* Only xfail windows models in CI
* downloader: make model updates more robust.
* Separate baseline and native benchmarks in pytest.
* Fix native benchmarks
* Fix torchvision model utils.
* Fix sharktank generation and add batch_size pytest option for torch.
* Disable torch dynamo until py3.11 supported
* Compile torchmodel without dynamo if torch.compile fails
* Use release versions of TF/Keras for importer.
* Pin torchvision and remove debug prints.
* Remove duplicates from torch model list.
* Update generate_sharktank.py
* xfail a few models that fail sharktank generation/ numerics
* Move most xfails to entries in tank/all_models.csv
* enable usage of pytest without specifying tank/test_models.py
* add dict_configs.py to gitignore.
* Pin versions for runtimes and torch-mlir for setup.
* Use IREE tf tools to save .mlir modules when generating shark_tank.
* Add option to pytest for enabling auto-updates to local shark tank.
* xfail mobilenet torch on cpu, cuda and fix CI macos setup
* Update test-models.yml to disable macos vulkan CI.
* Add ONNX env var flags for venv setup.
* Setup arguments for ONNX benchmarking via pytest.
* Enable ONNX benchmarking on MiniLM via pytest (experimental)
* Fix sequence lengths to 128 for TF model creation and fix issue with benchmarks.
* Disable CI CPU benchmarks on A100, change some default args.
* add xfails for roberta TF model tests on GPU.
