[Bug] MutableTorchTRTModule refit flag stuck at NEEDS_REFIT, never transitions to LIVE on B100/H100 with CUDA 13.x

[apbose]

Bug Description

test_resnet18_modify_attribute_no_refit fails because update_refit_condition() does not transition the RefitFlag from NEEDS_REFIT (2) to LIVE (4). This reproduces across all CUDA 13.x versions on both B100-TS2 and H100, and surfaces through multiple dynamo test suites (backend, conversion, models, partitioning).

Environment

• GPUs: B100-TS2, H100
• Arch: x86_64
• CUDA: 13.2.0 / 13.1.1 / 13.0.2
• OS: Ubuntu 24.04
• cuDNN: 8.9.7.29
• • TensorRT: 10.16.0.59
• Myelin: 2.17.78+7
• CASK: 5.16.17+1
• Python: 3.12
• Package: qa_tar_py3.12

Failing Test

FAILED runtime/test_mutable_torchtrt_module.py::test_resnet18_modify_attribute_no_refit
  AssertionError: <RefitFlag.NEEDS_REFIT: 2> != <RefitFlag.LIVE: 4> :
  update_refit_condition() failed to set the flag to LIVE.

Reproducible Configurations

GPU	CUDA	Test Suites Affected	Result
B100-TS2/x86_64	r13.0.2, r13.1.1, r13.2.0	backend, conversion, models, partitioning	FAILED
H100/x86_64	r13.1.1, r13.2.0	backend, conversion, models, partitioning	FAILED

All 20 logged test runs failed — no passing configuration observed.

Steps to Reproduce

1. Run on B100-TS2 or H100 with CUDA 13.x and the environment above
2. Execute: pytest runtime/test_mutable_torchtrt_module.py::test_resnet18_modify_attribute_no_refit

Expected Behavior

After modifying a model attribute without triggering a refit, update_refit_condition() should transition the RefitFlag from NEEDS_REFIT to LIVE, indicating the engine is still valid and does not require a full refit.

Additional Context

The failure appears in all four dynamo test suite categories (backend, conversion, models, partitioning), suggesting the issue is in the core MutableTorchTRTModule runtime logic rather than in any specific converter or partitioning path.