GlobalAveragePooling2D

  • namespace: Rindow\NeuralNetworks\Layer
  • classname: GlobalAveragePooling2D

Global mean for each channel in image data.

GlobalAveragePooling2D implements the operation:

  • output := globalaveragepooling(input)

Methods

constructor

$builer->GlobalAveragePooling2D(
    string $data_format='channels_last',
    array $input_shape=null,
    string $name=null,
)

You can create a GlobalAveragePooling2D layer instances with the Layer Builder.

Options

  • data_format: Either “channels_last” or “channels_first”. Specify which of the input shapes is the channel.
  • input_shape: Specify the first layer the shape of the input data. In input_shape, the batch dimension is not included.

Input shape

[Batch size, height, width, number of channels] when data_format is “channels_last”, [Batch size, number of input channels, height, width] when “channels_first”. Four-dimensional NDArray.

Output shape

[Batch size, channels] regardless of input shape and data_format. two-dimensional NDArray.

Examples

$model->add($nn->layers()->GlobalAveragePooling2D());