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Testing FBGEMM_GPU

The tests (in the fbgemm_gpu/test/ directory) and benchmarks (in the fbgemm_gpu/bench/ directory) provide good examples on how to use FBGEMM_GPU.

FBGEMM_GPU Tests

To run the tests after building / installing the FBGEMM_GPU package:

# From the /fbgemm_gpu/ directory
cd test

python -m pytest -v -rsx -s -W ignore::pytest.PytestCollectionWarning split_table_batched_embeddings_test.py
python -m pytest -v -rsx -s -W ignore::pytest.PytestCollectionWarning quantize_ops_test.py
python -m pytest -v -rsx -s -W ignore::pytest.PytestCollectionWarning sparse_ops_test.py
python -m pytest -v -rsx -s -W ignore::pytest.PytestCollectionWarning split_embedding_inference_converter_test.py

Testing with the CUDA Variant

For the FBGEMM_GPU CUDA package, GPUs will be automatically detected and used for testing. To run the tests and benchmarks on a GPU-capable device in CPU-only mode, CUDA_VISIBLE_DEVICES=-1 must be set in the environment:

# Enable for running in CPU-only mode (when on a GPU-capable machine)
export CUDA_VISIBLE_DEVICES=-1

# Enable for debugging failed kernel executions
export CUDA_LAUNCH_BLOCKING=1

python -m pytest -v -rsx -s -W ignore::pytest.PytestCollectionWarning split_table_batched_embeddings_test.py

Testing with the ROCm Variant

For ROCm machines, testing against a ROCm GPU needs to be enabled with FBGEMM_TEST_WITH_ROCM=1 set in the environment:

# From the /fbgemm_gpu/ directory
cd test

export FBGEMM_TEST_WITH_ROCM=1
# Enable for debugging failed kernel executions
export HIP_LAUNCH_BLOCKING=1

python -m pytest -v -rsx -s -W ignore::pytest.PytestCollectionWarning split_table_batched_embeddings_test.py

FBGEMM_GPU Benchmarks

To run the benchmarks:

# From the /fbgemm_gpu/ directory
cd bench

python split_table_batched_embeddings_benchmark.py uvm

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