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[https://nvbugs/5509024][fix] Print full parsed outputs and update keywords for multimodal model#7670
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📝 WalkthroughWalkthroughPrecomputes parsed multimodal outputs once per test, reuses them in assertions, expands assertion failure messages to include full parsed outputs, updates expected token lists for several models, and enables additional Gemma-specific CLI options in multimodal end-to-end tests. Changes are limited to tests. Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes ✨ Finishing touches
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Actionable comments posted: 3
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tests/integration/defs/test_e2e.py (1)
2728-2740:Do not rely on zip() truncation; assert full coverage firstSame fix pattern as above to guarantee 1:1 checking.
- parsed_outputs = parse_output(output)- for prompt_output, prompt_keywords in zip(- parsed_outputs, expected_keywords[model_name]["image"]):+ parsed_outputs = parse_output(output)+ expected = expected_keywords[model_name]["image"]+ assert len(parsed_outputs) == len(expected), (+ f"Expected {len(expected)} outputs, got {len(parsed_outputs)}. "+ f"Full output: {parsed_outputs}"+ )+ for prompt_output, prompt_keywords in zip(parsed_outputs, expected): matches = [ keyword in prompt_output.lower() for keyword in prompt_keywords ] obs_match_ratio = 1. * sum(matches) / len(matches) print("prompt_output:", prompt_output) print("prompt_keywords:", prompt_keywords) print("matches:", matches) print("obs_match_ratio:", obs_match_ratio) assert obs_match_ratio >= match_ratio, f"Incorrect output!\nFull output: {parsed_outputs}\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}"
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ad210d1 toe3ac09dCompare294ae94 tod84fde4Compare* Also print parsed_ouput for easy debugging.Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>
d84fde4 to2a6a059CompareWanli-Jiang commentedSep 16, 2025
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tensorrt-cicd commentedSep 16, 2025
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tests/integration/defs/test_e2e.py (3)
2381-2388:Add a length assertion before zipping to avoid silent truncationZip truncates on length mismatch; assert counts first and reuse a local expected variable.
- parsed_outputs = parse_output(output)- for prompt_output, prompt_keywords in zip(- parsed_outputs, expected_keywords[model_name][modality]):+ parsed_outputs = parse_output(output)+ expected = expected_keywords[model_name][modality]+ assert len(parsed_outputs) == len(expected), (+ f"Expected {len(expected)} outputs, got {len(parsed_outputs)}. "+ f"Parsed outputs: {parsed_outputs}"+ )+ for prompt_output, prompt_keywords in zip(parsed_outputs, expected): matches = [ keyword in prompt_output.lower() for keyword in prompt_keywords ] obs_match_ratio = 1. * sum(matches) / len(matches)- assert obs_match_ratio >= match_ratio, f"Incorrect output!\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\nParsed output for all prompts: {parsed_outputs}"+ assert obs_match_ratio >= match_ratio, f"Incorrect output!\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\nParsed output for all prompts: {parsed_outputs}"
2521-2528:Same here: guard against mismatched counts before zip()Mirror the length check and local expected var for Phi‑4‑MM.
- parsed_outputs = parse_output(output)- for prompt_output, prompt_keywords in zip(parsed_outputs,- expected_keywords[modality]):+ parsed_outputs = parse_output(output)+ expected = expected_keywords[modality]+ assert len(parsed_outputs) == len(expected), (+ f"Expected {len(expected)} outputs, got {len(parsed_outputs)}. "+ f"Parsed outputs: {parsed_outputs}"+ )+ for prompt_output, prompt_keywords in zip(parsed_outputs, expected): matches = [ keyword in prompt_output.lower() for keyword in prompt_keywords ] obs_match_ratio = 1. * sum(matches) / len(matches)- assert obs_match_ratio >= match_ratio, f"Incorrect output!\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\nParsed output for all prompts: {parsed_outputs}"+ assert obs_match_ratio >= match_ratio, f"Incorrect output!\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\nParsed output for all prompts: {parsed_outputs}"
2628-2635:Also add the count check for the 2‑GPU pathPrevent silent passes in the multi‑GPU variant.
- parsed_outputs = parse_output(output)- for prompt_output, prompt_keywords in zip(- parsed_outputs, expected_keywords[model_name]["image"]):+ parsed_outputs = parse_output(output)+ expected = expected_keywords[model_name]["image"]+ assert len(parsed_outputs) == len(expected), (+ f"Expected {len(expected)} outputs, got {len(parsed_outputs)}. "+ f"Parsed outputs: {parsed_outputs}"+ )+ for prompt_output, prompt_keywords in zip(parsed_outputs, expected): matches = [ keyword in prompt_output.lower() for keyword in prompt_keywords ] obs_match_ratio = 1. * sum(matches) / len(matches)- assert obs_match_ratio >= match_ratio, f"Incorrect output!\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\nParsed output for all prompts: {parsed_outputs}"+ assert obs_match_ratio >= match_ratio, f"Incorrect output!\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\nParsed output for all prompts: {parsed_outputs}"
🧹 Nitpick comments (3)
tests/integration/defs/test_e2e.py (3)
1-14:Update SPDX year range to include 2025Coding guideline requests current year in headers. Update to 2022-2025.
-# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.+# SPDX-FileCopyrightText: Copyright (c) 2022-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
2731-2743:Add length assertion before zipping in multiturn testApply the same guard here to avoid truncated comparisons.
- parsed_outputs = parse_output(output)- for prompt_output, prompt_keywords in zip(- parsed_outputs, expected_keywords[model_name]["image"]):+ parsed_outputs = parse_output(output)+ expected = expected_keywords[model_name]["image"]+ assert len(parsed_outputs) == len(expected), (+ f"Expected {len(expected)} outputs, got {len(parsed_outputs)}. "+ f"Parsed outputs: {parsed_outputs}"+ )+ for prompt_output, prompt_keywords in zip(parsed_outputs, expected): matches = [ keyword in prompt_output.lower() for keyword in prompt_keywords ] obs_match_ratio = 1. * sum(matches) / len(matches) print("prompt_output:", prompt_output) print("prompt_keywords:", prompt_keywords) print("matches:", matches) print("obs_match_ratio:", obs_match_ratio)- assert obs_match_ratio >= match_ratio, f"Incorrect output!\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\nParsed output for all prompts: {parsed_outputs}"+ assert obs_match_ratio >= match_ratio, f"Incorrect output!\nGenerated \"{prompt_output}\"\nExpected keywords \"{prompt_keywords}\"\n Matched keywords: {matches}\n Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\nParsed output for all prompts: {parsed_outputs}"
2381-2388:Optional: factor repeated matching logic into a tiny helperReduces duplication across four tests; keeps failure messaging consistent.
+def _assert_keywords_match_all(parsed_outputs, expected, match_ratio):+ assert len(parsed_outputs) == len(expected), (+ f"Expected {len(expected)} outputs, got {len(parsed_outputs)}. "+ f"Parsed outputs: {parsed_outputs}"+ )+ for prompt_output, prompt_keywords in zip(parsed_outputs, expected):+ matches = [kw in prompt_output.lower() for kw in prompt_keywords]+ obs_match_ratio = 1.0 * sum(matches) / len(matches)+ assert obs_match_ratio >= match_ratio, (+ f"Incorrect output!\nGenerated \"{prompt_output}\"\n"+ f"Expected keywords \"{prompt_keywords}\"\n"+ f"Matched keywords: {matches}\n"+ f"Observed match ratio {obs_match_ratio} below threshold {match_ratio}\n\n"+ f"Parsed output for all prompts: {parsed_outputs}"+ )Then call it with the appropriate expected list in each test.
Also applies to: 2521-2528, 2628-2635, 2731-2743
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**/*.py: Python code must target Python 3.8+.
Indent Python code with 4 spaces; do not use tabs.
Maintain module namespace when importing; prefer 'from package.subpackage import foo' then 'foo.SomeClass()' instead of importing the class directly.
Python filenames should be snake_case (e.g., some_file.py).
Python classes use PascalCase names.
Functions and methods use snake_case names.
Local variables use snake_case; prefix 'k' for variables that start with a number (e.g., k_99th_percentile).
Global variables use upper SNAKE_CASE prefixed with 'G' (e.g., G_MY_GLOBAL).
Constants use upper SNAKE_CASE (e.g., MY_CONSTANT).
Avoid shadowing variables from an outer scope.
Initialize all externally visible members of a class in the constructor.
Prefer docstrings for interfaces that may be used outside a file; comments for in-function or file-local interfaces.
Use Google-style docstrings for classes and functions (Sphinx-parsable).
Document attributes and variables inline so they render under the class/function docstring.
Avoid reflection when a simpler, explicit approach suffices (e.g., avoid dict(**locals()) patterns).
In try/except, catch the most specific exceptions possible.
For duck-typing try/except, keep the try body minimal and use else for the main logic.
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tests/integration/defs/test_e2e.py
**/*.{cpp,cxx,cc,h,hpp,hh,hxx,cu,cuh,py}
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tests/integration/defs/test_e2e.py (2)
2337-2337:Keyword tweaks look fineUpdated expected tokens for mixture_text_image improve stability.
2672-2690:Keyword updates LGTMRevised tokens for gemma/mistral/phi multiturn look reasonable.
Please confirm these keywords reflect the latest model baselines captured in CI to avoid flakiness.
tensorrt-cicd commentedSep 16, 2025
PR_Github #18684 [ run ] completed with state |
Wanli-Jiang commentedSep 16, 2025
/bot run |
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Wanli-Jiang commentedSep 16, 2025
/bot run |
tensorrt-cicd commentedSep 16, 2025
PR_Github #18741 [ run ] triggered by Bot |
tensorrt-cicd commentedSep 16, 2025
PR_Github #18741 [ run ] completed with state |
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…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
…ywords for multimodal model (NVIDIA#7670)Signed-off-by: Wanli Jiang <35160485+Wanli-Jiang@users.noreply.github.com>Signed-off-by: Wangshanshan <30051912+dominicshanshan@users.noreply.github.com>
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