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    ·2úh¦  ã                   @   sP   d dl mZ d dlmZ d dlmZ edƒG dd„ deƒƒZedƒdd	„ ƒZd
S )é    )Úops)Úkeras_export)ÚMergezkeras.layers.Averagec                   @   s   e Zd ZdZdd„ ZdS )ÚAveragea0  Averages a list of inputs element-wise..

    It takes as input a list of tensors, all of the same shape,
    and returns a single tensor (also of the same shape).

    Examples:

    >>> input_shape = (2, 3, 4)
    >>> x1 = np.random.rand(*input_shape)
    >>> x2 = np.random.rand(*input_shape)
    >>> y = keras.layers.Average()([x1, x2])

    Usage in a Keras model:

    >>> input1 = keras.layers.Input(shape=(16,))
    >>> x1 = keras.layers.Dense(8, activation='relu')(input1)
    >>> input2 = keras.layers.Input(shape=(32,))
    >>> x2 = keras.layers.Dense(8, activation='relu')(input2)
    >>> # equivalent to `y = keras.layers.average([x1, x2])`
    >>> y = keras.layers.Average()([x1, x2])
    >>> out = keras.layers.Dense(4)(y)
    >>> model = keras.models.Model(inputs=[input1, input2], outputs=out)

    c                 C   s8   |d }t dt|ƒƒD ]
}t ||| ¡}q|t|ƒ S )Nr   é   )ÚrangeÚlenr   Úadd)ÚselfÚinputsÚoutputÚi© r   ú[/var/www/html/chatgem/venv/lib/python3.10/site-packages/keras/src/layers/merging/average.pyÚ_merge_function!   s   zAverage._merge_functionN)Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   r   r   r   r   r      s    r   zkeras.layers.averagec                 K   s   t di |¤Ž| ƒS )ay  Functional interface to the `keras.layers.Average` layer.

    Args:
        inputs: A list of input tensors , all of the same shape.
        **kwargs: Standard layer keyword arguments.

    Returns:
        A tensor as the element-wise product of the inputs with the same
        shape as the inputs.

    Examples:

    >>> input_shape = (2, 3, 4)
    >>> x1 = np.random.rand(*input_shape)
    >>> x2 = np.random.rand(*input_shape)
    >>> y = keras.layers.average([x1, x2])

    Usage in a Keras model:

    >>> input1 = keras.layers.Input(shape=(16,))
    >>> x1 = keras.layers.Dense(8, activation='relu')(input1)
    >>> input2 = keras.layers.Input(shape=(32,))
    >>> x2 = keras.layers.Dense(8, activation='relu')(input2)
    >>> y = keras.layers.average([x1, x2])
    >>> out = keras.layers.Dense(4)(y)
    >>> model = keras.models.Model(inputs=[input1, input2], outputs=out)

    Nr   )r   )r   Úkwargsr   r   r   Úaverage(   s   r   N)Ú	keras.srcr   Úkeras.src.api_exportr   Ú#keras.src.layers.merging.base_merger   r   r   r   r   r   r   Ú<module>   s    !