[https://nvbugs/5443039][fix] Fix AutoDeploy pattern matcher for torch 2.8 #7076
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📝 WalkthroughWalkthroughPatched wrapper for lowering.unsupported_input_tensor now accepts arbitrary positional and keyword arguments and forwards them as original_fn(t, *args, **kwargs); retains the meta-tensor short-circuit (t.is_meta) and replaces lowering.unsupported_input_tensor with the patched function. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
participant Caller
participant PatchedFn as patched_fn
participant OrigFn as original_fn
Caller->>PatchedFn: call(t, *args, **kwargs)
alt t.is_meta
PatchedFn-->>Caller: return False (short-circuit)
else non-meta
note right of PatchedFn #D6EAF8: Forward arbitrary args to original
PatchedFn->>OrigFn: original_fn(t, *args, **kwargs)
OrigFn-->>PatchedFn: result
PatchedFn-->>Caller: result
end
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tensorrt_llm/_torch/auto_deploy/utils/pattern_matcher.py (1)
1-5: Missing NVIDIA copyright header (2025).Per repository guidelines, prepend the NVIDIA copyright header.
Apply something like:
+# Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# +""" Utilities for registering and applying Torch-Inductor FX-based pattern matchers. Work with `torch._inductor.pattern_matcher` in PyTorch ≥ 2.7.0. """If the repo uses a canonical header block, please use that exact text instead.
🧹 Nitpick comments (1)
tensorrt_llm/_torch/auto_deploy/utils/pattern_matcher.py (1)
50-53: Avoid broad TypeError probing in hot-path; determine the calling convention once.Catching all TypeErrors can mask real bugs and adds overhead on every call for older Torch. If you don’t adopt the pure pass-through fix, compute the adapter once via inspect and avoid exceptions in the hot path.
A compact pattern:
# Place this just before defining patched_fn sig = inspect.signature(original_fn) uses_parent = "parent" in sig.parameters def patched_fn(t: torch.Tensor, parent=None, node=None, *args, **kwargs): if t.is_meta: return False if uses_parent: # Filter kwargs to what original accepts (defensive) filtered = {k: v for k, v in kwargs.items() if k in sig.parameters} return original_fn(t, parent, node, *args, **filtered) else: filtered = {k: v for k, v in kwargs.items() if k in sig.parameters} # Use the second positional we received (parent) as `node` return original_fn(t, parent, *args, **filtered)
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Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com> rabbit feedback Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
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/bot run |
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PR_Github #15965 [ run ] triggered by Bot |
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PR_Github #15965 [ run ] completed with state |
…h 2.8 (NVIDIA#7076) Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com> Signed-off-by: Yuxin <yuxinz@nvidia.com>
3 participants
Torch 2.8 update
unsupported_input_tensor(t, parent, node)tounsupported_input_tensor(t, node)and our patch breaks.This fix uses generic arguments to accommodate the API change
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