tf.compat.v1.layers.average_pooling2d

Average pooling layer for 2D inputs (e.g. images).

tf.compat.v1.layers.average_pooling2d(
    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.AveragePooling2D.

Structural Mapping to Native TF2

None of the supported arguments have changed name.

Before:

 y = tf.compat.v1.layers.average_pooling2d(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.AveragePooling2D(pool_size=2, strides=2)(x)
 model = tf.keras.Model(x, y)

Description

inputs The tensor over which to pool. Must have rank 4.
pool_size An integer or tuple/list of 2 integers: (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 2 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, height, width, channels) while channels_first corresponds to inputs with shape (batch, channels, height, width).
name A string, the name of the layer.

Output tensor.

ValueError if eager execution is enabled.