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    «»ˆd¶  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 adds several inputs.é    )Ú_Merge)Úkeras_exportzkeras.layers.Addc               @   s   e Zd ZdZdd„ ZdS )ÚAddas  Layer that adds 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).

    Examples:

    >>> input_shape = (2, 3, 4)
    >>> x1 = tf.random.normal(input_shape)
    >>> x2 = tf.random.normal(input_shape)
    >>> y = tf.keras.layers.Add()([x1, x2])
    >>> print(y.shape)
    (2, 3, 4)

    Used 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)
    >>> # equivalent to `added = tf.keras.layers.add([x1, x2])`
    >>> added = tf.keras.layers.Add()([x1, x2])
    >>> out = tf.keras.layers.Dense(4)(added)
    >>> model = tf.keras.models.Model(inputs=[input1, input2], outputs=out)

    c             C   s0   |d }x"t dt|ƒƒD ]}||| 7 }qW |S )Nr   é   )ÚrangeÚlen)ÚselfÚinputsÚoutputÚi© r   úJ/var/www/html/venv/lib/python3.7/site-packages/keras/layers/merging/add.pyÚ_merge_function6   s    zAdd._merge_functionN)Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   r   r   r   r   r      s   r   zkeras.layers.addc             K   s   t f |Ž| ƒS )a¡  Functional interface to the `tf.keras.layers.Add` layer.

    Args:
        inputs: A list of input tensors with the same shape.
        **kwargs: Standard layer keyword arguments.

    Returns:
        A tensor as the sum of the inputs. It has the same shape as the inputs.

    Examples:

    >>> input_shape = (2, 3, 4)
    >>> x1 = tf.random.normal(input_shape)
    >>> x2 = tf.random.normal(input_shape)
    >>> y = tf.keras.layers.add([x1, x2])
    >>> print(y.shape)
    (2, 3, 4)

    Used 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)
    >>> added = tf.keras.layers.add([x1, x2])
    >>> out = tf.keras.layers.Dense(4)(added)
    >>> model = tf.keras.models.Model(inputs=[input1, input2], outputs=out)

    )r   )r	   Úkwargsr   r   r   Úadd=   s    r   N)r   Zkeras.layers.merging.base_merger   Z tensorflow.python.util.tf_exportr   r   r   r   r   r   r   Ú<module>   s
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