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Hey! First of all thanks for the tutorial, I have a problem and not able to resolve it.
The accuracy what I have got is around 63% it's not good enough has mentioned in the video so I thought of adding more bidirectional LSTM layers to the existing network to check out the result but I am getting this error. Please help me to resolve this issue.
Hey! First of all thanks for the tutorial, I have a problem and not able to resolve it.
The accuracy what I have got is around 63% it's not good enough has mentioned in the video so I thought of adding more bidirectional LSTM layers to the existing network to check out the result but I am getting this error. Please help me to resolve this issue.
The Error which I am getting is this,
IndexError Traceback (most recent call last)
in ()
6 bi_lstm = Bidirectional(LSTM(lstm_layer_dim))(batch_norm)
7 drop_out = Dropout(0.25)(bi_lstm)
----> 8 bi_lstm_1 = Bidirectional(LSTM(lstm_layer_dim_1))(drop_out)
9 drop_out_1 = Dropout(0.25)(bi_lstm_1)
10 preds = Dense(2, activation = 'softmax')(drop_out_1)
C:\Users\Akshath\AppData\Local\Continuum\Anaconda3\envs\py35\lib\site-packages\keras\engine\topology.py in call(self, inputs, **kwargs)
573 '
layer.build(batch_input_shape)
')574 if len(input_shapes) == 1:
--> 575 self.build(input_shapes[0])
576 else:
577 self.build(input_shapes)
C:\Users\Akshath\AppData\Local\Continuum\Anaconda3\envs\py35\lib\site-packages\keras\layers\wrappers.py in build(self, input_shape)
322 def build(self, input_shape):
323 with K.name_scope(self.forward_layer.name):
--> 324 self.forward_layer.build(input_shape)
325 with K.name_scope(self.backward_layer.name):
326 self.backward_layer.build(input_shape)
C:\Users\Akshath\AppData\Local\Continuum\Anaconda3\envs\py35\lib\site-packages\keras\layers\recurrent.py in build(self, input_shape)
1015
1016 batch_size = input_shape[0] if self.stateful else None
-> 1017 self.input_dim = input_shape[2]
1018 self.input_spec[0] = InputSpec(shape=(batch_size, None, self.input_dim))
1019
IndexError: tuple index out of range
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