[FEATURE] Validation labels txt or csv file

I have trained model using timm distributed_train.sh, but I have 0.1 validation accuracy on imagenet. Images in validation folder are all placed in root directory going like `ILSVRC2012_val_00000001.JPEG ... ILSVRC2012_val_00050000.JPEG`.

**Describe the solution you'd like**
I would like to have parameter in `validate.py` file similar to `'--real-labels'` that will take csv or txt file with structure like
```
ImageId,Class
ILSVRC2012_val_00000001,n01751748
```

Start in validate.py by reading the existing --real-labels handling and how validation image paths are resolved; distributed_train.sh provides the training context. Check how the requested CSV or TXT ImageId/Class mapping should connect to the root-level ImageNet validation filenames, and consider the feature complete when validation accepts that mapping and produces usable accuracy results.

Written by the indexing model from the issue text.