According to the documentation for torch.nn. InstanceNorm1d, when affine is set to True, the beta (additive) and gamma (multiplicative) parameters are learnable.
When affine is set to False, should we infer that beta and gamma are simply absent (i.e., functionally 0 and 1, respectively)?
Also, no details are given about the parameter initialization:  when affine is True, how are they initialized?  Can the initialization be changed?
(The same question applies to the 2d version, if the answers are different.)