Refactor autoaugment.py: extract _AutoAugmentBase to eliminate duplicated fill logic

[sunnycho100]

Description

There is a FIXME comment at line 103 of torchvision/transforms/autoaugment.py:

# FIXME: Eliminate copy-pasted code for fill standardization and _augmentation_space() by moving stuff on a base class

Four classes (AutoAugment, RandAugment, TrivialAugmentWide, AugMix) all independently repeat the same fill-standardization logic in their forward() methods:

fill = self.fill
channels, height, width = F.get_dimensions(img)
if isinstance(img, Tensor):
    if isinstance(fill, (int, float)):
        fill = [float(fill)] * channels
    elif fill is not None:
        fill = [float(f) for f in fill]

They also independently inherit from torch.nn.Module and define interpolation and fill in their __init__.

Proposal

Create an _AutoAugmentBase class (like v2 already did in torchvision/transforms/v2/_auto_augment.py) that:

1. Inherits from torch.nn.Module
2. Holds common __init__ params: interpolation and fill
3. Provides a _get_fill() helper to eliminate the duplicated fill-standardization logic

This is a pure internal refactor — no public API changes, no behavior changes. All existing tests should pass as-is.

Note: _augmentation_space() is intentionally not unified since each class uses different signatures and contents.

cc @pmeier