forked from alexa/dialoglue
/
dump_outputs_fewshot.py
168 lines (147 loc) · 5.73 KB
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dump_outputs_fewshot.py
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import json
import os
hwu_command = """
CUDA_VISIBLE_DEVICES=0 python run.py \
--train_data_path data_utils/dialoglue/hwu/train.csv \
--val_data_path data_utils/dialoglue/hwu/val.csv \
--test_data_path data_utils/dialoglue/hwu/test.csv \
--token_vocab_path bert-base-uncased-vocab.txt \
--output_dir {} \
--train_batch_size 64 --dropout 0.1 --num_epochs 0 --learning_rate 6e-5 \
--model_name_or_path bert-base-uncased --task intent --do_lowercase --max_seq_length 50 --mlm_pre --mlm_during --dump_outputs \
"""
banking_command = """
CUDA_VISIBLE_DEVICES=0 python run.py \
--train_data_path data_utils/dialoglue/banking/train.csv \
--val_data_path data_utils/dialoglue/banking/val.csv \
--test_data_path data_utils/dialoglue/banking/test.csv \
--token_vocab_path bert-base-uncased-vocab.txt \
--output_dir {} \
--train_batch_size 64 --dropout 0.1 --num_epochs 0 --learning_rate 6e-5 \
--model_name_or_path bert-base-uncased --task intent --do_lowercase --max_seq_length 50 --mlm_pre --mlm_during --dump_outputs \
"""
clinc_command = """
CUDA_VISIBLE_DEVICES=0 python run.py \
--train_data_path data_utils/dialoglue/clinc/train.csv \
--val_data_path data_utils/dialoglue/clinc/val.csv \
--test_data_path data_utils/dialoglue/clinc/test.csv \
--token_vocab_path bert-base-uncased-vocab.txt \
--output_dir {} \
--train_batch_size 64 --dropout 0.1 --num_epochs 0 --learning_rate 6e-5 \
--model_name_or_path bert-base-uncased --task intent --do_lowercase --max_seq_length 50 --mlm_pre --mlm_during --dump_outputs \
"""
restaurant8k_command = """
CUDA_VISIBLE_DEVICES=0 python run.py \
--train_data_path data_utils/dialoglue/restaurant8k/train.json \
--val_data_path data_utils/dialoglue/restaurant8k/val.json \
--test_data_path data_utils/dialoglue/restaurant8k/test.json \
--token_vocab_path bert-base-uncased-vocab.txt \
--output_dir {} \
--train_batch_size 64 --dropout 0.1 --num_epochs 0 --learning_rate 6e-5 \
--model_name_or_path bert-base-uncased --task slot --do_lowercase --max_seq_length 50 --mlm_pre --mlm_during --dump_outputs \
"""
dstc8_command = """
CUDA_VISIBLE_DEVICES=0 python run.py \
--train_data_path data_utils/dialoglue/dstc8_sgd/train.json \
--val_data_path data_utils/dialoglue/dstc8_sgd/val.json \
--test_data_path data_utils/dialoglue/dstc8_sgd/test.json \
--token_vocab_path bert-base-uncased-vocab.txt \
--output_dir {} \
--train_batch_size 64 --dropout 0.1 --num_epochs 0 --learning_rate 6e-5 \
--model_name_or_path bert-base-uncased --task slot --do_lowercase --max_seq_length 50 --mlm_pre --mlm_during --dump_outputs \
"""
top_command = """
CUDA_VISIBLE_DEVICES=0 python run.py \
--train_data_path data_utils/dialoglue/top/train.txt \
--val_data_path data_utils/dialoglue/top/eval.txt \
--test_data_path data_utils/dialoglue/top/test.txt \
--token_vocab_path bert-base-uncased-vocab.txt \
--output_dir {} \
--train_batch_size 64 --dropout 0.1 --num_epochs 0 --learning_rate 6e-5 \
--model_name_or_path bert-base-uncased --task top --do_lowercase --max_seq_length 100 --mlm_pre --mlm_during --dump_outputs \
"""
multiwoz_command = """
cd trippy;
TASK="multiwoz21"
DATA_DIR="data/MULTIWOZ2.1"
OUT_DIR={0}
args_add="--do_eval --predict_type=test"
CUDA_VISIBLE_DEVICES=0 python3 run_dst.py \
--task_name=${TASK} \
--data_dir=${DATA_DIR} \
--dataset_config=dataset_config/${TASK}.json \
--model_type="bert" \
--model_name_or_path="bert-base-uncased" \
--do_lower_case \
--learning_rate=1e-4 \
--num_train_epochs=50 \
--max_seq_length=180 \
--per_gpu_train_batch_size=48 \
--per_gpu_eval_batch_size=1 \
--output_dir=${OUT_DIR} \
--save_epochs=20 \
--logging_steps=10 \
--warmup_proportion=0.1 \
--adam_epsilon=1e-6 \
--label_value_repetitions \
--swap_utterances \
--append_history \
--use_history_labels \
--delexicalize_sys_utts \
--class_aux_feats_inform \
--class_aux_feats_ds \
--seed 42 \
--mlm_pre \
--mlm_during \
${args_add} \
2>&1 | tee ${OUT_DIR}/test.log
python3 metric_bert_dst.py \
${TASK} \
dataset_config/${TASK}.json \
"${OUT_DIR}/pred_res.test.json" \
2>&1 | tee ${OUT_DIR}/eval_pred_test.log
"""
commands = [
hwu_command,
banking_command,
clinc_command,
restaurant8k_command,
dstc8_command,
top_command,
multiwoz_command
]
checkpoints = [
"checkpoints/hwu/",
"checkpoints/banking/",
"checkpoints/clinc/",
"checkpoints/restaurant8k/",
"checkpoints/dstc8/",
"checkpoints/top/",
"checkpoints/multiwoz/",
]
datasets = [
"hwu",
"banking",
"clinc",
"restaurant8k",
"dstc8",
"top",
"multiwoz",
]
for cmd,ckpts in zip(commands, checkpoints):
for ckpt in ckpts:
if "multiwoz" in ckpt:
open("mwoz_command_temp.sh", "w+").write(cmd.replace("{0}", "../" + ckpt))
cmd = "bash mwoz_command_temp.sh"
os.system(cmd.format(ckpt))
output_dict = {}
for dataset,ckpts in zip(datasets,checkpoints):
dataset_data = []
for ckpt in ckpts:
if dataset == "multiwoz":
data = json.load(open(ckpt + "pred_res.test.final.json"))
else:
data = json.load(open(ckpt + "outputs.json"))
dataset_data.append(data)
output_dict[dataset] = dataset_data
json.dump(output_dict, open("fewshot_submission.json", "w+"))