Functional interface to the tf.keras.layers.Average
layer.
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Compat aliases for migration
See
Migration guide for
more details.
`tf.compat.v1.keras.layers.average`
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)
Args |
inputs
|
A list of input tensors.
|
**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.
|