description: Functional interface to the tf.keras.layers.Average layer.

tf.keras.layers.average

Functional interface to the tf.keras.layers.Average layer.

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

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)

Arguments

inputs A list of input tensors (at least 2).
**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.