Yijun-Mao
commented
5 years ago 我在用data中的小规模数据训练的时候出现了下面的错误，因为数据规模小，所以同时将post和response词表的大小都改成了100，不知道有没有这方面的原因。
Caused by op _u'model_with_buckets/embedding_attention_seq2seq_1/embedding_attention_decoder/attention_decoder/Reshape_3',_` defined at: File "baseline.py", line 392, in <module> tf.app.run() File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 48, in run _sys.exit(main(_sys.argv[:1] + flags_passthrough)) File "baseline.py", line 388, in main train() File "baseline.py", line 195, in train model = create_model(sess, False, False) File "baseline.py", line 139, in create_model dtype=dtype) File "/home/emotion_generation/mcy/ecm/seq2seq_model.py", line 157, in __init__ softmax_loss_function=softmax_loss_function, use_imemory=use_imemory, use_ememory=use_ememory) File "/home/emotion_generation/mcy/ecm/seq2seq.py", line 1322, in model_with_buckets decoder_inputs[:bucket[1]], decoder_emotions) File "/home/emotion_generation/mcy/ecm/seq2seq_model.py", line 156, in <lambda> lambda x, y, z: seq2seq_f(x, y, z, False), File "/home/emotion_generation/mcy/ecm/seq2seq_model.py", line 119, in seq2seq_f beam_size=beam_size) File "/home/emotion_generation/mcy/ecm/seq2seq.py", line 1171, in embedding_attention_seq2seq beam_size=beam_size) File "/home/emotion_generation/mcy/ecm/seq2seq.py", line 1055, in embedding_attention_decoder initial_state_attention=initial_state_attention) File "/home/emotion_generation/mcy/ecm/seq2seq.py", line 701, in attention_decoder s1 = tf.nn.softmax(output1, dim=0) * g File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py", line 1667, in softmax return _softmax(logits, gen_nn_ops._softmax, dim, name) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py", line 1630, in _softmax logits = _flatten_outer_dims(logits) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py", line 1551, in _flatten_outer_dims output = array_ops.reshape(logits, array_ops.concat([[-1], last_dim_size], 0)) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 3938, in reshape "Reshape", tensor=tensor, shape=shape, name=name) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper op_def=op_def) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2956, in create_op op_def=op_def) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1470, in __init__ self._traceback = self._graph._extract_stack() # pylint: disable=protected-access InvalidArgumentError (see above for traceback): Reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero [[Node: model_with_buckets/embedding_attention_seq2seq_1/embedding_attention_decoder/attention_decoder/Reshape_3 = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:GPU:0"](model_with_buckets/embedding_attention_seq2seq_1/embedding_attention_decoder/attention_decoder/transpose_3, model_with_buckets/embedding_attention_seq2seq_1/embedding_attention_decoder/attention_decoder/concat_6)]] [[Node: clip_by_global_norm_1/mul_8/_1657 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_21552_clip_by_global_norm_1/mul_8", tensor_type=DT_FLOAT, `_device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]```您好，我也遇到这个问题了。请问最后你解决了吗？是如何解决的？
luomuqinghan
我在用data中的小规模数据训练的时候出现了下面的错误，因为数据规模小，所以同时将post和response词表的大小都改成了100，不知道有没有这方面的原因。