(我自己print出来的train_path.txt文件)
.\data_path\train_data.txt
(自己print train_data.txt 文件为空)
[]
Namespace(CRF=True, batch_size=64, clip=5.0, demo_model='1521112368', dropout=0.5, embedding_dim=300, epoch=5, hidden_dim=300, lr=0.001, mode='train', optimizer='Adam', pretrain_embedding='random', shuffle=True, test_data='data_path
', train_data='data_path', update_embedding=True)
C:\Users\le\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gradients_impl.py:112: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of me
mory.
"Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
train data: 0 (train_data值为0)
(我自己print出来的train_path.txt文件) .\data_path\train_data.txt (自己print train_data.txt 文件为空) [] Namespace(CRF=True, batch_size=64, clip=5.0, demo_model='1521112368', dropout=0.5, embedding_dim=300, epoch=5, hidden_dim=300, lr=0.001, mode='train', optimizer='Adam', pretrain_embedding='random', shuffle=True, test_data='data_path ', train_data='data_path', update_embedding=True) C:\Users\le\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gradients_impl.py:112: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of me mory. "Converting sparse IndexedSlices to a dense Tensor of unknown shape. " train data: 0 (train_data值为0)