My task has the following description:
We condition on the noise vector multiple times throughout the network. One of the most popular ways of doing that is via adaptive batch normalization:
𝑥=𝑥−𝜇𝜎𝛾+𝛽,𝛾=𝑓(𝑧), 𝛽=𝑔(𝑧)
The first part of this operation is a standard batch normalization, but instead of optimizing  𝛾  and  𝛽  as a vector, we optimize functions  𝑓  and 𝑔 , which predict affine parameters from a noise vector 𝑧 . Typically these functions are simple linear mappings.
I don’t know how to do that. I am pretty new to PyTorch. Please, help me.