Average pooling for temporal data.
Inherits From: Layer, Module
tf.keras.layers.AveragePooling1D(
pool_size=2, strides=None, padding='valid',
data_format='channels_last', **kwargs
)
Arguments |
|---|
pool_size
|
Integer, size of the average 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).
"valid" means no padding. "same" results in padding evenly to
the left/right or up/down of the input such that output has the same
height/width dimension as the input.
|
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).
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TensorFlow 1 version
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