class Fs extends Ci{static MODEL_CLASS_MAPPINGS=[ts]}class Cs extends Ci{static MODEL_CLASS_MAPPINGS=[ns]}class Es extends Ci{static MODEL_CLASS_MAPPINGS=[rs]}class Os extends Ci{static MODEL_CLASS_MAPPINGS=[os]}class Is extends z{constructor({logits:e,past_key_values:t,encoder_outputs:n,decoder_attentions:r=null,cross_attentions:o=null}){super(),this.logits=e,this.past_key_values=t,this.encoder_outputs=n,this.decoder_attentions=r,this.cross_attentions=o}}class Ds extends z{constructor({logits:e}){super(),this.logits=e}}class Ls extends z{constructor({logits:e,embeddings:t}){super(),this.logits=e,this.embeddings=t}}class Ns extends z{constructor({logits:e}){super(),this.logits=e}}class $s extends z{constructor({logits:e}){super(),this.logits=e}}class Bs extends z{constructor({start_logits:e,end_logits:t}){super(),this.start_logits=e,this.end_logits=t}}class zs extends z{constructor({logits:e}){super(),this.logits=e}}class Rs extends z{constructor({logits:e,past_key_values:t}){super(),this.logits=e,this.past_key_values=t}}class js extends z{constructor({alphas:e}){super(),this.alphas=e}}class Vs extends z{constructor({waveform:e,spectrogram:t}){super(),this.waveform=e,this.spectrogram=t}}},"./src/pipelines.js":
+/*!**************************!*\
+  !*** ./src/pipelines.js ***!
+  \**************************/(e,t,n)=>{n.r(t),n.d(t,{AudioClassificationPipeline:()=>P,AutomaticSpeechRecognitionPipeline:()=>F,DepthEstimationPipeline:()=>z,DocumentQuestionAnsweringPipeline:()=>N,FeatureExtractionPipeline:()=>M,FillMaskPipeline:()=>b,ImageClassificationPipeline:()=>E,ImageFeatureExtractionPipeline:()=>S,ImageSegmentationPipeline:()=>O,ImageToImagePipeline:()=>B,ImageToTextPipeline:()=>C,ObjectDetectionPipeline:()=>D,Pipeline:()=>h,QuestionAnsweringPipeline:()=>g,SummarizationPipeline:()=>x,Text2TextGenerationPipeline:()=>w,TextClassificationPipeline:()=>f,TextGenerationPipeline:()=>v,TextToAudioPipeline:()=>$,TokenClassificationPipeline:()=>m,TranslationPipeline:()=>y,ZeroShotAudioClassificationPipeline:()=>A,ZeroShotClassificationPipeline:()=>k,ZeroShotImageClassificationPipeline:()=>I,ZeroShotObjectDetectionPipeline:()=>L,pipeline:()=>V});var r=n(/*! ./tokenizers.js */"./src/tokenizers.js"),o=n(/*! ./models.js */"./src/models.js"),i=n(/*! ./processors.js */"./src/processors.js"),s=n(/*! ./utils/core.js */"./src/utils/core.js"),a=n(/*! ./utils/maths.js */"./src/utils/maths.js"),l=n(/*! ./utils/audio.js */"./src/utils/audio.js"),c=n(/*! ./utils/tensor.js */"./src/utils/tensor.js"),u=n(/*! ./utils/image.js */"./src/utils/image.js");async function p(e){return Array.isArray(e)||(e=[e]),await Promise.all(e.map((e=>u.RawImage.read(e))))}async function d(e,t){return Array.isArray(e)||(e=[e]),await Promise.all(e.map((e=>"string"==typeof e||e instanceof URL?(0,l.read_audio)(e,t):e instanceof Float64Array?new Float32Array(e):e)))}function _(e,t){t&&(e=e.map((e=>0|e)));const[n,r,o,i]=e;return{xmin:n,ymin:r,xmax:o,ymax:i}}class h extends s.Callable{constructor({task:e,model:t,tokenizer:n=null,processor:r=null}){super(),this.task=e,this.model=t,this.tokenizer=n,this.processor=r}async dispose(){await this.model.dispose()}}class f extends h{constructor(e){super(e)}async _call(e,{topk:t=1}={}){const n=this.tokenizer(e,{padding:!0,truncation:!0}),r=await this.model(n),o="multi_label_classification"===this.model.config.problem_type?e=>e.sigmoid().data:e=>(0,a.softmax)(e.data),i=this.model.config.id2label,s=[];for(const e of r.logits){const n=o(e),r=(0,a.getTopItems)(n,t).map((e=>({label:i[e[0]],score:e[1]})));1===t?s.push(...r):s.push(r)}return Array.isArray(e)||1===t?s:s[0]}}class m extends h{constructor(e){super(e)}async _call(e,{ignore_labels:t=["O"]}={}){const n=Array.isArray(e),r=this.tokenizer(n?e:[e],{padding:!0,truncation:!0}),o=(await this.model(r)).logits,i=this.model.config.id2label,s=[];for(let e=0;e<o.dims[0];++e){const n=r.input_ids[e],l=o[e],c=[];for(let e=0;e<l.dims[0];++e){const r=l[e],o=(0,a.max)(r.data)[1],s=i?i[o]:`LABEL_${o}`;if(t.includes(s))continue;const u=this.tokenizer.decode([n[e].item()],{skip_special_tokens:!0});if(""===u)continue;const p=(0,a.softmax)(r.data);c.push({entity:s,score:p[o],index:e,word:u,start:null,end:null})}s.push(c)}return n?s:s[0]}}class g extends h{constructor(e){super(e)}async _call(e,t,{topk:n=1}={}){const r=this.tokenizer(e,{text_pair:t,padding:!0,truncation:!0}),o=await this.model(r),i=[];for(let e=0;e<o.start_logits.dims[0];++e){const t=r.input_ids[e],l=t.indexOf(this.tokenizer.sep_token_id),c=Array.from((0,a.softmax)(o.start_logits[e].data)).map(((e,t)=>[e,t])).filter((e=>e[1]>l)),u=Array.from((0,a.softmax)(o.end_logits[e].data)).map(((e,t)=>[e,t])).filter((e=>e[1]>l)),p=(0,s.product)(c,u).filter((e=>e[0][1]<=e[1][1])).map((e=>[e[0][1],e[1][1],e[0][0]*e[1][0]])).sort(((e,t)=>t[2]-e[2]));for(let e=0;e<Math.min(p.length,n);++e){const[n,r,o]=p[e],s=[...t].slice(n,r+1),a=this.tokenizer.decode(s,{skip_special_tokens:!0});i.push({answer:a,score:o})}}return 1===n?i[0]:i}}class b extends h{constructor(e){super(e)}async _call(e,{topk:t=5}={}){const n=this.tokenizer(e,{padding:!0,truncation:!0}),r=await this.model(n),o=[];for(let e=0;e<n.input_ids.dims[0];++e){const i=n.input_ids[e],s=i.indexOf(this.tokenizer.mask_token_id);if(-1===s)throw Error(`Mask token (${this.tokenizer.mask_token}) not found in text.`);const l=r.logits[e][s],c=(0,a.getTopItems)((0,a.softmax)(l.data),t);o.push(c.map((e=>{const t=[...i];return t[s]=e[0],{score:e[1],token:e[0],token_str:this.tokenizer.model.vocab[e[0]],sequence:this.tokenizer.decode(t,{skip_special_tokens:!0})}})))}return Array.isArray(e)?o:o[0]}}class w extends h{_key="generated_text";constructor(e){super(e)}async _call(e,t={}){Array.isArray(e)||(e=[e]),this.model.config.prefix&&(e=e.map((e=>this.model.config.prefix+e)));const n=this.model.config.task_specific_params;n&&n[this.task]&&n[this.task].prefix&&(e=e.map((e=>n[this.task].prefix+e)));const r=this.tokenizer,o={padding:!0,truncation:!0};let i;i=this instanceof y&&"_build_translation_inputs"in r?r._build_translation_inputs(e,o,t).input_ids:r(e,o).input_ids;const s=await this.model.generate(i,t);return r.batch_decode(s,{skip_special_tokens:!0}).map((e=>({[this._key]:e})))}}class x extends w{_key="summary_text";constructor(e){super(e)}}class y extends w{_key="translation_text";constructor(e){super(e)}}function T(e){return Array.isArray(e)&&e.every((e=>"role"in e&&"content"in e))}class v extends h{constructor(e){super(e)}async _call(e,t={}){let n,r=!1,o=!1;if("string"==typeof e)n=e=[e];else if(Array.isArray(e)&&e.every((e=>"string"==typeof e)))r=!0,n=e;else{if(T(e))e=[e];else{if(!Array.isArray(e)||!e.every(T))throw new Error("Input must be a string, an array of strings, a Chat, or an array of Chats");r=!0}o=!0,n=e.map((e=>this.tokenizer.apply_chat_template(e,{tokenize:!1,add_generation_prompt:!0})))}const i=t.add_special_tokens??!1,s=!o&&(t.return_full_text??!0);this.tokenizer.padding_side="left";const{input_ids:a,attention_mask:l}=this.tokenizer(n,{add_special_tokens:i,padding:!0,truncation:!0}),c=await this.model.generate(a,t,null,{inputs_attention_mask:l});let u,p=this.tokenizer.batch_decode(c,{skip_special_tokens:!0});!s&&a.dims.at(-1)>0&&(u=this.tokenizer.batch_decode(a,{skip_special_tokens:!0}).map((e=>e.length)));const d=Array.from({length:e.length},(e=>[]));for(let t=0;t<p.length;++t){const n=Math.floor(t/c.length*e.length);u&&(p[t]=p[t].slice(u[n])),d[n].push({generated_text:o?[...e[n],{role:"assistant",content:p[t]}]:p[t]})}return r||1!==d.length?d:d[0]}}class k extends h{constructor(e){super(e),this.label2id=Object.fromEntries(Object.entries(this.model.config.label2id).map((([e,t])=>[e.toLowerCase(),t]))),this.entailment_id=this.label2id.entailment,void 0===this.entailment_id&&(console.warn("Could not find 'entailment' in label2id mapping. Using 2 as entailment_id."),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,void 0===this.contradiction_id&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(e,t,{hypothesis_template:n="This example is {}.",multi_label:r=!1}={}){const o=Array.isArray(e);o||(e=[e]),Array.isArray(t)||(t=[t]);const i=t.map((e=>n.replace("{}",e))),s=r||1===t.length,l=[];for(const n of e){const e=[];for(const t of i){const r=this.tokenizer(n,{text_pair:t,padding:!0,truncation:!0}),o=await this.model(r);s?e.push([o.logits.data[this.contradiction_id],o.logits.data[this.entailment_id]]):e.push(o.logits.data[this.entailment_id])}const r=(s?e.map((e=>(0,a.softmax)(e)[1])):(0,a.softmax)(e)).map(((e,t)=>[e,t])).sort(((e,t)=>t[0]-e[0]));l.push({sequence:n,labels:r.map((e=>t[e[1]])),scores:r.map((e=>e[0]))})}return o?l:l[0]}}class M extends h{constructor(e){super(e)}async _call(e,{pooling:t="none",normalize:n=!1,quantize:r=!1,precision:o="binary"}={}){const i=this.tokenizer(e,{padding:!0,truncation:!0}),s=await this.model(i);let a=s.last_hidden_state??s.logits??s.token_embeddings;if("none"===t);else if("mean"===t)a=(0,c.mean_pooling)(a,i.attention_mask);else{if("cls"!==t)throw Error(`Pooling method '${t}' not supported.`);a=a.slice(null,0)}return n&&(a=a.normalize(2,-1)),r&&(a=(0,c.quantize_embeddings)(a,o)),a}}class S extends h{constructor(e){super(e)}async _call(e,{pool:t=null}={}){const n=await p(e),{pixel_values:r}=await this.processor(n),o=await this.model({pixel_values:r});let i;if(t){if(!("pooler_output"in o))throw Error("No pooled output was returned. Make sure the model has a 'pooler' layer when using the 'pool' option.");i=o.pooler_output}else i=o.last_hidden_state??o.logits??o.image_embeds;return i}}class P extends h{constructor(e){super(e)}async _call(e,{topk:t=null}={}){const n=!Array.isArray(e),r=this.processor.feature_extractor.config.sampling_rate,o=await d(e,r),i=this.model.config.id2label,s=[];for(const e of o){const n=await this.processor(e),r=(await this.model(n)).logits[0],o=(0,a.getTopItems)((0,a.softmax)(r.data),t).map((e=>({label:i[e[0]],score:e[1]})));1===t?s.push(...o):s.push(o)}return n&&1!==t?s[0]:s}}class A extends h{constructor(e){super(e)}async _call(e,t,{hypothesis_template:n="This is a sound of {}."}={}){const r=!Array.isArray(e);r&&(e=[e]);const o=t.map((e=>n.replace("{}",e))),i=this.tokenizer(o,{padding:!0,truncation:!0}),s=this.processor.feature_extractor.config.sampling_rate,l=await d(e,s),c=[];for(const e of l){const n=await this.processor(e),r=await this.model({...i,...n}),o=(0,a.softmax)(r.logits_per_audio.data);c.push([...o].map(((e,n)=>({score:e,label:t[n]}))))}return r?c[0]:c}}class F extends h{constructor(e){super(e)}async _call(e,t={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(e,t);case"wav2vec2":case"wav2vec2-bert":case"unispeech":case"unispeech-sat":case"hubert":return this._call_wav2vec2(e,t);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(e,t={}){t.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),t.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');const n=!Array.isArray(e);n&&(e=[e]);const r=this.processor.feature_extractor.config.sampling_rate,o=await d(e,r),i=[];for(const e of o){const t=await this.processor(e),n=(await this.model(t)).logits[0],r=[];for(const e of n)r.push((0,a.max)(e.data)[1]);const o=this.tokenizer.decode(r);i.push({text:o})}return n?i[0]:i}async _call_whisper(e,t={}){const n=t.return_timestamps??!1,r=t.chunk_length_s??0,o=t.chunk_callback??null,i=t.force_full_sequences??!1;let l=t.stride_length_s??null;"word"===n&&(t.return_token_timestamps=!0);const c=(0,s.pop)(t,"language",null),u=(0,s.pop)(t,"task",null);if(c||u||n){if(t.forced_decoder_ids)throw new Error("Cannot specify `language`/`task`/`return_timestamps` and `forced_decoder_ids` at the same time.");const e=this.tokenizer.get_decoder_prompt_ids({language:c,task:u,no_timestamps:!n});e.length>0&&(t.forced_decoder_ids=e)}const p=!Array.isArray(e);p&&(e=[e]);const _=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,h=this.processor.feature_extractor.config.hop_length,f=this.processor.feature_extractor.config.sampling_rate,m=await d(e,f),g=[];for(const e of m){let s=[];if(r>0){if(null===l)l=r/6;else if(r<=l)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const t=f*r,n=f*l,o=t-2*n;let i=0;for(;i<e.length;){const r=e.subarray(i,i+t),a=await this.processor(r),l=0===i,c=i+o>=e.length;s.push({stride:[r.length,l?0:n,c?0:n],input_features:a.input_features,is_last:c}),i+=o}}else s=[{stride:[e.length,0,0],input_features:(await this.processor(e)).input_features,is_last:!0}];for(const e of s){t.num_frames=Math.floor(e.stride[0]/h);const r=await this.model.generate(e.input_features,t);"word"===n?(e.tokens=r.sequences[0],e.token_timestamps=r.token_timestamps.tolist()[0].map((e=>(0,a.round)(e,2)))):e.tokens=r[0],e.stride=e.stride.map((e=>e/f)),null!==o&&o(e)}const[c,u]=this.tokenizer._decode_asr(s,{time_precision:_,return_timestamps:n,force_full_sequences:i});g.push({text:c,...u})}return p?g[0]:g}}class C extends h{constructor(e){super(e)}async _call(e,t={}){const n=Array.isArray(e),r=await p(e),{pixel_values:o}=await this.processor(r),i=[];for(const e of o){e.dims=[1,...e.dims];const n=await this.model.generate(e,t),r=this.tokenizer.batch_decode(n,{skip_special_tokens:!0}).map((e=>({generated_text:e.trim()})));i.push(r)}return n?i:i[0]}}class E extends h{constructor(e){super(e)}async _call(e,{topk:t=1}={}){const n=Array.isArray(e),r=await p(e),{pixel_values:o}=await this.processor(r),i=await this.model({pixel_values:o}),s=this.model.config.id2label,l=[];for(const e of i.logits){const n=(0,a.getTopItems)((0,a.softmax)(e.data),t).map((e=>({label:s[e[0]],score:e[1]})));1===t?l.push(...n):l.push(n)}return n||1===t?l:l[0]}}class O extends h{constructor(e){super(e),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(e,{threshold:t=.5,mask_threshold:n=.5,overlap_mask_area_threshold:r=.8,label_ids_to_fuse:o=null,target_sizes:i=null,subtask:s=null}={}){if(Array.isArray(e)&&1!==e.length)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");const a=await p(e),l=a.map((e=>[e.height,e.width])),{pixel_values:c,pixel_mask:d}=await this.processor(a),_=await this.model({pixel_values:c,pixel_mask:d});let h=null;if(null!==s)h=this.subtasks_mapping[s];else for(let[e,t]of Object.entries(this.subtasks_mapping))if(t in this.processor.feature_extractor){h=this.processor.feature_extractor[t].bind(this.processor.feature_extractor),s=e;break}const f=this.model.config.id2label,m=[];if("panoptic"===s||"instance"===s){const e=h(_,t,n,r,o,i??l)[0],s=e.segmentation;for(const t of e.segments_info){const e=new Uint8ClampedArray(s.data.length);for(let n=0;n<s.data.length;++n)s.data[n]===t.id&&(e[n]=255);const n=new u.RawImage(e,s.dims[1],s.dims[0],1);m.push({score:t.score,label:f[t.label_id],mask:n})}}else{if("semantic"!==s)throw Error(`Subtask ${s} not supported.