1 | /// <amd-module name="@tensorflow/tfjs-layers/dist/exports_constraints" />
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2 | /**
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3 | * @license
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4 | * Copyright 2018 Google LLC
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5 | *
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6 | * Use of this source code is governed by an MIT-style
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7 | * license that can be found in the LICENSE file or at
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8 | * https://opensource.org/licenses/MIT.
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9 | * =============================================================================
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10 | */
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11 | import { Constraint, MaxNormArgs, MinMaxNormArgs, UnitNormArgs } from './constraints';
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12 | /**
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13 | * MaxNorm weight constraint.
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14 | *
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15 | * Constrains the weights incident to each hidden unit
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16 | * to have a norm less than or equal to a desired value.
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17 | *
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18 | * References
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19 | * - [Dropout: A Simple Way to Prevent Neural Networks from Overfitting
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20 | * Srivastava, Hinton, et al.
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21 | * 2014](http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf)
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22 | *
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23 | * @doc {heading: 'Constraints',namespace: 'constraints'}
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24 | */
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25 | export declare function maxNorm(args: MaxNormArgs): Constraint;
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26 | /**
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27 | * Constrains the weights incident to each hidden unit to have unit norm.
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28 | *
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29 | * @doc {heading: 'Constraints', namespace: 'constraints'}
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30 | */
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31 | export declare function unitNorm(args: UnitNormArgs): Constraint;
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32 | /**
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33 | * Constrains the weight to be non-negative.
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34 | *
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35 | * @doc {heading: 'Constraints', namespace: 'constraints'}
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36 | */
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37 | export declare function nonNeg(): Constraint;
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38 | /** @doc {heading: 'Constraints', namespace: 'constraints'} */
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39 | export declare function minMaxNorm(config: MinMaxNormArgs): Constraint;
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