From 6daadd33e8c37dd1d12c3c895a44a76d4048a9f5 Mon Sep 17 00:00:00 2001
From: zqwerty <zhuq96@hotmail.com>
Date: Sun, 10 Apr 2022 13:15:37 +0800
Subject: [PATCH] fix import bug in dst/merge_predict_res.py
---
convlab2/base_models/t5/dst/dst_metric.py | 4 +-
.../base_models/t5/dst/merge_predict_res.py | 4 +-
convlab2/base_models/t5/dst/run_multiwoz21.sh | 43 +++++++++----------
convlab2/base_models/t5/rg/run_rg.sh | 28 ++++++------
4 files changed, 39 insertions(+), 40 deletions(-)
diff --git a/convlab2/base_models/t5/dst/dst_metric.py b/convlab2/base_models/t5/dst/dst_metric.py
index 8a4f73b0..aedef34d 100644
--- a/convlab2/base_models/t5/dst/dst_metric.py
+++ b/convlab2/base_models/t5/dst/dst_metric.py
@@ -75,8 +75,8 @@ class DSTMetrics(datasets.Metric):
pred_state = deserialize_dialogue_state(prediction)
gold_state = deserialize_dialogue_state(reference)
- predicts = sorted(list({(domain, slot, value) for domain in pred_state for slot, value in pred_state[domain].items() if len(value)>0}))
- labels = sorted(list({(domain, slot, value) for domain in gold_state for slot, value in gold_state[domain].items() if len(value)>0}))
+ predicts = sorted(list({(domain, slot, ''.join(value.split()).lower()) for domain in pred_state for slot, value in pred_state[domain].items() if len(value)>0}))
+ labels = sorted(list({(domain, slot, ''.join(value.split()).lower()) for domain in gold_state for slot, value in gold_state[domain].items() if len(value)>0}))
flag = True
for ele in predicts:
diff --git a/convlab2/base_models/t5/dst/merge_predict_res.py b/convlab2/base_models/t5/dst/merge_predict_res.py
index ebdada8a..0a80ee80 100755
--- a/convlab2/base_models/t5/dst/merge_predict_res.py
+++ b/convlab2/base_models/t5/dst/merge_predict_res.py
@@ -1,7 +1,7 @@
import json
import os
from convlab2.util import load_dataset, load_dst_data
-from convlab2.base_models.t5.dst.serialization import deserialize_state
+from convlab2.base_models.t5.dst.serialization import deserialize_dialogue_state
def merge(dataset_name, speaker, save_dir, context_window_size, predict_result):
@@ -13,7 +13,7 @@ def merge(dataset_name, speaker, save_dir, context_window_size, predict_result):
save_dir = os.path.dirname(predict_result)
else:
os.makedirs(save_dir, exist_ok=True)
- predict_result = [deserialize_state(json.loads(x)['predictions'].strip()) for x in open(predict_result)]
+ predict_result = [deserialize_dialogue_state(json.loads(x)['predictions'].strip()) for x in open(predict_result)]
for sample, prediction in zip(data, predict_result):
sample['predictions'] = {'state': prediction}
diff --git a/convlab2/base_models/t5/dst/run_multiwoz21.sh b/convlab2/base_models/t5/dst/run_multiwoz21.sh
index e031be48..e7573e95 100644
--- a/convlab2/base_models/t5/dst/run_multiwoz21.sh
+++ b/convlab2/base_models/t5/dst/run_multiwoz21.sh
@@ -26,7 +26,7 @@ num_train_epochs=10
python ../create_data.py --tasks ${task_name} --datasets ${dataset_name} --speaker ${speaker} --context_window_size ${context_window_size}
-python -m torch.distributed.launch --master_port 29501 \
+python -m torch.distributed.launch \
--nproc_per_node ${n_gpus} ../run_seq2seq.py \
--task_name ${task_name} \
--train_file ${train_file} \
@@ -43,8 +43,7 @@ python -m torch.distributed.launch --master_port 29501 \
--do_predict \
--save_strategy epoch \
--evaluation_strategy epoch \
- --load_best_model_at_end \
- --predict_with_generate \
+ --prediction_loss_only \
--metric_name_or_path ${metric_name_or_path} \
--cache_dir ${cache_dir} \
--output_dir ${output_dir} \
