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9bd15f1937
* TensorRT-LLM Release 0.10.0 --------- Co-authored-by: Loki <lokravi@amazon.com> Co-authored-by: meghagarwal <16129366+megha95@users.noreply.github.com>
42 lines
1016 B
Python
42 lines
1016 B
Python
#!/usr/bin/env python
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from mpi4py.futures import MPICommExecutor
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from tensorrt_llm._utils import mpi_comm, mpi_rank, mpi_world_size
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from tensorrt_llm.hlapi.mpi_session import MpiCommSession, MPINodeState
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class MpiTask:
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def __init__(self):
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self.executor = MpiCommSession(n_workers=4)
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@staticmethod
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def task():
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if MPINodeState.state is None:
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MPINodeState.state = 0
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MPINodeState.state += 1
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print(f"rank: {mpi_rank()}, state: {MPINodeState.state}")
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return (mpi_rank(), MPINodeState.state)
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def run(self):
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results = self.executor.submit_sync(MpiTask.task)
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results = sorted(results, key=lambda x: x[0])
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assert results == [(i, 1) for i in range(mpi_world_size())], results
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def main():
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# The root node
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if mpi_rank() == 0:
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the_task = MpiTask()
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the_task.run()
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else: # The worker node
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with MPICommExecutor(mpi_comm()) as executor:
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pass
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if __name__ == '__main__':
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main()
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