134 lines
3.5 KiB
Bash
134 lines
3.5 KiB
Bash
#!/bin/bash
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# Path
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LOCAL_DIR=../data/wikitext-103/
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GSDATA=
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GSEXP=
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# TPU setting
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NUM_HOST=4
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NUM_CORE=16 # TPUv2 -> 8 | TPUv3 -> 16
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TEST_NUM_HOST=1
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TEST_NUM_CORE=8 # TPUv2 -> 8 | TPUv3 -> 16
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# Model
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DIV_VAL=4
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N_LAYER=18
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D_MODEL=1024
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D_EMBED=1024
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N_HEAD=16
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D_HEAD=64
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D_INNER=4096
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# Training
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TGT_LEN=384
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MEM_LEN=384
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TRAIN_BSZ=128
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VALID_BSZ=128
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# Testing
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TEST_TGT_LEN=128
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TEST_MEM_LEN=1600
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TEST_CLAMP_LEN=1000
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TEST_BSZ=8
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if [[ $1 == 'train_data' ]]; then
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python data_utils.py \
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--data_dir=${LOCAL_DIR}/ \
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--dataset=wt103 \
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--tgt_len=${TGT_LEN} \
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--per_host_train_bsz=${TRAIN_BSZ} \
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--per_host_valid_bsz=${VALID_BSZ} \
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--num_core_per_host=${NUM_CORE} \
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--num_passes=10 \
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--use_tpu=True \
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${@:2}
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SRC_PATTERN=train.bsz-${TRAIN_BSZ}.tlen-${TGT_LEN}.core-${NUM_CORE}*
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gsutil cp ${LOCAL_DIR}/tfrecords/${SRC_PATTERN} ${GSDATA}/wt103-tfrecords/
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SRC_PATTERN=valid.bsz-${VALID_BSZ}.tlen-${TGT_LEN}.core-${NUM_CORE}*
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gsutil cp ${LOCAL_DIR}/tfrecords/${SRC_PATTERN} ${GSDATA}/wt103-tfrecords/
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elif [[ $1 == 'test_data' ]]; then
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python data_utils.py \
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--data_dir=${LOCAL_DIR}/ \
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--dataset=wt103 \
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--tgt_len=${TEST_TGT_LEN} \
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--per_host_test_bsz=${TEST_BSZ} \
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--num_core_per_host=${TEST_NUM_CORE} \
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--num_passes=1 \
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--use_tpu=True \
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${@:2}
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SRC_PATTERN=test.bsz-${TEST_BSZ}.tlen-${TEST_TGT_LEN}.core-${TEST_NUM_CORE}*
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gsutil cp ${LOCAL_DIR}/tfrecords/${SRC_PATTERN} ${GSDATA}/wt103-tfrecords/
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elif [[ $1 == 'train' ]]; then
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echo 'Run training...'
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python train.py \
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--data_dir=${GSDATA}/wt103-tfrecords \
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--record_info_dir=${LOCAL_DIR}/tfrecords/ \
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--corpus_info_path=${LOCAL_DIR}/corpus-info.json \
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--model_dir=${GSEXP}/wt103 \
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--div_val=${DIV_VAL} \
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--untie_r=True \
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--proj_share_all_but_first=True \
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--proj_same_dim=True \
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--n_layer=${N_LAYER} \
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--d_model=${D_MODEL} \
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--d_embed=${D_EMBED} \
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--n_head=${N_HEAD} \
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--d_head=${D_HEAD} \
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--d_inner=${D_INNER} \
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--dropout=0.2 \
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--dropatt=0.2 \
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--init_std=0.005 \
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--learning_rate=0.00025 \
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--warmup_steps=16000 \
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--train_steps=4000000 \
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--tgt_len=${TGT_LEN} \
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--mem_len=${MEM_LEN} \
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--train_batch_size=${TRAIN_BSZ} \
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--num_hosts=${NUM_HOST} \
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--num_core_per_host=${NUM_CORE} \
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--iterations=1000 \
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--save_steps=10000 \
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--use_tpu=True \
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--do_eval=False \
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${@:2}
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elif [[ $1 == 'eval' ]]; then
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echo 'Run evaluation...'
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python train.py \
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--data_dir=${GSDATA}/wt103-tfrecords \
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--record_info_dir=${LOCAL_DIR}/tfrecords/ \
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--corpus_info_path=${LOCAL_DIR}/corpus-info.json \
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--model_dir=${GSEXP}/wt103 \
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--div_val=${DIV_VAL} \
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--untie_r=True \
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--proj_share_all_but_first=True \
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--proj_same_dim=True \
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--n_layer=${N_LAYER} \
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--d_model=${D_MODEL} \
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--d_embed=${D_EMBED} \
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--n_head=${N_HEAD} \
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--d_head=${D_HEAD} \
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--d_inner=${D_INNER} \
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--tgt_len=${TEST_TGT_LEN} \
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--mem_len=${TEST_MEM_LEN} \
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--clamp_len=${TEST_CLAMP_LEN} \
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--same_length=True \
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--eval_batch_size=${TEST_BSZ} \
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--num_host=${TEST_NUM_HOST} \
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--num_core_per_host=${TEST_NUM_CORE} \
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--use_tpu=True \
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--do_train=False \
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--do_eval_only=True \
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--eval_split=test \
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${@:2}
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else
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echo 'unknown argment 1'
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fi
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