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1 |
| -name: OpenVINO - Examples Test |
| 1 | +name: OpenVINO - Notebooks and Examples Test |
2 | 2 |
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3 | 3 | on:
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4 | 4 | workflow_dispatch:
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5 | 5 | schedule:
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6 | 6 | - cron: '14 3 * * 1' # run weekly: every Monday at 3:14
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7 | 7 | push:
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8 | 8 | paths:
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| 9 | + - '.github/workflows/test_openvino_notebooks.yml' |
9 | 10 | - '.github/workflows/test_openvino_examples.yml'
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| 11 | + - 'notebooks/openvino/*' |
10 | 12 | - 'examples/openvino/*'
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11 | 13 | pull_request:
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12 | 14 | paths:
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| 15 | + - '.github/workflows/test_openvino_notebooks.yml' |
13 | 16 | - '.github/workflows/test_openvino_examples.yml'
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| 17 | + - 'notebooks/openvino/*' |
14 | 18 | - 'examples/openvino/*'
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15 | 19 |
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16 | 20 |
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38 | 42 | run: |
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39 | 43 | # Install PyTorch CPU to prevent unnecessary downloading/installing of CUDA packages
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40 | 44 | # ffmpeg, torchaudio and pillow are required for image classification and audio classification pipelines
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41 |
| - pip install optimum[openvino] nncf |
42 |
| - pip install -r examples/openvino/audio-classification/requirements.txt |
| 45 | + sudo apt-get install ffmpeg |
| 46 | + # pip install torch torchaudio --extra-index-url https://download.pytorch.org/whl/cpu |
| 47 | + pip install ".[tests, openvino]" nbval |
| 48 | + pip install optimum[openvino] nncf torchaudio datasets==2.4.0 |
| 49 | + pip install -r notebooks/openvino/requirements.txt |
43 | 50 | pip install -r examples/openvino/image-classification/requirements.txt
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44 | 51 | pip install -r examples/openvino/question-answering/requirements.txt
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45 | 52 | pip install -r examples/openvino/text-classification/requirements.txt
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48 | 55 | - run: lscpu
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49 | 56 | - run: pip freeze
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50 | 57 |
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| 58 | + - name: Test with Pytest |
| 59 | + run: | |
| 60 | + python -m pytest --nbval-lax notebooks/openvino/optimum_openvino_inference.ipynb notebooks/openvino/question_answering_quantization.ipynb |
| 61 | +
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51 | 62 | - name: Test examples
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52 | 63 | run: |
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53 |
| - python examples/openvino/audio-classification/run_audio_classification.py --model_name_or_path facebook/wav2vec2-base --nncf_compression_config examples/openvino/audio-classification/configs/wav2vec2-base-qat.json --dataset_name superb --dataset_config_name ks --max_train_samples 10 --max_eval_samples 2 --output_dir /tmp/qat-wav2vec2-base-ft-keyword-spotting --overwrite_output_dir --remove_unused_columns False --do_train --learning_rate 3e-5 --max_length_seconds 1 --attention_mask False --warmup_ratio 0.1 --num_train_epochs 1 --gradient_accumulation_steps 1 --dataloader_num_workers 1 --logging_strategy steps --logging_steps 1 --evaluation_strategy epoch --save_strategy epoch --load_best_model_at_end False --seed 42 |
| 64 | + #python examples/openvino/audio-classification/run_audio_classification.py --model_name_or_path facebook/wav2vec2-base --nncf_compression_config examples/openvino/audio-classification/configs/wav2vec2-base-qat.json --dataset_name superb --dataset_config_name ks --max_train_samples 10 --max_eval_samples 2 --output_dir /tmp/qat-wav2vec2-base-ft-keyword-spotting --overwrite_output_dir --remove_unused_columns False --do_train --learning_rate 3e-5 --max_length_seconds 1 --attention_mask False --warmup_ratio 0.1 --num_train_epochs 1 --gradient_accumulation_steps 1 --dataloader_num_workers 1 --logging_strategy steps --logging_steps 1 --evaluation_strategy epoch --save_strategy epoch --load_best_model_at_end False --seed 42 |
54 | 65 | TASK_NAME=sst2 && python examples/openvino/text-classification/run_glue.py --model_name_or_path sshleifer/tiny-distilbert-base-cased-distilled-squad --task_name $TASK_NAME --max_train_samples 10 --max_eval_samples 2 --output_dir /tmp/qat-bert-base-ft-$TASK_NAME --overwrite_output_dir --do_train --do_eval --max_seq_length 128 --learning_rate 1e-5 --optim adamw_torch --num_train_epochs 1 --logging_steps 10 --evaluation_strategy steps --eval_steps 5 --save_strategy epoch --seed 42
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55 | 66 | python examples/openvino/question-answering/run_qa.py --model_name_or_path sshleifer/tiny-distilbert-base-cased-distilled-squad --dataset_name squad --do_train --do_eval --max_train_samples 10 --max_eval_samples 2 --learning_rate 3e-5 --num_train_epochs 1 --max_seq_length 384 --doc_stride 128 --output_dir /tmp/outputs_squad/ --overwrite_output_dir
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56 | 67 | python examples/openvino/image-classification/run_image_classification.py --model_name_or_path nateraw/vit-base-beans --dataset_name beans --max_train_samples 10 --max_eval_samples 2 --remove_unused_columns False --do_train --learning_rate 2e-5 --num_train_epochs 1 --logging_strategy steps --logging_steps 1 --evaluation_strategy epoch --save_strategy epoch --save_total_limit 1 --seed 1337 --output_dir /tmp/beans_outputs/
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