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Max pooling operation for temporal data.
tf.keras.layers.MaxPool1D(
pool_size=2, strides=None, padding='valid', data_format='channels_last',
**kwargs
)
pool_size
: Integer, size of the max pooling windows.strides
: Integer, or None. Factor by which to downscale.
E.g. 2 will halve the input.
If None, it will default to pool_size
.padding
: One of "valid"
or "same"
(case-insensitive).data_format
: A string,
one of channels_last
(default) or channels_first
.
The ordering of the dimensions in the inputs.
channels_last
corresponds to inputs with shape
(batch, steps, features)
while channels_first
corresponds to inputs with shape
(batch, features, steps)
.data_format='channels_last'
:
3D tensor with shape (batch_size, steps, features)
.data_format='channels_first'
:
3D tensor with shape (batch_size, features, steps)
.data_format='channels_last'
:
3D tensor with shape (batch_size, downsampled_steps, features)
.data_format='channels_first'
:
3D tensor with shape (batch_size, features, downsampled_steps)
.