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[recipe] refactor: refactor ray trainer for separate recipe use. (fully async / one step off)#5184

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ArronHZG merged 13 commits intoverl-project:mainfrom
meituan-search:refactor_fully_async_ray_trainer
Feb 6, 2026
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[recipe] refactor: refactor ray trainer for separate recipe use. (fully async / one step off)#5184
ArronHZG merged 13 commits intoverl-project:mainfrom
meituan-search:refactor_fully_async_ray_trainer

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@ArronHZG ArronHZG commented Feb 3, 2026

What does this PR do?

  • Add a new Ray Trainer class to facilitate reusing the core logic.
  • And fix fully async / one step off CI.
  • Currently, our parameter synchronization logic is still in a broken state.

CI break in #4280

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@ArronHZG ArronHZG changed the title [recipe] refactor: refactor ray trainer for separate recipe use. (fully asyn / one step off) [recipe] refactor: refactor ray trainer for separate recipe use. (fully async / one step off) Feb 4, 2026
@ArronHZG ArronHZG marked this pull request as ready for review February 5, 2026 12:29
"""
如果 algorithm.rollout_correction.bypass_mode 为 False,则计算 old_log_prob
"""
# If local_triger_step == 1, load the training engine's parameters to the CPU
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'local_triger_step' is a typo.

trainer_future = executor.submit(self._create_trainer, config)
# Wait for both to complete
rollouter_future.result()
trainer_future.result()
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Suggesting keep _create_rollouter and _create_trainer sequential until [pr 4792](#4792) is merged, considering standalone launching mode does not promise bundled allocation.

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Ok, We can make revisions after it's fully tested and running.

if self.local_trigger_step == 1:
self.actor_rollout_wg.save_model_to_cpu(1)
old_log_prob, old_log_prob_mfu = super()._compute_old_log_prob(batch)
elif self.local_trigger_step is not None:
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Is this still necessary? The default value of local_trigger_step is 1 now and at no case should it be None.

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get it, i will change it.

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                if bypass_recomputing_logprobs:
                   ...
                else:  # Recompute old_log_probs
                    with marked_timer("old_log_prob", timing_raw, color="blue"):
                        old_log_prob, old_log_prob_mfu = self._compute_old_log_prob(batch)

_compute_old_log_prob will use in not bypass_recomputing_logprobs mode.

@ArronHZG ArronHZG requested a review from wuxibin89 February 6, 2026 06:15
@ArronHZG ArronHZG merged commit 32f2d3d into verl-project:main Feb 6, 2026
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Tjh-UKN pushed a commit to Tjh-UKN/verl that referenced this pull request Feb 13, 2026
…ly async / one step off) (verl-project#5184)

### What does this PR do?

* Add a new Ray Trainer class to facilitate reusing the core logic.
* And fix  fully async / one step off CI.
* Currently, our parameter synchronization logic is still in a broken
state.

CI break in verl-project#4280


### Checklist Before Starting

- [x] Search for similar PRs. Paste at least one query link here: ...
- [x] Format the PR title as `[{modules}] {type}: {description}` (This
will be checked by the CI)
- `{modules}` include `fsdp`, `megatron`, `veomni`, `sglang`, `vllm`,
`rollout`, `trainer`, `ci`, `training_utils`, `recipe`, `hardware`,
`deployment`, `ray`, `worker`, `single_controller`, `misc`, `perf`,
`model`, `algo`, `env`, `tool`, `ckpt`, `doc`, `data`, `cfg`, `reward`
- If this PR involves multiple modules, separate them with `,` like
`[megatron, fsdp, doc]`
  - `{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

> [!IMPORTANT]
> Please check all the following items before requesting a review,
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3 participants