`);{const{segmentation:e,labels:t}=h(_,i??l)[0];for(const n of t){const t=new Uint8ClampedArray(e.data.length);for(let r=0;r<e.data.length;++r)e.data[r]===n&&(t[r]=255);const r=new u.RawImage(t,e.dims[1],e.dims[0],1);m.push({score:null,label:f[n],mask:r})}}}return m}}class I extends h{constructor(e){super(e)}async _call(e,t,{hypothesis_template:n="This is a photo of {}"}={}){const r=Array.isArray(e),o=await p(e),i=t.map((e=>n.replace("{}",e))),s=this.tokenizer(i,{padding:"siglip"!==this.model.config.model_type||"max_length",truncation:!0}),{pixel_values:l}=await this.processor(o),c=await this.model({...s,pixel_values:l}),u="siglip"===this.model.config.model_type?e=>e.sigmoid().data:e=>(0,a.softmax)(e.data),d=[];for(const e of c.logits_per_image){const n=[...u(e)].map(((e,n)=>({score:e,label:t[n]})));n.sort(((e,t)=>t.score-e.score)),d.push(n)}return r?d:d[0]}}class D extends h{constructor(e){super(e)}async _call(e,{threshold:t=.9,percentage:n=!1}={}){const r=Array.isArray(e);if(r&&1!==e.length)throw Error("Object detection pipeline currently only supports a batch size of 1.");const o=await p(e),i=n?null:o.map((e=>[e.height,e.width])),{pixel_values:s,pixel_mask:a}=await this.processor(o),l=await this.model({pixel_values:s,pixel_mask:a}),c=this.processor.feature_extractor.post_process_object_detection(l,t,i),u=this.model.config.id2label,d=c.map((e=>e.boxes.map(((t,r)=>({score:e.scores[r],label:u[e.classes[r]],box:_(t,!n)})))));return r?d:d[0]}}class L extends h{constructor(e){super(e)}async _call(e,t,{threshold:n=.1,topk:r=null,percentage:o=!1}={}){const i=Array.isArray(e),s=await p(e),a=this.tokenizer(t,{padding:!0,truncation:!0}),l=await this.processor(s),c=[];for(let e=0;e<s.length;++e){const i=s[e],u=o?null:[[i.height,i.width]],p=l.pixel_values[e].unsqueeze_(0),d=await this.model({...a,pixel_values:p}),h=this.processor.feature_extractor.post_process_object_detection(d,n,u,!0)[0];let f=h.boxes.map(((e,n)=>({score:h.scores[n],label:t[h.classes[n]],box:_(e,!o)}))).sort(((e,t)=>t.score-e.score));null!==r&&(f=f.slice(0,r)),c.push(f)}return i?c:c[0]}}class N extends h{constructor(e){super(e)}async _call(e,t,n={}){const r=(await p(e))[0],{pixel_values:o}=await this.processor(r),i=`<s_docvqa><s_question>${t}</s_question><s_answer>`,s=this.tokenizer(i,{add_special_tokens:!1,padding:!0,truncation:!0}).input_ids,a=await this.model.generate(o,{...n,decoder_input_ids:s,max_length:this.model.config.decoder.max_position_embeddings}),l=this.tokenizer.batch_decode(a)[0].match(/<s_answer>(.*?)<\/s_answer>/);let c=null;return l&&l.length>=2&&(c=l[1].trim()),[{answer:c}]}}class $ extends h{DEFAULT_VOCODER_ID="Xenova/speecht5_hifigan";constructor(e){super(e),this.vocoder=e.vocoder??null}async _call(e,{speaker_embeddings:t=null}={}){return this.processor?this._call_text_to_spectrogram(e,{speaker_embeddings:t}):this._call_text_to_waveform(e)}async _call_text_to_waveform(e){const t=this.tokenizer(e,{padding:!0,truncation:!0}),{waveform:n}=await this.model(t),r=this.model.config.sampling_rate;return{audio:n.data,sampling_rate:r}}async _call_text_to_spectrogram(e,{speaker_embeddings:t}){if(this.vocoder||(console.log("No vocoder specified, using default HifiGan vocoder."),this.vocoder=await o.AutoModel.from_pretrained(this.DEFAULT_VOCODER_ID,{quantized:!1})),("string"==typeof t||t instanceof URL)&&(t=new Float32Array(await(await fetch(t)).arrayBuffer())),t instanceof Float32Array)t=new c.Tensor("float32",t,[1,t.length]);else if(!(t instanceof c.Tensor))throw new Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");const{input_ids:n}=this.tokenizer(e,{padding:!0,truncation:!0}),{waveform:r}=await this.model.generate_speech(n,t,{vocoder:this.vocoder}),i=this.processor.feature_extractor.config.sampling_rate;return{audio:r.data,sampling_rate:i}}}class B extends h{constructor(e){super(e)}async _call(e){const t=await p(e),n=await this.processor(t),r=await this.model(n),o=[];for(const e of r.reconstruction){const t=e.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");o.push(u.RawImage.fromTensor(t))}return o.length>1?o:o[0]}}class z extends h{constructor(e){super(e)}async _call(e){const t=await p(e),n=await this.processor(t),{predicted_depth:r}=await this.model(n),o=[];for(let e=0;e<t.length;++e){const n=(0,c.interpolate)(r[e],t[e].size.reverse(),"bilinear",!1),i=n.mul_(255/(0,a.max)(n.data)[0]).to("uint8");o.push({predicted_depth:r[e],depth:u.RawImage.fromTensor(i)})}return o.length>1?o:o[0]}}const R=Object.freeze({"text-classification":{tokenizer:r.AutoTokenizer,pipeline:f,model:o.AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:r.AutoTokenizer,pipeline:m,model:o.AutoModelForTokenClassification,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:r.AutoTokenizer,pipeline:g,model:o.AutoModelForQuestionAnswering,default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:r.AutoTokenizer,pipeline:b,model:o.AutoModelForMaskedLM,default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:r.AutoTokenizer,pipeline:x,model:o.AutoModelForSeq2SeqLM,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:r.AutoTokenizer,pipeline:y,model:o.AutoModelForSeq2SeqLM,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:r.AutoTokenizer,pipeline:w,model:o.AutoModelForSeq2SeqLM,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:r.AutoTokenizer,pipeline:v,model:o.AutoModelForCausalLM,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:r.AutoTokenizer,pipeline:k,model:o.AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:P,model:o.AutoModelForAudioClassification,processor:i.AutoProcessor,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:r.AutoTokenizer,pipeline:A,model:o.AutoModel,processor:i.AutoProcessor,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:r.AutoTokenizer,pipeline:F,model:[o.AutoModelForSpeechSeq2Seq,o.AutoModelForCTC],processor:i.AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:r.AutoTokenizer,pipeline:$,model:[o.AutoModelForTextToWaveform,o.AutoModelForTextToSpectrogram],processor:[i.AutoProcessor,null],default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:r.AutoTokenizer,pipeline:C,model:o.AutoModelForVision2Seq,processor:i.AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:E,model:o.AutoModelForImageClassification,processor:i.AutoProcessor,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:O,model:[o.AutoModelForImageSegmentation,o.AutoModelForSemanticSegmentation],processor:i.AutoProcessor,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:r.AutoTokenizer,pipeline:I,model:o.AutoModel,processor:i.AutoProcessor,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:D,model:o.AutoModelForObjectDetection,processor:i.AutoProcessor,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"zero-shot-object-detection":{tokenizer:r.AutoTokenizer,pipeline:L,model:o.AutoModelForZeroShotObjectDetection,processor:i.AutoProcessor,default:{model:"Xenova/owlvit-base-patch32"},type:"multimodal"},"document-question-answering":{tokenizer:r.AutoTokenizer,pipeline:N,model:o.AutoModelForDocumentQuestionAnswering,processor:i.AutoProcessor,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"image-to-image":{pipeline:B,model:o.AutoModelForImageToImage,processor:i.AutoProcessor,default:{model:"Xenova/swin2SR-classical-sr-x2-64"},type:"image"},"depth-estimation":{pipeline:z,model:o.AutoModelForDepthEstimation,processor:i.AutoProcessor,default:{model:"Xenova/dpt-large"},type:"image"},"feature-extraction":{tokenizer:r.AutoTokenizer,pipeline:M,model:o.AutoModel,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"},"image-feature-extraction":{processor:i.AutoProcessor,pipeline:S,model:[o.AutoModelForImageFeatureExtraction,o.AutoModel],default:{model:"Xenova/vit-base-patch16-224-in21k"},type:"image"}}),j=Object.freeze({"sentiment-analysis":"text-classification",ner:"token-classification",asr:"automatic-speech-recognition","text-to-speech":"text-to-audio",embeddings:"feature-extraction"});async function V(e,t=null,{quantized:n=!0,progress_callback:r=null,config:o=null,cache_dir:i=null,local_files_only:a=!1,revision:l="main",model_file_name:c=null}={}){e=j[e]??e;const u=R[e.split("_",1)[0]];if(!u)throw Error(`Unsupported pipeline: ${e}. 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+  !*** ./src/processors.js ***!
+  \***************************/(e,t,n)=>{n.r(t),n.d(t,{ASTFeatureExtractor:()=>G,AutoProcessor:()=>J,BeitFeatureExtractor:()=>I,BitImageProcessor:()=>b,CLIPFeatureExtractor:()=>x,ChineseCLIPFeatureExtractor:()=>y,ClapFeatureExtractor:()=>q,ConvNextFeatureExtractor:()=>v,ConvNextImageProcessor:()=>k,DPTFeatureExtractor:()=>m,DPTImageProcessor:()=>g,DeiTFeatureExtractor:()=>O,DetrFeatureExtractor:()=>N,DonutFeatureExtractor:()=>D,EfficientNetImageProcessor:()=>P,FeatureExtractor:()=>_,GLPNFeatureExtractor:()=>w,ImageFeatureExtractor:()=>h,MobileViTFeatureExtractor:()=>A,MobileViTImageProcessor:()=>F,NougatImageProcessor:()=>L,OwlViTFeatureExtractor:()=>C,OwlViTProcessor:()=>Z,Owlv2ImageProcessor:()=>E,Processor:()=>H,SamImageProcessor:()=>B,SamProcessor:()=>X,SeamlessM4TFeatureExtractor:()=>U,SegformerFeatureExtractor:()=>f,SiglipImageProcessor:()=>T,SpeechT5FeatureExtractor:()=>W,SpeechT5Processor:()=>K,Swin2SRImageProcessor:()=>z,ViTFeatureExtractor:()=>M,ViTImageProcessor:()=>S,VitMatteImageProcessor:()=>R,Wav2Vec2FeatureExtractor:()=>V,Wav2Vec2ProcessorWithLM:()=>Y,WhisperFeatureExtractor:()=>j,WhisperProcessor:()=>Q,YolosFeatureExtractor:()=>$});var r=n(/*! ./utils/core.js */"./src/utils/core.js"),o=n(/*! ./utils/hub.js */"./src/utils/hub.js"),i=n(/*! ./utils/maths.js */"./src/utils/maths.js"),s=n(/*! ./utils/tensor.js */"./src/utils/tensor.js"),a=(n(/*! ./utils/image.js */"./src/utils/image.js"),n(/*! ./utils/audio.js */"./src/utils/audio.js"));function l([e,t,n,r]){return[e-n/2,t-r/2,e+n/2,t+r/2]}function c(e,t=.5,n=null,r=!1){const o=e.logits,s=e.pred_boxes,[a,c,u]=o.dims;if(null!==n&&n.length!==a)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let p=[];for(let e=0;e<a;++e){let a=null!==n?n[e]:null,d={boxes:[],classes:[],scores:[]},_=o[e],h=s[e];for(let e=0;e<c;++e){let n,o=_[e],s=[];if(r){n=o.sigmoid().data;for(let e=0;e<n.length;++e)n[e]>t&&s.push(e)}else{let e=(0,i.max)(o.data)[1];if(e===u-1)continue;s.push(e),n=(0,i.softmax)(o.data)}for(const t of s){let r=h[e].data;r=l(r),null!==a&&(r=r.map(((e,t)=>e*a[(t+1)%2]))),d.boxes.push(r),d.classes.push(t),d.scores.push(n[t])}}p.push(d)}return p}function u(e,t){if(!(e instanceof Float32Array||e instanceof Float64Array))throw new Error(`${t} expects input to be a Float32Array or a Float64Array, but got ${e?.constructor?.name??typeof e} instead. 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_{constructor(e){super(e),this.image_mean=this.config.image_mean??this.config.mean,this.image_std=this.config.image_std??this.config.std,this.resample=this.config.resample??2,this.do_rescale=this.config.do_rescale??!0,this.rescale_factor=this.config.rescale_factor??1/255,this.do_normalize=this.config.do_normalize,this.do_resize=this.config.do_resize,this.do_thumbnail=this.config.do_thumbnail,this.size=this.config.size,this.size_divisibility=this.config.size_divisibility??this.config.size_divisor,this.do_center_crop=this.config.do_center_crop,this.crop_size=this.config.crop_size,this.do_convert_rgb=this.config.do_convert_rgb??!0,this.do_crop_margin=this.config.do_crop_margin,this.pad_size=this.config.pad_size,this.do_pad=this.config.do_pad,this.do_pad&&!this.pad_size&&this.size&&void 0!==this.size.width&&void 0!==this.size.height&&(this.pad_size=this.size),this.do_flip_channel_order=this.config.do_flip_channel_order??!1}async thumbnail(e,t,n=2){const r=e.height,o=e.width,i=t.height,s=t.width;let a=Math.min(r,i),l=Math.min(o,s);return a===r&&l===o?e:(r>o?l=Math.floor(o*a/r):o>r&&(a=Math.floor(r*l/o)),await e.resize(l,a,{resample:n}))}async crop_margin(e,t=200){const n=e.clone().grayscale(),r=(0,i.min)(n.data)[0],o=(0,i.max)(n.data)[0]-r;if(0===o)return e;const s=t/255;let a=n.width,l=n.height,c=0,u=0;for(let e=0;e<n.height;++e){const t=e*n.width;for(let i=0;i<n.width;++i)(n.data[t+i]-r)/o<s&&(a=Math.min(a,i),l=Math.min(l,e),c=Math.max(c,i),u=Math.max(u,e))}return e=await e.crop([a,l,c,u])}pad_image(e,t,n,{mode:o="constant",center:i=!1,constant_values:s=0}={}){const[a,l,c]=t;let u,p;if("number"==typeof n?(u=n,p=n):(u=n.width,p=n.height),u!==l||p!==a){const n=new Float32Array(u*p*c);if(Array.isArray(s))for(let e=0;e<n.length;++e)n[e]=s[e%c];else 0!==s&&n.fill(s);const[d,_]=i?[Math.floor((u-l)/2),Math.floor((p-a)/2)]:[0,0];for(let t=0;t<a;++t){const r=(t+_)*u,o=t*l;for(let t=0;t<l;++t){const i=(r+t+d)*c,s=(o+t)*c;for(let t=0;t<c;++t)n[i+t]=e[s+t]}}if("symmetric"===o){if(i)throw new Error("`center` padding is not supported when `mode` is set to `symmetric`.");const t=a-1,o=l-1;for(let i=0;i<p;++i){const s=i*u,p=(0,r.calculateReflectOffset)(i,t)*l;for(let t=0;t<u;++t){if(i<a&&t<l)continue;const u=(s+t)*c,d=(p+(0,r.calculateReflectOffset)(t,o))*c;for(let t=0;t<c;++t)n[u+t]=e[d+t]}}}e=n,t=[p,u,c]}return[e,t]}rescale(e){for(let t=0;t<e.length;++t)e[t]=this.rescale_factor*e[t]}get_resize_output_image_size(e,t){const[n,r]=e.size;let o,i;if(this.do_thumbnail){const{height:e,width:n}=t;o=Math.min(e,n)}else Number.isInteger(t)?(o=t,i=this.config.max_size??o):void 0!==t&&(o=t.shortest_edge,i=t.longest_edge);if(void 0!==o||void 0!==i){const e=void 0===o?1:Math.max(o/n,o/r),t=n*e,s=r*e,a=void 0===i?1:Math.min(i/t,i/s);let l=Math.floor(Number((t*a).toFixed(2))),c=Math.floor(Number((s*a).toFixed(2)));return void 0!==this.size_divisibility&&([l,c]=d([l,c],this.size_divisibility)),[l,c]}if(void 0!==t&&void 0!==t.width&&void 0!==t.height){let e=t.width,o=t.height;if(this.config.keep_aspect_ratio&&this.config.ensure_multiple_of){let t=o/r,i=e/n;Math.abs(1-i)<Math.abs(1-t)?t=i:i=t,o=p(t*r,this.config.ensure_multiple_of),e=p(i*n,this.config.ensure_multiple_of)}return[e,o]}if(void 0!==this.size_divisibility)return d([n,r],this.size_divisibility);throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(t)}`)}async resize(e){const[t,n]=this.get_resize_output_image_size(e,this.size);return await e.resize(t,n,{resample:this.resample})}async preprocess(e,{do_normalize:t=null,do_pad:n=null,do_convert_rgb:r=null,do_convert_grayscale:o=null,do_flip_channel_order:i=null}={}){this.do_crop_margin&&(e=await this.crop_margin(e));const[a,l]=e.size;if(r??this.do_convert_rgb?e=e.rgb():o&&(e=e.grayscale()),this.do_resize&&(e=await this.resize(e)),this.do_thumbnail&&(e=await this.thumbnail(e,this.size,this.resample)),this.do_center_crop){let t,n;Number.isInteger(this.crop_size)?(t=this.crop_size,n=this.crop_size):(t=this.crop_size.width,n=this.crop_size.height),e=await e.center_crop(t,n)}const c=[e.height,e.width];let u=Float32Array.from(e.data),p=[e.height,e.width,e.channels];if(this.do_rescale&&this.rescale(u),t??this.do_normalize){let t=this.image_mean;Array.isArray(this.image_mean)||(t=new Array(e.channels).fill(t));let n=this.image_std;if(Array.isArray(this.image_std)||(n=new Array(e.channels).fill(t)),t.length!==e.channels||n.length!