if args.snapshot is None:
if args.CNN:
print("loading CNN model.....")
model = model_CNN.CNN_Text(args)
elif args.DEEP_CNN:
print("loading DEEP_CNN model......")
model = model_DeepCNN.DEEP_CNN(args)
elif args.LSTM:
print("loading LSTM model......")
model = model_LSTM.LSTM(args)
elif args.GRU:
print("loading GRU model......")
model = model_GRU.GRU(args)
elif args.BiLSTM:
print("loading BiLSTM model......")
model = model_BiLSTM.BiLSTM(args)
elif args.BiLSTM_1:
print("loading BiLSTM_1 model......")
model = model_BiLSTM_1.BiLSTM_1(args)
elif args.CNN_LSTM:
print("loading CNN_LSTM model......")
model = model_CNN_LSTM.CNN_LSTM(args)
elif args.CLSTM:
print("loading CLSTM model......")
model = model_CLSTM.CLSTM(args)
elif args.CBiLSTM:
print("loading CBiLSTM model......")
model = model_CBiLSTM.CBiLSTM(args)
elif args.CGRU:
print("loading CGRU model......")
model = model_CGRU.CGRU(args)
train_topic_var = Variable(torch.LongTensor(topic_index))
train_text_var = Variable(torch.LongTensor(text_index))
train_label_var = Variable(torch.LongTensor(label_index))
# dev_topic_var = Variable(torch.LongTensor(dev_topic_index))
# dev_text_var = Variable(torch.LongTensor(dev_text_index))
# dev_label_var = Variable(torch.LongTensor(dev_label_index))
test_topic_var = Variable(torch.LongTensor(test_topic_index))
test_text_var = Variable(torch.LongTensor(test_text_index))
test_label_var = Variable(torch.LongTensor(test_label_index))
# # print("ssss",test_topic_var)
# print(test_text_var)
# print(test_label_var)
# dev_iter = dataProcessing.create_batches(dev_topic_var, dev_text_var, dev_label_var, params.batch_size)
# print(dev_iter)
test_iter = dataProcessing.create_batches(test_topic_var, test_text_var,
test_label_var,
params.batch_size)
# print(test_iter)
# print("train_var",train_topic_var) #2414x6
# print("train_text_var",train_text_var) #2414x35
# print("train_label_var",train_label_var) #2414x1
if params.use_lstm is True:
model = model_BiLSTM.BiLSTM(params)
if params.cuda_use is True:
model = model.cuda()
train2.train(train_topic_var, train_text_var, train_label_var, model,
label2id, id2label, params, test_iter)