function standardizeWeights(_x, _x2, _x3, _x4) {
	  return _standardizeWeights.apply(this, arguments);
	}
Standardize by-sample and/or by-class weights for training.

Note that this function operates on one model output at a time. For a model
with multiple outputs, you must call this function multiple times.

@param y The target tensor that the by-sample and/or by-class weight is for.
    The values of y are assumed to encode the classes, either directly
    as an integer index, or as one-hot encoding.
@param sampleWeight By-sample weights.
@param classWeight By-class weights: an object mapping class indices
    (integers) to a weight (float) to apply to the model's loss for the
    samples from this class during training. This can be useful to tell the
    model to "pay more attention" to samples from an under-represented class.
@param sampleWeightMode The mode for the sample weights.
@return A Promise of weight tensor, of which the size of the first dimension
    matches that of `y`.