Masks a sequence by using a mask value to skip timesteps.
For each timestep in the input tensor (dimension #1 in the tensor),
if all values in the input tensor at that timestep
are equal to mask_value, then the timestep will be masked (skipped)
in all downstream layers (as long as they support masking).
If any downstream layer does not support masking yet receives such
an input mask, an exception will be raised.
Masking(mask_value, input_shape = NULL)
mask_value |
the value to use in the masking |
input_shape |
only need when first layer of a model; sets the input shape of the data |
Taylor B. Arnold, taylor.arnold@acm.org
Chollet, Francois. 2015. Keras: Deep Learning library for Theano and TensorFlow.
Other layers: Activation,
ActivityRegularization,
AdvancedActivation,
BatchNormalization, Conv,
Dense, Dropout,
Embedding, Flatten,
GaussianNoise, LayerWrapper,
LocallyConnected, MaxPooling,
Permute, RNN,
RepeatVector, Reshape,
Sequential
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