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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 5, 18:30 UTC

Fix document of torchrun_example.py (#31113)

Maosheng Liao committed Mar 31, 2026 at 18:54 UTC aae3e688f8849bdad382943b78a7872f70b75046
1 file changed +4 -3
examples/offline_inference/torchrun_example.py
+4 -3
@@ -4,9 +4,10 @@
4 experimental support for tensor-parallel inference with torchrun,
5 see https://github.com/vllm-project/vllm/issues/11400 for
6 the motivation and use case for this example.
7 -run the script with `torchrun --nproc-per-node=2 torchrun_example.py`,
8 -the argument 2 should match the `tensor_parallel_size` below.
9 -see `tests/distributed/test_torchrun_example.py` for the unit test.
7 +run the script with `torchrun --nproc-per-node=4 torchrun_example.py`,
8 +the argument `4` should match the product of `tensor_parallel_size` and
9 +`pipeline_parallel_size` below. see `tests/distributed/test_torchrun_example.py`
10 +for the unit test.
11 """
12
13 import torch.distributed as dist