Method constructor

tfjs-layers/src/layers/core.ts:207–238

(args: DenseLayerArgs)

  private readonly biasRegularizer?: Regularizer;

  constructor(args: DenseLayerArgs) {
    super(args);
    if (args.batchInputShape == null && args.inputShape == null &&
        args.inputDim != null) {
      // This logic is copied from Layer's constructor, since we can't
      // do exactly what the Python constructor does for Dense().
      let batchSize: number = null;
      if (args.batchSize != null) {
        batchSize = args.batchSize;
      }
      this.batchInputShape = [batchSize, args.inputDim];
    }

    this.units = args.units;
    assertPositiveInteger(this.units, 'units');
    this.activation = getActivation(args.activation);
    if (args.useBias != null) {
      this.useBias = args.useBias;
    }
    this.kernelInitializer = getInitializer(
        args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);
    this.biasInitializer =
        getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);
    this.kernelConstraint = getConstraint(args.kernelConstraint);
    this.biasConstraint = getConstraint(args.biasConstraint);
    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);
    this.biasRegularizer = getRegularizer(args.biasRegularizer);
    this.activityRegularizer = getRegularizer(args.activityRegularizer);
    this.supportsMasking = true;

    this.inputSpec = [{minNDim: 2}];
  }

  public override build(inputShape: Shape|Shape[]): void {
    inputShape = getExactlyOneShape(inputShape);