Add multi-GPU worker assignment

[L-M-Sherlock]

No description provided.

[gemini-code-assist]

Code Review

This pull request introduces multi-GPU support for worker processes, allowing for round-robin assignment of CUDA devices. The implementation includes command-line argument parsing for GPU selection, validation of device IDs, and configuration of worker processes. The changes are well-structured. I have one suggestion to improve error handling in the device configuration logic to prevent silent failures.

[gemini-code-assist]

Using a broad except Exception: pass is risky as it can hide important errors, such as ImportError if reptile_trainer is not found or AttributeError if DEVICE is not a member. This could lead to the model silently running on the wrong device. It's better to catch specific exceptions and log a warning to make debugging easier.

Suggested change

	except Exception:
	pass
	except (ImportError, AttributeError) as e:
	print(f"Warning: Could not configure device for reptile_trainer: {e}")