# tf.keras.layers.add

<br />

|---|
| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v2.10.0/keras/layers/merging/add.py#L61-L92) |

Functional interface to the [`tf.keras.layers.Add`](https://www.tensorflow.org/versions/r2.10/api_docs/python/tf/keras/layers/Add) layer.

#### View aliases


**Compat aliases for migration**

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

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

<br />

    tf.keras.layers.add(
        inputs, **kwargs
    )

<br />

<br />

<br />

| ## Args ||
|---|---|
| `inputs` | A list of input tensors with the same shape. |
| `**kwargs` | Standard layer keyword arguments. |

<br />

<br />

<br />

<br />

| ## Returns ||
|---|---|
| A tensor as the sum of the inputs. It has the same shape as the inputs. ||

<br />

#### 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)