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    ’7?e1  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 )z4Layer that multiplies (element-wise) several inputs.é    )Ú_Merge)Úkeras_exportzkeras.layers.Multiplyc                   @   s   e Zd ZdZdd„ ZdS )ÚMultiplya³  Layer that multiplies (element-wise) a list of inputs.

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

    >>> tf.keras.layers.Multiply()([np.arange(5).reshape(5, 1),
    ...                             np.arange(5, 10).reshape(5, 1)])
    <tf.Tensor: shape=(5, 1), dtype=int64, numpy=
    array([[ 0],
         [ 6],
         [14],
         [24],
         [36]])>

    >>> x1 = tf.keras.layers.Dense(8)(np.arange(10).reshape(5, 2))
    >>> x2 = tf.keras.layers.Dense(8)(np.arange(10, 20).reshape(5, 2))
    >>> multiplied = tf.keras.layers.Multiply()([x1, x2])
    >>> multiplied.shape
    TensorShape([5, 8])
    c                 C   s,   |d }t dt|ƒƒD ]}|||  }q|S )Nr   é   )ÚrangeÚlen)ÚselfÚinputsÚoutputÚi© r   úb/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/keras/src/layers/merging/multiply.pyÚ_merge_function/   s   zMultiply._merge_functionN)Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   r   r   r   r   r      s    r   zkeras.layers.multiplyc                 K   s   t di |¤Ž| ƒS )a¡  Functional interface to the `Multiply` layer.

    Example:

    >>> x1 = np.arange(3.0)
    >>> x2 = np.arange(3.0)
    >>> tf.keras.layers.multiply([x1, x2])
    <tf.Tensor: shape=(3,), dtype=float32, numpy=array([0., 1., 4.], ...)>

    Usage in a functional model:

    >>> input1 = tf.keras.layers.Input(shape=(16,))
    >>> x1 = tf.keras.layers.Dense(
    ...     8, activation='relu')(input1) #shape=(None, 8)
    >>> input2 = tf.keras.layers.Input(shape=(32,))
    >>> x2 = tf.keras.layers.Dense(
    ...     8, activation='relu')(input2) #shape=(None, 8)
    >>> out = tf.keras.layers.multiply([x1,x2]) #shape=(None, 8)
    >>> out = tf.keras.layers.Dense(4)(out)
    >>> 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 element-wise product of the inputs.
    Nr   )r   )r	   Úkwargsr   r   r   Úmultiply6   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   