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[model] chore: deprecated legacy code for GRM #3885
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Code Review
This pull request deprecates and removes legacy code for the sglang-based Generative Reward Model (GRM), which is a positive step towards simplifying the codebase. The changes primarily involve deleting the RewardModelWorker and its related engine implementation. While the removal seems largely self-contained, I've identified a potential critical issue regarding a patch for the sglang library that is also being removed. This could affect other parts of the system that rely on sglang.
### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
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### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
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### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
### Checklist Before Starting
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### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
### Checklist Before Starting
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### Design & Code Changes
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### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
### Checklist Before Starting
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- If this PR involves multiple modules, separate them with `,` like
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- If this PR breaks any API (CLI arguments, config, function signature,
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### Test
> For changes that can not be tested by CI (e.g., algorithm
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results like training curve plots, evaluation results, etc.
### API and Usage Example
> Demonstrate how the API changes if any, and provide usage example(s)
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```python
# Add code snippet or script demonstrating how to use this
```
### Design & Code Changes
> Demonstrate the high-level design if this PR is complex, and list the
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### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
### Checklist Before Starting
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### API and Usage Example
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# Add code snippet or script demonstrating how to use this
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### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
### Checklist Before Starting
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### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
### Checklist Before Starting
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- If this PR involves multiple modules, separate them with `,` like
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- `{type}` is in `feat`, `fix`, `refactor`, `chore`, `test`
- If this PR breaks any API (CLI arguments, config, function signature,
etc.), add `[BREAKING]` to the beginning of the title.
- Example: `[BREAKING][fsdp, megatron] feat: dynamic batching`
### Test
> For changes that can not be tested by CI (e.g., algorithm
implementation, new model support), validate by experiment(s) and show
results like training curve plots, evaluation results, etc.
### API and Usage Example
> Demonstrate how the API changes if any, and provide usage example(s)
if possible.
```python
# Add code snippet or script demonstrating how to use this
```
### Design & Code Changes
> Demonstrate the high-level design if this PR is complex, and list the
specific changes.
### Checklist Before Submitting
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### What does this PR do?
Deprecate legacy code for GRM as it's now supported in `reward loop`.
Future PR may further deprecate `{fsdp/megatron}_reward_model` by the
following steps:
1. support discriminative reward models in `reward loop`
2. make the reward model & router arch stable for large-scale training
3. refactor the config of reward models (in replace with the ones in
`recipe/fapo/config/rm_config.yaml`)
4. deprecate legacy `{fsdp/megatron}_reward_models`
### Checklist Before Starting
- [ ] Search for similar PRs. Paste at least one query link here: ...
- [ ] Format the PR title as `[{modules}] {type}: {description}` (This
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# Add code snippet or script demonstrating how to use this
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### Design & Code Changes
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What does this PR do?
Deprecate legacy code for GRM as it's now supported in
reward loop.Future PR may further deprecate
{fsdp/megatron}_reward_modelby the following steps:reward looprecipe/fapo/config/rm_config.yaml){fsdp/megatron}_reward_modelsChecklist Before Starting
[{modules}] {type}: {description}(This will be checked by the CI){modules}includefsdp,megatron,sglang,vllm,rollout,trainer,ci,training_utils,recipe,hardware,deployment,ray,worker,single_controller,misc,perf,model,algo,env,tool,ckpt,doc,data,like[megatron, fsdp, doc]{type}is infeat,fix,refactor,chore,test[BREAKING]to the beginning of the title.[BREAKING][fsdp, megatron] feat: dynamic batchingTest
API and Usage Example
# Add code snippet or script demonstrating how to use thisDesign & Code Changes
Checklist Before Submitting
Important
Please check all the following items before requesting a review, otherwise the reviewer might deprioritize this PR for review.
pre-commit install && pre-commit run --all-files --show-diff-on-failure --color=alwaysci-requestchannel in theverlSlack workspace. (If not accessible, please try the Feishu group (飞书群).)