# tf.keras.layers.Add

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v2.13.1/keras/layers/merging/add.py#L24-L58) |

Layer that adds a list of inputs.

Inherits From: [`Layer`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/keras/layers/Layer), [`Module`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/Module)

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

\`tf.compat.v1.keras.layers.Add\`

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    tf.keras.layers.Add(
        **kwargs
    )

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)

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| ## Args ||
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| `**kwargs` | standard layer keyword arguments. |

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