diff --git a/tda/README.md b/tda/README.md
index b6db66cf442b4f7a87a601ca3bd5f3eac1b7c552..f4020eb0db8e7cda367d00702a9276e061068b2c 100644
--- a/tda/README.md
+++ b/tda/README.md
@@ -1,17 +1,39 @@
# TDA code for Dialogue Term Extraction using Transfer Learning and Topological Data Analysis
This is the Topological Data Analysis portion of the code for the paper
-Dialogue Term Extraction using Transfer Learning and Topological Data Analysis.
+'Dialogue Term Extraction using Transfer Learning and Topological Data Analysis'.
+
+The scripts in this folder should be executed in the `tda` working directory.
## Create embeddings
-TODO
+Precomputed sbert embeddings are contained in the `/data` folder
+for the ambient fastText vocabulary, and the joint multiwoz and sgd vocabulary.
+These embeddings are the basis for computing neighborhoods.
+It is not necessary to recompute these embeddings,
+for the neighborhood extraction and TDA features skip ahead to the next section.
+
+The following command loads the precomputed embeddings
+of the fastText vocabulary into an interactive python session:
+```bash
+python -i sbert_create_static_embeddings.py \
+ --embeddings_config_path ./sbert_static_embeddings_config_50_0.yaml \
+ --vocab_desc pretrained_cc_en \
+ --load_embeddings
+```
+To compute and save embeddings of the multiwoz and sgd vocabulary:
+```bash
+python sbert_create_static_embeddings.py \
+ --embeddings_config_path ./sbert_static_embeddings_config_50_0.yaml \
+ --vocab_desc multiwoz_and_sgd \
+ --save_embeddings
+```
## Build neighbourhoods and extract persistence features
TODO
-## 8. License
+## License
This project is licensed under the Apache License, Version 2.0 (the "License");
you may not use the files except in compliance with the License.
You may obtain a copy of the License at
diff --git a/tda/sbert_create_static_embeddings.py b/tda/sbert_create_static_embeddings.py
index 2cb2873844f3d769dbcaac46b87a3e9314c5d055..1995e0c128c04961d3f2e292387f8c554224f1f5 100644
--- a/tda/sbert_create_static_embeddings.py
+++ b/tda/sbert_create_static_embeddings.py
@@ -49,6 +49,13 @@ parser = argparse.ArgumentParser()
# Required parameters
parser.add_argument("--embeddings_config_path", default=None, type=str, required=True,
help="Dataset configuration file.")
+parser.add_argument("--vocab_desc", choices=["multiwoz_and_sgd", "pretrained_cc_en"],
+ default=None, type=str, required=True,
+ help="String describing which embeddings should be created.")
+parser.add_argument("--save_embeddings", default=False, action="store_true",
+ help="Flag to save embeddings to disk.")
+parser.add_argument("--load_embeddings", default=False, action="store_true",
+ help="Flag to load embeddings from disk.")
# Optional parameters
# None
@@ -59,22 +66,20 @@ args = parser.parse_args()
embeddings_config_path = args.embeddings_config_path
embeddings_config = yaml.safe_load(open(embeddings_config_path))
-# # # # # # # # # # # # # # # # #
-# MODIFY: Program parameters
-DEVELOP_MODE = False
+vocab_desc = args.vocab_desc
+# the fields in the config file are named
+# 'pretrained_cc_en_vocabulary_path' and 'multiwoz_and_sgd_vocabulary_path'
+vocab_path = embeddings_config['data'][vocab_desc + '_vocabulary_path']
-SAVE_EMBEDDINGS = True
-LOAD_EMBEDDINGS = False
+SAVE_EMBEDDINGS = args.save_embeddings
+LOAD_EMBEDDINGS = args.load_embeddings
data_desc_list = ['paraphrase-MiniLM-L6-v2']
+# # # # # # # # # # # # # # # # #
+# Debug parameters
DEBUG_DATA_DESC = 'paraphrase-MiniLM-L6-v2'
-VOCAB_PATH = embeddings_config['data']['multiwoz_and_sgd_joint_vocabulary_path']
-VOCAB_DESC = 'multiwoz_and_sgd'
-# VOCAB_PATH = embeddings_config['data']['pretrained_cc_en_vocabulary_path']
-# VOCAB_DESC = 'pretrained_cc_en'
-
# Set up logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)
@@ -108,12 +113,14 @@ models = {}
# Pooling: Mean Pooling
models['paraphrase-MiniLM-L6-v2'] = SentenceTransformer('paraphrase-MiniLM-L6-v2')
+# more models could be added here as additional keys,
+# the embeddings will be computed for each model
# Load data
logging.info('Loading data ...')