==e.channels)throw new Error(`When set to arrays, the length of \`image_mean\` (${t.length}) and \`image_std\` (${n.length}) must match the number of channels in the image (${e.channels}).`);for(let r=0;r<u.length;r+=e.channels)for(let o=0;o<e.channels;++o)u[r+o]=(u[r+o]-t[o])/n[o]}if(n??this.do_pad)if(this.pad_size){const t=this.pad_image(u,[e.height,e.width,e.channels],this.pad_size);[u,p]=t}else if(this.size_divisibility){const[e,t]=d([p[1],p[0]],this.size_divisibility);[u,p]=this.pad_image(u,p,{width:e,height:t})}if(i??this.do_flip_channel_order){if(3!==p[2])throw new Error("Flipping channel order is only supported for RGB images.");for(let e=0;e<u.length;e+=3){const t=u[e];u[e]=u[e+2],u[e+2]=t}}return{original_size:[l,a],reshaped_input_size:c,pixel_values:new s.Tensor("float32",u,p).permute(2,0,1)}}async _call(e,...t){Array.isArray(e)||(e=[e]);const n=await Promise.all(e.map((e=>this.preprocess(e))));return{pixel_values:(0,s.stack)(n.map((e=>e.pixel_values)),0),original_sizes:n.map((e=>e.original_size)),reshaped_input_sizes:n.map((e=>e.reshaped_input_size))}}}class f extends h{post_process_semantic_segmentation(e,t=null){const n=e.logits,r=n.dims[0];if(null!==t&&t.length!==r)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const o=[];for(let e=0;e<r;++e){const r=null!==t?t[e]:null;let i=n[e];null!==r&&(i=(0,s.interpolate)(i,r,"bilinear",!1));const[a,l]=r??i.dims.slice(-2),c=new s.Tensor("int32",new Int32Array(a*l),[a,l]),u=i[0].data;for(let e=1;e<i.dims[0];++e){const t=i[e].data;for(let n=0;n<t.length;++n)t[n]>u[n]&&(u[n]=t[n],c.data[n]=e)}const p=new Array(i.dims[0]),d=c.data;for(let e=0;e<d.length;++e){const t=d[e];p[t]=t}const _=p.filter((e=>void 0!==e));o.push({segmentation:c,labels:_})}return o}}class m extends h{}class g extends m{}class b extends h{}class w extends h{}class x extends h{}class y extends h{}class T extends h{}class v extends h{constructor(e){super(e),this.crop_pct=this.config.crop_pct??.875}async resize(e){const t=this.size?.shortest_edge;if(void 0===t)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(t<384){const n=Math.floor(t/this.crop_pct),[r,o]=this.get_resize_output_image_size(e,{shortest_edge:n});e=await e.resize(r,o,{resample:this.resample}),e=await e.center_crop(t,t)}else e=await e.resize(t,t,{resample:this.resample});return e}}class k extends v{}class M extends h{}class S extends h{}class P extends h{constructor(e){super(e),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map((e=>e*e)))}}class A extends h{}class F extends A{}class C extends h{post_process_object_detection(...e){return c(...e)}}class E extends C{}class O extends h{}class I extends h{}class D extends h{pad_image(e,t,n,r={}){const[o,i,s]=t;let a=this.image_mean;Array.isArray(this.image_mean)||(a=new Array(s).fill(a));let l=this.image_std;Array.isArray(l)||(l=new Array(s).fill(a));const c=a.map(((e,t)=>-e/l[t]));return super.pad_image(e,t,n,{center:!0,constant_values:c,...r})}}class L extends D{}class N extends h{async _call(e){const t=await super._call(e),n=[t.pixel_values.dims[0],64,64],r=new s.Tensor("int64",new BigInt64Array(n.reduce(((e,t)=>e*t))).fill(1n),n);return{...t,pixel_mask:r}}post_process_object_detection(...e){return c(...e)}remove_low_and_no_objects(e,t,n,r){let o=[],s=[],a=[];for(let l=0;l<e.dims[0];++l){let c=e[l],u=t[l],p=(0,i.max)(c.data)[1];if(p===r)continue;let d=(0,i.softmax)(c.data)[p];d>n&&(o.push(u),s.push(d),a.push(p))}return[o,s,a]}check_segment_validity(e,t,n,r=.5,o=.8){let i=[],s=0,a=0;for(let o=0;o<e.length;++o)e[o]===n&&(i.push(o),++s),t[n].data[o]>=r&&++a;let l=s>0&&a>0;if(l){l=s/a>o}return[l,i]}compute_segments(e,t,n,r,o,i=null,a=null){let[l,c]=a??e[0].dims,u=new s.Tensor("int32",new Int32Array(l*c),[l,c]),p=[];if(null!==a)for(let t=0;t<e.length;++t)e[t]=(0,s.interpolate)(e[t],a,"bilinear",!1);let d=new Int32Array(e[0].data.length),_=new Float32Array(e[0].data.length);for(let n=0;n<e.length;++n){let r=t[n];for(let t=0;t<e[n].data.length;++t)e[n].data[t]*=r,e[n].data[t]>_[t]&&(d[t]=n,_[t]=e[n].data[t])}let h=0;for(let i=0;i<n.length;++i){let s=n[i],[a,l]=this.check_segment_validity(d,e,i,r,o);if(a){++h;for(let e of l)u.data[e]=h;p.push({id:h,label_id:s,score:t[i]})}}return[u,p]}post_process_panoptic_segmentation(e,t=.5,n=.5,r=.8,o=null,i=null){null===o&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),o=new Set);const a=e.logits,l=e.pred_masks.sigmoid();let[c,u,p]=a.dims;if(p-=1,null!==i&&i.length!==c)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let d=[];for(let e=0;e<c;++e){let c=null!==i?i[e]:null,u=a[e],_=l[e],[h,f,m]=this.remove_low_and_no_objects(u,_,t,p);if(0===m.length){let[e,t]=c??_.dims.slice(-2),n=new s.Tensor("int32",new Int32Array(e*t).fill(-1),[e,t]);d.push({segmentation:n,segments_info:[]});continue}let[g,b]=this.compute_segments(h,f,m,n,r,o,c);d.push({segmentation:g,segments_info:b})}return d}post_process_instance_segmentation(){throw Error("Not implemented yet")}}class $ extends h{post_process_object_detection(...e){return c(...e)}}class B extends h{reshape_input_points(e,t,n){e=structuredClone(e);let o=(0,r.calculateDimensions)(e);if(3===o.length)o=[1,...o],e=[e];else if(4!==o.length)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");for(let r=0;r<e.length;++r){let o=t[r],i=n[r],s=[i[0]/o[0],i[1]/o[1]];for(let t=0;t<e[r].length;++t)for(let n=0;n<e[r][t].length;++n)for(let o=0;o<e[r][t][n].length;++o)e[r][t][n][o]*=s[o]}return new s.Tensor("float32",Float32Array.from(e.flat(1/0)),o)}add_input_labels(e,t){let n=(0,r.calculateDimensions)(e);if(2===n.length)n=[1,...n],e=[e];else if(3!==n.length)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");if(n.some(((e,n)=>e!==t.dims[n])))throw Error(`The first ${n.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new s.Tensor("int64",e.flat(1/0).map(BigInt),n)}async _call(e,t=null,n=null){const r=await super._call(e);if(t&&(r.input_points=this.reshape_input_points(t,r.original_sizes,r.reshaped_input_sizes)),n){if(!r.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");r.input_labels=this.add_input_labels(n,r.input_points)}return r}post_process_masks(e,t,n,{mask_threshold:r=0,binarize:o=!0,pad_size:i=null}={}){const a=[],l=[(i=i??this.pad_size).height,i.width];for(let i=0;i<t.length;++i){const c=t[i],u=n[i],p=e[i],d=[];for(let e=0;e<p.dims[0];++e){const t=p[e];let n=(0,s.interpolate)(t,l,"bilinear",!1);if(n=n.slice(null,[0,u[0]],[0,u[1]]),n=(0,s.interpolate)(n,c,"bilinear",!1),o){const e=new Uint8Array(n.data.length);for(let t=0;t<n.data.length;++t)n.data[t]>r&&(e[t]=1);n=new s.Tensor("bool",e,n.dims)}d.push(n)}a.push((0,s.stack)(d))}return a}}class z extends h{pad_image(e,t,n,r={}){const[o,i,s]=t;return super.pad_image(e,t,{width:i+(n-i%n)%n,height:o+(n-o%n)%n},{mode:"symmetric",center:!1,constant_values:-1,...r})}}class R extends h{async _call(e,t){Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);const n=await Promise.all(e.map((e=>this.preprocess(e)))),r=await Promise.all(t.map((e=>this.preprocess(e,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0}))));return{pixel_values:(0,s.stack)(n.map(((e,t)=>(0,s.cat)([e.pixel_values,r[t].pixel_values],0))),0),original_sizes:n.map((e=>e.original_size)),reshaped_input_sizes:n.map((e=>e.reshaped_input_size))}}}class j extends _{constructor(e){super(e),this.config.mel_filters??=(0,a.mel_filter_bank)(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney"),this.window=(0,a.window_function)(this.config.n_fft,"hann")}_extract_fbank_features(e){const{data:t,dims:n}=(0,a.spectrogram)(e,this.window,this.config.n_fft,this.config.hop_length,{power:2,mel_filters:this.config.mel_filters,log_mel:"log10",max_num_frames:this.config.nb_max_frames}),r=(0,i.max)(t)[0];for(let e=0;e<t.length;++e)t[e]=(Math.max(t[e],r-8)+4)/4;return{data:t,dims:n}}async _call(e){let t;u(e,"WhisperFeatureExtractor"),e.length>this.config.n_samples?(console.warn("Attempting to extract features for audio longer than 30 seconds. If using a pipeline to extract transcript from a long audio clip, remember to specify `chunk_length_s` and/or `stride_length_s`."),t=e.slice(0,this.config.n_samples)):(t=new Float32Array(this.config.n_samples),t.set(e));const{data:n,dims:r}=this._extract_fbank_features(t);return{input_features:new s.Tensor("float32",n,[1,...r])}}}class V extends _{_zero_mean_unit_var_norm(e){const t=e.reduce(((e,t)=>e+t),0)/e.length,n=e.reduce(((e,n)=>e+(n-t)**2),0)/e.length;return e.map((e=>(e-t)/Math.sqrt(n+1e-7)))}async _call(e){u(e,"Wav2Vec2FeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));let t=e;this.config.do_normalize&&(t=this._zero_mean_unit_var_norm(t));const n=[1,t.length];return{input_values:new s.Tensor("float32",t,n),attention_mask:new s.Tensor("int64",new BigInt64Array(t.length).fill(1n),n)}}}class U extends _{constructor(e){super(e);const t=this.config.sampling_rate,n=(0,a.mel_filter_bank)(256,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);for(let e=0;e<n.length;++e)n[e].push(0);this.mel_filters=n,this.window=(0,a.window_function)(400,"povey",{periodic:!1})}_extract_fbank_features(e,t){return e=e.map((e=>32768*e)),(0,a.spectrogram)(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1.192092955078125e-7,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e,{padding:t=!0,pad_to_multiple_of:n=2,do_normalize_per_mel_bins:r=!0,return_attention_mask:o=!0}={}){u(e,"SeamlessM4TFeatureExtractor");let i,a=this._extract_fbank_features(e,this.config.max_length);if(r){const[e,t]=a.dims;for(let n=0;n<t;++n){let r=0;for(let o=0;o<e;++o)r+=a.data[o*t+n];const o=r/e;let i=0;for(let r=0;r<e;++r)i+=(a.data[r*t+n]-o)**2;i/=e-1;const s=Math.sqrt(i+1e-7);for(let r=0;r<e;++r){const e=r*t+n;a.data[e]=(a.data[e]-o)/s}}}if(t){const[e,t]=a.dims,r=e%n;if(r>0){const n=new Float32Array(t*(e+r));n.set(a.data),n.fill(this.config.padding_value,a.data.length);const l=e+r;a={data:n,dims:[l,t]},o&&(i=new s.Tensor("int64",new BigInt64Array(l),[1,l]),i.data.fill(1n,0,e))}}const[l,c]=a.dims,p=this.config.stride;if(0!==l%p)throw new Error(`The number of frames (${l}) must be a multiple of the stride (${p}).`);const d=new s.Tensor("float32",a.data,a.dims).view(1,Math.floor(l/p),c*p),_={input_features:d};if(o){const e=d.dims[1],t=new s.Tensor("int64",new BigInt64Array(e),[1,e]);if(i)for(let e=1,n=0;e<l;e+=p,++n)t.data[n]=i.data[e];else t.data.fill(1n);_.attention_mask=t}return _}}class G extends _{constructor(e){super(e);const t=this.config.sampling_rate,n=(0,a.mel_filter_bank)(256,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);for(let e=0;e<n.length;++e)n[e].push(0);this.mel_filters=n,this.window=(0,a.window_function)(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}_extract_fbank_features(e,t){return(0,a.spectrogram)(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1.192092955078125e-7,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e){u(e,"ASTFeatureExtractor");const t=this._extract_fbank_features(e,this.config.max_length);if(this.config.do_normalize){const e=2*this.std;for(let n=0;n<t.data.length;++n)t.data[n]=(t.data[n]-this.mean)/e}return{input_values:new s.Tensor("float32",t.data,[1,...t.dims])}}}class q extends _{constructor(e){super(e),this.mel_filters=(0,a.mel_filter_bank)(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,null,"htk"),this.mel_filters_slaney=(0,a.mel_filter_bank)(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,"slaney","slaney"),this.window=(0,a.window_function)(this.config.fft_window_size,"hann")}_get_input_mel(e,t,n,r){let o,i=!1;const s=e.length-t;if(s>0){if("rand_trunc"!==n)throw new Error(`Truncation strategy "${n}" not implemented`);{i=!0;const n=Math.floor(Math.random()*(s+1));e=e.subarray(n,n+t),o=this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples),o.dims=[1,...o.dims]}}else{if(s<0){let n=new Float64Array(t);if(n.set(e),"repeat"===r)for(let r=e.length;r<t;r+=e.length)n.set(e.subarray(0,Math.min(e.length,t-r)),r);else if("repeatpad"===r)for(let t=e.length;t<-s;t+=e.length)n.set(e,t);e=n}if("fusion"===n)throw new Error(`Truncation strategy "${n}" not implemented`);o=this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples),o.dims=[1,...o.dims]}return{...o,longer:i}}_extract_fbank_features(e,t,n=null){return(0,a.spectrogram)(e,this.window,this.config.fft_window_size,this.config.hop_length,{power:2,mel_filters:t,log_mel:"dB",max_num_frames:n,do_pad:!1,transpose:!0})}async _call(e,{max_length:t=null}={}){u(e,"ClapFeatureExtractor");const n=this._get_input_mel(e,t??this.config.nb_max_samples,this.config.truncation,this.config.padding);return{input_features:new s.Tensor("float32",n.data,[1,...n.dims])}}}class W extends _{}class H extends r.Callable{constructor(e){super(),this.feature_extractor=e}async _call(e,...t){return await this.feature_extractor(e,...t)}}class X extends H{async _call(...e){return await this.feature_extractor(...e)}post_process_masks(...e){return this.feature_extractor.post_process_masks(...e)}reshape_input_points(...e){return this.feature_extractor.reshape_input_points(...e)}}class Q extends H{async _call(e){return await this.feature_extractor(e)}}class Y extends H{async _call(e){return await this.feature_extractor(e)}}class K extends H{async _call(e){return await this.feature_extractor(e)}}class Z extends H{}class J{static FEATURE_EXTRACTOR_CLASS_MAPPING={ImageFeatureExtractor:h,WhisperFeatureExtractor:j,ViTFeatureExtractor:M,MobileViTFeatureExtractor:A,MobileViTImageProcessor:F,OwlViTFeatureExtractor:C,Owlv2ImageProcessor:E,CLIPFeatureExtractor:x,ChineseCLIPFeatureExtractor:y,SiglipImageProcessor:T,ConvNextFeatureExtractor:v,ConvNextImageProcessor:k,SegformerFeatureExtractor:f,BitImageProcessor:b,DPTImageProcessor:g,DPTFeatureExtractor:m,GLPNFeatureExtractor:w,BeitFeatureExtractor:I,DeiTFeatureExtractor:O,DetrFeatureExtractor:N,YolosFeatureExtractor:$,DonutFeatureExtractor:D,NougatImageProcessor:L,EfficientNetImageProcessor:P,ViTImageProcessor:S,VitMatteImageProcessor:R,SamImageProcessor:B,Swin2SRImageProcessor:z,Wav2Vec2FeatureExtractor:V,SeamlessM4TFeatureExtractor:U,SpeechT5FeatureExtractor:W,ASTFeatureExtractor:G,ClapFeatureExtractor:q};static PROCESSOR_CLASS_MAPPING={WhisperProcessor:Q,Wav2Vec2ProcessorWithLM:Y,SamProcessor:X,SpeechT5Processor:K,OwlViTProcessor:Z};static async from_pretrained(e,{progress_callback:t=null,config:n=null,cache_dir:r=null,local_files_only:i=!1,revision:s="main"}={}){let a=n??await(0,o.getModelJSON)(e,"preprocessor_config.json",!0,{progress_callback:t,config:n,cache_dir:r,local_files_only:i,revision:s}),l=a.feature_extractor_type??a.image_processor_type,c=this.FEATURE_EXTRACTOR_CLASS_MAPPING[l];if(!c){if(void 0===a.size)throw new Error(`Unknown Feature Extractor type: ${l}`);console.warn(`Feature extractor type "${l}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),c=h}return new(this.PROCESSOR_CLASS_MAPPING[a.processor_class]??H)(new c(a))}}},"./src/tokenizers.js":
+/*!***************************!*\
+  !*** ./src/tokenizers.js ***!
