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run.sh
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#! /bin/bash
export FLAGS_enable_parallel_graph=1
export FLAGS_sync_nccl_allreduce=1
export CUDA_VISIBLE_DEVICES=0
export FLAGS_fraction_of_gpu_memory_to_use=0.95
export CPU_NUM=1
TASK_NAME='senta'
DATA_PATH=./senta_data/
CKPT_PATH=./save_models
MODEL_PATH=./save_models/step_1800/
# run_train on train.tsv and do_val on test.tsv
train() {
python -u run_classifier.py \
--task_name ${TASK_NAME} \
--use_cuda true \
--do_train true \
--do_val false \
--do_infer false \
--batch_size 8 \
--data_dir ${DATA_PATH} \
--vocab_path ${DATA_PATH}/word_dict.txt \
--checkpoints ${CKPT_PATH} \
--save_steps 50 \
--validation_steps 50 \
--epoch 3 \
--senta_config_path ./senta_config.json \
--skip_steps 10
}
# run_eval on test.tsv
evaluate() {
python -u run_classifier.py \
--task_name ${TASK_NAME} \
--use_cuda true \
--do_train false \
--do_val true \
--do_infer false \
--batch_size 10 \
--data_dir ${DATA_PATH} \
--vocab_path ${DATA_PATH}/word_dict.txt \
--init_checkpoint ${MODEL_PATH} \
--senta_config_path ./senta_config.json
}
# run_infer on infer.tsv
infer() {
python -u run_classifier.py \
--task_name ${TASK_NAME} \
--use_cuda true \
--do_train false \
--do_val false \
--do_infer true \
--batch_size 10 \
--data_dir ${DATA_PATH} \
--vocab_path ${DATA_PATH}/word_dict.txt \
--init_checkpoint ${MODEL_PATH} \
--senta_config_path ./senta_config.json
}
# run_save_inference_model
save_inference_model() {
python -u inference_model.py \
--use_cuda false \
--do_save_inference_model true \
--init_checkpoint ${MODEL_PATH} \
--inference_model_dir ./inference_model
}
main() {
local cmd=${1:-help}
case "${cmd}" in
train)
train "$@";
;;
eval)
evaluate "$@";
;;
infer)
infer "$@";
;;
save_inference_model)
save_inference_model "$@";
;;
help)
echo "Usage: ${BASH_SOURCE} {train|eval|infer|save_inference_model}";
return 0;
;;
*)
echo "Unsupport commend [${cmd}]";
echo "Usage: ${BASH_SOURCE} {train|eval|infer|save_inference_model}";
return 1;
;;
esac
}
main "$@"