tf.keras.layers.average

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

Used in the notebooks

Used in the guide

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)

inputs A list of input tensors (at least 2).
**kwargs Standard layer keyword arguments.

A tensor, the average of the inputs.

ValueError If there is a shape mismatch between the inputs and the shapes cannot be broadcasted to match.