+  \***************************/(e,t,n)=>{n.r(t),n.d(t,{AlbertTokenizer:()=>ge,AutoTokenizer:()=>pt,BartTokenizer:()=>Ee,BertTokenizer:()=>me,BlenderbotSmallTokenizer:()=>st,BlenderbotTokenizer:()=>it,BloomTokenizer:()=>Le,CLIPTokenizer:()=>tt,CamembertTokenizer:()=>Se,CodeGenTokenizer:()=>et,CodeLlamaTokenizer:()=>Be,CohereTokenizer:()=>ut,ConvBertTokenizer:()=>ve,DebertaTokenizer:()=>xe,DebertaV2Tokenizer:()=>ye,DistilBertTokenizer:()=>Me,ElectraTokenizer:()=>Ae,EsmTokenizer:()=>Ue,FalconTokenizer:()=>je,GPT2Tokenizer:()=>Ce,GPTNeoXTokenizer:()=>Ve,GemmaTokenizer:()=>qe,Grok1Tokenizer:()=>We,HerbertTokenizer:()=>Te,LlamaTokenizer:()=>$e,M2M100Tokenizer:()=>Qe,MBart50Tokenizer:()=>Ie,MBartTokenizer:()=>Oe,MPNetTokenizer:()=>Re,MarianTokenizer:()=>rt,MobileBertTokenizer:()=>be,NllbTokenizer:()=>Xe,NougatTokenizer:()=>lt,PreTrainedTokenizer:()=>fe,Qwen2Tokenizer:()=>Ge,RoFormerTokenizer:()=>ke,RobertaTokenizer:()=>De,SiglipTokenizer:()=>nt,SpeechT5Tokenizer:()=>at,SqueezeBertTokenizer:()=>we,T5Tokenizer:()=>Fe,TokenizerModel:()=>b,VitsTokenizer:()=>ct,Wav2Vec2CTCTokenizer:()=>ot,WhisperTokenizer:()=>Je,XLMRobertaTokenizer:()=>ze,XLMTokenizer:()=>Pe});var r=n(/*! ./utils/core.js */"./src/utils/core.js"),o=n(/*! ./utils/hub.js */"./src/utils/hub.js"),i=n(/*! ./utils/maths.js */"./src/utils/maths.js"),s=n(/*! ./utils/tensor.js */"./src/utils/tensor.js"),a=n(/*! ./utils/data-structures.js */"./src/utils/data-structures.js"),l=n(/*! @huggingface/jinja */"./node_modules/@huggingface/jinja/dist/index.js");async function c(e,t){const n=await Promise.all([(0,o.getModelJSON)(e,"tokenizer.json",!0,t),(0,o.getModelJSON)(e,"tokenizer_config.json",!0,t)]);return null!==t.legacy&&(n[1].legacy=t.legacy),n}function u(e,t=!0){if(void 0!==e.Regex){let t=e.Regex.replace(/\\([#&~])/g,"$1");for(const[e,n]of m)t=t.replaceAll(e,n);return new RegExp(t,"gu")}if(void 0!==e.String){const n=(0,r.escapeRegExp)(e.String);return new RegExp(t?n:`(${n})`,"gu")}return console.warn("Unknown pattern type:",e),null}function p(e){return new Map(Object.entries(e))}function d(e){const t=e.dims;switch(t.length){case 1:return e.tolist();case 2:if(1!==t[0])throw new Error("Unable to decode tensor with `batch size !== 1`. Use `tokenizer.batch_decode(...)` for batched inputs.");return e.tolist()[0];default:throw new Error(`Expected tensor to have 1-2 dimensions, got ${t.length}.`)}}function _(e){return e.replace(/ \./g,".").replace(/ \?/g,"?").replace(/ \!/g,"!").replace(/ ,/g,",").replace(/ \' /g,"'").replace(/ n\'t/g,"n't").replace(/ \'m/g,"'m").replace(/ \'s/g,"'s").replace(/ \'ve/g,"'ve").replace(/ \'re/g,"'re")}function h(e){return e.replace(/[\u0300-\u036f]/g,"")}const f="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E",m=new Map([["(?i:'s|'t|'re|'ve|'m|'ll|'d)","(?:'([sS]|[tT]|[rR][eE]|[vV][eE]|[mM]|[lL][lL]|[dD]))"]]);class g{constructor(e){this.content=e.content,this.id=e.id,this.single_word=e.single_word??!1,this.lstrip=e.lstrip??!1,this.rstrip=e.rstrip??!1,this.special=e.special??!1,this.normalized=e.normalized??null}}class b extends r.Callable{constructor(e){super(),this.config=e,this.vocab=[],this.tokens_to_ids=new Map,this.unk_token_id=void 0,this.unk_token=void 0,this.end_of_word_suffix=void 0,this.fuse_unk=this.config.fuse_unk??!1}static fromConfig(e,...t){switch(e.type){case"WordPiece":return new w(e);case"Unigram":return new x(e,...t);case"BPE":return new v(e);default:if(e.vocab)return new k(e,...t);throw new Error(`Unknown TokenizerModel type: ${e.type}`)}}_call(e){let t=this.encode(e);return this.fuse_unk&&(t=function(e,t,n){const r=[];let o=0;for(;o<e.length;)if(r.push(e[o]),(n.get(e[o])??t)===t)for(;o<e.length&&(n.get(e[o])??t)===t;)++o;else++o;return r}(t,this.unk_token_id,this.tokens_to_ids)),t}encode(e){throw Error("encode should be implemented in subclass.")}convert_tokens_to_ids(e){return e.map((e=>this.tokens_to_ids.get(e)??this.unk_token_id))}convert_ids_to_tokens(e){return e.map((e=>this.vocab[e]??this.unk_token))}}class w extends b{constructor(e){super(e),this.tokens_to_ids=p(e.vocab),this.unk_token_id=this.tokens_to_ids.get(e.unk_token),this.unk_token=e.unk_token,this.max_input_chars_per_word=e.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[e,t]of this.tokens_to_ids)this.vocab[t]=e}encode(e){const t=[];for(const n of e){const e=[...n];if(e.length>this.max_input_chars_per_word){t.push(this.unk_token);continue}let r=!1,o=0;const i=[];for(;o<e.length;){let t=e.length,n=null;for(;o<t;){let r=e.slice(o,t).join("");if(o>0&&(r=this.config.continuing_subword_prefix+r),this.tokens_to_ids.has(r)){n=r;break}--t}if(null===n){r=!0;break}i.push(n),o=t}r?t.push(this.unk_token):t.push(...i)}return t}}class x extends b{constructor(e,t){super(e);const n=e.vocab.length;this.vocab=new Array(n),this.scores=new Array(n);for(let t=0;t<n;++t){const n=e.vocab[t];this.vocab[t]=n[0],this.scores[t]=n[1]}this.unk_token_id=e.unk_id,this.unk_token=this.vocab[e.unk_id],this.tokens_to_ids=new Map(this.vocab.map(((e,t)=>[e,t]))),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=t.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=(0,i.min)(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new a.CharTrie,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(e){const t=e.sentence,n=t.length;let r=0;for(;r<n;){const n=1;let o=!1;const i=[];for(let s of this.trie.commonPrefixSearch(t.slice(r))){i.push(s);const t=this.tokens_to_ids.get(s),a=this.scores[t],l=s.length;e.insert(r,l,a,t),o||l!==n||(o=!0)}o||e.insert(r,n,this.unkScore,this.unk_token_id),r+=n}}tokenize(e){const t=new a.TokenLattice(e,this.bosTokenId,this.eosTokenId);return this.populateNodes(t),t.tokens()}encode(e){const t=[];for(const n of e){const e=this.tokenize(n);t.push(...e)}return t}}const y=(()=>{const e=[...Array.from({length:"~".charCodeAt(0)-"!".charCodeAt(0)+1},((e,t)=>t+"!".charCodeAt(0))),...Array.from({length:"¬".charCodeAt(0)-"¡".charCodeAt(0)+1},((e,t)=>t+"¡".charCodeAt(0))),...Array.from({length:"ÿ".charCodeAt(0)-"®".charCodeAt(0)+1},((e,t)=>t+"®".charCodeAt(0)))],t=e.slice();let n=0;for(let r=0;r<256;++r)e.includes(r)||(e.push(r),t.push(256+n),n+=1);const r=t.map((e=>String.fromCharCode(e)));return Object.fromEntries(e.map(((e,t)=>[e,r[t]])))})(),T=(0,r.reverseDictionary)(y);class v extends b{constructor(e){super(e),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=p(e.vocab),this.unk_token_id=this.tokens_to_ids.get(e.unk_token),this.unk_token=e.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[e,t]of this.tokens_to_ids)this.vocab[t]=e;this.bpe_ranks=new Map(e.merges.map(((e,t)=>[e,t]))),this.merges=e.merges.map((e=>e.split(this.BPE_SPLIT_TOKEN))),this.end_of_word_suffix=e.end_of_word_suffix,this.continuing_subword_suffix=e.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.ignore_merges=this.config.ignore_merges??!1,this.cache=new Map}bpe(e){if(0===e.length)return[];const t=this.cache.get(e);if(void 0!==t)return t;const n=Array.from(e);this.end_of_word_suffix&&(n[n.length-1]+=this.end_of_word_suffix);let r=[];if(n.length>1){const e=new a.PriorityQueue(((e,t)=>e.score<t.score));let t={token:n[0],bias:0,prev:null,next:null},o=t;for(let t=1;t<n.length;++t){const r={bias:t/n.length,token:n[t],prev:o,next:null};o.next=r,this._add_node(e,o),o=r}for(;!e.isEmpty();){const n=e.pop();if(n.deleted||!n.next||n.next.deleted)continue;if(n.deleted=!0,n.next.deleted=!0,n.prev){const e={...n.prev};n.prev.deleted=!0,n.prev=e,e.prev?e.prev.next=e:t=e}const r={token:n.token+n.next.token,bias:n.bias,prev:n.prev,next:n.next.next};r.prev?(r.prev.next=r,this._add_node(e,r.prev)):t=r,r.next&&(r.next.prev=r,this._add_node(e,r))}for(let e=t;null!==e;e=e.next)r.push(e.token)}else r=n;if(this.continuing_subword_suffix)for(let e=0;e<r.length-1;++e)r[e]+=this.continuing_subword_suffix;return this.cache.set(e,r),r}_add_node(e,t){const n=this.bpe_ranks.get(t.token+this.BPE_SPLIT_TOKEN+t.next.token);void 0!==n&&(t.score=n+t.bias,e.push(t))}encode(e){const t=[];for(const n of e){if(this.ignore_merges&&this.tokens_to_ids.has(n)){t.push(n);continue}const e=this.bpe(n);for(const n of e)this.tokens_to_ids.has(n)?t.push(n):this.byte_fallback?t.push(...Array.from(this.text_encoder.encode(n)).map((e=>`<0x${e.toString(16).toUpperCase().padStart(2,"0")}>`))):t.push(this.unk_token)}return t}}class k extends b{constructor(e,t){super(e),this.tokens_to_ids=p(t.target_lang?e.vocab[t.target_lang]:e.vocab),this.bos_token=t.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=t.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=t.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=t.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=new Array(this.tokens_to_ids.size);for(const[e,t]of this.tokens_to_ids)this.vocab[t]=e}encode(e){return e}}class M extends r.Callable{constructor(e){super(),this.config=e}static fromConfig(e){if(null===e)return null;switch(e.type){case"BertNormalizer":return new L(e);case"Precompiled":return new ae(e);case"Sequence":return new D(e);case"Replace":return new S(e);case"NFC":return new P(e);case"NFKC":return new A(e);case"NFKD":return new F(e);case"Strip":return new C(e);case"StripAccents":return new E(e);case"Lowercase":return new O(e);case"Prepend":return new I(e);default:throw new Error(`Unknown Normalizer type: ${e.type}`)}}normalize(e){throw Error("normalize should be implemented in subclass.")}_call(e){return this.normalize(e)}}class S extends M{normalize(e){const t=u(this.config.pattern);return null===t?e:e.replaceAll(t,this.config.content)}}class P extends M{normalize(e){return e=e.normalize("NFC")}}class A extends M{normalize(e){return e=e.normalize("NFKC")}}class F extends M{normalize(e){return e=e.normalize("NFKD")}}class C extends M{normalize(e){return this.config.strip_left&&this.config.strip_right?e=e.trim():(this.config.strip_left&&(e=e.trimStart()),this.config.strip_right&&(e=e.trimEnd())),e}}class E extends M{normalize(e){return e=h(e)}}class O extends M{normalize(e){return e=e.toLowerCase()}}class I extends M{normalize(e){return e=this.config.prepend+e}}class D extends M{constructor(e){super(e),this.normalizers=e.normalizers.map((e=>M.fromConfig(e)))}normalize(e){return this.normalizers.reduce(((e,t)=>t.normalize(e)),e)}}class L extends M{_tokenize_chinese_chars(e){const t=[];for(let n=0;n<e.length;++n){const r=e[n],o=r.charCodeAt(0);this._is_chinese_char(o)?(t.push(" "),t.push(r),t.push(" ")):t.push(r)}return t.join("")}_is_chinese_char(e){return e>=19968&&e<=40959||e>=13312&&e<=19903||e>=131072&&e<=173791||e>=173824&&e<=177983||e>=177984&&e<=178207||e>=178208&&e<=183983||e>=63744&&e<=64255||e>=194560&&e<=195103}stripAccents(e){return e.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}_is_control(e){switch(e){case"\t":case"\n":case"\r":return!1;default:return/^\p{Cc}|\p{Cf}|\p{Co}|\p{Cs}$/u.test(e)}}_clean_text(e){const t=[];for(const n of e){const e=n.charCodeAt(0);0===e||65533===e||this._is_control(n)||(/^\s$/.test(n)?t.push(" "):t.push(n))}return t.join("")}normalize(e){return this.config.clean_text&&(e=this._clean_text(e)),this.config.handle_chinese_chars&&(e=this._tokenize_chinese_chars(e)),this.config.lowercase?(e=e.toLowerCase(),!1!==this.config.strip_accents&&(e=this.stripAccents(e))):this.config.strip_accents&&(e=this.stripAccents(e)),e}}class N extends r.Callable{static fromConfig(e){if(null===e)return null;switch(e.type){case"BertPreTokenizer":return new $(e);case"Sequence":return new le(e);case"Whitespace":return new ce(e);case"WhitespaceSplit":return new ue(e);case"Metaspace":return new ie(e);case"ByteLevel":return new B(e);case"Split":return new z(e);case"Punctuation":return new R(e);case"Digits":return new j(e);case"Replace":return new pe(e);default:throw new Error(`Unknown PreTokenizer type: ${e.type}`)}}pre_tokenize_text(e,t){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(e,t){return(Array.isArray(e)?e.map((e=>this.pre_tokenize_text(e,t))):this.pre_tokenize_text(e,t)).flat()}_call(e,t){return this.pre_tokenize(e,t)}}class $ extends N{constructor(e){super(),this.pattern=new RegExp(`[^\\s${f}]+|[${f}]`,"gu")}pre_tokenize_text(e,t){return e.trim().match(this.pattern)||[]}}class B extends N{constructor(e){super(),this.config=e,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=/'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+/gu,this.byte_encoder=y,this.text_encoder=new TextEncoder}pre_tokenize_text(e,t){this.add_prefix_space&&!e.startsWith(" ")&&(e=" "+e);return(this.use_regex?e.match(this.pattern)||[]:[e]).map((e=>Array.from(this.text_encoder.encode(e),(e=>this.byte_encoder[e])).join("")))}}class z extends N{constructor(e){super(),this.config=e,this.pattern=u(this.config.pattern,this.config.invert)}pre_tokenize_text(e,t){return null===this.pattern?