
    2Vh                     p    d dl mZ d dlmZ d dlmZ  ed       G d de             Z ed      d        Zy	)
    )ops)keras_export)Mergezkeras.layers.Averagec                       e Zd ZdZd Zy)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                     |d   }t        dt        |            D ]  }t        j                  |||         } |t        |      z  S )Nr      )rangelenr   add)selfinputsoutputis       P/home/dcms/DCMS/lib/python3.12/site-packages/keras/src/layers/merging/average.py_merge_functionzAverage._merge_function!   sH    q#f+& 	0AWWVVAY/F	0F##    N)__name__
__module____qualname____doc__r    r   r   r   r      s    2$r   r   zkeras.layers.averagec                 $     t        di ||       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)

    r   )r   )r   kwargss     r   averager   (   s    < 7VV$$r   N)	keras.srcr   keras.src.api_exportr   #keras.src.layers.merging.base_merger   r   r   r   r   r   <module>r      sJ     - 5 $%$e $ &$B $%% &%r   