Add Llama 3.1 & 3.2 to Arc Performance test (#12225)
* Add llama3.1 and llama3.2 in arc perf (#12202) * Add llama3.1 and llama3.2 in arc perf * Uninstall trl after arc test on transformers>=4.40 * Fix arc llama3 perf (#12212) * Fix pip uninstall * Uninstall trl after test on transformers==4.43.1 * Fix llama3 arc perf (#12218) --------- Co-authored-by: Jin, Qiao <89779290+JinBridger@users.noreply.github.com>
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.github/workflows/llm_performance_tests.yml
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.github/workflows/llm_performance_tests.yml
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@ -233,6 +233,76 @@ jobs:
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python run.py
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python run.py
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mv *.csv test_batch1
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mv *.csv test_batch1
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- name: Test on xpu(transformers==4.43.1)
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shell: bash
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run: |
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source /opt/intel/oneapi/setvars.sh
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export USE_XETLA=OFF
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export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
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# upgrade for default transformers version
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python -m pip install transformers==4.43.1
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python -m pip install trl
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# batch_size 1
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cp python/llm/test/benchmark/arc-perf-transformers-443.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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# change csv name
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sed -i 's/test3_batch1/test4_batch1/g' run.py
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python run.py
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mv *.csv test_batch1
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# batch_size 2
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cd ../../../../../
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cp python/llm/test/benchmark/arc-perf-transformers-443-batch2.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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# change csv name
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sed -i 's/batch1/batch2/g' run.py
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python run.py
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mv *.csv test_batch2
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# batch_size 4
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cd ../../../../../
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cp python/llm/test/benchmark/arc-perf-transformers-443-batch4.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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# change csv name
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sed -i 's/batch2/batch4/g' run.py
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python run.py
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mv *.csv test_batch4
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python -m pip uninstall -y trl
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- name: Test on xpu(transformers==4.45.0)
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shell: bash
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run: |
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source /opt/intel/oneapi/setvars.sh
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export USE_XETLA=OFF
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export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
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# upgrade for default transformers version
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python -m pip install transformers==4.45.0
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python -m pip install trl
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python -m pip install accelerate==0.33.0
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# batch_size 1
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cp python/llm/test/benchmark/arc-perf-transformers-445.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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# change csv name
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sed -i 's/test4_batch4/test5_batch1/g' run.py
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python run.py
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mv *.csv test_batch1
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# batch_size 2
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cd ../../../../../
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cp python/llm/test/benchmark/arc-perf-transformers-445-batch2.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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# change csv name
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sed -i 's/batch1/batch2/g' run.py
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python run.py
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mv *.csv test_batch2
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# batch_size 4
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cd ../../../../../
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cp python/llm/test/benchmark/arc-perf-transformers-445-batch4.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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# change csv name
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sed -i 's/batch2/batch4/g' run.py
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python run.py
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mv *.csv test_batch4
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python -m pip install accelerate==0.23.0
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python -m pip uninstall -y trl
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- name: Concat csv and generate html
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- name: Concat csv and generate html
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shell: bash
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shell: bash
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run: |
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run: |
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@ -0,0 +1,16 @@
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repo_id:
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- 'meta-llama/Llama-3.1-8B-Instruct'
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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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batch_size: 2 # default to 1
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in_out_pairs:
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- '32-32'
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- '1024-128'
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- '2048-256'
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test_api:
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- "transformer_int4_fp16_gpu" # on Intel GPU
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cpu_embedding: False # whether put embedding to CPU (only avaiable now for gpu win related test_api)
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task: 'continuation' # task can be 'continuation', 'QA' and 'summarize'
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@ -0,0 +1,16 @@
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repo_id:
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- 'meta-llama/Llama-3.1-8B-Instruct'
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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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batch_size: 4 # default to 1
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in_out_pairs:
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- '32-32'
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- '1024-128'
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- '2048-256'
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test_api:
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- "transformer_int4_fp16_gpu" # on Intel GPU
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cpu_embedding: False # whether put embedding to CPU (only avaiable now for gpu win related test_api)
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task: 'continuation' # task can be 'continuation', 'QA' and 'summarize'
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16
python/llm/test/benchmark/arc-perf-transformers-443.yaml
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16
python/llm/test/benchmark/arc-perf-transformers-443.yaml
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@ -0,0 +1,16 @@
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repo_id:
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- 'meta-llama/Llama-3.1-8B-Instruct'
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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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batch_size: 1 # default to 1
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in_out_pairs:
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- '32-32'
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- '1024-128'
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- '2048-256'
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test_api:
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- "transformer_int4_fp16_gpu" # on Intel GPU
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cpu_embedding: False # whether put embedding to CPU (only avaiable now for gpu win related test_api)
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task: 'continuation' # task can be 'continuation', 'QA' and 'summarize'
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@ -0,0 +1,17 @@
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repo_id:
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- 'meta-llama/Llama-3.2-1B-Instruct'
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- 'meta-llama/Llama-3.2-3B-Instruct'
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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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batch_size: 2 # default to 1
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in_out_pairs:
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- '32-32'
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- '1024-128'
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- '2048-256'
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test_api:
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- "transformer_int4_fp16_gpu" # on Intel GPU
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cpu_embedding: False # whether put embedding to CPU (only avaiable now for gpu win related test_api)
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task: 'continuation' # task can be 'continuation', 'QA' and 'summarize'
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@ -0,0 +1,17 @@
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repo_id:
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- 'meta-llama/Llama-3.2-1B-Instruct'
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- 'meta-llama/Llama-3.2-3B-Instruct'
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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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batch_size: 4 # default to 1
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in_out_pairs:
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- '32-32'
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- '1024-128'
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- '2048-256'
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test_api:
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- "transformer_int4_fp16_gpu" # on Intel GPU
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cpu_embedding: False # whether put embedding to CPU (only avaiable now for gpu win related test_api)
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task: 'continuation' # task can be 'continuation', 'QA' and 'summarize'
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17
python/llm/test/benchmark/arc-perf-transformers-445.yaml
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17
python/llm/test/benchmark/arc-perf-transformers-445.yaml
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repo_id:
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- 'meta-llama/Llama-3.2-1B-Instruct'
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- 'meta-llama/Llama-3.2-3B-Instruct'
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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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batch_size: 1 # default to 1
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in_out_pairs:
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- '32-32'
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- '1024-128'
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- '2048-256'
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test_api:
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- "transformer_int4_fp16_gpu" # on Intel GPU
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cpu_embedding: False # whether put embedding to CPU (only avaiable now for gpu win related test_api)
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task: 'continuation' # task can be 'continuation', 'QA' and 'summarize'
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