[]:this.config.invert?e.match(this.pattern)||[]:function(e,t){const n=[];let r=0;for(const o of e.matchAll(t)){const t=o[0];r<o.index&&n.push(e.slice(r,o.index)),t.length>0&&n.push(t),r=o.index+t.length}return r<e.length&&n.push(e.slice(r)),n}(e,this.pattern)}}class R extends N{constructor(e){super(),this.config=e,this.pattern=new RegExp(`[^${f}]+|[${f}]+`,"gu")}pre_tokenize_text(e,t){return e.match(this.pattern)||[]}}class j extends N{constructor(e){super(),this.config=e;const t="[^\\d]+|\\d"+(this.config.individual_digits?"":"+");this.pattern=new RegExp(t,"gu")}pre_tokenize_text(e,t){return e.match(this.pattern)||[]}}class V extends r.Callable{constructor(e){super(),this.config=e}static fromConfig(e){if(null===e)return null;switch(e.type){case"TemplateProcessing":return new q(e);case"ByteLevel":return new W(e);case"RobertaProcessing":return new G(e);case"BertProcessing":return new U(e);case"Sequence":return new H(e);default:throw new Error(`Unknown PostProcessor type: ${e.type}`)}}post_process(e,...t){throw Error("post_process should be implemented in subclass.")}_call(e,...t){return this.post_process(e,...t)}}class U extends V{constructor(e){super(e),this.cls=e.cls[0],this.sep=e.sep[0]}post_process(e,t=null,{add_special_tokens:n=!0}={}){n&&(e=(0,r.mergeArrays)([this.cls],e,[this.sep]));let o=new Array(e.length).fill(0);if(null!==t){const i=n&&this instanceof G?[this.sep]:[],s=n?[this.sep]:[];e=(0,r.mergeArrays)(e,i,t,s),o=(0,r.mergeArrays)(o,new Array(t.length+i.length+s.length).fill(1))}return{tokens:e,token_type_ids:o}}}class G extends U{}class q extends V{constructor(e){super(e),this.single=e.single,this.pair=e.pair}post_process(e,t=null,{add_special_tokens:n=!0}={}){const o=null===t?this.single:this.pair;let i=[],s=[];for(const a of o)"SpecialToken"in a?n&&(i.push(a.SpecialToken.id),s.push(a.SpecialToken.type_id)):"Sequence"in a&&("A"===a.Sequence.id?(i=(0,r.mergeArrays)(i,e),s=(0,r.mergeArrays)(s,new Array(e.length).fill(a.Sequence.type_id))):"B"===a.Sequence.id&&(i=(0,r.mergeArrays)(i,t),s=(0,r.mergeArrays)(s,new Array(t.length).fill(a.Sequence.type_id))));return{tokens:i,token_type_ids:s}}}class W extends V{post_process(e,t=null){return t&&(e=(0,r.mergeArrays)(e,t)),{tokens:e}}}class H extends V{constructor(e){super(e),this.processors=e.processors.map((e=>V.fromConfig(e)))}post_process(e,t=null,n={}){let r;for(const o of this.processors)if(o instanceof W){if(e=o.post_process(e).tokens,t){t=o.post_process(t).tokens}}else{const i=o.post_process(e,t,n);e=i.tokens,r=i.token_type_ids}return{tokens:e,token_type_ids:r}}}class X extends r.Callable{constructor(e){super(),this.config=e,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=e.trim_offsets}static fromConfig(e){if(null===e)return null;switch(e.type){case"WordPiece":return new J(e);case"Metaspace":return new se(e);case"ByteLevel":return new ee(e);case"Replace":return new Q(e);case"ByteFallback":return new Y(e);case"Fuse":return new K(e);case"Strip":return new Z(e);case"Sequence":return new ne(e);case"CTC":return new te(e);case"BPEDecoder":return new re(e);default:throw new Error(`Unknown Decoder type: ${e.type}`)}}_call(e){return this.decode(e)}decode(e){return this.decode_chain(e).join("")}decode_chain(e){throw Error("`decode_chain` should be implemented in subclass.")}}class Q extends X{decode_chain(e){const t=u(this.config.pattern);return null===t?e:e.map((e=>e.replaceAll(t,this.config.content)))}}class Y extends X{constructor(e){super(e),this.text_decoder=new TextDecoder}decode_chain(e){const t=[];let n=[];for(const r of e){let e=null;if(6===r.length&&r.startsWith("<0x")&&r.endsWith(">")){const t=parseInt(r.slice(3,5),16);isNaN(t)||(e=t)}if(null!==e)n.push(e);else{if(n.length>0){const e=this.text_decoder.decode(Uint8Array.from(n));t.push(e),n=[]}t.push(r)}}if(n.length>0){const e=this.text_decoder.decode(Uint8Array.from(n));t.push(e),n=[]}return t}}class K extends X{decode_chain(e){return[e.join("")]}}class Z extends X{constructor(e){super(e),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(e){return e.map((e=>{let t=0;for(let n=0;n<this.start&&e[n]===this.content;++n)t=n+1;let n=e.length;for(let t=0;t<this.stop;++t){const r=e.length-t-1;if(e[r]!==this.content)break;n=r}return e.slice(t,n)}))}}class J extends X{constructor(e){super(e),this.cleanup=e.cleanup}decode_chain(e){return e.map(((e,t)=>(0!==t&&(e=e.startsWith(this.config.prefix)?e.replace(this.config.prefix,""):" "+e),this.cleanup&&(e=_(e)),e)))}}class ee extends X{constructor(e){super(e),this.byte_decoder=T,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(e){const t=e.join(""),n=new Uint8Array([...t].map((e=>this.byte_decoder[e])));return this.text_decoder.decode(n)}decode_chain(e){const t=[];let n=[];for(const r of e)void 0!==this.added_tokens.find((e=>e.content===r))?(n.length>0&&(t.push(this.convert_tokens_to_string(n)),n=[]),t.push(r)):n.push(r);return n.length>0&&t.push(this.convert_tokens_to_string(n)),t}}class te extends X{constructor(e){super(e),this.pad_token=this.config.pad_token,this.word_delimiter_token=this.config.word_delimiter_token,this.cleanup=this.config.cleanup}convert_tokens_to_string(e){if(0===e.length)return"";const t=[e[0]];for(let n=1;n<e.length;++n)e[n]!==t.at(-1)&&t.push(e[n]);let n=t.filter((e=>e!==this.pad_token)).join("");return this.cleanup&&(n=_(n).replaceAll(this.word_delimiter_token," ").trim()),n}decode_chain(e){return[this.convert_tokens_to_string(e)]}}class ne extends X{constructor(e){super(e),this.decoders=e.decoders.map((e=>X.fromConfig(e)))}decode_chain(e){return this.decoders.reduce(((e,t)=>t.decode_chain(e)),e)}}class re extends X{constructor(e){super(e),this.suffix=this.config.suffix}decode_chain(e){return e.map(((t,n)=>t.replaceAll(this.suffix,n===e.length-1?"":" ")))}}class oe extends X{decode_chain(e){let t="";for(let n=1;n<e.length;n+=2)t+=e[n];return[t]}}class ie extends N{constructor(e){super(),this.addPrefixSpace=e.add_prefix_space,this.replacement=e.replacement,this.strRep=e.str_rep||this.replacement,this.prepend_scheme=e.prepend_scheme??"always"}pre_tokenize_text(e,{section_index:t}={}){let n=e.replaceAll(" ",this.strRep);return this.addPrefixSpace&&!n.startsWith(this.replacement)&&("always"===this.prepend_scheme||"first"===this.prepend_scheme&&0===t)&&(n=this.strRep+n),[n]}}class se extends X{constructor(e){super(e),this.addPrefixSpace=e.add_prefix_space,this.replacement=e.replacement}decode_chain(e){const t=[];for(let n=0;n<e.length;++n){let r=e[n].replaceAll(this.replacement," ");this.addPrefixSpace&&0==n&&r.startsWith(" ")&&(r=r.substring(1)),t.push(r)}return t}}class ae extends M{constructor(e){super(e),this.charsmap=e.precompiled_charsmap}normalize(e){if((e=(e=e.replace(/[\u0001-\u0008\u000B\u000E-\u001F\u007F\u008F\u009F]/gm,"")).replace(/[\u0009\u000A\u000C\u000D\u1680\u200B\u200C\u200E\u200F\u2028\u2029\u2581\uFEFF\uFFFD]/gm," ")).includes("～")){const t=e.split("～");e=t.map((e=>e.normalize("NFKC"))).join("～")}else e=e.normalize("NFKC");return e}}class le extends N{constructor(e){super(),this.tokenizers=e.pretokenizers.map((e=>N.fromConfig(e)))}pre_tokenize_text(e,t){return this.tokenizers.reduce(((e,n)=>n.pre_tokenize(e,t)),[e])}}class ce extends N{constructor(e){super()}pre_tokenize_text(e,t){return e.match(/\w+|[^\w\s]+/g)||[]}}class ue extends N{constructor(e){super()}pre_tokenize_text(e,t){return function(e){return e.match(/\S+/g)||[]}(e)}}class pe extends N{constructor(e){super(),this.config=e,this.pattern=u(this.config.pattern),this.content=this.config.content}pre_tokenize_text(e,t){return null===this.pattern?[e]:[e.replaceAll(this.pattern,this.config.content)]}}const de=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function _e(e,t,n,o){for(const i of Object.keys(e)){const s=t-e[i].length,a=n(i),l=new Array(s).fill(a);e[i]="right"===o?(0,r.mergeArrays)(e[i],l):(0,r.mergeArrays)(l,e[i])}}function he(e,t){for(const n of Object.keys(e))e[n].length=t}class fe extends r.Callable{return_token_type_ids=!1;_default_chat_template="{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}";constructor(e,t){super(),this._tokenizer_config=t,this.normalizer=M.fromConfig(e.normalizer),this.pre_tokenizer=N.fromConfig(e.pre_tokenizer),this.model=b.fromConfig(e.model,t),this.post_processor=V.fromConfig(e.post_processor),this.decoder=X.fromConfig(e.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(const t of e.added_tokens){const e=new g(t);this.added_tokens.push(e),this.model.tokens_to_ids.set(e.content,e.id),this.model.vocab[e.id]=e.content,e.special&&(this.special_tokens.push(e.content),this.all_special_ids.push(e.id))}if(this.additional_special_tokens=t.additional_special_tokens??[],this.special_tokens.push(...this.additional_special_tokens),this.special_tokens=[...new Set(this.special_tokens)],this.decoder&&(this.decoder.added_tokens=this.added_tokens,this.decoder.end_of_word_suffix=this.model.end_of_word_suffix),this.added_tokens_regex=this.added_tokens.length>0?new RegExp(this.added_tokens.map((e=>`${e.lstrip?"\\s*":""}(${(0,r.escapeRegExp)(e.content)})${e.rstrip?"\\s*":""}`)).join("|")):null,this.mask_token=this.getToken("mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken("pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken("sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.unk_token=this.getToken("unk_token"),this.unk_token_id=this.model.tokens_to_ids.get(this.unk_token),this.model_max_length=t.model_max_length,this.remove_space=t.remove_space,this.clean_up_tokenization_spaces=t.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=t.do_lowercase_and_remove_accent??!1,this.padding_side="right",this.legacy=!1,this.chat_template=t.chat_template??null,Array.isArray(this.chat_template)){const e=Object.create(null);for(const{name:t,template:n}of this.chat_template){if("string"!=typeof t||"string"!=typeof n)throw new Error('Chat template must be a list of objects with "name" and "template" properties');e[t]=n}this.chat_template=e}this._compiled_template_cache=new Map}getToken(...e){for(const t of e){const e=this._tokenizer_config[t];if(e){if("object"==typeof e){if("AddedToken"===e.__type)return e.content;throw Error(`Unknown token: ${e}`)}return e}}return null}static async from_pretrained(e,{progress_callback:t=null,config:n=null,cache_dir:r=null,local_files_only:o=!1,revision:i="main",legacy:s=null}={}){return new this(...await c(e,{progress_callback:t,config:n,cache_dir:r,local_files_only:o,revision:i,legacy:s}))}_call(e,{text_pair:t=null,add_special_tokens:n=!0,padding:r=!1,truncation:o=null,max_length:a=null,return_tensor:l=!0,return_token_type_ids:c=null}={}){const u=Array.isArray(e);let p;if(u){if(0===e.length)throw Error("text array must be non-empty");if(null!==t){if(!Array.isArray(t))throw Error("text_pair must also be an array");if(e.length!==t.length)throw Error("text and text_pair must have the same length");p=e.map(((e,r)=>this._encode_plus(e,t[r],{add_special_tokens:n,return_token_type_ids:c})))}else p=e.map((e=>this._encode_plus(e,null,{add_special_tokens:n,return_token_type_ids:c})))}else{if(null==e)throw Error("text may not be null or undefined");if(Array.isArray(t))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");p=[this._encode_plus(e,t,{add_special_tokens:n,return_token_type_ids:c})]}if(null===a?a="max_length"===r?this.model_max_length:(0,i.max)(p.map((e=>e.input_ids.length)))[0]:o||console.warn("Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation=true` to explicitly truncate examples to max length."),a=Math.min(a,this.model_max_length),r||o)for(let e=0;e<p.length;++e)p[e].input_ids.length!==a&&(p[e].input_ids.length>a?o&&he(p[e],a):r&&_e(p[e],a,(e=>"input_ids"===e?this.pad_token_id:0),this.padding_side));const d={};if(l){if((!r||!o)&&p.some((e=>{for(const t of Object.keys(e))if(e[t].length!==p[0][t]?.length)return!0;return!1})))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");const e=[p.length,p[0].input_ids.length];for(const t of Object.keys(p[0]))d[t]=new s.Tensor("int64",BigInt64Array.from(p.flatMap((e=>e[t])).map(BigInt)),e)}else{for(const e of Object.keys(p[0]))d[e]=p.map((t=>t[e]));if(!u)for(const e of Object.keys(d))d[e]=d[e][0]}return d}_encode_text(e){if(null===e)return null;const t=(this.added_tokens_regex?e.split(this.added_tokens_regex).filter((e=>e)):[e]).map(((e,t)=>{if(void 0!==this.added_tokens.find((t=>t.content===e)))return e;{if(!0===this.remove_space&&(e=e.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(e=function(e){return h(e.toLowerCase())}(e)),null!==this.normalizer&&(e=this.normalizer(e)),0===e.length)return[];const n=null!==this.pre_tokenizer?this.pre_tokenizer(e,{section_index:t}):[e];return this.model(n)}})).flat();return t}_encode_plus(e,t=null,{add_special_tokens:n=!0,return_token_type_ids:o=null}={}){const i=this._encode_text(e),s=this._encode_text(t),a=this.post_processor?this.post_processor(i,s,{add_special_tokens:n}):{tokens:(0,r.mergeArrays)(i??[],s??