mirror of
https://github.com/wassname/Castor.git
synced 2026-09-09 11:13:20 +08:00
Victor Yang
51d8e29525
* update nce-sm * refactor code, update torchtext * use shared evaluation * refactor code, use shared data loader * refactor code * refactor code * refactor code according to Michael's great suggestions * update readme and requirement * update datasets and readme * update data loader * add space between + * update refactor code * add nce-mp * remove duplicate files * update readme, refactor code according to mp_cnn and delete duplicate code, follow PEP8 standard * refactor code, add/delete comments * import exit from sys
44 lines
2.4 KiB
Python
44 lines
2.4 KiB
Python
import argparse
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from random import uniform
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from subprocess import call
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# set parameters from random uniform sampling
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def get_param():
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for eps in [1e-8, 1e-6]:
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for learning_rate in [0.0001, 0.0003, 0.0006, 0.001]:
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for reg in [3e-5, 9e-5, 3e-4, 9e-4]:
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yield learning_rate, eps, reg
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def run(device, epochs, neg_sample, neg_num, dataset, dev_log_interval, batch_size):
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# for _ in range(count):
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param_gen = get_param()
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for learning_rate, eps, reg in param_gen:
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filename = "grid_{dataset}_lr_{learning_rate}_eps_{eps}_reg_{reg}_device_{dev}.txt".format(
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learning_rate=learning_rate, eps=eps, reg=reg, dev=device, dataset=dataset)
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model_name = filename[:-4] + ".castor"
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command = "python -u main.py saved_models/{model} --epochs {epo} --device {dev} --dataset {dataset} " \
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"--batch-size {batch_size} --lr {learning_rate} --epsilon {eps} --regularization {reg} --tensorboard " \
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"--run-label {label} --dev_log_interval {dev_log_interval} --neg_sample {neg_sample} --neg_num {neg_num}" \
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.format(epo=epochs, model=model_name, dev=device, dataset=dataset, batch_size=batch_size,
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learning_rate=learning_rate, eps=eps,
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reg=reg, label=filename, dev_log_interval=dev_log_interval, neg_sample=neg_sample, neg_num=neg_num)
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print("Running: " + command)
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with open(filename, 'w') as outfile:
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call(command, shell=True, stderr=outfile)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='Hyper parameters sweeper')
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parser.add_argument('--device', type=int, default=2, help='GPU device, -1 for CPU (default: 0)')
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parser.add_argument('--epochs', type=int, default=8, help='number of epochs to run')
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parser.add_argument('--neg_num', type=int, default=8, help='number of negative samples')
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parser.add_argument('--neg_sample', type=str, default="max", help='strategy of negative samples')
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parser.add_argument('--dataset', type=str, default="trecqa", help='dataset')
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parser.add_argument('--dev_log_interval', type=int, default=150, help='number of negative samples')
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parser.add_argument('--batch_size', type=int, default=32, help='batch size')
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args = parser.parse_args()
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run(args.device, args.epochs, neg_sample=args.neg_sample, neg_num=args.neg_num, dataset=args.dataset,
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dev_log_interval=args.dev_log_interval, batch_size=args.batch_size) |