Remove and restore masks for layers that do not support masking. Note that the result may be incorrect in most cases.
pip install keras-trans-maskConv1D does not support masking. By removing the mask you'll get a "nearly correct" output:
from tensorflow import keras
from keras_trans_mask import RemoveMask, RestoreMask
input_layer = keras.layers.Input(shape=(None,))
embed_layer = keras.layers.Embedding(
input_dim=10,
output_dim=15,
mask_zero=True,
)(input_layer)
removed_layer = RemoveMask()(embed_layer) # Remove mask from embeddings
conv_layer = keras.layers.Conv1D(
filters=32,
kernel_size=3,
padding='same',
)(removed_layer)
restored_layer = RestoreMask()([conv_layer, embed_layer]) # Restore mask from embeddings
lstm_layer = keras.layers.LSTM(units=5)(restored_layer)
dense_layer = keras.layers.Dense(units=2, activation='softmax')(lstm_layer)
model = keras.models.Model(inputs=input_layer, outputs=dense_layer)
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy')
model.summary()