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run.sh
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run.sh
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#! /bin/bash
set -e
mod=$1
log=$2
device=$3
if [ -z $3 ]; then
device=0
fi
echo "mod: ${mod}"
echo "device: ${device}"
cd src
if [[ ${mod} == "train_svamp" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_svamp.py \
--model_type 're' \
--dataset_name 'svamp' \
--log_text ${log} \
--data_path '../data/SVAMP' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"roberta-base","lr":2e-5,"max_step_size":5,"num_epochs":1000,"batch_size":8}'
fi
# use_data_aug true
if [[ ${mod} == "debug_svamp" ]];
then
CUDA_LAUNCH_BLOCKING=1 CUDA_VISIBLE_DEVICES=${device} python train_svamp.py \
--model_type 're' \
--dataset_name 'svamp' \
--log_text '(debug)' \
--data_path '../data/SVAMP' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--cfg '{"model_name":"roberta-base","lr":2e-5,"max_step_size":5,"save_result":true,"batch_size":8}' \
--head 1000 \
--debug
fi
if [[ ${mod} == "train_mawps" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_mawps.py \
--model_type 're' \
--dataset_name 'mawps' \
--log_text ${log} \
--data_path '../data/MAWPS' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"roberta-base","lr":2e-5,"max_step_size":5,"save_result":false,"num_epochs":500}'
fi
if [[ ${mod} == "debug_mawps" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_mawps.py \
--model_type 're' \
--dataset_name 'mawps' \
--log_text '(debug)' \
--data_path '../data/MAWPS' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--cfg '{"model_name":"roberta-base","lr":2e-5,"max_step_size":5,"save_result":false,"num_epochs":500}' \
--head 1000 \
--debug
fi
if [[ ${mod} == "train_mathqa" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_mathqa.py \
--model_type 're' \
--dataset_name 'mathqa' \
--log_text ${log} \
--data_path '../data/MathQA' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"roberta-base","lr":2e-5,"save_result":true,"num_epochs":200}'
fi
# --cfg '{"model_name":"roberta-base","lr":2e-5,"save_result":true,"num_epochs":200}'
if [[ ${mod} == "test_mathqa" ]];
then
CUDA_VISIBLE_DEVICES=${device} python test_mathqa.py \
--model_type 're' \
--dataset_name 'mathqa' \
--log_text ${log} \
--data_path '../data/MathQA' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"roberta-base","beam_size":4}'
fi
# --cfg '{"model_name":"roberta-base","beam_size":4}'
if [[ ${mod} == "debug_mathqa" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_mathqa.py \
--model_type 're' \
--dataset_name 'mathqa' \
--log_text '(debug)' \
--data_path '../data/MathQA' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--cfg '{"model_name":"roberta-base","lr":5e-6,"save_result":false,"num_epochs":200}' \
--head 100 \
--debug
fi
# --cfg '{"model_name":"roberta-base","lr":2e-5,"save_result":false,"num_epochs":200}' \
if [[ ${mod} == "train_math23k" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_math23k.py \
--model_type 're' \
--dataset_name 'math23k' \
--log_text ${log} \
--data_path '../data/Math23K' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"hfl/chinese-roberta-wwm-ext","num_epochs":200,"lr":2e-5,"lr_alpha":1.0,"save_result":true}'
fi
# --cfg '{"model_name":"hfl/chinese-roberta-wwm-ext","num_epochs":200,"lr":2e-5,"lr_alpha":1.0,"save_result":true}'
if [[ ${mod} == "test_math23k" ]];
then
CUDA_VISIBLE_DEVICES=${device} python test_math23k.py \
--model_type 're' \
--dataset_name 'math23k' \
--log_text ${log} \
--data_path '../data/Math23K' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"hfl/chinese-roberta-wwm-ext-large","beam_size":4}'
fi
# debug
if [[ ${mod} == "debug_math23k" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_math23k.py \
--model_type 're' \
--dataset_name 'math23k' \
--log_text '(debug)' \
--data_path '../data/Math23K' \
--load_model_dir 'models_test' \
--save_model_dir 'models_test' \
--cfg '{"model_name":"hfl/chinese-roberta-wwm-ext","num_epochs":200,"lr":2e-5,"lr_alpha":1.0}' \
--head 1000 \
--debug
fi
# --cfg '{"model_name":"hfl/chinese-roberta-wwm-ext","num_epochs":200,"lr":2e-5,"lr_alpha":1.0}'
if [[ ${mod} == "train_math23k_5fold" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_math23k_5fold.py \
--model_type 're' \
--dataset_name 'math23k' \
--log_text ${log} \
--data_path '../data/Math23K-5fold' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"hfl/chinese-roberta-wwm-ext","num_epochs":200,"lr":2e-5,"lr_alpha":1.0}'
fi
if [[ ${mod} == "train_math23k_raw" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_math23k_raw.py \
--model_type 're' \
