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Transfer masking in Keras

Project description

Keras Transfer Masking

Travis Coverage

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:

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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