Dimensions must be equal, but are 15 and 100 for 'att_layer_2/mul' (op: 'Mul') with input shapes: [?,15], [?,15,100]. #37
Description
When I ran by using python textClassifierHATT.py in Anaconda, I got this error:
Using TensorFlow backend.
(25000, 3)
textClassifierHATT.py:56: UserWarning: No parser was explicitly specified, so I'm using the best available HTML parser for this system ("html.parser"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently.
The code that caused this warning is on line 56 of the file textClassifierHATT.py. To get rid of this warning, pass the additional argument 'features="html.parser"' to the BeautifulSoup constructor.
text = BeautifulSoup(data_train.review[idx])
/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/keras_preprocessing/text.py:177: UserWarning: The nb_words argument in Tokenizer has been renamed num_words.
warnings.warn('The nb_words argument in Tokenizer '
Total 80568 unique tokens.
('Shape of data tensor:', (25000, 15, 100))
('Shape of label tensor:', (25000, 2))
Number of positive and negative reviews in traing and validation set
[10026. 9974.]
[2474. 2526.]
Total 400000 word vectors.
2018-11-20 09:49:08.166457: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Traceback (most recent call last):
File "textClassifierHATT.py", line 188, in
l_att_sent = AttLayer(100)(l_lstm_sent)
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/keras/engine/base_layer.py", line 457, in call
output = self.call(inputs, **kwargs)
File "textClassifierHATT.py", line 167, in call
ait *= K.cast(mask, K.floatx())
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 866, in binary_op_wrapper
return func(x, y, name=name)
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 1131, in _mul_dispatch
return gen_math_ops.mul(x, y, name=name)
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 5042, in mul
"Mul", x=x, y=y, name=name)
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
op_def=op_def)
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1792, in init
control_input_ops)
File "/home/user/anaconda3/envs/py27_env/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1631, in _create_c_op
raise ValueError(str(e))
ValueError: Dimensions must be equal, but are 15 and 100 for 'att_layer_2/mul' (op: 'Mul') with input shapes: [?,15], [?,15,100].
What was going wrong？Can anyone help me？