Function regularNormalizeBatchInTraining

tfjs-layers/src/layers/normalization.ts:89–100

* Non-broadcasting batch normalization for use in training (not inference). * * The input is normalized to zero mean and unit variance along the * `reductionAxes`, followed by scaling with `gamma` and shifted by `beta`. * The result of that is returned as the first element * of the returned `Ar

(
    x: Tensor, gamma: Tensor, beta: Tensor, reductionAxes: number[],
    epsilon = 1e-3)

 *   [normalized tensor, mean of input, variance of input].
 */
function regularNormalizeBatchInTraining(
    x: Tensor, gamma: Tensor, beta: Tensor, reductionAxes: number[],
    epsilon = 1e-3): [Tensor, Tensor, Tensor] {
  return tidy(() => {
           const meanAndVariance = tfc.moments(x, reductionAxes);
           const mean = meanAndVariance.mean;
           const variance = meanAndVariance.variance;
           const normed =
               batchNormalization(x, mean, variance, beta, gamma, epsilon);
           return [normed, mean, variance];
         }) as [Tensor, Tensor, Tensor];
}

/**
 * Broadcasting batch normalization for use in training (not inference).