Add optional SyncBatchNorm support to ImageNet example

[snehasonkusare-tech]

This PR adds optional SyncBatchNorm support to the ImageNet training script.

What’s included:

• Added new CLI argument: --sync-bn

• If both (a) distributed training is enabled and (b) --sync-bn is passed, BatchNorm layers are converted to SyncBatchNorm using:

  nn.SyncBatchNorm.convert_sync_batchnorm(model)

• Conversion happens before DistributedDataParallel wrapping, as required.

Why this is useful:

SyncBatchNorm improves performance and stability in multi-GPU distributed training and is commonly used in ImageNet training recipes. Adding this option makes the example more complete and aligned with standard training practices.

Testing:

• Verified that the script runs correctly with dummy data on CPU.
• Ensured that normal execution is unchanged unless --sync-bn is passed.

Addresses Issue #793.

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[snehasonkusare-tech]

Hi, this is my first contribution to PyTorch. Please let me know if any changes are needed. Thanks!

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