tf.compat.v1.layers.average_pooling3d

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

tf.compat.v1.layers.average_pooling3d(
    inputs, pool_size, strides, padding='valid',
    data_format='channels_last', name=None
)

Migrate to TF2

This API is not compatible with eager execution or tf.function.

Please refer to tf.layers section of the migration guide to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2 layer is tf.keras.layers.AveragePooling3D.

Structural Mapping to Native TF2

None of the supported arguments have changed name.

Before:

 y = tf.compat.v1.layers.average_pooling3d(x, pool_size=2, strides=2)

After:

To migrate code using TF1 functional layers use the Keras Functional API:

 x = tf.keras.Input((28, 28, 1))
 y = tf.keras.layers.AveragePooling3D(pool_size=2, strides=2)(x)
 model = tf.keras.Model(x, y)

Description

inputs The tensor over which to pool. Must have rank 5.
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.

Output tensor.

ValueError if eager execution is enabled.