TextRCNN 模型报错，维度不一致。

[rucJuanLi]

output_conv=self.conv_layer_with_recurrent_structure() #shape:[None,sentence_length,embed_size*3]
File "/home/juan_li/work_bishe/text_classification-master/text_classification-master/a04_TextRCNN/p71_TextRCNN_model_hg.py", line 122, in conv_layer_with_recurrent_structure
representation=tf.concat([context_left_list[index],current_embedding_word,context_right_list[index]],axis=1)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/array_ops.py", line 1099, in concat
return gen_array_ops._concat_v2(values=values, axis=axis, name=name)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 706, in _concat_v2
"ConcatV2", values=values, axis=axis, name=name)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 2956, in create_op
op_def=op_def)
File "/usr/local/lib/python3.4/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): ConcatOp : Dimensions of inputs should match: shape[0] = [64,100] vs. shape[1] = [1,100]
[[Node: concat = ConcatV2[N=3, T=DT_FLOAT, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Tanh, Squeeze, Tanh_300, concat/axis)]]

TextRCNN 报错。

[xuehui0725]

请问这个问题你解决了吗？我也碰到了 @rucJuanLi

[TingNLP]

I have a same error...
Is there a solution?