mirror of
https://github.com/huggingface/transformers.git
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Run CI on deepspeed and fairscale (#11172)
* Run CI on deepspeed and fairscale * Test it on this branch :) * Rename * Update the CI image
This commit is contained in:
Lysandre Debut
GitHub
parent
f38cd4373f
commit
1ad7b0398c
77
.github/workflows/self-push.yml
vendored
77
.github/workflows/self-push.yml
vendored
@ -5,6 +5,7 @@ on:
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branches:
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- master
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- ci_*
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- ci-*
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paths:
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- "src/**"
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- "tests/**"
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@ -186,11 +187,85 @@ jobs:
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name: run_all_tests_tf_multi_gpu_test_reports
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path: reports
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run_tests_torch_cuda_extensions_gpu:
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runs-on: [self-hosted, docker-gpu, single-gpu]
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container:
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image: nvcr.io/nvidia/pytorch:21.03-py3
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options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
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steps:
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- name: Launcher docker
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uses: actions/checkout@v2
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- name: NVIDIA-SMI
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run: |
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nvidia-smi
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- name: Install dependencies
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run: |
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pip install --upgrade pip
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pip install .[testing,deepspeed]
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- name: Are GPUs recognized by our DL frameworks
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run: |
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python -c "import torch; print('Cuda available:', torch.cuda.is_available())"
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python -c "import torch; print('Cuda version:', torch.version.cuda)"
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python -c "import torch; print('CuDNN version:', torch.backends.cudnn.version())"
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python -c "import torch; print('Number of GPUs available:', torch.cuda.device_count())"
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- name: Run all tests on GPU
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run: |
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python -m pytest -n 1 --dist=loadfile --make-reports=tests_torch_cuda_extensions_gpu tests/deepspeed tests/extended
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- name: Failure short reports
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if: ${{ always() }}
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run: cat reports/tests_torch_cuda_extensions_gpu_failures_short.txt
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run_tests_torch_cuda_extensions_multi_gpu:
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runs-on: [self-hosted, docker-gpu, multi-gpu]
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container:
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image: nvcr.io/nvidia/pytorch:21.03-py3
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options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
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steps:
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- name: Launcher docker
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uses: actions/checkout@v2
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- name: NVIDIA-SMI
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run: |
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nvidia-smi
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- name: Install dependencies
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run: |
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pip install --upgrade pip
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pip install .[testing,deepspeed,fairscale]
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- name: Are GPUs recognized by our DL frameworks
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run: |
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python -c "import torch; print('Cuda available:', torch.cuda.is_available())"
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python -c "import torch; print('Cuda version:', torch.version.cuda)"
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python -c "import torch; print('CuDNN version:', torch.backends.cudnn.version())"
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python -c "import torch; print('Number of GPUs available:', torch.cuda.device_count())"
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- name: Run all tests on GPU
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run: |
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python -m pytest -n 1 --dist=loadfile --make-reports=tests_torch_cuda_extensions_multi_gpu tests/deepspeed tests/extended
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- name: Failure short reports
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if: ${{ always() }}
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run: cat reports/tests_torch_cuda_extensions_multi_gpu_failures_short.txt
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send_results:
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name: Send results to webhook
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runs-on: ubuntu-latest
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if: always()
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needs: [run_tests_torch_gpu, run_tests_tf_gpu, run_tests_torch_multi_gpu, run_tests_tf_multi_gpu]
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needs: [
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run_tests_torch_gpu,
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run_tests_tf_gpu,
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run_tests_torch_multi_gpu,
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run_tests_tf_multi_gpu,
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run_tests_torch_cuda_extensions_gpu,
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run_tests_torch_cuda_extensions_multi_gpu
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]
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steps:
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- uses: actions/checkout@v2
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75
.github/workflows/self-scheduled.yml
vendored
75
.github/workflows/self-scheduled.yml
vendored
@ -246,11 +246,84 @@ jobs:
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name: run_all_tests_tf_multi_gpu_test_reports
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path: reports
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run_all_tests_torch_cuda_extensions_gpu:
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runs-on: [self-hosted, docker-gpu, single-gpu]
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container:
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image: nvcr.io/nvidia/pytorch:21.03-py3
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options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
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steps:
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- name: Launcher docker
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uses: actions/checkout@v2
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- name: NVIDIA-SMI
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run: |
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nvidia-smi
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- name: Install dependencies
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run: |
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pip install --upgrade pip
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pip install .[testing,deepspeed]
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- name: Are GPUs recognized by our DL frameworks
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run: |
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python -c "import torch; print('Cuda available:', torch.cuda.is_available())"
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python -c "import torch; print('Cuda version:', torch.version.cuda)"
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python -c "import torch; print('CuDNN version:', torch.backends.cudnn.version())"
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python -c "import torch; print('Number of GPUs available:', torch.cuda.device_count())"
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- name: Run all tests on GPU
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run: |
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python -m pytest -n 1 --dist=loadfile --make-reports=tests_torch_cuda_extensions_gpu tests/deepspeed tests/extended
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- name: Failure short reports
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if: ${{ always() }}
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run: cat reports/tests_torch_cuda_extensions_gpu_failures_short.txt
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run_all_tests_torch_cuda_extensions_multi_gpu:
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runs-on: [self-hosted, docker-gpu, multi-gpu]
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container:
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image: nvcr.io/nvidia/pytorch:21.03-py3
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options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
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steps:
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- name: Launcher docker
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uses: actions/checkout@v2
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- name: NVIDIA-SMI
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run: |
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nvidia-smi
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- name: Install dependencies
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run: |
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pip install --upgrade pip
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pip install .[testing,deepspeed,fairscale]
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- name: Are GPUs recognized by our DL frameworks
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run: |
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python -c "import torch; print('Cuda available:', torch.cuda.is_available())"
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python -c "import torch; print('Cuda version:', torch.version.cuda)"
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python -c "import torch; print('CuDNN version:', torch.backends.cudnn.version())"
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python -c "import torch; print('Number of GPUs available:', torch.cuda.device_count())"
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- name: Run all tests on GPU
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run: |
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python -m pytest -n 1 --dist=loadfile --make-reports=tests_torch_cuda_extensions_multi_gpu tests/deepspeed tests/extended
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- name: Failure short reports
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if: ${{ always() }}
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run: cat reports/tests_torch_cuda_extensions_multi_gpu_failures_short.txt
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send_results:
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name: Send results to webhook
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runs-on: ubuntu-latest
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if: always()
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needs: [run_all_tests_torch_gpu, run_all_tests_tf_gpu, run_all_tests_torch_multi_gpu, run_all_tests_tf_multi_gpu]
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needs: [
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run_all_tests_torch_gpu,
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run_all_tests_tf_gpu,
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run_all_tests_torch_multi_gpu,
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run_all_tests_tf_multi_gpu,
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run_all_tests_torch_cuda_extensions_gpu,
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run_all_tests_torch_cuda_extensions_multi_gpu
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]
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steps:
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- uses: actions/checkout@v2
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