Transfer masking in Keras
Project description
Keras Transfer Masking
Remove and restore masks for layers that do not support masking. Note that the result may be incorrect in most cases.
Install
pip install keras-trans-mask
Usage
Conv1D
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()
Project details
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keras-trans-mask-0.6.0.tar.gz
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