[#8384][fix] use dict.get() instead of getattr() for rope_scaling dict access - #11575
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⚠️ Outside diff range comments (1)
tensorrt_llm/_torch/modules/qk_norm_attention.py (1)
1-1:⚠️ Potential issue | 🟡 MinorUpdate the copyright year to 2026.
The file was meaningfully modified in this PR but the copyright header still reads
2025. As per coding guidelines, the year must be updated on modified files.📝 Proposed fix
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.As per coding guidelines: "Include NVIDIA copyright header on ALL new files and update year on modified files."
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@tensorrt_llm/_torch/modules/qk_norm_attention.py` at line 1, Update the copyright year in the file header: find the SPDX header line containing "SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES" and change the year from 2025 to 2026 so the header reads 2026.
🧹 Nitpick comments (1)
tensorrt_llm/_torch/modules/qk_norm_attention.py (1)
48-49: RedundantNonedefault in.get("rope_type", None).
dict.get()already returnsNonewhen the key is absent; passing it explicitly adds noise.rope_scaling.get("rope_type")is idiomatic.♻️ Proposed nit
- if rope_scaling is None or rope_scaling.get("rope_type", - None) != "yarn": + if rope_scaling is None or rope_scaling.get("rope_type") != "yarn":🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@tensorrt_llm/_torch/modules/qk_norm_attention.py` around lines 48 - 49, The condition uses a redundant explicit None default in rope_scaling.get("rope_type", None); change it to rope_scaling.get("rope_type") so the check becomes if rope_scaling is None or rope_scaling.get("rope_type") != "yarn": — update the expression in the qk_norm_attention logic where rope_scaling is inspected to remove the unnecessary None argument.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Outside diff comments:
In `@tensorrt_llm/_torch/modules/qk_norm_attention.py`:
- Line 1: Update the copyright year in the file header: find the SPDX header
line containing "SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION &
AFFILIATES" and change the year from 2025 to 2026 so the header reads 2026.
---
Nitpick comments:
In `@tensorrt_llm/_torch/modules/qk_norm_attention.py`:
- Around line 48-49: The condition uses a redundant explicit None default in
rope_scaling.get("rope_type", None); change it to rope_scaling.get("rope_type")
so the check becomes if rope_scaling is None or rope_scaling.get("rope_type") !=
"yarn": — update the expression in the qk_norm_attention logic where
rope_scaling is inspected to remove the unnecessary None argument.
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rope_scaling from HuggingFace PretrainedConfig is a dict, not an object. Using getattr() on a dict doesn't access dict keys - it always returns the default value. This caused YaRN RoPE scaling to never be activated: - rope_type check always returned None instead of 'yarn' - factor always returned 1.0 instead of the configured scaling factor Fixes NVIDIA#8384 Signed-off-by: Wojciech Wais <wojciech.wais@gmail.com>
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They should be addressed now. |
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rope_scaling from HuggingFace PretrainedConfig is a dict, not an object. Using getattr() on a dict doesn't access dict keys - it always returns the default value. This caused YaRN RoPE scaling to never be activated:
Fixes #8384
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