tf.compat.v1.layers.AveragePooling2D

Average pooling layer for 3D inputs (e.g. volumes).

Inherits From: AveragePooling3D, Layer, Layer, Module

tf.compat.v1.layers.AveragePooling3D(
    pool_size, strides, padding='valid',
    data_format='channels_last', name=None, **kwargs
)

Arguments
`pool_size`	An integer or tuple/list of 3 integers: (pool_depth, pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions.
`strides`	An integer or tuple/list of 3 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions.
`padding`	A string. The padding method, either 'valid' or 'same'. Case-insensitive.
`data_format`	A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, depth, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, depth, height, width)`.
`name`	A string, the name of the layer.

Attributes
`graph`
`scope_name`

TensorFlow

tf.compat / v1 / v1.layers.AveragePooling2D

Arguments

Attributes

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.compat / v1 / v1.layers.AveragePooling2D

Arguments

Attributes