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tf.keras.activations.swish
Swish activation function, swish(x) = x * sigmoid(x).
tf.keras.activations.swish(
    x
)
Swish activation function which returns x*sigmoid(x). It is a smooth, non-monotonic function that consistently matches or outperforms ReLU on deep networks, it is unbounded above and bounded below.
Example Usage:
a = tf.constant([-20, -1.0, 0.0, 1.0, 20], dtype = tf.float32)
b = tf.keras.activations.swish(a)
b.numpy()
array([-4.1223075e-08, -2.6894143e-01,  0.0000000e+00,  7.3105860e-01,
          2.0000000e+01], dtype=float32)
| Arguments | |
|---|---|
| x | Input tensor. | 
| Returns | |
|---|---|
| The swish activation applied to x(see reference paper for details). | 
Reference:
© 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/activations/swish