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Signed-off-by: Peter Jin <pjin@nvidia.com>
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nemo_gym/ray_utils.py
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| for node in nodes: | ||
| worker_options = {} | ||
| worker_options["num_gpus"] = num_gpus | ||
| worker_options["scheduling_strategy"] = NodeAffinitySchedulingStrategy( |
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there might be more than 1 resources server that needs some gpu resources. is there a way to provide a pool of node ids and let ray schedule for us? so like we keep the node affinity scheduling strategy, that's how we want ray to place workers, but then just provide it with the pool of nodes assigned to gym
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
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… were presumably released). Signed-off-by: Peter Jin <pjin@nvidia.com>
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@pjin-nvidia can you add a description for the scope of PR and/or link an issue? |
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
…4a70fd3405ffdeb7906e4). Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Peter Jin <pjin@nvidia.com>
Signed-off-by: Jiaqi Zeng <jiaqiz@nvidia.com> Signed-off-by: Peter Jin <pjin@nvidia.com>
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changes covered in #558 |
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This PR adds support for spinning up GPU Ray actors, including and especially VLLM instances, from within Gym servers.
Issue resolved:
PR merge dependency:
Related: