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    ’7?eA  ã                   @   sH   d 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 )z#Layer that averages several inputs.é    )Ú_Merge)Úkeras_exportzkeras.layers.Averagec                   @   s   e Zd ZdZdd„ ZdS )ÚAveragea¡  Layer that 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).

    Example:

    >>> x1 = np.ones((2, 2))
    >>> x2 = np.zeros((2, 2))
    >>> y = tf.keras.layers.Average()([x1, x2])
    >>> y.numpy().tolist()
    [[0.5, 0.5], [0.5, 0.5]]

    Usage in a functional model:

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

    Raises:
      ValueError: If there is a shape mismatch between the inputs and the shapes
        cannot be broadcasted to match.
    c                 C   s4   |d }t dt|ƒƒD ]}||| 7 }q|t|ƒ S )Nr   é   )ÚrangeÚlen)ÚselfÚinputsÚoutputÚi© r   úa/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/keras/src/layers/merging/average.pyÚ_merge_function6   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 )aÓ  Functional interface to the `tf.keras.layers.Average` layer.

    Example:

    >>> x1 = np.ones((2, 2))
    >>> x2 = np.zeros((2, 2))
    >>> y = tf.keras.layers.Average()([x1, x2])
    >>> y.numpy().tolist()
    [[0.5, 0.5], [0.5, 0.5]]

    Usage in a functional model:

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

    Args:
        inputs: A list of input tensors.
        **kwargs: Standard layer keyword arguments.

    Returns:
        A tensor, the average of the inputs.

    Raises:
      ValueError: If there is a shape mismatch between the inputs and the shapes
        cannot be broadcasted to match.
    Nr   )r   )r	   Úkwargsr   r   r   Úaverage=   s   !r   N)r   Z#keras.src.layers.merging.base_merger   Z tensorflow.python.util.tf_exportr   r   r   r   r   r   r   Ú<module>   s   $