def meta_nanmedian_dim(input, dim=-1, keepdim=False):
dim = utils.reduction_dims(input.shape, (dim, ))
output_shape = _compute_reduction_shape(input, dim, keepdim)
return (
input.new_empty(output_shape),
input.new_empty(output_shape, dtype=torch.long),
)
def meta_nansum(input, dims=None, keepdim=False, *, dtype=None):
output_dtype = _get_reduction_dtype(input, dtype, promote_int_to_long=True)
dims = utils.reduction_dims(input.shape, dims)
output_shape = _compute_reduction_shape(input, dims, keepdim)
return input.new_empty(output_shape, dtype=output_dtype)
def meta_var_mean_correction(self, dim, *, correction, keepdim=False):
dim = utils.reduction_dims(self.shape, dim)
output_shape = _compute_reduction_shape(self, dim, keepdim)
result1 = self.new_empty(output_shape, dtype=toRealValueType(self.dtype))
result2 = self.new_empty(output_shape)
return result1, result2