[])},l=this.model.convert_tokens_to_ids(a.tokens),c={input_ids:l,attention_mask:new Array(l.length).fill(1)};return(o??this.return_token_type_ids)&&a.token_type_ids&&(c.token_type_ids=a.token_type_ids),c}encode(e,t=null,{add_special_tokens:n=!0,return_token_type_ids:r=null}={}){const{input_ids:o}=this._encode_plus(e,t,{add_special_tokens:n,return_token_type_ids:r});return o}batch_decode(e,t={}){return e instanceof s.Tensor&&(e=e.tolist()),e.map((e=>this.decode(e,t)))}decode(e,t={}){if(e instanceof s.Tensor&&(e=d(e)),!Array.isArray(e)||0===e.length||!(0,r.isIntegralNumber)(e[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(e,t)}decode_single(e,{skip_special_tokens:t=!1,clean_up_tokenization_spaces:n=null}){let r=this.model.convert_ids_to_tokens(e);t&&(r=r.filter((e=>!this.special_tokens.includes(e))));let o=this.decoder?this.decoder(r):r.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(o=o.replaceAll(this.decoder.end_of_word_suffix," "),t&&(o=o.trim())),(n??this.clean_up_tokenization_spaces)&&(o=_(o)),o}get default_chat_template(){return this._warned_about_chat_template||(console.warn("No chat template is defined for this tokenizer - using a default chat template that implements the ChatML format. If the default is not appropriate for your model, please set `tokenizer.chat_template` to an appropriate template. See https://huggingface.co/docs/transformers/main/chat_templating for more information."),this._warned_about_chat_template=!0),this._default_chat_template}apply_chat_template(e,{chat_template:t=null,add_generation_prompt:n=!1,tokenize:r=!0,padding:o=!1,truncation:i=!1,max_length:s=null,return_tensor:a=!0,tokenizer_kwargs:c={},...u}={}){if(this.chat_template&&"object"==typeof this.chat_template||null===this.chat_template&&this.default_chat_template&&"object"==typeof this.default_chat_template){const e=this.chat_template??this.default_chat_template;if(null!==t&&Object.hasOwn(e,t))t=e[t];else if(null===t&&"default"in e)t=e.default;else if(null===t)throw Error(`This model has multiple chat templates with no default specified! Please either pass a chat template or the name of the template you wish to use to the 'chat_template' argument. Available template names are ${Object.keys(e).sort()}.`)}else t??=this.chat_template??this.default_chat_template;if("string"!=typeof t)throw Error("chat_template must be a string, but got "+typeof t);let p=this._compiled_template_cache.get(t);void 0===p&&(p=new l.Template(t),this._compiled_template_cache.set(t,p));const d=Object.create(null);for(const e of de){const t=this.getToken(e);t&&(d[e]=t)}const _=p.render({messages:e,add_generation_prompt:n,...d,...u});return r?this._call(_,{add_special_tokens:!1,padding:o,truncation:i,max_length:s,return_tensor:a,...c}).input_ids:_}}class me extends fe{return_token_type_ids=!0}class ge extends fe{return_token_type_ids=!0}class be extends fe{return_token_type_ids=!0}class we extends fe{return_token_type_ids=!0}class xe extends fe{return_token_type_ids=!0}class ye extends fe{return_token_type_ids=!0}class Te extends fe{return_token_type_ids=!0}class ve extends fe{return_token_type_ids=!0}class ke extends fe{return_token_type_ids=!0}class Me extends fe{}class Se extends fe{}class Pe extends fe{return_token_type_ids=!0;constructor(e,t){super(e,t),console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}}class Ae extends fe{return_token_type_ids=!0}class Fe extends fe{}class Ce extends fe{_default_chat_template='{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}'}class Ee extends fe{}class Oe extends fe{constructor(e,t){super(e,t),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter((e=>this.languageRegex.test(e))),this.lang_to_token=e=>e}_build_translation_inputs(e,t,n){return He(this,e,t,n)}}class Ie extends Oe{}class De extends fe{}class Le extends Ce{constructor(e,t){const n=".,!?…。，、।۔،",r=e.pre_tokenizer?.pretokenizers[0]?.pattern;r&&r.Regex===` ?[^(\\s|[${n}])]+`&&(r.Regex=` ?[^\\s${n}]+`),super(e,t)}}const Ne="▁";class $e extends fe{_default_chat_template="{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif USE_DEFAULT_PROMPT == true and not '<<SYS>>' in messages[0]['content'] %}{% set loop_messages = messages %}{% set system_message = 'DEFAULT_SYSTEM_MESSAGE' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'system' %}{{ '<<SYS>>\n' + content.strip() + '\n<</SYS>>\n\n' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}";DEFAULT_SYSTEM_PROMPT="You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.";constructor(e,t){super(e,t),this.use_default_system_prompt=t.use_default_system_prompt??!1,this.legacy=t.legacy??!0,this.legacy||(this.normalizer=null,this.pre_tokenizer=new ie({replacement:Ne,add_prefix_space:!0,prepend_scheme:"first"}))}_encode_text(e){if(null===e)return null;if(this.legacy||0===e.length)return super._encode_text(e);let t=super._encode_text(Ne+e.replaceAll(Ne," "));return t.length>1&&t[0]===Ne&&this.special_tokens.includes(t[1])&&(t=t.slice(1)),t}get default_chat_template(){return super.default_chat_template.replaceAll("USE_DEFAULT_PROMPT",this.use_default_system_prompt?"true":"false").replaceAll("DEFAULT_SYSTEM_MESSAGE",this.DEFAULT_SYSTEM_PROMPT.replaceAll("\n","\\n").replaceAll("'","\\'"))}}class Be extends $e{}class ze extends fe{}class Re extends fe{}class je extends fe{}class Ve extends fe{}class Ue extends fe{}class Ge extends fe{}class qe extends fe{_default_chat_template="{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}"}class We extends fe{}function He(e,t,n,r){if(!("language_codes"in e)||!Array.isArray(e.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in e&&e.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in e)||"function"!=typeof e.lang_to_token)throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const o=r.src_lang,i=r.tgt_lang;if(!e.language_codes.includes(i))throw new Error(`Target language code "${i}" is not valid. Must be one of: {${e.language_codes.join(", ")}}`);if(void 0!==o){if(!e.language_codes.includes(o))throw new Error(`Source language code "${o}" is not valid. Must be one of: {${e.language_codes.join(", ")}}`);for(const t of e.post_processor.config.single)if("SpecialToken"in t&&e.languageRegex.test(t.SpecialToken.id)){t.SpecialToken.id=e.lang_to_token(o);break}}return r.forced_bos_token_id=e.model.convert_tokens_to_ids([e.lang_to_token(i)])[0],e._call(t,n)}class Xe extends fe{constructor(e,t){super(e,t),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter((e=>this.languageRegex.test(e))),this.lang_to_token=e=>e}_build_translation_inputs(e,t,n){return He(this,e,t,n)}}class Qe extends fe{constructor(e,t){super(e,t),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter((e=>this.languageRegex.test(e))).map((e=>e.slice(2,-2))),this.lang_to_token=e=>`__${e}__`}_build_translation_inputs(e,t,n){return He(this,e,t,n)}}const Ye=[["en","english"],["zh","chinese"],["de","german"],["es","spanish"],["ru","russian"],["ko","korean"],["fr","french"],["ja","japanese"],["pt","portuguese"],["tr","turkish"],["pl","polish"],["ca","catalan"],["nl","dutch"],["ar","arabic"],["sv","swedish"],["it","italian"],["id","indonesian"],["hi","hindi"],["fi","finnish"],["vi","vietnamese"],["he","hebrew"],["uk","ukrainian"],["el","greek"],["ms","malay"],["cs","czech"],["ro","romanian"],["da","danish"],["hu","hungarian"],["ta","tamil"],["no","norwegian"],["th","thai"],["ur","urdu"],["hr","croatian"],["bg","bulgarian"],["lt","lithuanian"],["la","latin"],["mi","maori"],["ml","malayalam"],["cy","welsh"],["sk","slovak"],["te","telugu"],["fa","persian"],["lv","latvian"],["bn","bengali"],["sr","serbian"],["az","azerbaijani"],["sl","slovenian"],["kn","kannada"],["et","estonian"],["mk","macedonian"],["br","breton"],["eu","basque"],["is","icelandic"],["hy","armenian"],["ne","nepali"],["mn","mongolian"],["bs","bosnian"],["kk","kazakh"],["sq","albanian"],["sw","swahili"],["gl","galician"],["mr","marathi"],["pa","punjabi"],["si","sinhala"],["km","khmer"],["sn","shona"],["yo","yoruba"],["so","somali"],["af","afrikaans"],["oc","occitan"],["ka","georgian"],["be","belarusian"],["tg","tajik"],["sd","sindhi"],["gu","gujarati"],["am","amharic"],["yi","yiddish"],["lo","lao"],["uz","uzbek"],["fo","faroese"],["ht","haitian creole"],["ps","pashto"],["tk","turkmen"],["nn","nynorsk"],["mt","maltese"],["sa","sanskrit"],["lb","luxembourgish"],["my","myanmar"],["bo","tibetan"],["tl","tagalog"],["mg","malagasy"],["as","assamese"],["tt","tatar"],["haw","hawaiian"],["ln","lingala"],["ha","hausa"],["ba","bashkir"],["jw","javanese"],["su","sundanese"]],Ke=new Map(Ye),Ze=new Map([...Ye.map((([e,t])=>[t,e])),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);class Je extends fe{_default_chat_template='{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}';_decode_asr(e,{return_timestamps:t=!1,return_language:n=!1,time_precision:r=null,force_full_sequences:o=!0}={}){if(null===r)throw Error("Must specify time_precision");let s=null;const a="word"===t;function l(){return{language:s,timestamp:[null,null],text:""}}const c=[];let u=l(),p=0;const d=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let _=[],h=[],f=!1,m=null;const g=new Set(this.all_special_ids);for(const n of e){const e=n.tokens,o=a?n.token_timestamps:null;let b=null,w=d;if("stride"in n){const[t,o,i]=n.stride;if(p-=o,m=t-i,o&&(w=o/r+d),i)for(let t=e.length-1;t>=0;--t){const n=e[t];if(n>=d){if(null!==b&&(n-d)*r<m)break;b=n}}}let x=[],y=[];for(let n=0;n<e.length;++n){const m=e[n];if(g.has(m)){const e=this.decode([m]),n=Ke.get(e.slice(2,-2));if(void 0!==n){if(null!==s&&n!==s&&!t){_.push(x);const e=this.findLongestCommonSequence(_)[0],t=this.decode(e);u.text=t,c.push(u),_=[],x=[],u=l()}s=u.language=n}}else if(m>=d){const e=(m-d)*r+p,t=(0,i.round)(e,2);if(null!==b&&m>=b)f=!0;else if(f||_.length>0&&m<w)f=!1;else if(null===u.timestamp[0])u.timestamp[0]=t;else if(t===u.timestamp[0]);else{u.timestamp[1]=t,_.push(x),a&&h.push(y);const[e,n]=this.findLongestCommonSequence(_,h),r=this.decode(e);u.text=r,a&&(u.words=this.collateWordTimestamps(e,n,s)),c.push(u),_=[],x=[],h=[],y=[],u=l()}}else if(x.push(m),a){let e,t=(0,i.round)(o[n]+p,2);e=n+1<o.length?(0,i.round)(o[n+1]+p,2):null,y.push([t,e])}}if("stride"in n){const[e,t,r]=n.stride;p+=e-r}x.length>0?(_.push(x),a&&h.push(y)):_.every((e=>0===e.length))&&(u=l(),_=[],x=[],h=[],y=[])}if(_.length>0){if(o&&t)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[e,n]=this.findLongestCommonSequence(_,h),r=this.decode(e);u.text=r,a&&(u.words=this.collateWordTimestamps(e,n,s)),c.push(u)}let b=Object.create(null);const w=c.map((e=>e.text)).join("");if(t||n){for(let e=0;e<c.length;++e){const r=c[e];t||delete r.timestamp,n||delete r.language}if(a){const e=[];for(const t of c)for(const n of t.words)e.push(n);b={chunks:e}}else b={chunks:c}}return[w,b]}findLongestCommonSequence(e,t=null){let n=e[0],r=n.length,o=[];const i=Array.isArray(t)&&t.length>0;let s=i?[]:null,a=i?t[0]:null;for(let l=1;l<e.length;++l){const c=e[l];let u=0,p=[r,r,0,0];const d=c.length;for(let e=1;e<r+d;++e){const t=e/1e4,o=Math.max(0,r-e),i=Math.min(r,r+d-e),s=n.slice(o,i),a=Math.max(0,e-r),l=Math.min(d,e),_=c.slice(a,l);if(s.length!==_.length)throw new Error("There is a bug within whisper `decode_asr` function, please report it. Dropping to prevent bad inference.");const h=s.filter(((e,t)=>e===_[t])).length,f=h/e+t;h>1&&f>u&&(u=f,p=[o,i,a,l])}const[_,h,f,m]=p,g=Math.floor((h+_)/2),b=Math.floor((m+f)/2);o.push(...n.slice(0,g)),n=c.slice(b),r=n.length,i&&(s.push(...a.slice(0,g)),a=t[l].slice(b))}return o.push(...n),i?(s.push(...a),[o,s]):[o,[]]}collateWordTimestamps(e,t,n){const[r,o,i]=this.combineTokensIntoWords(e,n),s=[];for(let e=0;e<r.length;++e){const n=i[e];s.push({text:r[e],timestamp:[t[n.at(0)][0],t[n.at(-1)][1]]})}return s}combineTokensIntoWords(e,t,n="\"'“¡¿([{-",r="\"'.。,，!！?？:：”)]}、"){let o,i,s;return["chinese","japanese","thai","lao","myanmar"].includes(t=t??"english")?[o,i,s]=this.splitTokensOnUnicode(e):[o,i,s]=this.splitTokensOnSpaces(e),this.mergePunctuations(o,i,s,n,r)}decode(e,t){let n;return t&&t.decode_with_timestamps?(e instanceof s.Tensor&&(e=d(e)),n=this.decodeWithTimestamps(e,t)):n=super.decode(e,t),n}decodeWithTimestamps(e,t){const n=t?.time_precision??.02,r=Array.from(this.all_special_ids).at(-1)+1;let o=[[]];for(const t of e)if(t>=r){const e=(0,i.round)((t-r)*n,2);o.push(`<|${e}|>`),o.push([])}else o[o.length-1].push(t);return o=o.map((e=>"string"==typeof e?e:super.decode(e,t))),o.join("")}splitTokensOnUnicode(e){const t=this.decode(e,{decode_with_timestamps:!0}),n=[],r=[],o=[];let i=[],s=[],a=0;for(let l=0;l<e.length;++l){const c=e[l];i.push(c),s.push(l);const u=this.decode(i,{decode_with_timestamps:!0});u.includes("�")&&"�"!==t[a+u.indexOf("�")]||(n.push(u),r.push(i),o.push(s),i=[],s=[],a+=u.length)}return[n,r,o]}splitTokensOnSpaces(e){const[t,n,r]=this.splitTokensOnUnicode(e),o=[],i=[],s=[],a=new RegExp(`^[${f}]$`,"gu");for(let e=0;e<t.length;++e){const l=t[e],c=n[e],u=r[e],p=c[0]>=this.model.tokens_to_ids.get("<|endoftext|>"),d=l.startsWith(" "),_=l.trim(),h=a.test(_);if(p||d||h||0===o.length)o.push(l),i.push(c),s.push(u);else{const e=o.length-1;o[e]+=l,i[e].push(...c),s[e].push(...u)}}return[o,i,s]}mergePunctuations(e,t,n,o,i){const s=structuredClone(e),a=structuredClone(t),l=structuredClone(n);let c=s.length-2,u=s.length-1;for(;c>=0;)s[c].startsWith(" ")&&o.includes(s[c].trim())?