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Implementation:Tensorflow Tfjs Exports Constraints

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Knowledge Sources
Domains Deep_Learning, Layers_API, Constraints
Last Updated 2026-02-10 06:00 GMT

Overview

This module provides the public API factory functions for creating weight constraint instances in TensorFlow.js Layers. These functions are thin wrappers around the constraint classes defined in constraints.ts, exposed under the tf.constraints namespace. Each function takes a configuration object and returns the corresponding Constraint instance.

Code Reference

Source Location

tfjs-layers/src/exports_constraints.ts (GitHub)

Imports

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

Factory Functions

maxNorm

Creates a MaxNorm constraint that limits the L2 norm of weight vectors.

export function maxNorm(args: MaxNormArgs): Constraint

unitNorm

Creates a UnitNorm constraint that normalizes weights to unit L2 norm.

export function unitNorm(args: UnitNormArgs): Constraint

nonNeg

Creates a NonNeg constraint that clips weights to non-negative values.

export function nonNeg(): Constraint

minMaxNorm

Creates a MinMaxNorm constraint that bounds the L2 norm between min and max values.

export function minMaxNorm(config: MinMaxNormArgs): Constraint

I/O Contract

Function Input Output
maxNorm MaxNormArgs ({maxValue?, axis?}) Constraint
unitNorm UnitNormArgs ({axis?}) Constraint
nonNeg (none) Constraint
minMaxNorm MinMaxNormArgs ({minValue?, maxValue?, rate?, axis?}) Constraint

Usage Example

import * as tf from '@tensorflow/tfjs';

const model = tf.sequential();
model.add(tf.layers.dense({
  units: 32,
  kernelConstraint: tf.constraints.maxNorm({maxValue: 2, axis: 0}),
  biasConstraint: tf.constraints.nonNeg(),
  inputShape: [64]
}));

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