Babel / Optimus /code /scripts /scripts_local /eval_vae_generation.sh
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export PYTHONPATH="${PYTHONPATH}:/workspace/code"
# export TRAIN_FILE=../data/datasets/wikitext-2/train.txt
# export TEST_FILE=../data/datasets/wikitext-2/valid.txt
# export GPU_ID=0,1
# CUDA_VISIBLE_DEVICES=$GPU_ID python examples/big_ae/run_encoding_generation.py \
# --checkpoint_dir=../output/philly_clm_wiki2_0.0 \
# --output_dir=../output/philly_clm_wiki2_0.0 \
# --encoder_model_type=bert \
# --encoder_model_name_or_path=bert-base-uncased \
# --decoder_model_type=gpt2 \
# --decoder_model_name_or_path=gpt2 \
# --eval_data_file=$TEST_FILE \
# --per_gpu_eval_batch_size=1
# export TRAIN_FILE=../data/datasets/debug_data/train.txt
# export TEST_FILE=../data/datasets/debug_data/test.txt
# export GPU_ID=0,1
# CUDA_VISIBLE_DEVICES=$GPU_ID python examples/big_ae/run_encoding_generation.py \
# --checkpoint_dir=../output/local_lm_vae_debug_bert_gpt \
# --output_dir=../output/local_lm_vae_debug_bert_gpt \
# --encoder_model_type=bert \
# --encoder_model_name_or_path=bert-base-uncased \
# --decoder_model_type=gpt2 \
# --decoder_model_name_or_path=gpt2 \
# --eval_data_file=$TEST_FILE \
# --per_gpu_eval_batch_size=1 \
# --gloabl_step_eval 400
export TRAIN_FILE=../data/datasets/snli_data/train.txt
export TEST_FILE=../data/datasets/snli_data/test.txt
export GPU_ID=1
CUDA_VISIBLE_DEVICES=$GPU_ID python examples/big_ae/run_encoding_generation.py \
--dataset Snli \
--checkpoint_dir=../output/philly_vae_snli_epoch20_b1.0_d0.5_r00.5_ra0.25 \
--output_dir=../output/local_lm_vae_snli_bert_gpt \
--encoder_model_type=bert \
--encoder_model_name_or_path=bert-base-cased \
--decoder_model_type=gpt2 \
--decoder_model_name_or_path=gpt2 \
--train_data_file=$TRAIN_FILE \
--eval_data_file=$TEST_FILE \
--per_gpu_eval_batch_size=1 \
--gloabl_step_eval 50000 \
--block_size 100 \
--max_seq_length 100 \
--play_mode interpolation \
--num_interpolation_steps 20
# export TRAIN_FILE=../data/datasets/debug_data/train.txt
# export TEST_FILE=../data/datasets/debug_data/test.txt
# export GPU_ID=1
# CUDA_VISIBLE_DEVICES=$GPU_ID python examples/big_ae/run_encoding_generation.py \
# --dataset Debug \
# --checkpoint_dir=../output/local_lm_vae_debug_bert_gpt \
# --output_dir=../output/local_lm_vae_debug_bert_gpt \
# --encoder_model_type=bert \
# --encoder_model_name_or_path=bert-base-uncased \
# --decoder_model_type=gpt2 \
# --decoder_model_name_or_path=gpt2 \
# --train_data_file=$TRAIN_FILE \
# --eval_data_file=$TEST_FILE \
# --per_gpu_eval_batch_size=1 \
# --gloabl_step_eval 800 \
# --total_sents 10