Create a workflow to run benchmarks #73
Workflow file for this run
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| name: Benchmarks | |
| on: | |
| pull_request: | |
| branches: | |
| - main | |
| workflow_dispatch: | |
| inputs: | |
| halt-for-connection: | |
| description: 'Should this workflow run wait for a remote connection?' | |
| type: choice | |
| required: true | |
| default: 'no' | |
| options: | |
| - 'yes' | |
| - 'no' | |
| jobs: | |
| jax-build-and-test: | |
| runs-on: linux-x86-g2-48-l4-4gpu # Use a GPU-enabled runner | |
| container: | |
| image: "gcr.io/tensorflow-testing/nosla-cuda12.3-cudnn9.1-ubuntu20.04-manylinux2014-multipython:latest" | |
| env: | |
| JAXCI_HERMETIC_PYTHON_VERSION: 3.11 | |
| steps: | |
| - name: Checkout JAX Fork | |
| uses: actions/checkout@v3 | |
| with: | |
| repository: 'google-ml-infra/jax-fork' | |
| path: jax-fork | |
| - name: Install JAX Dependencies | |
| working-directory: jax-fork | |
| run: | | |
| python -m pip install --upgrade pip | |
| pip install pytest | |
| pip install absl-py | |
| pip install "jax[cuda12_pip]" # Adjust CUDA version if needed | |
| pip install google-benchmark | |
| - name: Run JAX Multiprocess GPU Test | |
| working-directory: jax-fork | |
| continue-on-error: true | |
| run: python -m pytest tests/multiprocess_gpu_test.py | |
| build-xla-gpu-and-test: | |
| runs-on: linux-x86-g2-48-l4-4gpu # Use a GPU-enabled runner | |
| container: | |
| image: "gcr.io/tensorflow-testing/nosla-cuda12.3-cudnn9.1-ubuntu20.04-manylinux2014-multipython:latest" | |
| options: --gpus all --privileged # Might need privileged mode, use with caution | |
| steps: | |
| - name: Checkout XLA | |
| uses: actions/checkout@v3 | |
| with: | |
| repository: openxla/xla # Replace with your fork if needed | |
| path: xla | |
| - name: Create results directory | |
| working-directory: xla | |
| run: mkdir -p results | |
| - name: Get GPU spec | |
| working-directory: xla | |
| continue-on-error: true | |
| run: nvidia-smi | |
| - name: Configure XLA | |
| working-directory: xla | |
| run: ./configure.py --backend CUDA --nccl | |
| - name: Set TF_CPP_MAX_VLOG_LEVEL | |
| working-directory: xla | |
| run: echo "TF_CPP_MAX_VLOG_LEVEL=1" >> $GITHUB_ENV # Use GITHUB_ENV to persist across steps | |
| - name: Check TF_CPP_MAX_VLOG_LEVEL | |
| working-directory: xla | |
| run: echo "$TF_CPP_MAX_VLOG_LEVEL" | |
| - name: Build hlo_runner_main | |
| working-directory: xla | |
| run: bazel build -c opt --config=cuda --dynamic_mode=off //xla/tools/multihost_hlo_runner:hlo_runner_main | |
| - name: Create gemm_006f564ad71b327343de5f090e801883.hlo | |
| working-directory: xla | |
| run: | | |
| cat << EOF > gemm_00881937d6d49056045c3325a12b108b.hlo | |
| HloModule gemm_fusion_dot.542, entry_computation_layout={(bf16[1,8192,3072]{2,1,0}, s8[3072,6,512]{2,1,0})->bf16[1,8192,6,512]{3,2,1,0}} | |
| %gemm_fusion_dot.542_computation.clone (parameter_0.543: bf16[1,8192,3072], parameter_1.543: s8[3072,6,512]) -> bf16[1,8192,6,512] { | |
| %parameter_0.543 = bf16[1,8192,3072]{2,1,0} parameter(0) | |
| %bitcast.69925 = bf16[8192,3072]{1,0} bitcast(bf16[1,8192,3072]{2,1,0} %parameter_0.543) | |
| %parameter_1.543 = s8[3072,6,512]{2,1,0} parameter(1) | |
| %bitcast.69926 = s8[3072,3072]{1,0} bitcast(s8[3072,6,512]{2,1,0} %parameter_1.543) | |
| %convert.18528 = bf16[3072,3072]{1,0} convert(s8[3072,3072]{1,0} %bitcast.69926), metadata={op_name="pjit(_wrapped_fn)/jit(main)/tarzan_lm.apply/tarzan_lm.decode_with_params/lm/transformer/x_layers_0/self_attention/query/query.quantized_einsum/ABD,DNH->ABNH/convert_element_type[new_dtype=bfloat16 weak_type=False]" source_file="third_party/py/praxis/layers/quantization/operations.py" source_line=220} | |
| %dot.4949 = bf16[8192,3072]{1,0} dot(bf16[8192,3072]{1,0} %bitcast.69925, bf16[3072,3072]{1,0} %convert.18528), lhs_contracting_dims={1}, rhs_contracting_dims={0}, metadata={op_name="pjit(_wrapped_fn)/jit(main)/tarzan_lm.apply/tarzan_lm.decode_with_params/lm/transformer/x_layers_0/self_attention/query/query.quantized_einsum/ABD,DNH->ABNH/dot_general[dimension_numbers=(((2,), (0,)), ((), ())) precision=None preferred_element_type=None]" source_file="third_party/py/praxis/layers/quantization/operations.py" source_line=220} | |
