Add timeslice-verl package and verl fully-async time-slicing guide - #158
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Adds the timeslice-verl integration package and a guide that time-slices two verl fully_async_policy RL jobs' trainers on one shared 1-GPU node (each job keeps a dedicated 1-GPU rollout node; 2-pod Ray cluster per job). The package ships TimesliceFullyAsyncTrainer, a subclass of verl's FullyAsyncTrainer that overrides the trainer's empty on_* lifecycle hooks (same template-method convention as verl's v1 trainers). It registers under the trainer name "timeslice" via verl's fully-async trainer registry — the package's verl.plugins entry point makes `import verl` load the registering module — and is selected with the hydra override async_training.trainer_name=timeslice. No meta_path monkey-patching. Placement-group pinning uses verl's per-pool extra bundle resources (ray_pg_extra_resources hydra override) instead of patching placement_group; the trainer refuses to train unpinned when TIMESLICE_REQUIRE_PG_PINNING=1. Both verl features ship as format-patch files in the guide's patches/ dir until they are available upstream (default install path: the feat/fully-async-lifecycle-hooks fork branch). New: pkg/integrations/verl/ (TimesliceFullyAsyncTrainer = TimesliceHooksMixin over FullyAsyncTrainer, + PhaseLocks; 33 tests, pure-python: no verl/ray/ grpc/GPU needed) New: guides/rl-frameworks/verl/ (README, job manifests for a math-RLVR and a code-RLVR job, GPU monitor, platform values, verl feature patches)
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Adds the timeslice-verl integration package and a guide that time-slices two verl
fully_async_policyRL jobs' trainers on one shared 1-GPU node (each job keeps a dedicated 1-GPU rollout node; 2-pod Ray cluster per job).pkg/integrations/verl/—TimesliceFullyAsyncTrainer, a subclass of verl'sFullyAsyncTrainerthat overrides the trainer's emptyon_*lifecycle hooks (verl's native v1 template-method convention) and registers under trainer nametimeslicevia verl's fully-async trainer registry; selected withasync_training.trainer_name=timeslice. No meta_path monkey-patching. Placement-group pinning uses verl's per-pool extra bundle resources (ray_pg_extra_resources).guides/rl-frameworks/verl/— framework landing README plusexamples/fully-async/(example README and job manifests for a math-RLVR and a code-RLVR job).Design note: the lifecycle hooks and PG-pinning features the package consumes are not yet upstream in verl; they are installed directly from the fork branch
aishukamal/verl@feat/fully-async-lifecycle-hooks(temporary until the commits land upstream).Validation: validated e2e on GKE (3x 1-GPU H100 nodes; full 90-minute run with demand-driven alternation, zero lock overlaps, zero NCCL errors); 24 pure-python unit tests included (no verl/ray/GPU required).