Method build

tfjs-layers/src/layers/normalization.ts:526–569

(inputShape: Shape|Shape[])

  }

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

    // Convert axis to array and resolve negatives.
    if (typeof this.axis === 'number') {
      this.axis = [this.axis];
    }
    for (let i = 0; i < this.axis.length; ++i) {
      if (this.axis[i] < 0) {
        this.axis[i] += nDims;
      }
    }

    // Further validate axes.
    for (const axis of this.axis) {
      if (axis < 0 || axis >= nDims) {
        throw new Error(`Invalid axis: ${axis}`);
      }
    }
    if (this.axis.length !== generic_utils.unique(this.axis).length) {
      throw new Error(`Found duplicate axes in: ${this.axis}`);
    }

    const paramShape = this.axis.map(axis => inputShape[axis]) as number[];

    const trainable = true;
    if (this.scale) {
      this.gamma = this.addWeight(
          'gamma', paramShape, 'float32', this.gammaInitializer,
          this.gammaRegularizer, trainable);
    } else {
      this.gamma = null;
    }
    if (this.center) {
      this.beta = this.addWeight(
          'beta', paramShape, 'float32', this.betaInitializer,
          this.betaRegularizer, trainable);
    } else {
      this.beta = null;
    }

    this.built = true;
  }

  override call(inputs: Tensor|Tensor[], kwargs: Kwargs): Tensor|Tensor[] {
    const input = getExactlyOneTensor(inputs);