| ROOT %bitcast.69927 = bf16[1,8192,6,512]{3,2,1,0} bitcast(bf16[8192,3072]{1,0} %dot.4949) | |
| } | |
| ENTRY %entry_computation (multiply.28104: bf16[1,8192,3072], Arg_51.52: s8[3072,6,512]) -> bf16[1,8192,6,512] { | |
| %multiply.28104 = bf16[1,8192,3072]{2,1,0} parameter(0) | |
| %Arg_51.52 = s8[3072,6,512]{2,1,0} parameter(1) | |
| ROOT %micro_kernel = bf16[1,8192,6,512]{3,2,1,0} fusion(bf16[1,8192,3072]{2,1,0} %multiply.28104, s8[3072,6,512]{2,1,0} %Arg_51.52), kind=kCustom, calls=%gemm_fusion_dot.542_computation.clone, metadata={op_name="pjit(_wrapped_fn)/jit(main)/tarzan_lm.apply/tarzan_lm.decode_with_params/lm/transformer/x_layers_0/self_attention/query/query.quantized_einsum/ABD,DNH->ABNH/dot_general[dimension_numbers=(((2,), (0,)), ((), ())) precision=None preferred_element_type=None]" source_file="third_party/py/praxis/layers/quantization/operations.py" source_line=220}, backend_config={"operation_queue_id":"0","wait_on_operation_queues":[],"fusion_backend_config":{"kind":"__triton_gemm"},"force_earliest_schedule":false} | |
| } | |
| EOF | |
| # - name: Wait For Connection | |
| # uses: google-ml-infra/actions/ci_connection@main | |
| # with: | |
| # halt-dispatch-input: ${{ inputs.halt-for-connection }} | |
| - name: Run specific HLO file | |
| working-directory: xla | |
| run: ./bazel-bin/xla/tools/multihost_hlo_runner/hlo_runner_main --device_type=gpu --use_spmd_partitioning gemm_00881937d6d49056045c3325a12b108b.hlo &> results/gemm_00881937d6d49056045c3325a12b108b.hlo.log | |
| # - name: Run HLO Module Benchmarks with GPU in xla/tests/fuzz | |
| # working-directory: xla | |
| # continue-on-error: true | |
| # run: | | |
| # for file in xla/tests/fuzz/*.hlo; do | |
| # filename=$(basename "$file") | |
| # # Skip expected failed hlo files. | |
| # if [[ "$filename" == "rand_000060.hlo" || "$filename" == "rand_000067.hlo" || "$filename" == "rand_000072.hlo" ]]; then | |
| # echo "Skipping benchmark on $file" | |
| # continue | |
| # fi | |
| # echo "Running benchmark on $file" | |
| # ./bazel-bin/xla/tools/multihost_hlo_runner/hlo_runner_main --device_type=gpu --use_spmd_partitioning "$file" &> results/"$filename".log | |
| # done | |
| - name: Wait For Connection | |
| uses: google-ml-infra/actions/ci_connection@main | |
| with: | |
| halt-dispatch-input: ${{ inputs.halt-for-connection }} | |
| - name: Download parse_xla_logs.py | |
| working-directory: xla | |
| run: wget https://raw.githubusercontent.com/juliagmt-google/xla/main/.github/workflows/parse_xla_logs.py | |
| - name: Parse XLA logs | |
| working-directory: xla | |
| run: python parse_xla_logs.py results/gemm_00881937d6d49056045c3325a12b108b.hlo.log | |
| - name: Wait For Connection | |
| uses: google-ml-infra/actions/ci_connection@main | |
| with: | |
| halt-dispatch-input: ${{ inputs.halt-for-connection }} | |
| - name: Upload Results | |
| uses: actions/upload-artifact@v4 | |
| with: | |
| name: gpu-xla-benchmarks | |
| path: xla/results | |
| # - name: Wait For Connection | |
| # uses: google-ml-infra/actions/ci_connection@main | |
| # with: | |
| # halt-dispatch-input: ${{ inputs.halt-for-connection }} | |
| # - name: Run HLO Module Benchmarks withg GPU in xla/tests/fuzz | |
| # working-directory: xla | |
| # continue-on-error: true | |
| # run: | | |
| # for file in xla/tests/fuzz/*.hlo; do | |
| # filename=$(basename "$file") | |
| # # Skip expected failed hlo files. | |
| # if [[ "$filename" == "rand_000060.hlo" || "$filename" == "rand_000067.hlo" || "$filename" == "rand_000072.hlo" ]]; then | |
| # echo "Skipping benchmark on $file" | |
| # continue | |
| # fi | |
| # echo "Running benchmark on $file" &> results/"$filename".log | |
| # ./bazel-bin/xla/tools/multihost_hlo_runner/hlo_runner_main --device_type=gpu --use_spmd_partitioning "$file" &> results/"$filename".log | |
| # done | |
| # - name: Upload Results | |
| # uses: actions/upload-artifact@v4 | |
| # with: | |
| # name: gpu-xla-benchmarks | |
| # path: xla/results |