tf.keras.layers.AveragePooling2D

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
)

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".

Input shape:

  • 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).