
    2Vh	                     X    d dl mZ d dlmZ d dlmZ  eddg       G d de             Zy)	    )ops)keras_export)BaseGlobalPoolingz#keras.layers.GlobalAveragePooling2Dzkeras.layers.GlobalAvgPool2Dc                   *     e Zd ZdZd fd	Zd Z xZS )GlobalAveragePooling2Da  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)
    c                 ,    t        |   dd||d| y )N   )pool_dimensionsdata_formatkeepdims )super__init__)selfr   r   kwargs	__class__s       a/home/dcms/DCMS/lib/python3.12/site-packages/keras/src/layers/pooling/global_average_pooling2d.pyr   zGlobalAveragePooling2D.__init__9   s(     	
#	
 		
    c                     | j                   dk(  r$t        j                  |ddg| j                        S t        j                  |ddg| j                        S )Nchannels_last   r	   )axisr      )r   r   meanr   )r   inputss     r   callzGlobalAveragePooling2D.callA   sF    .88F!Q$--HHxxaVdmmDDr   )NF)__name__
__module____qualname____doc__r   r   __classcell__)r   s   @r   r   r      s    *X
Er   r   N)	keras.srcr   keras.src.api_exportr   ,keras.src.layers.pooling.base_global_poolingr   r   r   r   r   <module>r%      s=     - J -&8E. 8E8Er   