[TRTLLM-8201][feat] Topological graph helpers #8457
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Signed-off-by: greg-kwasniewski1 <213329731+greg-kwasniewski1@users.noreply.github.com>
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📝 WalkthroughWalkthroughTwo new utility functions added to node_utils.py for tensor graph analysis: Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes Pre-merge checks and finishing touches❌ Failed checks (2 warnings)
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⚠️ Outside diff range comments (1)
tensorrt_llm/_torch/auto_deploy/utils/node_utils.py (1)
1-1: Add required NVIDIA Apache-2.0 copyright header.Per coding guidelines, all Python source files must include the NVIDIA Apache-2.0 copyright header with the current year (2025) at the top.
Add the copyright header before the module docstring:
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Common utils for torch fx graph transformation."""
🧹 Nitpick comments (1)
tensorrt_llm/_torch/auto_deploy/utils/node_utils.py (1)
453-457: Enhance docstrings to follow Google-style format.Per coding guidelines, use Google-style docstrings with Args, Returns, and Examples sections. The current docstrings lack parameter documentation and don't clarify the recursion behavior when nodes are filtered.
Example for
predecessors:""" Build predecessor tree by recursively traversing node.args up to specified depth. Args: node: The starting node for traversal. depth: Maximum recursion depth (default: 1). Use depth=1 to get immediate predecessors only. include: Optional predicate to filter nodes. Only nodes satisfying this condition are included. exclude: Optional predicate to filter nodes. Nodes satisfying this condition are excluded. Returns: List of predecessor nodes that pass the include/exclude filters. Note: Recursion does not traverse through excluded or non-included nodes. """Also applies to: 478-482
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**/*.{h,hpp,hh,hxx,cpp,cxx,cc,cu,cuh,py}
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**/*.py
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Files:
tensorrt_llm/_torch/auto_deploy/utils/node_utils.py
**/*.{cpp,cxx,cc,h,hpp,hh,hxx,cu,cuh,py}
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tensorrt_llm/_torch/auto_deploy/utils/node_utils.py
🧬 Code graph analysis (1)
tensorrt_llm/_torch/auto_deploy/utils/node_utils.py (2)
tensorrt_llm/_torch/auto_deploy/custom_ops/attention_interface.py (1)
args(252-254)tensorrt_llm/_torch/auto_deploy/shim/interface.py (1)
args(23-25)
🪛 Ruff (0.14.0)
tensorrt_llm/_torch/auto_deploy/utils/node_utils.py
450-450: PEP 484 prohibits implicit Optional
Convert to T | None
(RUF013)
451-451: PEP 484 prohibits implicit Optional
Convert to T | None
(RUF013)
475-475: PEP 484 prohibits implicit Optional
Convert to T | None
(RUF013)
476-476: PEP 484 prohibits implicit Optional
Convert to T | None
(RUF013)
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tensorrt_llm/_torch/auto_deploy/utils/node_utils.py (1)
472-492: Logic is correct, but ensure consistency withpredecessorsafter its fix.The filtering logic here correctly skips nodes that don't pass
include/excludechecks and doesn't recurse into them. After fixing thepredecessorsfunction, verify both functions have consistent behavior.
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Signed-off-by: greg-kwasniewski1 <213329731+greg-kwasniewski1@users.noreply.github.com>
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Signed-off-by: greg-kwasniewski1 <213329731+greg-kwasniewski1@users.noreply.github.com>
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Description
This tiny PR does not introduce any "end-user" features, but it adds two helper functions predecessors and successors that are very helpful to detect and analyze subgraph patterns. They are continuously used for sharding analysis, and I believe it is useful to have them in the main branch, rather than recreating them for each new feature development.
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