torch.nanmean
torch.nanmean(input, dim=None, keepdim=False, *, dtype=None, out=None) -> Tensor
Computes the mean of all non-NaN elements along the specified
   dimensions.
This function is identical to "torch.mean()" when there are no
   NaN values in the "input" tensor. In the presence of NaN,
   "torch.mean()" will propagate the NaN to the output whereas
   "torch.nanmean()" will ignore the NaN values (torch.nanmean(a)
   is equivalent to torch.mean(a[~a.isnan()])).
If "keepdim" is "True", the output tensor is of the same size as
   "input" except in the dimension(s) "dim" where it is of size 1.
   Otherwise, "dim" is squeezed (see "torch.squeeze()"), resulting in
   the output tensor having 1 (or "len(dim)") fewer dimension(s).
Parameters:
      * input (Tensor) -- the input tensor.
  * **dim** (*int** or **tuple of ints**, **optional*) -- the
    dimension or dimensions to reduce. If "None", all dimensions
    are reduced.