(s[u]=s[c]+s[u],a[u]=(0,r.mergeArrays)(a[c],a[u]),l[u]=(0,r.mergeArrays)(l[c],l[u]),s[c]="",a[c]=[],l[c]=[]):u=c,--c;for(c=0,u=1;u<s.length;)!s[c].endsWith(" ")&&i.includes(s[u])?(s[c]+=s[u],a[c]=(0,r.mergeArrays)(a[c],a[u]),l[c]=(0,r.mergeArrays)(l[c],l[u]),s[u]="",a[u]=[],l[u]=[]):c=u,++u;return[s.filter((e=>e)),a.filter((e=>e.length>0)),l.filter((e=>e.length>0))]}get_decoder_prompt_ids({language:e=null,task:t=null,no_timestamps:n=!0}={}){const r=[];if(e){e=e.toLowerCase();let t=Ze.get(e);if(void 0===t){if(!Ke.has(e)){const t=2===e.length?Ke.keys():Ke.values();throw new Error(`Language "${e}" is not supported. Must be one of: ${JSON.stringify(t)}`)}t=e}const n=this.model.tokens_to_ids.get(`<|${t}|>`);if(void 0===n)throw new Error(`Unable to find language "${t}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);r.push(n)}else r.push(null);if(t){if("transcribe"!==(t=t.toLowerCase())&&"translate"!==t)throw new Error(`Task "${t}" is not supported. Must be one of: ["transcribe", "translate"]`);const e=this.model.tokens_to_ids.get(`<|${t}|>`);if(void 0===e)throw new Error(`Unable to find task "${t}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);r.push(e)}else r.push(null);if(n){const e=this.model.tokens_to_ids.get("<|notimestamps|>");if(void 0===e)throw new Error('Unable to find "<|notimestamps|>" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.');r.push(e)}return r.map(((e,t)=>[t+1,e])).filter((e=>null!==e[1]))}}class et extends fe{}class tt extends fe{}class nt extends fe{}class rt extends fe{constructor(e,t){super(e,t),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter((e=>this.languageRegex.test(e))),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(e){if(null===e)return null;const[t,...n]=e.trim().split(this.languageRegex);if(0===n.length)return super._encode_text(t);if(2===n.length){const[e,t]=n;return this.supported_language_codes.includes(e)||console.warn(`Unsupported language code "${e}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),(0,r.mergeArrays)([e],super._encode_text(t))}}}class ot extends fe{}class it extends fe{_default_chat_template="{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ '  ' }}{% endif %}{% endfor %}{{ eos_token }}"}class st extends it{}class at extends fe{}class lt extends fe{}class ct extends fe{constructor(e,t){super(e,t),this.decoder=new oe({})}}class ut extends fe{}class pt{static TOKENIZER_CLASS_MAPPING={T5Tokenizer:Fe,DistilBertTokenizer:Me,CamembertTokenizer:Se,DebertaTokenizer:xe,DebertaV2Tokenizer:ye,BertTokenizer:me,HerbertTokenizer:Te,ConvBertTokenizer:ve,RoFormerTokenizer:ke,XLMTokenizer:Pe,ElectraTokenizer:Ae,MobileBertTokenizer:be,SqueezeBertTokenizer:we,AlbertTokenizer:ge,GPT2Tokenizer:Ce,BartTokenizer:Ee,MBartTokenizer:Oe,MBart50Tokenizer:Ie,RobertaTokenizer:De,WhisperTokenizer:Je,CodeGenTokenizer:et,CLIPTokenizer:tt,SiglipTokenizer:nt,MarianTokenizer:rt,BloomTokenizer:Le,NllbTokenizer:Xe,M2M100Tokenizer:Qe,LlamaTokenizer:$e,CodeLlamaTokenizer:Be,XLMRobertaTokenizer:ze,MPNetTokenizer:Re,FalconTokenizer:je,GPTNeoXTokenizer:Ve,EsmTokenizer:Ue,Wav2Vec2CTCTokenizer:ot,BlenderbotTokenizer:it,BlenderbotSmallTokenizer:st,SpeechT5Tokenizer:at,NougatTokenizer:lt,VitsTokenizer:ct,Qwen2Tokenizer:Ge,GemmaTokenizer:qe,Grok1Tokenizer:We,CohereTokenizer:ut,PreTrainedTokenizer:fe};static async from_pretrained(e,{quantized:t=!0,progress_callback:n=null,config:r=null,cache_dir:o=null,local_files_only:i=!1,revision:s="main",legacy:a=null}={}){const[l,u]=await c(e,{quantized:t,progress_callback:n,config:r,cache_dir:o,local_files_only:i,revision:s,legacy:a}),p=u.tokenizer_class?.replace(/Fast$/,"")??"PreTrainedTokenizer";let d=this.TOKENIZER_CLASS_MAPPING[p];return d||(console.warn(`Unknown tokenizer class "${p}", attempting to construct from base class.`),d=fe),new d(l,u)}}},"./src/transformers.js":
+/*!*****************************!*\
+  !*** ./src/transformers.js ***!
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+/*!*********************************!*\
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+  \*********************************/(e,t,n)=>{n.r(t),n.d(t,{ForceTokensLogitsProcessor:()=>a,ForcedBOSTokenLogitsProcessor:()=>l,ForcedEOSTokenLogitsProcessor:()=>c,GenerationConfig:()=>g,LogitsProcessor:()=>s,LogitsProcessorList:()=>i,MinLengthLogitsProcessor:()=>h,MinNewTokensLengthLogitsProcessor:()=>f,NoBadWordsLogitsProcessor:()=>m,NoRepeatNGramLogitsProcessor:()=>d,RepetitionPenaltyLogitsProcessor:()=>_,Sampler:()=>b,SuppressTokensAtBeginLogitsProcessor:()=>u,WhisperTimeStampLogitsProcessor:()=>p});n(/*! ./tensor.js */"./src/utils/tensor.js");var r=n(/*! ./core.js */"./src/utils/core.js"),o=n(/*! ./maths.js */"./src/utils/maths.js");class i extends r.Callable{constructor(){super(),this.processors=[]}push(e){this.processors.push(e)}extend(e){this.processors.push(...e)}_call(e,t){for(let n of t)this.processors.forEach((t=>t(e,n)))}[Symbol.iterator](){return this.processors.values()}}class s extends r.Callable{_call(e,t){throw Error("`_call` should be implemented in a 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+/*!****************************!*\
+  !*** ./src/utils/image.js ***!
+  \****************************/(e,t,n)=>{n.r(t),n.d(t,{RawImage:()=>h});var r=n(/*! ./hub.js */"./src/utils/hub.js"),o=n(/*! ../env.js */"./src/env.js"),i=n(/*! ./tensor.js */"./src/utils/tensor.js"),s=n(/*! sharp */"?2b25");const a="undefined"!=typeof self,l=a&&"DedicatedWorkerGlobalScope"===self.constructor.name;let c,u,p;if(a)c=(e,t)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this browser.");return new self.OffscreenCanvas(e,t)},p=self.createImageBitmap,u=self.ImageData;else{if(!s)throw new Error("Unable to load image processing library.");p=async e=>{const t=(await e.metadata()).channels;let{data:n,info:r}=await e.rotate().raw().toBuffer({resolveWithObject:!0});const o=new h(new Uint8ClampedArray(n),r.width,r.height,r.channels);return void 0!==t&&t!==r.channels&&o.convert(t),o}}const d={0:"nearest",1:"lanczos",2:"bilinear",3:"bicubic",4:"box",5:"hamming"},_=new Map([["png","image/png"],["jpg","image/jpeg"],["jpeg","image/jpeg"],["gif","image/gif"]]);class h{constructor(e,t,n,r){this.data=e,this.width=t,this.height=n,this.channels=r}get size(){return[this.width,this.height]}static async read(e){if(e instanceof h)return e;if("string"==typeof e||e instanceof URL)return await this.fromURL(e);throw new Error("Unsupported input type: "+typeof e)}static async fromURL(e){let t=await(0,r.getFile)(e);if(200!==t.status)throw new Error(`Unable to read image from "${e}" (${t.status} ${t.statusText})`);let n=await t.blob();return this.fromBlob(n)}static async fromBlob(e){if(a){let t=await p(e);const n=c(t.width,t.height).getContext("2d");return n.drawImage(t,0,0),new this(n.getImageData(0,0,t.width,t.height).data,t.width,t.height,4)}{let t=s(await e.arrayBuffer());return await p(t)}}static fromTensor(e,t="CHW"){if(3!==e.dims.length)throw new Error(`Tensor should have 3 dimensions, but has ${e.dims.length} dimensions.`);if("CHW"===t)e=e.transpose(1,2,0);else if("HWC"!==t)throw new Error(`Unsupported channel format: ${t}`);if(!(e.data instanceof Uint8ClampedArray||e.data instanceof Uint8Array))throw new Error(`Unsupported tensor type: ${e.type}`);switch(e.dims[2]){case 1:case 2:case 3:case 4:return new h(e.data,e.dims[1],e.dims[0],e.dims[2]);default:throw new Error(`Unsupported number of channels: ${e.dims[2]}`)}}grayscale(){if(1===this.channels)return this;let e=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let t=0,n=0;t<this.data.length;t+=this.channels){const r=this.data[t],o=this.data[t+1],i=this.data[t+2];e[n++]=Math.round(.2989*r+.587*o+.114*i)}break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(e,this.width,this.height,1)}rgb(){if(3===this.channels)return this;let e=new Uint8ClampedArray(this.width*this.height*3);switch(this.channels){case 1:for(let t=0,n=0;t<this.data.length;++t)e[n++]=this.data[t],e[n++]=this.data[t],e[n++]=this.data[t];break;case 4:for(let t=0,n=0;t<this.data.length;t+=4)e[n++]=this.data[t],e[n++]=this.data[t+1],e[n++]=this.data[t+2];break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(e,this.width,this.height,3)}rgba(){if(4===this.channels)return this;let e=new Uint8ClampedArray(this.width*this.height*4);switch(this.channels){case 1:for(let t=0,n=0;t<this.data.length;++t)e[n++]=this.data[t],e[n++]=this.data[t],e[n++]=this.data[t],e[n++]=255;break;case 3:for(let t=0,n=0;t<this.data.length;t+=3)e[n++]=this.data[t],e[n++]=this.data[t+1],e[n++]=this.data[t+2],e[n++]=255;break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(e,this.width,this.height,4)}async resize(e,t,{resample:n=2}={}){let r=d[n]??n;if(a){let n=this.channels,r=this.toCanvas();const o=c(e,t).getContext("2d");return o.drawImage(r,0,0,e,t),new h(o.getImageData(0,0,e,t).data,e,t,4).convert(n)}{let n=this.toSharp();switch(r){case"box":case"hamming":"box"!==r&&"hamming"!==r||(console.warn(`Resampling method ${r} is not yet supported. Using bilinear instead.`),r="bilinear");case"nearest":case"bilinear":case"bicubic":n=n.affine([e/this.width,0,0,t/this.height],{interpolator:r});break;case"lanczos":n=n.resize({width:e,height:t,fit:"fill",kernel:"lanczos3"});break;default:throw new Error(`Resampling method ${r} is not supported.`)}return await p(n)}}async pad([e,t,n,r]){if(e=Math.max(e,0),t=Math.max(t,0),n=Math.max(n,0),r=Math.max(r,0),0===e&&0===t&&0===n&&0===r)return this;if(a){let o=this.channels,i=this.toCanvas(),s=this.width+e+t,a=this.height+n+r;const l=c(s,a).getContext("2d");return l.drawImage(i,0,0,this.width,this.height,e,n,s,a),new h(l.getImageData(0,0,s,a).data,s,a,4).convert(o)}{let o=this.toSharp().extend({left:e,right:t,top:n,bottom:r});return await p(o)}}async crop([e,t,n,r]){if(e=Math.max(e,0),t=Math.max(t,0),n=Math.min(n,this.width-1),r=Math.min(r,this.height-1),0===e&&0===t&&n===this.width-1&&r===this.height-1)return this;const o=n-e+1,i=r-t+1;if(a){const n=this.channels,r=this.toCanvas(),s=c(o,i).getContext("2d");s.drawImage(r,e,t,o,i,0,0,o,i);return new h(s.getImageData(0,0,o,i).data,o,i,4).convert(n)}{const n=this.toSharp().extract({left:e,top:t,width:o,height:i});return await p(n)}}async center_crop(e,t){if(this.width===e&&this.height===t)return this;let n=(this.width-e)/2,r=(this.height-t)/2;if(a){let o=this.channels,i=this.toCanvas();const s=c(e,t).getContext("2d");let a=0,l=0,u=0,p=0;return n>=0?a=n:u=-n,r>=0?l=r:p=-r,s.drawImage(i,a,l,e,t,u,p,e,t),new h(s.getImageData(0,0,e,t).data,e,t,4).convert(o)}{let o=this.toSharp();if(n>=0&&r>=0)o=o.extract({left:Math.floor(n),top:Math.floor(r),width:e,height:t});else if(n<=0&&r<=0){let i=Math.floor(-r),s=Math.floor(-n);o=o.extend({top:i,left:s,right:e-this.width-s,bottom:t-this.height-i})}else{let i=[0,0],s=0;r<0?(i[0]=Math.floor(-r),i[1]=t-this.height-i[0]):s=Math.floor(r);let a=[0,0],l=0;n<0?(a[0]=Math.floor(-n),a[1]=e-this.width-a[0]):l=Math.floor(n),o=o.extend({top:i[0],bottom:i[1],left:a[0],right:a[1]}).extract({left:l,top:s,width:e,height:t})}return await p(o)}}async toBlob(e="image/png",t=1){if(!a)throw new Error("toBlob() is only supported in browser environments.");const n=this.toCanvas();return await n.convertToBlob({type:e,quality:t})}toTensor(e="CHW"){let t=new i.Tensor("uint8",new Uint8Array(this.data),[this.height,this.width,this.channels]);if("HWC"===e);else{if("CHW"!==e)throw new Error(`Unsupported channel format: ${e}`);t=t.permute(2,0,1)}return t}toCanvas(){if(!a)throw new Error("toCanvas() is only supported in browser environments.");let e=this.clone().rgba(),t=c(e.width,e.height),n=new u(e.data,e.width,e.height);return t.getContext("2d").putImageData(n,0,0),t}_update(e,t,n,r=null){return this.data=e,this.width=t,this.height=n,null!==r&&(this.channels=r),this}clone(){return new h(this.data.slice(),this.width,this.height,this.channels)}convert(e){if(this.channels===e)return this;switch(e){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(e){if(!a){if(o.env.useFS){const t=this.toSharp();return await t.toFile(e)}throw new Error("Unable to save the image because filesystem is disabled in this environment.")}{if(l)throw new Error("Unable to save an image from a Web Worker.");const t=e.split(".").pop().toLowerCase(),n=_.get(t)??"image/png",r=await this.toBlob(n),o=URL.createObjectURL(r),i=document.createElement("a");i.href=o,i.download=e,i.click(),i.remove()}}toSharp(){if(a)throw new Error("toSharp() is only supported in server-side environments.");return s(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}}},"./src/utils/maths.js":
+/*!****************************!*\
+  !*** ./src/utils/maths.js ***!
