
    0h4                     h    d Z ddlmZ ddlmZ  ed       G d de             Z ed      d        Zy	)
z4Layer that multiplies (element-wise) several inputs.    )_Merge)keras_exportzkeras.layers.Multiplyc                       e Zd ZdZd Zy)Multiplya  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                 T    |d   }t        dt        |            D ]
  }|||   z  } |S )Nr      )rangelen)selfinputsoutputis       ^/var/www/html/engine/venv/lib/python3.12/site-packages/tf_keras/src/layers/merging/multiply.py_merge_functionzMultiply._merge_function/   s8    q#f+& 	(AfQi'F	(    N)__name__
__module____qualname____doc__r    r   r   r   r      s    *r   r   zkeras.layers.multiplyc                 $     t        di ||       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.
    r   )r   )r   kwargss     r   multiplyr   6   s    < 8ff%%r   N)r   &tf_keras.src.layers.merging.base_merger    tensorflow.python.util.tf_exportr   r   r   r   r   r   <module>r      sO    ; : : %&v  ': %&& '&r   