A small collection of utils and a test suite for optimum-amd's Brevitas example.
The test suite has been tested with the following:
- python==3.11
- PyTorch==2.12
- accelerate==main
- transformers>=4.38.1
- optimum>=1.17.0
- brevitas==dev
- pytest==8.0.1
- optimum-amd (See instructions below)
The easiest way to set up the environment is with miniforge as follows:
mamba env create -n oamdu -f conda/oamd_hf_main_pt2.1.2_minimal.yml
pip install -e /path/to/optimum-amd/
ln -s /path/to/optimum-amd/examples/quantization/brevitas/quantize_llm.py src/optimum_amd_utils/examples/
ln -s /path/to/optimum-amd/examples/quantization/brevitas/validate_onnx.py src/optimum_amd_utils/examples/
pip install -e .
The tests have many markers representing different PTQ algorithms and device targets. To run a test suite which tests:
- Small and large OPT, Llama & Mistral models
- every PTQ algorithm individually
- every device (cpu, gpu, accelerate without CPU offload, accelerate with CPU offload, accelerate with multiple GPUs),
run the following:
CUDA_VISIBLE_DEVICES=0 pytest -m "short and (cpu or gpu or acc or acc_offload)"
Alternatively, to run all the tests with the "recommended" settings, run:
CUDA_VISIBLE_DEVICES=0 pytest -m "recommended"
For any failing tests, you can use it's name to run it individually, for example:
CUDA_VISIBLE_DEVICES=0 pytest "test/brevitas/test_main.py::test_toggle_opt_acc[run_toggle_args4]"
A good set of tests to run to test that the main modes don't fail are:
CUDA_VISIBLE_DEVICES=0 pytest -m "short and run and (opt or small_models) and (cpu or gpu) and not recommended"
CUDA_VISIBLE_DEVICES=1 pytest -m "short and run and (opt or small_models) and (acc or acc_offload) and not recommended"
CUDA_VISIBLE_DEVICES=2 pytest -m "short and run and (opt or small_models) and recommended"
assuming you have 3 GPUs.
To run the mulit-GPU tests, a good set is:
CUDA_VISIBLE_DEVICES=0,1,2 pytest -m "short and run and (opt or small_models) and recommended and acc_gpus"
Again, assuming you have 3 GPUs.
The following will test all the models that we're supposed to deliver on multiple GPUs:
CUDA_VISIBLE_DEVICES=0,1,2 pytest -m "large_models and ppl and acc_gpus"