/**

* @license

* Copyright 2018 Google LLC

*

* Use of this source code is governed by an MIT-style

* license that can be found in the LICENSE file or at

* https://opensource.org/licenses/MIT.

* =============================================================================

*/

// tslint:disable-next-line:max-line-length

import {Constraint, MaxNorm, MaxNormArgs, MinMaxNorm, MinMaxNormArgs, NonNeg, UnitNorm, UnitNormArgs} from './constraints';

/**

* MaxNorm weight constraint.

*

* Constrains the weights incident to each hidden unit

* to have a norm less than or equal to a desired value.

*

* References

* - [Dropout: A Simple Way to Prevent Neural Networks from Overfitting

* Srivastava, Hinton, et al.

* 2014](http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf)

*

* @doc {heading: 'Constraints',namespace: 'constraints'}

*/

export function maxNorm(args: MaxNormArgs): Constraint {

return new MaxNorm(args);

}

/**

* Constrains the weights incident to each hidden unit to have unit norm.

*

* @doc {heading: 'Constraints', namespace: 'constraints'}

*/

export function unitNorm(args: UnitNormArgs): Constraint {

return new UnitNorm(args);

}

/**

* Constrains the weight to be non-negative.

*

* @doc {heading: 'Constraints', namespace: 'constraints'}

*/

export function nonNeg(): Constraint {

return new NonNeg();

}

/** @doc {heading: 'Constraints', namespace: 'constraints'} */

export function minMaxNorm(config: MinMaxNormArgs): Constraint {

return new MinMaxNorm(config);

}