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[Issue 6193] Fix gemma3vl weight loader #6233

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Merged
merged 1 commit into from
Jul 22, 2025

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@johncalesp johncalesp commented Jul 21, 2025

Summary by CodeRabbit

  • New Features
    • Expanded model support by enabling additional registration for conditional generation tasks.
  • Improvements
    • Enhanced configuration handling for model initialization.
    • Updated weight loading interface to support custom weight mappers.
  • Tests
    • Adjusted test exclusion timing for a specific multimodal quickstart test in integration test configurations.

Description

This PR fixes issues with weight loading of gemma3vl by registering the model to the register_mapper and also move the test to pre-merge to make sure future changes are tested against this model too.

Test Coverage

  • test_e2e.py::test_ptp_quickstart_multimodal[gemma-3-27b-it-gemma/gemma-3-27b-it-image-True]

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Signed-off-by: John Calderon <[email protected]>
@johncalesp johncalesp requested a review from a team as a code owner July 21, 2025 19:41
@johncalesp johncalesp requested review from liji-nv and brb-nv July 21, 2025 19:41
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coderabbitai bot commented Jul 21, 2025

Walkthrough

The updates include registering the Gemma3HfWeightMapper for an additional model type, modifying the Gemma3VLM class to deep copy its configuration and accept a weight mapper in its load_weights method, and adjusting the test exclusion list for a specific multimodal test in the integration test configuration.

Changes

File(s) Change Summary
tensorrt_llm/_torch/models/checkpoints/hf/gemma3_weight_mapper.py Added registration decorator for "Gemma3ForConditionalGeneration" to Gemma3HfWeightMapper.
tensorrt_llm/_torch/models/modeling_gemma3vl.py Deep copy of model_config in Gemma3VLM constructor; updated load_weights to accept weight_mapper.
tests/integration/test_lists/test-db/l0_h100.yml Moved a specific multimodal test exclusion from post_merge to pre_merge for PyTorch backend.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant Gemma3VLM
    participant LLM
    participant BaseWeightMapper

    User->>Gemma3VLM: initialize(model_config)
    Gemma3VLM->>Gemma3VLM: deepcopy(model_config)
    User->>Gemma3VLM: load_weights(weights, weight_mapper)
    Gemma3VLM->>LLM: load_weights(weights, weight_mapper)
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Estimated code review effort

2 (~12 minutes)

Suggested reviewers

  • brb-nv
  • tijyojwad
  • hyukn
  • QiJune

Poem

In the warren where code bunnies dwell,
We mapped new weights and mapped them well.
A copy deep, a test moved near,
The Gemma3’s path is crystal clear!
With every hop, our models grow—
Onward, rabbits, to the next plateau! 🐇


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📥 Commits

Reviewing files that changed from the base of the PR and between 9645814 and 7b18e8d.

📒 Files selected for processing (3)
  • tensorrt_llm/_torch/models/checkpoints/hf/gemma3_weight_mapper.py (1 hunks)
  • tensorrt_llm/_torch/models/modeling_gemma3vl.py (4 hunks)
  • tests/integration/test_lists/test-db/l0_h100.yml (1 hunks)
🧰 Additional context used
🧬 Code Graph Analysis (1)
tensorrt_llm/_torch/models/checkpoints/hf/gemma3_weight_mapper.py (1)
tensorrt_llm/_torch/models/modeling_utils.py (1)
  • register_mapper (589-600)
🔇 Additional comments (6)
tensorrt_llm/_torch/models/checkpoints/hf/gemma3_weight_mapper.py (1)

9-9: LGTM! Registration enables gemma3vl weight loading support.

The additional registration for Gemma3ForConditionalGeneration allows the weight mapper to properly handle gemma3vl models alongside the existing causal LM support. The implementation correctly reuses the same weight mapping logic for both model types.

tests/integration/test_lists/test-db/l0_h100.yml (1)

78-78: Good move to validate gemma3vl in pre-merge.

Moving this multimodal test to the pre-merge stage ensures that the gemma3vl weight loading fixes are validated early in the development cycle. This aligns well with the PR's goal of improving reliability for this model variant.

tensorrt_llm/_torch/models/modeling_gemma3vl.py (4)

1-1: Import addition supports config deep copying.

Adding the copy module import to support the configuration isolation changes below.


11-12: Import enables flexible weight mapper integration.

The BaseWeightMapper import allows the load_weights method to accept different weight mapper implementations, including the newly registered Gemma3HfWeightMapper.


105-106: Excellent defensive programming with config deep copy.

Creating a deep copy of the model configuration prevents unintended mutations that could affect other parts of the system. This isolation is particularly important in multi-model scenarios.


149-151: Weight mapper integration completes the fix.

The updated method signature accepting BaseWeightMapper and passing it to the LLM's load_weights method enables the proper weight loading mechanism that this PR aims to fix. This works in conjunction with the mapper registration changes.

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@johncalesp
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/bot run

@johncalesp johncalesp requested review from brb-nv and removed request for brb-nv July 21, 2025 19:43
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LGTM. Thank you for looking into this, John!

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PR_Github #12472 [ run ] triggered by Bot

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PR_Github #12472 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #9277 completed with status: 'FAILURE'

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/bot run

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PR_Github #12572 [ run ] triggered by Bot

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PR_Github #12572 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #9351 completed with status: 'SUCCESS'

@brb-nv brb-nv merged commit b7c8a67 into NVIDIA:main Jul 22, 2025
3 checks passed
yali-arch pushed a commit to yali-arch/TensorRT-LLM that referenced this pull request Jul 23, 2025
@johncalesp johncalesp deleted the patch-gemma3vl-weight-loading branch July 23, 2025 14:15
NVShreyas pushed a commit to NVShreyas/TensorRT-LLM that referenced this pull request Jul 28, 2025
Signed-off-by: John Calderon <[email protected]>
Signed-off-by: Shreyas Misra <[email protected]>
Ransiki pushed a commit to Ransiki/TensorRT-LLM that referenced this pull request Jul 29, 2025
Signed-off-by: John Calderon <[email protected]>
Signed-off-by: Ransiki Zhang <[email protected]>
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