-with open(VOCAB_PATH, "r") as file:
+with open(vocab_path, "r") as file:
vocabulary = json.load(file)
# Testing tokenization of certain sentences
@@ -157,7 +164,7 @@ if SAVE_EMBEDDINGS is True and LOAD_EMBEDDINGS is False:
# save or load embeddings
try:
embeddings_path = os.path.join(embeddings_config['embeddings']['embeddings_dict_path'],
- f"{VOCAB_DESC}_vocab_embeddings_sbert.pkl")
+ f"{vocab_desc}_vocab_embeddings_sbert.pkl")
if SAVE_EMBEDDINGS is True:
logging.info("Saving embeddings ...")
logging.info(embeddings_path)
@@ -179,12 +186,16 @@ test_vocab = ['.', ':',
'cheap', 'expensive',
'xg1tx6q8', '07591624763']
-# Print the embeddings
-for word in test_vocab:
- embedding = embeddings['paraphrase-MiniLM-L6-v2'][word]
- print("Sentence:", word)
- print("Embedding:", embedding)
- print("")
+try:
+ # Print the embeddings
+ for word in test_vocab:
+ embedding = embeddings['paraphrase-MiniLM-L6-v2'][word]
+ print("Sentence:", word)
+ print("Embedding:", embedding)
+ print("")
+except Exception as e:
+ logging.error(traceback.format_exc())
+ pass
embedding_vectors = {}
diff --git a/tda/sbert_create_static_embeddings_50_0.log b/tda/sbert_create_static_embeddings_50_0.log
new file mode 100644
index 0000000000000000000000000000000000000000..e1cf5e2acc11b083f484cb0be170779f243b5720
--- /dev/null
+++ b/tda/sbert_create_static_embeddings_50_0.log
@@ -0,0 +1,49 @@
+2022-06-15 12:27:38,561 - root - INFO - Loading config file: ./sbert_static_embeddings_config_50_0.yaml
+2022-06-15 12:27:38,561 - root - INFO - {'data': {'data_folder_path': '../data', 'multiwoz_and_sgd_joint_vocabulary_path': '../data/multiwoz_and_sgd_joint_vocabulary.json', 'pretrained_cc_en_vocabulary_path': '../data/pretrained_cc_en_vocabulary.json'}, 'embeddings': {'embeddings_dict_path': '../data', 'embeddings_dataframes_path': '../data', 'context': 'word', 'pooling_method': 'mean', 'special_tokens': 'ignore'}, 'neighborhoods': {'nbhd_size': 50, 'nbhd_remove': 0, 'neighborhoods_path': '../data/neighborhoods', 'persistence_features_path': '../data', 'normalize': False}}
+2022-06-15 12:27:38,561 - sentence_transformers.SentenceTransformer - INFO - Load pretrained SentenceTransformer: paraphrase-MiniLM-L6-v2
+2022-06-15 12:27:45,634 - sentence_transformers.SentenceTransformer - INFO - Use pytorch device: cpu
+2022-06-15 12:27:45,634 - root - INFO - Loading data ...
+2022-06-15 12:27:45,636 - root - INFO - Creating embeddings...
