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Rename config var
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parent
bb3c26cfc5
commit
4bda515990
2 changed files with 6 additions and 6 deletions
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@ -27,7 +27,7 @@ class MetaReferenceInferenceConfig(BaseModel):
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# when this is False, we assume that the distributed process group is setup by someone
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# outside of this code (e.g., when run inside `torchrun`). that is useful for clients
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# (including our testing code) who might be using llama-stack as a library.
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use_elastic_agent: bool = True
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create_distributed_process_group: bool = True
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@field_validator("model")
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@classmethod
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@ -37,7 +37,7 @@ class MetaReferenceInferenceImpl(Inference, ModelsProtocolPrivate):
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async def initialize(self) -> None:
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print(f"Loading model `{self.model.descriptor()}`")
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if self.config.use_elastic_agent:
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if self.config.create_distributed_process_group:
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self.generator = LlamaModelParallelGenerator(self.config)
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self.generator.start()
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else:
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@ -55,7 +55,7 @@ class MetaReferenceInferenceImpl(Inference, ModelsProtocolPrivate):
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]
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async def shutdown(self) -> None:
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if self.config.use_elastic_agent:
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if self.config.create_distributed_process_group:
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self.generator.stop()
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def completion(
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@ -104,7 +104,7 @@ class MetaReferenceInferenceImpl(Inference, ModelsProtocolPrivate):
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f"Model mismatch: {request.model} != {self.model.descriptor()}"
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)
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if self.config.use_elastic_agent:
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if self.config.create_distributed_process_group:
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if SEMAPHORE.locked():
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raise RuntimeError("Only one concurrent request is supported")
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@ -160,7 +160,7 @@ class MetaReferenceInferenceImpl(Inference, ModelsProtocolPrivate):
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logprobs=logprobs if request.logprobs else None,
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)
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if self.config.use_elastic_agent:
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if self.config.create_distributed_process_group:
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async with SEMAPHORE:
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return impl()
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else:
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@ -284,7 +284,7 @@ class MetaReferenceInferenceImpl(Inference, ModelsProtocolPrivate):
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)
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)
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if self.config.use_elastic_agent:
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if self.config.create_distributed_process_group:
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async with SEMAPHORE:
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for x in impl():
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yield x
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