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Move V100 workflows from cuda 11.1/11.7 to 12.1 (#6607)
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‎.github/workflows/nv-accelerate-v100.yml‎

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jobs:
2121
unit-tests:
22-
runs-on: [self-hosted, nvidia, cu117, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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steps:
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- uses: actions/checkout@v4
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- name: Install pytorch
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run: |
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pip install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu118
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pip install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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‎.github/workflows/nv-ds-chat.yml‎

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jobs:
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unit-tests:
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runs-on: [self-hosted, nvidia, cu117, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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steps:
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- uses: actions/checkout@v4
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- name: Install pytorch
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run: |
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pip3 install -U --cache-dir $TORCH_CACHE torch --index-url https://download.pytorch.org/whl/cu118
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pip3 install -U --cache-dir $TORCH_CACHE torch --index-url https://download.pytorch.org/whl/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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‎.github/workflows/nv-inference.yml‎

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@@ -22,7 +22,7 @@ concurrency:
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jobs:
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unit-tests:
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runs-on: [self-hosted, nvidia, cu117, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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steps:
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- uses: actions/checkout@v4
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- name: Install pytorch
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run: |
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pip install -U --cache-dir $TORCH_CACHE torch==2.1.2 torchvision==0.16.2 --index-url https://download.pytorch.org/whl/cu118
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pip install -U --cache-dir $TORCH_CACHE torch==2.1.2 torchvision==0.16.2 --index-url https://download.pytorch.org/whl/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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unset TORCH_CUDA_ARCH_LIST # only jit compile for current arch
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cd tests
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#pytest $PYTEST_OPTS -m 'seq_inference' unit/ --torch_ver="2.1" --cuda_ver="11.8"
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pytest $PYTEST_OPTS -m 'inference_ops' unit/ --torch_ver="2.1" --cuda_ver="11.8"
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pytest $PYTEST_OPTS --forked -n 4 -m 'inference' unit/ --torch_ver="2.1" --cuda_ver="11.8"
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#pytest $PYTEST_OPTS -m 'seq_inference' unit/ --torch_ver="2.1" --cuda_ver="12.1"
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pytest $PYTEST_OPTS -m 'inference_ops' unit/ --torch_ver="2.1" --cuda_ver="12.1"
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pytest $PYTEST_OPTS --forked -n 4 -m 'inference' unit/ --torch_ver="2.1" --cuda_ver="12.1"
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# run ds_report again to check updated op list
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ds_report

‎.github/workflows/nv-lightning-v100.yml‎

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@@ -19,7 +19,7 @@ concurrency:
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jobs:
2121
unit-tests:
22-
runs-on: [self-hosted, nvidia, cu111, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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env: {ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION: true} # Allow using Node16 actions
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- name: Install pytorch
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run: |
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pip install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu118
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pip install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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‎.github/workflows/nv-mii.yml‎

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jobs:
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unit-tests:
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runs-on: [self-hosted, nvidia, cu117, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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steps:
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- uses: actions/checkout@v4
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- name: Install pytorch
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run: |
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pip3 install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu118
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pip3 install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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‎.github/workflows/nv-nightly.yml‎

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jobs:
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unit-tests:
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runs-on: [self-hosted, nvidia, cu117, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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steps:
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- uses: actions/checkout@v4
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- name: Install pytorch
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run: |
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pip install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu118
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pip install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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unset TORCH_CUDA_ARCH_LIST # only jit compile for current arch
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cd tests
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pytest $PYTEST_OPTS --forked -m 'nightly' unit/ --torch_ver="2.4" --cuda_ver="11.8"
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pytest $PYTEST_OPTS --forked -m 'nightly' unit/ --torch_ver="2.4" --cuda_ver="12.1"
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- name: Open GitHub issue if nightly CI fails
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if: ${{ failure() && (github.event_name == 'schedule') }}

‎.github/workflows/nv-torch-latest-v100.yml‎

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@@ -19,7 +19,7 @@ concurrency:
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jobs:
2121
unit-tests:
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runs-on: [self-hosted, nvidia, cu117, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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steps:
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- uses: actions/checkout@v4
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- name: Install pytorch
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run: |
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pip install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu118
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pip install -U --cache-dir $TORCH_CACHE torch torchvision --index-url https://download.pytorch.org/whl/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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unset TORCH_CUDA_ARCH_LIST # only jit compile for current arch
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cd tests
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pytest $PYTEST_OPTS --forked -n 4 unit/ --torch_ver="2.4" --cuda_ver="11.8"
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pytest $PYTEST_OPTS --forked -m 'sequential' unit/ --torch_ver="2.4" --cuda_ver="11.8"
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pytest $PYTEST_OPTS --forked -n 4 unit/ --torch_ver="2.4" --cuda_ver="12.1"
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pytest $PYTEST_OPTS --forked -m 'sequential' unit/ --torch_ver="2.4" --cuda_ver="12.1"

‎.github/workflows/nv-torch-nightly-v100.yml‎

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jobs:
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unit-tests:
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runs-on: [self-hosted, nvidia, cu117, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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- uses: actions/checkout@v4
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- name: Install pytorch
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pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu118
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pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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‎.github/workflows/nv-transformers-v100.yml‎

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jobs:
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unit-tests:
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runs-on: [self-hosted, nvidia, cu117, v100]
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runs-on: [self-hosted, nvidia, cu121, v100]
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- uses: actions/checkout@v4
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- name: Install pytorch
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# use the same pytorch version as transformers CI
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pip install -U --cache-dir $TORCH_CACHE torch==2.0.1+cu118 --index-url https://download.pytorch.org/whl/cu118
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pip install -U --cache-dir $TORCH_CACHE torch==2.0.1+cu121 --index-url https://download.pytorch.org/whl/cu121
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python -c "import torch; print('torch:', torch.__version__, torch)"
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python -c "import torch; print('CUDA available:', torch.cuda.is_available())"
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