from keras.models import Sequential
from keras.layers import Dense,LSTM
​
model = Sequential()
model.add(LSTM(units=20,input_shape=(X_train.shape[1],X_train.shape[2]),activation=‘relu’))
model.add(Dense(units=num_letters,activation=‘softmax’))
model.compile(optimizer=‘adam’,loss=‘categorical_crossentropy’,metrics=[‘accuracy’])
model.summary()

TypeError Traceback (most recent call last)
in
3
4 model = Sequential()
----> 5 model.add(LSTM(units=20,input_shape=(X_train.shape[1],X_train.shape[2]),activation=‘relu’))
6 model.add(Dense(units=num_letters,activation=‘softmax’))
7 model.compile(optimizer=‘adam’,loss=‘categorical_crossentropy’,metrics=[‘accuracy’])

D:\Anaconda\envs\py36\lib\site-packages\keras\engine\sequential.py in add(self, layer)
163 # and create the node connecting the current layer
164 # to the input layer we just created.
–> 165 layer(x)
166 set_inputs = True
167 else:

D:\Anaconda\envs\py36\lib\site-packages\keras\layers\recurrent.py in call(self, inputs, initial_state, constants, **kwargs)
530
531 if initial_state is None and constants is None:
–> 532 return super(RNN, self).call(inputs, **kwargs)
533
534 # If any of initial_state or constants are specified and are Keras

D:\Anaconda\envs\py36\lib\site-packages\keras\engine\base_layer.py in call(self, inputs, **kwargs)
455 # Actually call the layer,
456 # collecting output(s), mask(s), and shape(s).
–> 457 output = self.call(inputs, **kwargs)
458 output_mask = self.compute_mask(inputs, previous_mask)
459

D:\Anaconda\envs\py36\lib\site-packages\keras\layers\recurrent.py in call(self, inputs, mask, training, initial_state)
2192 mask=mask,
2193 training=training,
-> 2194 initial_state=initial_state)
2195
2196 @property

D:\Anaconda\envs\py36\lib\site-packages\keras\layers\recurrent.py in call(self, inputs, mask, training, initial_state, constants)
647 mask=mask,
648 unroll=self.unroll,
–> 649 input_length=timesteps)
650 if self.stateful:
651 updates = []

D:\Anaconda\envs\py36\lib\site-packages\keras\backend\tensorflow_backend.py in rnn(step_function, inputs, initial_states, go_backwards, mask, constants, unroll, input_length)
3009 parallel_iterations=32,
3010 swap_memory=True,
-> 3011 maximum_iterations=input_length)
3012 last_time = final_outputs[0]
3013 output_ta = final_outputs[1]

TypeError: while_loop() got an unexpected keyword argument ‘maximum_iterations’