HardSwish

lamp.autograd.HardSwish

case class HardSwish(scope: Scope, a: Variable) extends Op

Attributes

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Supertypes: trait Serializable

trait Product

trait Equals

trait Op

class Object

trait Matchable

class Any
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Value members

Inherited methods

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Inherited from:: Product

Attributes

Inherited from:: Product

Concrete fields

Implementation of the backward pass

A list of input variables paired up with an anonymous function computing the respective partial derivative. With the notation in the documentation of the trait lamp.autograd.Op: dy/dw2 => dy/dw2 * dw2/dw1. The first argument of the anonymous function is the incoming partial derivative (dy/dw2), the second argument is the output tensor into which the result (dy/dw2 * dw2/dw1) is accumulated (added).

If the operation does not support computing the partial derivative for some of its arguments, then do not include that argument in this list.

Attributes

See also: The documentation on the trait lamp.autograd.Op for more details and example.

The value of this operation

Attributes

Inherited fields

Attributes

Inherited from:: Op

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