tf.keras.layers.MaxPool3D | TensorFlow v2.0.0 (original) (raw)

tf.keras.layers.MaxPool3D

Stay organized with collections Save and categorize content based on your preferences.

Max pooling operation for 3D data (spatial or spatio-temporal).

Main aliases

tf.keras.layers.MaxPooling3D

Compat aliases for migration

SeeMigration guide for more details.

tf.keras.layers.MaxPool3D(
    pool_size=(2, 2, 2), strides=None, padding='valid', data_format=None, **kwargs
)

Arguments
pool_size	Tuple of 3 integers, factors by which to downscale (dim1, dim2, dim3).(2, 2, 2) will halve the size of the 3D input in each dimension.
strides	tuple of 3 integers, or None. Strides values.
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, spatial_dim1, spatial_dim2, spatial_dim3, channels)while channels_first corresponds to inputs with shape(batch, channels, spatial_dim1, spatial_dim2, spatial_dim3). 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': 5D tensor with shape:(batch_size, spatial_dim1, spatial_dim2, spatial_dim3, channels)
If data_format='channels_first': 5D tensor with shape:(batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3)

If data_format='channels_last': 5D tensor with shape:(batch_size, pooled_dim1, pooled_dim2, pooled_dim3, channels)
If data_format='channels_first': 5D tensor with shape:(batch_size, channels, pooled_dim1, pooled_dim2, pooled_dim3)

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2020-10-01 UTC.