qfeval_functions.functions.fillna

fillna(x, nan=0.0, posinf=inf, neginf=-inf)[source]

Replace NaN and infinity values with specified numbers.

This function replaces NaN (Not a Number), positive infinity, and negative infinity values in a tensor with user-specified values. By default, NaN values are replaced with 0, while infinity values are preserved. This behavior differs from torch.nan_to_num, which replaces infinities with the largest/smallest representable finite values by default.

Parameters:

  • x (Tensor) – The input tensor containing values to be replaced.

  • nan (float) – The value to replace NaN with. Default is 0.0.

  • posinf (float) – The value to replace positive infinity with. Default is math.inf (preserves positive infinity).

  • neginf (float) – The value to replace negative infinity with. Default is -math.inf (preserves negative infinity).

Returns:

A new tensor with the same shape and dtype as the input, where NaN and infinity values are replaced according to the specified parameters.

Return type:

Tensor

Example

>>> # Replace NaN values with 0 (default behavior)
>>> x = torch.tensor([1.0, nan, 3.0, nan])
>>> QF.fillna(x)
tensor([1., 0., 3., 0.])

>>> # Replace NaN with -1
>>> x = torch.tensor([[nan, 2.0], [3.0, nan]])
>>> QF.fillna(x, nan=-1.0)
tensor([[-1.,  2.],
        [ 3., -1.]])

>>> # Handle infinity values
>>> x = torch.tensor([1.0, inf, -inf, nan])
>>> QF.fillna(x, nan=0.0, posinf=999.0, neginf=-999.0)
tensor([   1.,  999., -999.,    0.])

>>> # Preserve infinity by default
>>> x = torch.tensor([inf, -inf, nan])
>>> QF.fillna(x)
tensor([inf, -inf, 0.])