On this page
tf.keras.layers.Average
Layer that averages a list of inputs element-wise.
tf.keras.layers.Average(
    **kwargs
)
It takes as input a list of tensors, all of the same shape, and returns a single tensor (also of the same shape).
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)
| Raises | |
|---|---|
| ValueError | If there is a shape mismatch between the inputs and the shapes cannot be broadcasted to match. | 
| Arguments | |
|---|---|
| **kwargs | standard layer keyword arguments. | 
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
 https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/layers/Average