torch.nanquantile
torch.nanquantile(input, q, dim=None, keepdim=False, *, interpolation='linear', out=None) -> Tensor
This is a variant of "torch.quantile()" that "ignores" "NaN"
   values, computing the quantiles "q" as if "NaN" values in "input"
   did not exist. If all values in a reduced row are "NaN" then the
   quantiles for that reduction will be "NaN". See the documentation
   for "torch.quantile()".
Parameters:
      * input (Tensor) -- the input tensor.
  * **q** (*float** or **Tensor*) -- a scalar or 1D tensor of
    quantile values in the range [0, 1]

  * **dim** (*int*) -- the dimension to reduce.

  * **keepdim** (*bool*) -- whether the output tensor has "dim"
    retained or not.

Keyword Arguments:
      * interpolation (str) -- interpolation method to use when
        the desired quantile lies between two data points. Can be
        "linear", "lower", "higher", "midpoint" and "nearest". Default
        is "linear".