+2022-06-15 14:50:27,346 - root - INFO - Loading config file: ./sbert_static_embeddings_config_50_0.yaml
+2022-06-15 14:50:27,347 - root - INFO - {'data': {'data_folder_path': '../data', 'multiwoz_and_sgd_vocabulary_path': '../data/multiwoz_and_sgd_joint_vocabulary.json', 'pretrained_cc_en_vocabulary_path': '../data/pretrained_cc_en_vocabulary.json'}, 'embeddings': {'embeddings_dict_path': '../data', 'embeddings_dataframes_path': '../data', 'context': 'word', 'pooling_method': 'mean', 'special_tokens': 'ignore'}, 'neighborhoods': {'nbhd_size': 50, 'nbhd_remove': 0, 'neighborhoods_path': '../data/neighborhoods', 'persistence_features_path': '../data', 'normalize': False}}
+2022-06-15 14:50:27,347 - sentence_transformers.SentenceTransformer - INFO - Load pretrained SentenceTransformer: paraphrase-MiniLM-L6-v2
+2022-06-15 14:50:34,329 - sentence_transformers.SentenceTransformer - INFO - Use pytorch device: cpu
+2022-06-15 14:50:34,329 - root - INFO - Loading data ...
+2022-06-15 14:50:34,469 - root - INFO - Creating embeddings...
+2022-06-15 15:12:27,980 - root - INFO - Loading config file: ./sbert_static_embeddings_config_50_0.yaml
+2022-06-15 15:12:27,980 - root - INFO - {'data': {'data_folder_path': '../data', 'multiwoz_and_sgd_vocabulary_path': '../data/multiwoz_and_sgd_joint_vocabulary.json', 'pretrained_cc_en_vocabulary_path': '../data/pretrained_cc_en_vocabulary.json'}, 'embeddings': {'embeddings_dict_path': '../data', 'embeddings_dataframes_path': '../data', 'context': 'word', 'pooling_method': 'mean', 'special_tokens': 'ignore'}, 'neighborhoods': {'nbhd_size': 50, 'nbhd_remove': 0, 'neighborhoods_path': '../data/neighborhoods', 'persistence_features_path': '../data', 'normalize': False}}
+2022-06-15 15:12:27,980 - sentence_transformers.SentenceTransformer - INFO - Load pretrained SentenceTransformer: paraphrase-MiniLM-L6-v2
+2022-06-15 15:12:34,965 - sentence_transformers.SentenceTransformer - INFO - Use pytorch device: cpu
+2022-06-15 15:12:34,965 - root - INFO - Loading data ...
+2022-06-15 15:12:35,103 - root - INFO - Loading embeddings ...
+2022-06-15 15:12:43,604 - root - INFO - Loading embeddings done.
+2022-06-15 15:13:47,810 - root - INFO - Loading config file: ./sbert_static_embeddings_config_50_0.yaml
+2022-06-15 15:13:47,810 - root - INFO - {'data': {'data_folder_path': '../data', 'multiwoz_and_sgd_vocabulary_path': '../data/multiwoz_and_sgd_joint_vocabulary.json', 'pretrained_cc_en_vocabulary_path': '../data/pretrained_cc_en_vocabulary.json'}, 'embeddings': {'embeddings_dict_path': '../data', 'embeddings_dataframes_path': '../data', 'context': 'word', 'pooling_method': 'mean', 'special_tokens': 'ignore'}, 'neighborhoods': {'nbhd_size': 50, 'nbhd_remove': 0, 'neighborhoods_path': '../data/neighborhoods', 'persistence_features_path': '../data', 'normalize': False}}
+2022-06-15 15:13:47,810 - sentence_transformers.SentenceTransformer - INFO - Load pretrained SentenceTransformer: paraphrase-MiniLM-L6-v2
+2022-06-15 15:13:54,786 - sentence_transformers.SentenceTransformer - INFO - Use pytorch device: cpu
+2022-06-15 15:13:54,786 - root - INFO - Loading data ...
+2022-06-15 15:13:54,911 - root - INFO - Loading embeddings ...
+2022-06-15 15:14:02,418 - root - INFO - Loading embeddings done.