--dataset_name 'math23k' \
--log_text ${log} \
--data_path '../data/Math23K-raw' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--cfg '{"model_name":"hfl/chinese-roberta-wwm-ext","num_epochs":200,"lr":2e-5}' \
--save_model \
--expr_mode v3
fi
if [[ ${mod} == "train_template" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_template.py \
--model_type 're' \
--dataset_name 'template' \
--log_text ${log} \
--data_path '../data/MathTemplate' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"roberta-large","num_epochs":200,"lr":5e-6,"quant_size":100,"save_result":false}'
fi
# --cfg '{"model_name":"roberta-base","num_epochs":200,"lr":2e-5,"quant_size":100,"save_result":false}'
# debug
if [[ ${mod} == "debug_template" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_template.py \
--model_type 're' \
--dataset_name 'template' \
--log_text '(debug)' \
--data_path '../data/MathTemplate' \
--load_model_dir 'models' \
--save_model_dir 'models' \
--cfg '{"model_name":"roberta-large","num_epochs":200,"lr":2e-5,"quant_size":100,"save_result":false}' \
--head 100 \
--debug
fi
# --cfg '{"model_name":"roberta-base","num_epochs":200,"lr":2e-5,"quant_size":100,"save_result":false}' \
if [[ ${mod} == "train_template_binary" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_template_binary.py \
--dataset_name 'templateBinary' \
--log_text ${log} \
--data_path '../data/MathTemplateBinary' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"roberta-base","num_epochs":200,"lr":2e-5,"quant_size":100,"save_result":false}'
fi
# debug
if [[ ${mod} == "debug_template_binary" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_template_binary.py \
--dataset_name 'templateBinary' \
--log_text '(debug)' \
--data_path '../data/MathTemplateBinary' \
--load_model_dir 'models' \
--save_model_dir 'models' \
--cfg '{"model_name":"roberta-base","num_epochs":200,"lr":2e-5,"quant_size":100,"save_result":false}' \
--head 100 \
--debug
fi
if [[ ${mod} == "train_mathqa_abl0" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_mathqa.py \
--model_type 'rpe_abl0' \
--dataset_name 'mathqa' \
--log_text ${log} \
--data_path '../data/MathQA' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--save_model \
--cfg '{"model_name":"roberta-base","lr":2e-5,"save_result":false,"num_epochs":200}'
fi
if [[ ${mod} == "debug_mathqa_abl0" ]];
then
CUDA_VISIBLE_DEVICES=${device} python train_mathqa.py \
--model_type 'rpe_abl0' \
--dataset_name 'mathqa' \
--log_text '(debug)' \
--data_path '../data/MathQA' \
--load_model_dir '../models' \
--save_model_dir '../models' \
--cfg '{"model_name":"roberta-base","lr":2e-5,"save_result":false,"num_epochs":200}' \
--head 100 \
--debug
fi
if [[ ${mod} == "compute_params" ]];
then
CUDA_VISIBLE_DEVICES=${device} python compute_params.py \
--model_type 're' \
--cfg '{"model_name":"roberta-base"}' \
fi
cd ..
# backup
# if [[ ${mod} == "train_math23k" ]];
# then
# CUDA_VISIBLE_DEVICES=${device} python train_math23k.py \
# --dataset_name 'math23k' \
# --log_text ${log} \
# --data_path '../data/Math23K' \
# --load_model_dir '../models' \
# --save_model_dir '../models' \
# --cfg '{"model_name":"hfl/chinese-roberta-wwm-ext","num_epochs":100}' \
# --fold -1 \
# --save_model \
# --expr_mode v3
# fi
# # debug
# if [[ ${mod} == "debug_math23k" ]];
# then
# CUDA_VISIBLE_DEVICES=${device} python train_math23k.py \
# --dataset_name 'math23k' \
# --log_text '(debug)' \
# --data_path '../data/Math23K' \
# --load_model_dir 'models_test' \
# --save_model_dir 'models_test' \
# --cfg '{"model_name":"hfl/chinese-roberta-wwm-ext","num_epochs":100}' \
# --head 1000 \
# --expr_mode v3 \
# --debug
# fi
# if [[ ${mod} == "debug_mathtoy" ]];
# then
# CUDA_VISIBLE_DEVICES=${device} python train_mathtoy.py \
# --dataset_name 'mathtoy' \
# --log_text '(debug)' \
# --data_path '../data/MathToy' \
# --load_model_dir 'models_test' \
# --save_model_dir 'models_test' \
# --cfg '{"num_epochs":30}' \
# --head 1000 \
# --debug
# fi
# if [[ ${mod} == "debug_webqsp" ]];
# then
# CUDA_VISIBLE_DEVICES=${device} python train_webqsp.py \
# --dataset_name 'webqsp' \
# --log_text '(debug)' \
# --data_path '../data/WebQSP' \
# --load_model_dir '../models' \
# --save_model_dir '../models' \
# --cfg '{"num_epochs":30,"model_name":"bert-base-uncased"}' \
# --debug
# fi
# if [[ ${mod} == "debug_webqsp" ]];
# then
# CUDA_VISIBLE_DEVICES=${device} python train_webqsp.py \
# --dataset_name 'webqsp' \
# --log_text '(debug)' \
# --data_path '../data/WebQSP' \
# --load_model_dir '../models' \
# --save_model_dir '../models' \
# --cfg '{"model_name":"roberta-base","num_epochs":30}' \
# --debug
# fi