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Keval Morabia
19e0121d0a
### What does this PR do? Type of change: Bug fix + new tests (test-suite only; changes are confined to `tests/`) - **Fix `test_parallel_load_and_export` hang on 2 GPUs.** The temp paths were built from `os.getpid()` *inside* the workers, so each rank got a different `ckpt_dir`; rank 1 then took `_resolve_checkpoint_dir`'s Hub branch and blocked on an extra barrier while rank 0 ran the loader's broadcasts. The checkpoint is now built once in the parent under `tmp_path` and passed in, so all ranks agree on the path. - **Imports moved to module top** across `tests/gpu*` and `tests/examples`; function-local imports kept only where guarded (`importorskip`/`try`), where the import *is* the test (JIT compile), or where it must follow `sys.path` setup. - **Reuse `_test_utils` instead of local copies:** added `get_tiny_mixtral`; deduped `assert_nodes_are_quantized` (5 copies), the accelerate-offload/layerwise config helpers, `make_quant_attention`, `get_dflash_config`, the NVFP4 amax assertions, and 3 copies of the `tiny_wan22_path` fixture. - **Shared model-dir fixtures assert they were not modified** (`assert_unmodified_tree`): a file manifest is compared on teardown, so a test that writes into a session-scoped fixture directory fails instead of silently changing what later tests see. - **Dropped dependency guards the CI env already guarantees** (diffusers, tensorrt_llm in `gpu_trtllm`, transformer_engine in `gpu_megatron`, transformers in examples) so a missing dep fails loudly instead of skipping. - **`test_heterogenous_sharded_state_dict` is skipped on Blackwell** (sm_120), matching the existing marker and its TE/CUDA-13 rationale — same tracking issue as #1901. ### Testing Local, 2x RTX 6000 Ada: `tests/gpu/torch/utils/test_model_load_utils.py` passes on 2 GPUs and on 1 GPU (previously hung on 2). Also ran the touched files in `tests/unit` (608 passed) and `tests/gpu` (~340 passed). ### Before your PR is "*Ready for review*" - Is this change backward compatible?: ✅ - If you copied code from any other sources or added a new PIP dependency, did you follow guidance in `CONTRIBUTING.md`: N/A - Did you write any new necessary tests?: N/A — test-only PR - Did you update [Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?: N/A - Did you get Claude approval on this PR?: ❌ — not yet run <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Tests** * Added reusable validation utilities for generated files, quantization behavior, attention modules, model fixtures, offloading, and speculative decoding. * Expanded coverage for tiny Wan, Mixtral, Llama, and related model scenarios. * Consolidated duplicated setup and assertions across ONNX, GPU, quantization, export, and sparsity tests. * Improved fixture integrity checks, NVFP4 validation, and handling of identity inputs. * Reduced unnecessary dependency-based skips and isolated known platform-specific flakiness. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>
Model Optimizer End-to-End Tests
This directory contains end-to-end tests for the Model Optimizer's examples.
Adding new tests
To add a test for a new example, create a new example directory in tests/examples following the existing examples as guidance.
Make sure to use as small models and less data as possible to keep the tests fast. Unless needed, have tests finish under 15 minutes.
Running the tests
To run a test, start from the recommended docker image from our installation docs.
Then mount your local modelopt directory to /workspace/Model-Optimizer and run this from the root of the repository.
cd /workspace/Model-Optimizer
pip install -e ".[all,dev-test]"
pytest tests/examples/$TEST
Environment variables
The following environment variables can be set to control the behavior of the tests:
MODELOPT_LOCAL_MODEL_ROOT: If set, the tests will use the local model directory instead of downloading the model from the internet. Default is not set, which means the model will be downloaded.