+2022-06-15 15:14:02,438 - root - ERROR - Traceback (most recent call last):
+ File "sbert_create_static_embeddings.py", line 190, in <module>
+ embedding = embeddings['paraphrase-MiniLM-L6-v2'][word]
+KeyError: 'xg1tx6q8'
+
+2022-06-15 15:15:33,524 - root - INFO - Loading config file: ./sbert_static_embeddings_config_50_0.yaml
+2022-06-15 15:15:33,524 - root - INFO - {'data': {'data_folder_path': '../data', 'multiwoz_and_sgd_vocabulary_path': '../data/multiwoz_and_sgd_joint_vocabulary.json', 'pretrained_cc_en_vocabulary_path': '../data/pretrained_cc_en_vocabulary.json'}, 'embeddings': {'embeddings_dict_path': '../data', 'embeddings_dataframes_path': '../data', 'context': 'word', 'pooling_method': 'mean', 'special_tokens': 'ignore'}, 'neighborhoods': {'nbhd_size': 50, 'nbhd_remove': 0, 'neighborhoods_path': '../data/neighborhoods', 'persistence_features_path': '../data', 'normalize': False}}
+2022-06-15 15:15:33,524 - sentence_transformers.SentenceTransformer - INFO - Load pretrained SentenceTransformer: paraphrase-MiniLM-L6-v2
+2022-06-15 15:15:40,440 - sentence_transformers.SentenceTransformer - INFO - Use pytorch device: cpu
+2022-06-15 15:15:40,440 - root - INFO - Loading data ...
+2022-06-15 15:15:40,565 - root - INFO - Loading embeddings ...
+2022-06-15 15:15:48,250 - root - INFO - Loading embeddings done.
+2022-06-15 15:15:48,273 - root - ERROR - Traceback (most recent call last):
+ File "sbert_create_static_embeddings.py", line 190, in <module>
+ embedding = embeddings['paraphrase-MiniLM-L6-v2'][word]
+KeyError: 'xg1tx6q8'
+
+2022-06-15 15:56:59,026 - root - INFO - Loading config file: ./sbert_static_embeddings_config_50_0.yaml
+2022-06-15 15:56:59,026 - root - INFO - {'data': {'data_folder_path': '../data', 'multiwoz_and_sgd_vocabulary_path': '../data/multiwoz_and_sgd_joint_vocabulary.json', 'pretrained_cc_en_vocabulary_path': '../data/pretrained_cc_en_vocabulary.json'}, 'embeddings': {'embeddings_dict_path': '../data', 'embeddings_dataframes_path': '../data', 'context': 'word', 'pooling_method': 'mean', 'special_tokens': 'ignore'}, 'neighborhoods': {'nbhd_size': 50, 'nbhd_remove': 0, 'neighborhoods_path': '../data/neighborhoods', 'persistence_features_path': '../data', 'normalize': False}}
+2022-06-15 15:56:59,026 - sentence_transformers.SentenceTransformer - INFO - Load pretrained SentenceTransformer: paraphrase-MiniLM-L6-v2
+2022-06-15 15:57:05,865 - sentence_transformers.SentenceTransformer - INFO - Use pytorch device: cpu
+2022-06-15 15:57:05,865 - root - INFO - Loading data ...
+2022-06-15 15:57:05,868 - root - INFO - Creating embeddings...
diff --git a/tda/sbert_static_embeddings_config_50_0.yaml b/tda/sbert_static_embeddings_config_50_0.yaml
index ba3965618a9967aa77f95b76e651630be7d82e21..612999d5cc38a6d03b71783d1c6a0a02a334c32c 100644
--- a/tda/sbert_static_embeddings_config_50_0.yaml
+++ b/tda/sbert_static_embeddings_config_50_0.yaml
@@ -1,6 +1,6 @@
data:
data_folder_path: '../data'
- multiwoz_and_sgd_joint_vocabulary_path: '../data/multiwoz_and_sgd_joint_vocabulary.json'
+ multiwoz_and_sgd_vocabulary_path: '../data/multiwoz_and_sgd_joint_vocabulary.json'
pretrained_cc_en_vocabulary_path: '../data/pretrained_cc_en_vocabulary.json'
embeddings:
embeddings_dict_path: '../data'