
    0hD                     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	)
z#Layer that averages several inputs.    )_Merge)keras_exportzkeras.layers.Averagec                       e Zd ZdZd Zy)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                 l    |d   }t        dt        |            D ]
  }|||   z  } |t        |      z  S )Nr      )rangelen)selfinputsoutputis       ]/var/www/html/engine/venv/lib/python3.12/site-packages/tf_keras/src/layers/merging/average.py_merge_functionzAverage._merge_function6   sB    q#f+& 	 AfQiF	 F##    N)__name__
__module____qualname____doc__r    r   r   r   r      s    8$r   r   zkeras.layers.averagec                 $     t        di ||       S )a  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.
    r   )r   )r   kwargss     r   averager   =   s    B 7VV$$r   N)r   &tf_keras.src.layers.merging.base_merger    tensorflow.python.util.tf_exportr   r   r   r   r   r   <module>r      sP    * : : $%!$f !$ &!$H $% % & %r   