[MOE]move weight transpose to wakeup for RL secnarios

[lhp-deep]

What this PR does / why we need it?

In reinforcement learning scenarios, the current inference applies a transpose operation to the weights. For a cleaner architecture, the weight transpose module was moved to wakeup.

Does this PR introduce any user-facing change?

How was this patch tested?

• vLLM version: v0.11.0
• vLLM main: vllm-project/vllm@2918c1b

[github-actions]

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[gemini-code-assist]

Code Review

This pull request aims to move the weight transposition logic for MoE layers to the wake_up function, enhancing support for Reinforcement Learning (RL) scenarios. The changes span an example file, the MoE operator implementation, and the worker logic. While the overall direction seems correct, I've identified a critical bug in the new code added to vllm_ascend/worker/worker_v1.py. The logic for retrieving a parameter's parent module is flawed and will lead to a runtime error. This needs to be addressed.

[gemini-code-assist]

The logic to retrieve the parent module of the w2_weight parameter is incorrect. module_path is assigned the parameter name string (parts[-1]), and the subsequent loop iterates over the characters of this string. This will cause getattr to fail at runtime.

You should iterate over the module path components to correctly traverse the model hierarchy. A cleaner way to achieve this is by using model.get_submodule().

Suggested change

	parent_module = model
	parts = name.split('.')
	param_name = parts[-1]
	module_path = parts[-1]
	for part in module_path:
	parent_module = getattr(parent_module, part)
	parts = name.split('.')
	param_name = parts[-1]
	parent_module = model.get_submodule(".".join(parts[:-1]))

[gemini-code-assist]

Similar to the w2_weight block, the logic to retrieve the parent module for w13_weight is incorrect. module_path is assigned the parameter name string, and the loop iterates over its characters, which will cause a runtime error. You should use model.get_submodule() to correctly get the parent module.

Suggested change

	parent_module = model
	parts = name.split('.')
	param_name = parts[-1]
	module_path = parts[-1]
	for part in module_path:
	parent_module = getattr(parent_module, part)
	parts = name.split('.')
	param_name = parts[-1]
	parent_module = model.get_submodule(".".join(parts[:-1]))