'tgt': optimizer_tgt,
'cl': optimizer_cl,
'ct': optimizer_ct,
'clct': optimizer_clct
}
processor = SeqLabelProcessor(gpu=use_gpu)
train_args = vars(args)
train_args['word_embed_size'] = word_embed_1.num_embeddings
state = {
'model': {
'word_embed': word_embed_1.state_dict(),
'char_embed': char_embed.state_dict(),
'char_hw': char_hw.state_dict(),
'lstm': lstm.state_dict(),
'crf': crf_1.state_dict(),
'univ_linear': shared_linear_1.state_dict(),
'spec_linear': spec_linear_1_1.state_dict(),
'lstm_crf': lstm_crf_tgt.state_dict()
},
'args': train_args,
'vocab': {
'token': token_vocab_1,
'label': label_vocab_1,
'char': char_vocab,
}
}
# Calculate mixing rates
batch_num = len(train_set_tgt) // batch_size
r_tgt = math.sqrt(len(train_set_tgt))
# Task
optimizer = optim.SGD(filter(lambda p: p.requires_grad, lstm_crf.parameters()),
lr=args.lr,
momentum=args.momentum)
processor = SeqLabelProcessor(gpu=use_gpu)
train_args = vars(args)
train_args['word_embed_size'] = word_embed.num_embeddings
state = {
'model': {
'word_embed': word_embed.state_dict(),
'char_embed': char_embed.state_dict(),
'char_hw': char_hw.state_dict(),
'lstm': lstm.state_dict(),
'crf': crf.state_dict(),
'linear': linear.state_dict(),
'lstm_crf': lstm_crf.state_dict()
},
'args': train_args,
'vocab': {
'token': token_vocab,
'label': label_vocab,
'char': char_vocab,
}
}
try:
global_step = 0
best_dev_score = best_test_score = 0.0
for epoch in range(args.max_epoch):
momentum=args.momentum)
optimizers = {
'tgt': optimizer_tgt,
'cl': optimizer_cl,
'ct': optimizer_ct,
'clct': optimizer_clct
}
state = {
'model': {
'word_embed_1': word_embed_1.state_dict(),
'word_embed_2': word_embed_2.state_dict(),
'char_cnn': char_cnn.state_dict(),
'char_highway': char_highway.state_dict(),
'lstm': lstm.state_dict(),
'crf_1': crf_1.state_dict(),
'crf_2': crf_2.state_dict(),
'shared_output_linear_1': shared_output_linear_1.state_dict(),
'spec_output_linear_1_1': spec_output_linear_1_1.state_dict(),
'spec_output_linear_1_2': spec_output_linear_1_2.state_dict(),
'shared_output_linear_2': shared_output_linear_2.state_dict(),
'spec_output_linear_2_1': spec_output_linear_2_1.state_dict(),
'spec_output_linear_2_2': spec_output_linear_2_2.state_dict(),
'lstm_crf_tgt': lstm_crf_tgt.state_dict(),
'lstm_crf_cl': lstm_crf_cl.state_dict(),
'lstm_crf_ct': lstm_crf_ct.state_dict(),
'lstm_crf_clct': lstm_crf_clct.state_dict()
},
'args': vars(args),
'vocab': {
'token_1': token_vocab_1,
