torch_nanquantile( self, q, dim =NULL, keepdim =FALSE, interpolation ="linear")
Arguments
self: (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.
interpolation: The interpolation method.
nanquantile(input, q, dim=None, keepdim=FALSE, *, 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().
Examples
if(torch_is_installed()){t <- torch_tensor(c(NaN,1,2))t$quantile(0.5)t$nanquantile(0.5)t <- torch_tensor(rbind(c(NaN,NaN), c(1,2)))t
t$nanquantile(0.5, dim=1)t$nanquantile(0.5, dim=2)torch_nanquantile(t,0.5, dim =1)torch_nanquantile(t,0.5, dim =2)}