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fix: Fix bug when targeting the TRT-LLM backend ensemble #7700

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merged 3 commits into from
Oct 16, 2024
Merged

fix: Fix bug when targeting the TRT-LLM backend ensemble #7700

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36a55e9
Fix bug when targeting the TRT-LLM backend ensemble
blongnv Oct 14, 2024
fbd009c
Update python/openai/openai_frontend/engine/triton_engine.py
blongnv Oct 14, 2024
319bd2a
Implement PR feedback
blongnv Oct 15, 2024
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3 changes: 3 additions & 0 deletions python/openai/openai_frontend/engine/triton_engine.py
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Expand Up @@ -250,6 +250,9 @@ def _get_model_metadata(self) -> Dict[str, TritonModelMetadata]:
for name, _ in self.server.models().keys():
model = self.server.model(name)
backend = model.config()["backend"]
if backend == "":
# look for ensemble setting if backend is undefined
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backend = model.config()["platform"]
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@rmccorm4 should we check against a list of supported platform types here to rule out any accidents

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@rmccorm4 rmccorm4 Oct 15, 2024 •
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Sure, we can be strict here just in case.

There's currently no use case I'm aware of where the platform would be used to specify a backend (ex: platform: tensorrt_plan) that doesn't have a backend equivalent (other than ensemble), and we generally encourage use of backend for this purpose for pretty much everything other than ensembles - so I think it's fine to be strict for now.

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@blongnv could you modify it to be something like this?

# Explicitly handle ensembles to avoid any runtime validation errors
if not backend and model.config()["platform"] == "ensemble":
  backend = "ensemble"

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Implemented, please check

print(f"Found model: {name=}, {backend=}")

metadata = TritonModelMetadata(
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