[ci][distributed] add tests for custom allreduce (#5689)
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@ -182,7 +182,11 @@ steps:
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- pip install -r requirements-docs.txt
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- SPHINXOPTS=\"-W\" make html
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- label: A100 status
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- label: Distributed Tests (A100)
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gpu: a100
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commands:
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- nvidia-smi
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# NOTE: don't test llama model here, it seems hf implementation is buggy
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# see https://github.com/vllm-project/vllm/pull/5689 for details
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- pytest -v -s distributed/test_custom_all_reduce.py
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- TEST_DIST_MODEL=facebook/opt-125m DISTRIBUTED_EXECUTOR_BACKEND=ray pytest -v -s distributed/test_basic_distributed_correctness.py
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- TEST_DIST_MODEL=facebook/opt-125m DISTRIBUTED_EXECUTOR_BACKEND=mp pytest -v -s distributed/test_basic_distributed_correctness.py
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@ -11,7 +11,8 @@ from vllm.distributed.communication_op import ( # noqa
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from vllm.distributed.parallel_state import (get_tensor_model_parallel_group,
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get_tp_group, graph_capture)
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from ..utils import (init_test_distributed_environment,
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from ..utils import (ensure_model_parallel_initialized,
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init_test_distributed_environment,
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multi_process_tensor_parallel)
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random.seed(42)
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@ -27,8 +28,8 @@ def graph_allreduce(tp_size, pp_size, rank, distributed_init_port):
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torch.cuda.set_device(device)
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init_test_distributed_environment(tp_size, pp_size, rank,
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distributed_init_port)
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group = get_tensor_model_parallel_group()
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ensure_model_parallel_initialized(tp_size, pp_size)
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group = get_tensor_model_parallel_group().device_group
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# A small all_reduce for warmup.
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# this is needed because device communicators might be created lazily
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