[ci] refactor: add ci test for refactored reward worker and add some args to GenRM config

[yyDing1]

What does this PR do?

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• add ci test for new reward model (accuracy check for the results of server mode rm and hf rm)
• add some args for genrm (e.g., reward_type, sampling parameters)

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[gemini-code-assist]

Code Review

This pull request refactors the reward model worker and adds a corresponding CI test. The configuration for the reward model is also updated. My review focuses on improving the new test's robustness and correctness. Specifically, I suggest adjusting the GPU resource allocation to prevent flakiness in CI and modifying the assertion logic to perform a more rigorous comparison of the model outputs.

[gemini-code-assist]

Hardcoding 8 GPUs for a CI test might make it flaky if the CI environment doesn't have that many GPUs available. Since tensor_model_parallel_size is 2, using 2 GPUs should be sufficient and more robust for a CI environment.

Suggested change

	resource_pool = RayResourcePool(process_on_nodes=[8])
	resource_pool = RayResourcePool(process_on_nodes=[2])

[yyDing1]

data parallel with multiple server instances should be tested, where more gpus are needed.