Wsrtjtyk

I'm trying to design a neural network including time dependent input with different lengths and I'm currently using a Masking layer.
This network worked well with TensorFlow version 1.9.0 but after updating to version 1.11.0, I get the following error:

Layer conv2d_1 does not support masking, but was passed an input_mask: Tensor("cnn1/Reshape_2:0", shape=(?, 81, 81), dtype=bool)

Any idea on how to solve this problem?

I'm using the following code:

from keras.models import Sequential

from keras.layers import Conv2D, MaxPooling2D, 

    TimeDistributed, Dense, Masking, Activation, BatchNormalization



model= Sequential()

# first layer

model.add(TimeDistributed(Masking(0., input_shape=(81,81,3)),

                                  input_shape=(None,81,81,3), name='mask'))

# CNN layers

model.add(TimeDistributed(Conv2D(filters=10,

                                 kernel_size=5,

                                 strides=1,

                                 padding='same'),

                         name='cnn1'))



model.add(Activation('relu', name='relu1'))

model.add(BatchNormalization())

model.add(TimeDistributed(MaxPooling2D(pool_size=(2, 2))))



# output layer

model.add(TimeDistributed(Dense(3, name='output')))

model.add(Activation('softmax'))



# compilation

model.compile(loss='categorical_crossentropy')