Max pooling operation for temporal data.
tf.keras.layers.MaxPool1D(
pool_size=2, strides=None, padding='valid', data_format='channels_last',
**kwargs
)
Arguments |
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) .
|
- If
data_format='channels_last'
:
3D tensor with shape (batch_size, steps, features)
.
- If
data_format='channels_first'
:
3D tensor with shape (batch_size, features, steps)
.
Output shape:
- If
data_format='channels_last'
:
3D tensor with shape (batch_size, downsampled_steps, features)
.
- If
data_format='channels_first'
:
3D tensor with shape (batch_size, features, downsampled_steps)
.