Upgrade to vllm 0.17.0 corex v4.1 overlay
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@@ -86,10 +86,7 @@ def cuda_platform_plugin() -> str | None:
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pynvml.nvmlShutdown()
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except Exception as e:
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logger.debug("Exception happens when checking CUDA platform: %s", str(e))
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nvml_related_error = (
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"nvml" in e.__class__.__name__.lower() or "nvml" in str(e).lower()
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)
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if not nvml_related_error:
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if "nvml" not in e.__class__.__name__.lower():
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# If the error is not related to NVML, re-raise it.
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raise e
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@@ -105,40 +102,7 @@ def cuda_platform_plugin() -> str | None:
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logger.debug("Confirmed CUDA platform is available on Jetson.")
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is_cuda = True
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else:
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try:
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import torch
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if vllm_version_matches_substr("cpu"):
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logger.debug(
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"CUDA platform torch fallback is skipped because "
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"vLLM is built with CPU."
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)
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elif not torch.cuda._is_compiled():
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logger.debug(
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"CUDA platform torch fallback reports CUDA is not compiled."
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)
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elif not torch.cuda.is_available():
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logger.debug(
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"CUDA platform torch fallback reports "
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"torch.cuda.is_available()=False."
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)
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elif torch.cuda.device_count() <= 0:
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logger.debug(
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"CUDA platform torch fallback reports no GPU is found."
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)
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else:
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logger.debug(
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"Confirmed CUDA platform is available via torch fallback "
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"after NVML check failed."
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)
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is_cuda = True
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except Exception as torch_e:
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logger.debug(
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"CUDA platform torch fallback failed because: %s", str(torch_e)
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)
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if not is_cuda:
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logger.debug("CUDA platform is not available because: %s", str(e))
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logger.debug("CUDA platform is not available because: %s", str(e))
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return "vllm.platforms.cuda.CudaPlatform" if is_cuda else None
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