[Torch] Add support for Huber Loss function
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Description
### Huber Loss function
https://docs.pytorch.org/docs/stable/generated/torch.nn.HuberLoss.html#torch.nn.HuberLoss
This op is missing in torch dialect. It can be implemented via decomposition to other primitive torch ops.
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the PyTorch HuberLoss documentation linked in the issue, then locate the torch dialect's existing loss operations and decomposition patterns. Implement Huber Loss using primitive torch operations and verify that the dialect supports the documented behavior; the issue names no specific files or tests.
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Assessment
- Tech stack
- cpp, pytorch
- Domain
- compilers, machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100