@@ -60,24 +59,24 @@ python -m torch.distributed.launch --master_port 29501 \
--adafactor \
--gradient_checkpointing
-# python -m torch.distributed.launch \
-# --nproc_per_node ${n_gpus} ../run_seq2seq.py \
-# --task_name ${task_name} \
-# --test_file ${test_file} \
-# --source_column ${source_column} \
-# --target_column ${target_column} \
-# --max_source_length ${max_source_length} \
-# --max_target_length ${max_target_length} \
-# --truncation_side ${truncation_side} \
-# --model_name_or_path ${output_dir} \
-# --do_predict \
-# --predict_with_generate \
-# --metric_name_or_path ${metric_name_or_path} \
-# --cache_dir ${cache_dir} \
-# --output_dir ${output_dir} \
-# --logging_dir ${logging_dir} \
-# --overwrite_output_dir \
-# --preprocessing_num_workers 4 \
-# --per_device_eval_batch_size ${per_device_eval_batch_size} \
+python -m torch.distributed.launch \
+ --nproc_per_node ${n_gpus} ../run_seq2seq.py \
+ --task_name ${task_name} \
+ --test_file ${test_file} \
+ --source_column ${source_column} \
+ --target_column ${target_column} \
+ --max_source_length ${max_source_length} \
+ --max_target_length ${max_target_length} \
+ --truncation_side ${truncation_side} \
+ --model_name_or_path ${output_dir} \
+ --do_predict \
+ --predict_with_generate \
+ --metric_name_or_path ${metric_name_or_path} \
+ --cache_dir ${cache_dir} \
+ --output_dir ${output_dir} \
+ --logging_dir ${logging_dir} \
+ --overwrite_output_dir \
+ --preprocessing_num_workers 4 \
+ --per_device_eval_batch_size ${per_device_eval_batch_size} \
python merge_predict_res.py -d ${dataset_name} -s ${speaker} -c ${context_window_size} -p ${output_dir}/generated_predictions.json
diff --git a/convlab2/base_models/t5/rg/run_rg.sh b/convlab2/base_models/t5/rg/run_rg.sh
index 55accadf..6fcffca2 100644
--- a/convlab2/base_models/t5/rg/run_rg.sh
+++ b/convlab2/base_models/t5/rg/run_rg.sh
@@ -16,24 +16,24 @@ truncation_side="left"
max_source_length=512
max_target_length=128
model_name_or_path="t5-small"
-per_device_train_batch_size=32
+per_device_train_batch_size=128
per_device_eval_batch_size=128
gradient_accumulation_steps=4
lr=1e-3
num_train_epochs=5
-# names=$(echo ${dataset_name} | tr "+" "\n")
-# mkdir -p ${data_dir}
-# for name in ${names};
-# do
-# echo "preprocessing ${name}"
-# python ../create_data.py --tasks ${task_name} --datasets ${name} --speaker ${speaker}
-# if [ "${name}" != "${dataset_name}" ]; then
-# cat "data/${task_name}/${name}/${speaker}/train.json" >> ${train_file}
-# cat "data/${task_name}/${name}/${speaker}/validation.json" >> ${validation_file}
-# cat "data/${task_name}/${name}/${speaker}/test.json" >> ${test_file}
-# fi
-# done
+names=$(echo ${dataset_name} | tr "+" "\n")
+mkdir -p ${data_dir}
+for name in ${names};
+do
+ echo "preprocessing ${name}"
+ python ../create_data.py --tasks ${task_name} --datasets ${name} --speaker ${speaker}
+ if [ "${name}" != "${dataset_name}" ]; then
+ cat "data/${task_name}/${name}/${speaker}/train.json" >> ${train_file}
+ cat "data/${task_name}/${name}/${speaker}/validation.json" >> ${validation_file}
+ cat "data/${task_name}/${name}/${speaker}/test.json" >> ${test_file}
+ fi
+done
python -m torch.distributed.launch \
--nproc_per_node ${n_gpus} ../run_seq2seq.py \
@@ -53,7 +53,7 @@ python -m torch.distributed.launch \
--save_strategy epoch \
--evaluation_strategy epoch \
--load_best_model_at_end \
- --predict_with_generate \
+ --prediction_loss_only \
--cache_dir ${cache_dir} \
--output_dir ${output_dir} \
--logging_dir ${logging_dir} \
--
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