Use to test llm-performance on spr-perf (#9316)
* Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update action.yml * Create cpu-perf-test.yaml * Update action.yml * Update action.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml * Update llm_performance_tests.yml
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								.github/workflows/llm_performance_tests.yml
									
									
									
									
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								.github/workflows/llm_performance_tests.yml
									
									
									
									
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					@ -137,4 +137,51 @@ jobs:
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          curl -T ./*.csv ${LLM_FTP_URL}/llm/ggml-actions/perf/
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					          curl -T ./*.csv ${LLM_FTP_URL}/llm/ggml-actions/perf/
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          cp ./*.csv /mnt/disk1/nightly_perf/
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					          cp ./*.csv /mnt/disk1/nightly_perf/
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          cd ../../../test/benchmark
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					          cd ../../../test/benchmark
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          python csv_to_html.py -f /mnt/disk1/nightly_perf/
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					          python csv_to_html.py -f ../../dev/benchmark/all-in-one
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					          cp ./*.html /mnt/disk1/nightly_perf/
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					  llm-performance-test-on-spr:
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					    needs: llm-cpp-build
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					    strategy:
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					      fail-fast: false
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					      matrix:
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					        python-version: ["3.9"]
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					    runs-on: [self-hosted, llm, spr-perf]
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					    env:
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					      OMP_NUM_THREADS: 16
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					      THREAD_NUM: 16
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					      ANALYTICS_ZOO_ROOT: ${{ github.workspace }}
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					    steps:
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					      - uses: actions/checkout@v3
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					      - name: Set up Python ${{ matrix.python-version }}
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					        uses: actions/setup-python@v4
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					        with:
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					          python-version: ${{ matrix.python-version }}
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					      - name: Install dependencies
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					        shell: bash
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					        run: |
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					          python -m pip install --upgrade pip
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					          python -m pip install --upgrade wheel
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					          python -m pip install --upgrade omegaconf
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					          python -m pip install --upgrade pandas
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					          python -m pip install --upgrade einops
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					      - name: Download llm binary
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					        uses: ./.github/actions/llm/download-llm-binary
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					      - name: Run LLM install (all) test
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					        uses: ./.github/actions/llm/setup-llm-env
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					      - name: Test on cpu
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					        shell: bash
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					        run: |
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					          mv python/llm/test/benchmark/cpu-perf-test.yaml python/llm/dev/benchmark/all-in-one/config.yaml
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					          cd python/llm/dev/benchmark/all-in-one
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					          export http_proxy=${HTTP_PROXY}
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					          export https_proxy=${HTTPS_PROXY}
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					          python run.py
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					          cp ./*.csv /mnt/disk1/nightly_perf_cpu/
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					          cd ../../../test/benchmark
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					          python csv_to_html.py -f /mnt/disk1/nightly_perf_cpu/
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								python/llm/test/benchmark/cpu-perf-test.yaml
									
									
									
									
									
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								python/llm/test/benchmark/cpu-perf-test.yaml
									
									
									
									
									
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					@ -0,0 +1,18 @@
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					repo_id:
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					  - 'meta-llama/Llama-2-7b-chat-hf'
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					local_model_hub: '/mnt/disk1/models'
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					warm_up: 1
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					num_trials: 3
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					num_beams: 1 # default to greedy search
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					low_bit: 'sym_int4' # default to use 'sym_int4' (i.e. symmetric int4)
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					in_out_pairs:
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					  - '32-32'
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					  - '1024-128'
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					test_api:
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					  - "transformer_int4"
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					  # - "native_int4"
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					  # - "optimize_model"
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					  # - "pytorch_autocast_bf16"
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					  # - "ipex_fp16_gpu" # on Intel GPU
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					  # - "transformer_int4_gpu"  # on Intel GPU
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					  # - "optimize_model_gpu"  # on Intel GPU
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