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fix issue with #108 that broke gpu ci #112

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Merged
SumanthRH merged 2 commits into from
Jul 26, 2025
Merged

fix issue with #108 that broke gpu ci #112

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69fd7e0
fix bug
erictang000 Jul 25, 2025
f6bd8ee
x
erictang000 Jul 26, 2025
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20 changes: 10 additions & 10 deletions skyrl-train/skyrl_train/utils/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -268,7 +268,15 @@ def initialize_ray(cfg: DictConfig):
env_vars["VLLM_USE_V1"] = "1"
env_vars["VLLM_ENABLE_V1_MULTIPROCESSING"] = "0"

if not peer_access_supported(cfg):
max_num_gpus_per_node = max(
[
cfg.trainer.placement.policy_num_gpus_per_node,
cfg.trainer.placement.critic_num_gpus_per_node,
cfg.trainer.placement.ref_num_gpus_per_node,
cfg.trainer.placement.reward_num_gpus_per_node,
]
)
if not peer_access_supported(max_num_gpus_per_node=max_num_gpus_per_node):
logger.info("Peer access is not supported on this node type, disabling P2P and SHM")
env_vars["NCCL_P2P_DISABLE"] = "1"
env_vars["NCCL_SHM_DISABLE"] = "1"
Expand Down Expand Up @@ -359,17 +367,9 @@ def run_p2p_access_check():
return True


def peer_access_supported(cfg: DictConfig):
def peer_access_supported(max_num_gpus_per_node: int):
# whatever the max num gpus per node is, we can check p2p access if there are at least 2 GPUs
# if max is 1, p2p access is not supported
max_num_gpus_per_node = max(
[
cfg.trainer.placement.policy_num_gpus_per_node,
cfg.trainer.placement.critic_num_gpus_per_node,
cfg.trainer.placement.ref_num_gpus_per_node,
cfg.trainer.placement.reward_num_gpus_per_node,
]
)
if max_num_gpus_per_node <= 1:
return False

Expand Down
2 changes: 1 addition & 1 deletion skyrl-train/tests/gpu/gpu_ci/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@ def ray_init_fixture():
if ray.is_initialized():
ray.shutdown()
env_vars = {}
if not peer_access_supported():
if not peer_access_supported(max_num_gpus_per_node=2):
log_once("Disabling NCCL P2P for CI environment")
env_vars = {"NCCL_P2P_DISABLE": "1", "NCCL_SHM_DISABLE": "1"}
ray.init(runtime_env={"env_vars": env_vars})
Expand Down