Average pooling operation for spatial data.
Inherits From: Layer, Module
tf.keras.layers.AveragePooling2D(
pool_size=(2, 2), strides=None, padding='valid', data_format=None,
**kwargs
)
Arguments |
|---|
pool_size
|
integer or tuple of 2 integers,
factors by which to downscale (vertical, horizontal).
(2, 2) will halve the input in both spatial dimension.
If only one integer is specified, the same window length
will be used for both dimensions.
|
strides
|
Integer, tuple of 2 integers, or None.
Strides values.
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, height, width, channels) while channels_first
corresponds to inputs with shape
(batch, channels, height, width).
It defaults to the image_data_format value found in your
Keras config file at ~/.keras/keras.json.
If you never set it, then it will be "channels_last".
|
- If
data_format='channels_last':
4D tensor with shape (batch_size, rows, cols, channels).
- If
data_format='channels_first':
4D tensor with shape (batch_size, channels, rows, cols).
Output shape:
- If
data_format='channels_last':
4D tensor with shape (batch_size, pooled_rows, pooled_cols, channels).
- If
data_format='channels_first':
4D tensor with shape (batch_size, channels, pooled_rows, pooled_cols).
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