+  \****************************/(e,t,n)=>{function r(e,[t,n,r],[o,i],s="bilinear",a=!1){const l=i/r,c=o/n,u=new e.constructor(o*i*t),p=n*r,d=o*i;for(let s=0;s<o;++s)for(let o=0;o<i;++o){const a=s*i+o,_=(o+.5)/l-.5,h=(s+.5)/c-.5;let f=Math.floor(_),m=Math.floor(h);const g=Math.min(f+1,r-1),b=Math.min(m+1,n-1);f=Math.max(f,0),m=Math.max(m,0);const w=_-f,x=h-m,y=(1-w)*(1-x),T=w*(1-x),v=(1-w)*x,k=w*x,M=m*r,S=b*r,P=M+f,A=M+g,F=S+f,C=S+g;for(let n=0;n<t;++n){const t=n*p;u[n*d+a]=y*e[t+P]+T*e[t+A]+v*e[t+F]+k*e[t+C]}}return u}function o(e,t,n){const r=new Array(n.length),o=new Array(n.length);for(let e=n.length-1,i=1;e>=0;--e)o[e]=i,r[e]=t[n[e]],i*=r[e];const i=n.map(((e,t)=>o[n.indexOf(t)])),s=new e.constructor(e.length);for(let n=0;n<e.length;++n){let r=0;for(let e=t.length-1,o=n;e>=0;--e)r+=o%t[e]*i[e],o=Math.floor(o/t[e]);s[r]=e[n]}return[s,r]}function i(e){const t=d(e)[0],n=e.map((e=>Math.exp(e-t))),r=n.reduce(((e,t)=>e+t),0);return n.map((e=>e/r))}function s(e){return 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i=e[r],s=e[r+1],a=e[r+o],l=e[r+o+1];t[n]=i+a,t[n+1]=s+l,t[n+2]=i-a,t[n+3]=s-l}_singleTransform4(e,t,n,r,o,i){const s=2*o,a=3*o,l=e[r],c=e[r+1],u=e[r+o],p=e[r+o+1],d=e[r+s],_=e[r+s+1],h=e[r+a],f=e[r+a+1],m=l+d,g=c+_,b=l-d,w=c-_,x=u+h,y=p+f,T=i*(u-h),v=i*(p-f);t[n]=m+x,t[n+1]=g+y,t[n+2]=b+v,t[n+3]=w-T,t[n+4]=m-x,t[n+5]=g-y,t[n+6]=b-v,t[n+7]=w+T}_realTransform4(e,t,n){const r=this._csize;let o,i,s=1<<this._width,a=r/s<<1;const l=this._bitrev;if(4===a)for(o=0,i=0;o<r;o+=a,++i){const n=l[i];this._singleRealTransform2(t,e,o,n>>>1,s>>>1)}else for(o=0,i=0;o<r;o+=a,++i){const r=l[i];this._singleRealTransform4(t,e,o,r>>>1,s>>>1,n)}const c=this.table;for(s>>=2;s>=2;s>>=2){a=r/s<<1;const t=a>>>1,i=t>>>1,l=i>>>1;for(o=0;o<r;o+=a)for(let r=0,a=0;r<=l;r+=2,a+=s){const s=o+r,u=s+i,p=u+i,d=p+i,_=e[s],h=e[s+1],f=e[u],m=e[u+1],g=e[p],b=e[p+1],w=e[d],x=e[d+1],y=_,T=h,v=c[a],k=n*c[a+1],M=f*v-m*k,S=f*k+m*v,P=c[2*a],A=n*c[2*a+1],F=g*P-b*A,C=g*A+b*P,E=c[3*a],O=n*c[3*a+1],I=w*E-x*O,D=w*O+x*E,L=y+F,N=T+C,$=y-F,B=T-C,z=M+I,R=S+D,j=n*(M-I),V=n*(S-D);if(e[s]=L+z,e[s+1]=N+R,e[u]=$+V,e[u+1]=B-j,0===r){e[p]=L-z,e[p+1]=N-R;continue}if(r===l)continue;const U=o+i-r,G=o+t-r;e[U]=$-n*V,e[U+1]=-B-n*j,e[G]=L-n*z,e[G+1]=n*R-N}}const u=r>>>1;for(let t=2;t<u;t+=2)e[r-t]=e[t],e[r-t+1]=-e[t+1]}_singleRealTransform2(e,t,n,r,o){const i=e[r],s=e[r+o];t[n]=i+s,t[n+1]=0,t[n+2]=i-s,t[n+3]=0}_singleRealTransform4(e,t,n,r,o,i){const s=2*o,a=3*o,l=e[r],c=e[r+o],u=e[r+s],p=e[r+a],d=l+u,_=l-u,h=c+p,f=i*(c-p);t[n]=d+h,t[n+1]=0,t[n+2]=_,t[n+3]=-f,t[n+4]=d-h,t[n+5]=0,t[n+6]=_,t[n+7]=f}}class f{constructor(e){const t=2*(e-1),n=2*(2*e-1),r=2**Math.ceil(Math.log2(n));this.bufferSize=r,this._a=t;const o=new Float64Array(n),i=new Float64Array(r);this._chirpBuffer=new Float64Array(r),this._buffer1=new Float64Array(r),this._buffer2=new Float64Array(r),this._outBuffer1=new Float64Array(r),this._outBuffer2=new Float64Array(r);const s=-2*Math.PI/e,a=Math.cos(s),l=Math.sin(s);for(let t=0;t<n>>1;++t){const n=(t+1-e)**2/2,r=Math.sqrt(a**2+l**2)**n,s=n*Math.atan2(l,a),c=2*t;o[c]=r*Math.cos(s),o[c+1]=r*Math.sin(s),i[c]=o[c],i[c+1]=-o[c+1]}this._slicedChirpBuffer=o.subarray(t,n),this._f=new h(r>>1),this._f.transform(this._chirpBuffer,i)}_transform(e,t,n){const r=this._buffer1,o=this._buffer2,i=this._outBuffer1,s=this._outBuffer2,a=this._chirpBuffer,l=this._slicedChirpBuffer,c=this._a;if(n)for(let e=0;e<l.length;e+=2){const n=e+1,o=t[e>>1];r[e]=o*l[e],r[n]=o*l[n]}else for(let e=0;e<l.length;e+=2){const n=e+1;r[e]=t[e]*l[e]-t[n]*l[n],r[n]=t[e]*l[n]+t[n]*l[e]}this._f.transform(i,r);for(let e=0;e<a.length;e+=2){const t=e+1;o[e]=i[e]*a[e]-i[t]*a[t],o[t]=i[e]*a[t]+i[t]*a[e]}this._f.inverseTransform(s,o);for(let t=0;t<s.length;t+=2){const n=s[t+c],r=s[t+c+1],o=l[t],i=l[t+1];e[t]=n*o-r*i,e[t+1]=n*i+r*o}}transform(e,t){this._transform(e,t,!1)}realTransform(e,t){this._transform(e,t,!0)}}class m{constructor(e){this.fft_length=e,this.isPowerOfTwo=_(e),this.isPowerOfTwo?(this.fft=new h(e),this.outputBufferSize=2*e):(this.fft=new f(e),this.outputBufferSize=this.fft.bufferSize)}realTransform(e,t){this.fft.realTransform(e,t)}transform(e,t){this.fft.transform(e,t)}}function g(e,t){if(t%2==0||t<=0)throw new Error("Window size must be a positive odd number");const n=new e.constructor(e.length),r=new e.constructor(t),o=Math.floor(t/2);for(let t=0;t<e.length;++t){let i=0;for(let n=-o;n<=o;++n){let o=t+n;o<0?o=Math.abs(o):o>=e.length&&(o=2*(e.length-1)-o),r[i++]=e[o]}r.sort(),n[t]=r[o]}return n}function b(e,t){const n=Math.pow(10,t);return Math.round(e*n)/n}function w(e){const t=Math.round(e);return Math.abs(e)%1==.5?t%2==0?t:t-1:t}},"./src/utils/tensor.js":
+/*!*****************************!*\
+  !*** ./src/utils/tensor.js ***!
+  \*****************************/(e,t,n)=>{n.r(t),n.d(t,{Tensor:()=>a,cat:()=>f,dynamicTimeWarping:()=>w,interpolate:()=>c,layer_norm:()=>p,mean:()=>b,mean_pooling:()=>u,ones:()=>x,ones_like:()=>y,permute:()=>l,quantize_embeddings:()=>T,stack:()=>m,std_mean:()=>g});var r=n(/*! ../backends/onnx.js */"./src/backends/onnx.js"),o=n(/*! ./maths.js */"./src/utils/maths.js");const i=Object.freeze({float32:Float32Array,float64:Float64Array,string:Array,int8:Int8Array,uint8:Uint8Array,int16:Int16Array,uint16:Uint16Array,int32:Int32Array,uint32:Uint32Array,int64:BigInt64Array,uint64:BigUint64Array,bool:Uint8Array}),s=r.ONNX.Tensor;class a{dims;type;data;size;constructor(...e){return e[0]instanceof s?Object.assign(this,e[0]):Object.assign(this,new s(e[0],e[1],e[2])),new Proxy(this,{get:(e,t)=>{if("string"==typeof t){let n=Number(t);if(Number.isInteger(n))return e._getitem(n)}return e[t]},set:(e,t,n)=>e[t]=n})}*[Symbol.iterator](){const[e,...t]=this.dims;if(t.length>0){const 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XLMWithLMHeadModel,__webpack_exports__XVectorOutput as XVectorOutput,__webpack_exports__YolosFeatureExtractor as YolosFeatureExtractor,__webpack_exports__YolosForObjectDetection as YolosForObjectDetection,__webpack_exports__YolosModel as YolosModel,__webpack_exports__YolosObjectDetectionOutput as YolosObjectDetectionOutput,__webpack_exports__YolosPreTrainedModel as YolosPreTrainedModel,__webpack_exports__ZeroShotAudioClassificationPipeline as ZeroShotAudioClassificationPipeline,__webpack_exports__ZeroShotClassificationPipeline as ZeroShotClassificationPipeline,__webpack_exports__ZeroShotImageClassificationPipeline as ZeroShotImageClassificationPipeline,__webpack_exports__ZeroShotObjectDetectionPipeline as ZeroShotObjectDetectionPipeline,__webpack_exports__bankers_round as bankers_round,__webpack_exports__cat as cat,__webpack_exports__cos_sim as cos_sim,__webpack_exports__dot as dot,__webpack_exports__dynamicTimeWarping as dynamicTimeWarping,__webpack_exports__env as env,__webpack_exports__getTopItems as getTopItems,__webpack_exports__hanning as hanning,__webpack_exports__interpolate as interpolate,__webpack_exports__interpolate_data as interpolate_data,__webpack_exports__layer_norm as layer_norm,__webpack_exports__log_softmax as log_softmax,__webpack_exports__magnitude as magnitude,__webpack_exports__max as max,__webpack_exports__mean as mean,__webpack_exports__mean_pooling as mean_pooling,__webpack_exports__medianFilter as medianFilter,__webpack_exports__mel_filter_bank as mel_filter_bank,__webpack_exports__min as min,__webpack_exports__ones as ones,__webpack_exports__ones_like as ones_like,__webpack_exports__permute as permute,__webpack_exports__permute_data as permute_data,__webpack_exports__pipeline as pipeline,__webpack_exports__quantize_embeddings as quantize_embeddings,__webpack_exports__read_audio as read_audio,__webpack_exports__round as round,__webpack_exports__softmax as softmax,__webpack_exports__spectrogram as spectrogram,__webpack_exports__stack as stack,__webpack_exports__std_mean as std_mean,__webpack_exports__window_function as window_function};
+//# sourceMappingURL=transformers.min.js.map
\ No newline at end of file
diff --git a/modules/ui.js b/modules/ui.js
new file mode 100644
index 0000000000000000000000000000000000000000..43050d4cf481a7094843919ba8296710750bdbf2
--- /dev/null
+++ b/modules/ui.js
@@ -0,0 +1,109 @@
+import { highlightText } from "./highlightText.js";
+import { submitFeedback } from "./feedback.js";
+
+/** handle what needs to be displayed in chat container */
+export function appendMessage(content, className, linkId = null, akkordeonId = null, bestToken = null, query = null) {
+  const messageContainer = document.createElement('div');
+  
+  if (className === 'user-message') {
+
+    const messageDiv = document.createElement('div');
+    messageDiv.textContent = content;
+    messageDiv.className = className;
+    messageContainer.appendChild(messageDiv);
+
+  } else {
+
+    /** drawing what chat response looks like */
+    messageContainer.className = 'bot-message-container';
+
+    const numberBox = document.createElement('div');
+    numberBox.textContent = "⦿";
+    numberBox.className = 'number-box';
+    
+    const messageDiv = document.createElement('div');
+    messageDiv.textContent = content;
+    messageDiv.className = className;
+    
+    const panelDiv = document.createElement('div');
+    panelDiv.textContent = '➜';
+    panelDiv.className = 'info-panel';
+    panelDiv.onclick = function () {
+
+      linkToPanel(linkId, akkordeonId, bestToken);
+    };
+
+    const feedbackContainer = document.createElement('div');
+    feedbackContainer.className = 'feedback-container';
+    
+    const plusButton = document.createElement('button');
+    plusButton.innerHTML = '+';
+    plusButton.className = 'feedback-button thumbs-up';
+    plusButton.onclick = function () {
+      
+      submitFeedback(query, bestToken, 'up');
+    };
+    
+    const minusButton = document.createElement('button');
+    minusButton.innerHTML = '-';
+    minusButton.className = 'feedback-button thumbs-down';
+    minusButton.onclick = function () {
+      
+      submitFeedback(query, bestToken, 'down');
+    };
+    
+    messageContainer.appendChild(numberBox);
+    messageContainer.appendChild(messageDiv);
+    messageContainer.appendChild(panelDiv);
+
+    feedbackContainer.appendChild(plusButton);
+    feedbackContainer.appendChild(minusButton);
+    messageContainer.appendChild(feedbackContainer);
+  }
+  
+  const messagesDiv = document.getElementById('messages');
+  messagesDiv.appendChild(messageContainer);
+  messagesDiv.scrollTop = messagesDiv.scrollHeight;
+}
+
+/** gets query from input field and performs search*/
+export function sendMessage(worker) {
+
+  const userInput = document.getElementById('user-input');
+  const message = userInput.value.trim();
+
+
+  if (message !== "") {
+    appendMessage(message, 'user-message');
+    userInput.value = '';
+    worker.postMessage({
+      act: 'semanticSearch',
+      query: message,
+    });
+  }
+}
+
+/** scrolls to the relavant panel and shows hidden answer text */
+export function linkToPanel(buttonId, akkordeonId, bestToken) {
+  
+  const selector = (window !== window.parent.parent) ? window.parent.parent.document : document;
+  
+  const parentContainer = selector.querySelector(`#${akkordeonId}`);
+  const panelButton = parentContainer.querySelector(`#${buttonId}`);
+  if (panelButton.classList.contains('collapsed')) {
+    panelButton.click();
+  }
+  
+  panelButton.scrollIntoView({ behavior: 'smooth', block: 'center' });
+  /** might leave highlighing out; works, but highlights are persistent until DOM is reloaded */
+  setTimeout(() => { highlightText(bestToken); }, 1000);
+}
+
+/** lets results in results iframe scroll to right panel */
+window.linkToPanel = linkToPanel;
+
+
+
+
+
+
diff --git a/modules/workerInterface.js b/modules/workerInterface.js
new file mode 100644
index 0000000000000000000000000000000000000000..9144b303d5e32605ff04da38a39c72e7a8e3a6a2
--- /dev/null
+++ b/modules/workerInterface.js
@@ -0,0 +1,59 @@
+import { appendMessage } from './ui.js';
+
+
+let processQueryCache = null;
+
+export function handleWorker(events){
+
+    const { act, results, embeddingCache: updatedCache, tokenEmbeddingCache: updatedTokenCache, query } = events.data;
+      
+      switch (act) {
+        case 'initialized':
+          localStorage.setItem('largeEmbedding', JSON.stringify(updatedCache));
+          
+          break;
+          
+        case 'tokeninit':
+          localStorage.setItem('smallEmbedding', JSON.stringify(updatedTokenCache));
+          
+          break;
+    
+        case 'searchResults':
+          /** pass our three results to ui so they can be displayed and worked with in chat */
+          results.forEach(result => {
+            appendMessage(
+              result.question,
+              'bot-message',
+              result.buttonId,
+              result.akkordeonId,
+              result.bestToken,
+              query
+            );
+          });
+          break;
+    
+        case 'topResults':
+          /** show results live in result iframe */
+          if (processQueryCache) {
+            const outputs = results.slice(0, 3).map(result => ({
+              question: result.question,
+              bestToken: result.bestToken,
+              buttonId: result.buttonId,
+              akkordeonId: result.akkordeonId,
+            }));
+
+            processQueryCache(outputs);
+            processQueryCache = null;
+          }
+          break;
+      }
+}
+
+export function processQuery(query, worker, cache) {
+  processQueryCache = cache;
+  worker.postMessage({
+    act: 'resultsSemantic',
+    query: query,
+  });
+}
+