[#8460][feat] Revive and simplify Model Explorer visualization integration

[karthikvetrivel]

Description

This PR revives the Model Explorer graph visualization integration that was broken/outdated (fixes #8460).

Test Coverage

Ran the AutoDeploy example with visualization enabled:

python examples/auto_deploy/build_and_run_ad.py \
  --model "TinyLlama/TinyLlama-1.1B-Chat-v1.0" \
  --args.transforms.visualize-namespace.enabled=true

Verified the transform gracefully skips when model_explorer is not installed:

• Returns TransformInfo(skipped=True, ...) without raising exceptions
• Pipeline continues without interruption

PR Checklist

Please review the following before submitting your PR:

• PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.

• PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.

• Test cases are provided for new code paths (see test instructions)

• Any new dependencies have been scanned for license and vulnerabilities

• CODEOWNERS updated if ownership changes

• Documentation updated as needed

• Update tava architecture diagram if there is a significant design change in PR.

• The reviewers assigned automatically/manually are appropriate for the PR.

• Please check this after reviewing the above items as appropriate for this PR.

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Summary by CodeRabbit

• Bug Fixes
  • Enhanced visualization pipeline resilience—visualization now gracefully handles missing dependencies without interrupting the deployment process.
  • Improved error handling and logging for visualization operations to provide better diagnostics.

_{✏️ Tip: You can customize this high-level summary in your review settings.}

[coderabbitai]

📝 Walkthrough

Walkthrough

Updated the visualization module to revive the broken model explorer integration. Removed legacy JSON handling utilities, introduced non-blocking workflow with guard against missing dependencies, switched to ExportedProgram-based export via te.export, and added comprehensive exception handling to gracefully skip visualization on errors.

Changes

Cohort / File(s)	Change Summary
Visualization module refactor tensorrt_llm/_torch/auto_deploy/transform/library/visualization.py	Removed module-level JSON utilities (print_tensor, _get_shape, add_outputs_metadata); replaced export pathway with ExportedProgram via te.export; added non-blocking guard for missing model_explorer with graceful skip; introduced try-catch error handling; added ad_logger import and enhanced docstring for VisualizeNamespace

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

• Export pathway migration: Verify te.export integration and custom ops nesting logic under parent modules
• Error handling coverage: Ensure exception handling catches all failure scenarios and logging is appropriately detailed
• Backward compatibility: Confirm removal of utilities doesn't break downstream dependencies
• Guard logic: Review the non-blocking check for model_explorer availability and TransformInfo skip behavior

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	You can run @coderabbitai generate docstrings to improve docstring coverage.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly and specifically describes the main change: reviving and simplifying Model Explorer visualization integration, with appropriate ticket reference.
Description check	✅ Passed	The description clearly explains the issue (broken Model Explorer integration), the solution (revived integration), and includes concrete test coverage details demonstrating functionality.
Linked Issues check	✅ Passed	The code changes directly address issue #8460 requirements: reviving Model Explorer integration, updating to latest features via ExportedProgram export, and ensuring graceful handling when model_explorer is unavailable.
Out of Scope Changes check	✅ Passed	All changes are scoped to the visualization.py file and directly support the objective of reviving Model Explorer integration; no unrelated modifications detected.

✨ Finishing touches

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🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment

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[coderabbitai]

Actionable comments posted: 1

Caution

Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (1)

tensorrt_llm/_torch/auto_deploy/transform/library/visualization.py (1)

1-1: Add the required NVIDIA copyright header.

As per coding guidelines, all TensorRT-LLM code must contain an NVIDIA copyright header with the year of its latest meaningful modification. The header is currently missing from this file.

🔎 Proposed fix

+# 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.
+
 """Transformation to the graph to render nicely in model_explorer."""

Based on coding guidelines.

📜 Review details

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Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 478b6b2 and b92a051.

📒 Files selected for processing (1)

• tensorrt_llm/_torch/auto_deploy/transform/library/visualization.py (2 hunks)

🧰 Additional context used

📓 Path-based instructions (2)

**/*.py

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

**/*.py: Code developed for TensorRT-LLM should conform to Python 3.8+
Indent Python code with 4 spaces. Do not use tabs
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Files:

• tensorrt_llm/_torch/auto_deploy/transform/library/visualization.py

**/*.{cpp,h,cu,cuh,py}

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

All TensorRT-LLM Open Source Software code should contain an NVIDIA copyright header that includes the year of its latest meaningful modification

Files:

• tensorrt_llm/_torch/auto_deploy/transform/library/visualization.py

🧬 Code graph analysis (1)

tensorrt_llm/_torch/auto_deploy/transform/library/visualization.py (2)

tensorrt_llm/_torch/auto_deploy/transform/interface.py (3)

• SharedConfig (61-69)
• TransformInfo (124-181)
• get (539-541)

tensorrt_llm/_torch/auto_deploy/shim/interface.py (3)

• CachedSequenceInterface (11-92)
• args (28-30)
• named_args (33-35)

🪛 Ruff (0.14.8)

tensorrt_llm/_torch/auto_deploy/transform/library/visualization.py

44-44: Unused method argument: factory

(ARG002)

---

45-45: Unused method argument: shared_config

(ARG002)

---

71-71: Do not catch blind exception: Exception

(BLE001)

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)

• GitHub Check: Pre-commit Check

🔇 Additional comments (5)

tensorrt_llm/_torch/auto_deploy/transform/library/visualization.py (5)

14-17: LGTM!

The import guard for the optional model_explorer dependency is well-implemented, allowing graceful degradation when the library is unavailable.

---

20-28: LGTM!

The CUSTOM_OPS constant follows proper naming conventions. The TODO comment appropriately flags future configurability as a potential enhancement.

---

31-38: LGTM!

The class follows proper naming conventions and the comprehensive docstring clearly describes the transform's purpose and behavior.

---

40-51: LGTM!

The early return guard when model_explorer is unavailable is well-implemented, returning TransformInfo(skipped=True, ...) to gracefully skip visualization without failing the pipeline. The unused factory and shared_config parameters are inherited from the BaseTransform interface signature.

---

71-76: Exception handling is appropriate for non-blocking visualization.

While broad exception catching is generally discouraged per coding guidelines, it's justified here to ensure visualization failures do not disrupt the transform pipeline. The error is logged and the transform gracefully skips, which aligns with the PR objective of making visualization non-blocking.