#!/bin/bash # Data DATA_ROOT=../data/text8/ # Model N_LAYER=12 D_MODEL=512 D_EMBED=512 N_HEAD=8 D_HEAD=64 D_INNER=2048 # Training TGT_LEN=512 MEM_LEN=512 BSZ=24 NUM_CORE=4 # Testing TEST_TGT_LEN=80 TEST_MEM_LEN=2100 TEST_CLAMP_LEN=820 TEST_BSZ=10 TEST_NUM_CORE=1 if [[ $1 == 'train_data' ]]; then python data_utils.py \ --data_dir=${DATA_ROOT}/ \ --dataset=text8 \ --tgt_len=${TGT_LEN} \ --per_host_train_bsz=${BSZ} \ --per_host_valid_bsz=${BSZ} \ --num_passes=1 \ --use_tpu=False \ ${@:2} elif [[ $1 == 'test_data' ]]; then python data_utils.py \ --data_dir=${DATA_ROOT}/ \ --dataset=text8 \ --tgt_len=${TEST_TGT_LEN} \ --per_host_test_bsz=${TEST_BSZ} \ --num_passes=1 \ --use_tpu=False \ ${@:2} elif [[ $1 == 'train' ]]; then echo 'Run training...' python train_gpu.py \ --data_dir=${DATA_ROOT}/tfrecords \ --record_info_dir=${DATA_ROOT}/tfrecords/ \ --corpus_info_path=${DATA_ROOT}/corpus-info.json \ --model_dir=EXP-text8 \ --n_layer=${N_LAYER} \ --d_model=${D_MODEL} \ --d_embed=${D_EMBED} \ --n_head=${N_HEAD} \ --d_head=${D_HEAD} \ --d_inner=${D_INNER} \ --dropout=0.1 \ --dropatt=0.0 \ --learning_rate=0.00025 \ --warmup_steps=0 \ --train_steps=400000 \ --tgt_len=${TGT_LEN} \ --mem_len=${MEM_LEN} \ --train_batch_size=${BSZ} \ --num_core_per_host=${NUM_CORE} \ --iterations=200 \ --save_steps=4000 \ --do_train=True \ --do_eval=False \ ${@:2} elif [[ $1 == 'eval' ]]; then echo 'Run evaluation...' python train_gpu.py \ --data_dir=${DATA_ROOT}/tfrecords \ --record_info_dir=${DATA_ROOT}/tfrecords/ \ --corpus_info_path=${DATA_ROOT}/corpus-info.json \ --model_dir=EXP-text8 \ --n_layer=${N_LAYER} \ --d_model=${D_MODEL} \ --d_embed=${D_EMBED} \ --n_head=${N_HEAD} \ --d_head=${D_HEAD} \ --d_inner=${D_INNER} \ --dropout=0.0 \ --dropatt=0.0 \ --tgt_len=${TEST_TGT_LEN} \ --mem_len=${TEST_MEM_LEN} \ --clamp_len=${TEST_CLAMP_LEN} \ --same_length=True \ --eval_batch_size=${TEST_BSZ} \ --num_core_per_host=${TEST_NUM_CORE} \ --do_train=False \ --do_eval=True \ --eval_split=test \ ${@:2} else echo 'unknown argment 1' fi