textClassifierRNN.py

[followsun]

File "/usr/local/lib/python3.5/dist-packages/keras/models.py", line 455, in add
output_tensor = layer(self.outputs[0])
File "/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py", line 554, in call
output = self.call(inputs, **kwargs)
File "/home/l148/xuyang/workshop/EEGDNN/Motor imagery classification/seg_CSP_ConvLSTM_debug.py", line 112, in call
eij = K.tanh(K.dot(x,self.W))
File "/usr/local/lib/python3.5/dist-packages/keras/backend/tensorflow_backend.py", line 838, in dot
y_permute_dim = [y_permute_dim.pop(-2)] + y_permute_dim
IndexError: pop index out of range

[xiaoleihuang]

I got a similar error...
IndexError: pop index out of range

IndexError Traceback (most recent call last)
in ()
4 l_lstm = Bidirectional(LSTM(100, return_sequences=True))(embedded_sequences)
5 l_dense = TimeDistributed(Dense(200))(l_lstm)
----> 6 l_att = AttLayer()(l_dense)
7 sentEncoder = Model(sentence_input, l_att)
8

/anaconda3/lib/python3.6/site-packages/keras/engine/topology.py in call(self, inputs, **kwargs)
552
553 # Actually call the layer, collecting output(s), mask(s), and shape(s).
--> 554 output = self.call(inputs, **kwargs)
555 output_mask = self.compute_mask(inputs, previous_mask)
556

in call(self, x, mask)
20
21 def call(self, x, mask=None):
---> 22 eij = K.tanh(K.dot(x, self.W))
23
24 ai = K.exp(eij)

/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in dot(x, y)
836 y_shape = tuple(y_shape)
837 y_permute_dim = list(range(ndim(y)))
--> 838 y_permute_dim = [y_permute_dim.pop(-2)] + y_permute_dim
839 xt = tf.reshape(x, [-1, x_shape[-1]])
840 yt = tf.reshape(tf.transpose(y, perm=y_permute_dim), [y_shape[-2], -1])

IndexError: pop index out of range

[rucJuanLi]

I think maybe you should use Theano backend.