keras (version 2.7.0)

layer_global_average_pooling_2d: Global average pooling operation for spatial data.

Description

Global average pooling operation for spatial data.

Usage

layer_global_average_pooling_2d(
  object,
  data_format = NULL,
  keepdims = FALSE,
  ...
)

Arguments

object

What to call the new Layer instance with. Typically a keras Model, another Layer, or a tf.Tensor/KerasTensor. If object is missing, the Layer instance is returned, otherwise, layer(object) is returned.

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".

keepdims

A boolean, whether to keep the spatial dimensions or not. If keepdims is FALSE (default), the rank of the tensor is reduced for spatial dimensions. If keepdims is TRUE, the spatial dimensions are retained with length 1. The behavior is the same as for tf.reduce_mean or np.mean.

...

standard layer arguments.

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

2D tensor with shape: (batch_size, channels)

See Also

Other pooling layers: layer_average_pooling_1d(), layer_average_pooling_2d(), layer_average_pooling_3d(), layer_global_average_pooling_1d(), layer_global_average_pooling_3d(), layer_global_max_pooling_1d(), layer_global_max_pooling_2d(), layer_global_max_pooling_3d(), layer_max_pooling_1d(), layer_max_pooling_2d(), layer_max_pooling_3d()