function activation(args) {
	  return new Activation$1(args);
	}
Applies an activation function to an output.

This layer applies element-wise activation function.  Other layers, notably
`dense` can also apply activation functions.  Use this isolated activation
function to extract the values before and after the
activation. For instance:

```js
const input = tf.input({shape: [5]});
const denseLayer = tf.layers.dense({units: 1});
const activationLayer = tf.layers.activation({activation: 'relu6'});

// Obtain the output symbolic tensors by applying the layers in order.
const denseOutput = denseLayer.apply(input);
const activationOutput = activationLayer.apply(denseOutput);

// Create the model based on the inputs.
const model = tf.model({
    inputs: input,
    outputs: [denseOutput, activationOutput]
});

// Collect both outputs and print separately.
const [denseOut, activationOut] = model.predict(tf.randomNormal([6, 5]));
denseOut.print();
activationOut.print();
```

@doc {heading: 'Layers', subheading: 'Basic', namespace: 'layers'}