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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 8, 00:00 UTC

[AMD][CI] Fix test_custom_allreduce for A100 testgroup (#34735)

Signed-off-by: Ryan Rock <ryan.rock@amd.com>

Ryan Rock committed Feb 20, 2026 at 15:33 UTC 0632ed8778cab44de6152eb873d09fa40c241962
1 file changed +2
tests/distributed/test_custom_all_reduce.py
+2
@@ -33,6 +33,7 @@ def graph_allreduce(
33 ):
34 with monkeypatch.context() as m:
35 m.delenv("CUDA_VISIBLE_DEVICES", raising=False)
36 + m.delenv("HIP_VISIBLE_DEVICES", raising=False)
37 device = torch.device(f"cuda:{rank}")
38 torch.cuda.set_device(device)
39 init_test_distributed_environment(tp_size, pp_size, rank, distributed_init_port)
@@ -92,6 +93,7 @@ def eager_allreduce(
93 ):
94 with monkeypatch.context() as m:
95 m.delenv("CUDA_VISIBLE_DEVICES", raising=False)
96 + m.delenv("HIP_VISIBLE_DEVICES", raising=False)
97 device = torch.device(f"cuda:{rank}")
98 torch.cuda.set_device(device)
99 init_test_distributed_environment(tp_size, pp_size, rank, distributed_init_port)