class_docstr: Global average pooling operation for 2D data.
  
  Args:
      data_format: string, either `"channels_last"` 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, features, height, weight)`. 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 temporal dimension or not.
          If `keepdims` is `False` (default), the rank of the tensor is
          reduced for spatial dimensions. If `keepdims` is `True`, the
          spatial dimension are retained with length 1.
          The behavior is the same as for `tf.reduce_mean` or `np.mean`.
  
  Input shape:
  
  - If `data_format='channels_last'`:
      4D tensor with shape:
      `(batch_size, height, width, channels)`
  - If `data_format='channels_first'`:
      4D tensor with shape:
      `(batch_size, channels, height, width)`
  
  Output shape:
  
  - If `keepdims=False`:
      2D tensor with shape `(batch_size, channels)`.
  - If `keepdims=True`:
      - If `data_format="channels_last"`:
          4D tensor with shape `(batch_size, 1, 1, channels)`
      - If `data_format="channels_first"`:
          4D tensor with shape `(batch_size, channels, 1, 1)`
  
  Example:
  
  >>> x = np.random.rand(2, 4, 5, 3)
  >>> y = keras.layers.GlobalAveragePooling2D()(x)
  >>> y.shape
  (2, 3)
code: def __init__(self, data_format=None, keepdims=False, **kwargs):
      super().__init__(
          pool_dimensions=2,
          data_format=data_format,
          keepdims=keepdims,
          **kwargs,
      )
  
imports: from keras import ops
  from keras.api_export import keras_export
  from keras.layers.pooling.base_global_pooling import BaseGlobalPooling
label_desc: Use image node_id 1 to create a new GlobalAveragePooling2D object from inherited base classes: BaseGlobalPooling with example: obj = GlobalAveragePooling2D(data_format, keepdims)