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Bordacarmocca
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Update CI setup (#13291)
* drop mamba * use legacy GPU machines
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.azure/gpu-benchmark.yml

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@@ -26,7 +26,7 @@ jobs:
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- job: benchmarks
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timeoutInMinutes: "90"
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cancelTimeoutInMinutes: "2"
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pool: azure-gpus-spot
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pool: azure-jirka-spot
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container:
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image: "pytorchlightning/pytorch_lightning:base-cuda-py3.9-torch1.11"
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options: "--runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all --shm-size=32g"

.azure/gpu-tests.yml

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@@ -29,7 +29,7 @@ jobs:
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# how much time to give 'run always even if cancelled tasks' before stopping them
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cancelTimeoutInMinutes: "2"
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pool: azure-gpus-spot
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pool: azure-jirka-spot
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container:
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image: $(image)

.github/workflows/ci_dockers.yml

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@@ -97,7 +97,7 @@ jobs:
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UBUNTU_VERSION=${{ matrix.ubuntu_version }}
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file: dockers/base-cuda/Dockerfile
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push: false
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timeout-minutes: 75
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timeout-minutes: 95
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build-Conda:
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runs-on: ubuntu-20.04
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CUDA_VERSION=${{ matrix.cuda_version }}
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file: dockers/base-conda/Dockerfile
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push: false
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timeout-minutes: 75
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timeout-minutes: 95
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build-ipu:
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runs-on: ubuntu-20.04

.github/workflows/events-nightly.yml

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file: dockers/base-cuda/Dockerfile
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push: ${{ env.PUSH_TO_HUB }}
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tags: pytorchlightning/pytorch_lightning:base-cuda-py${{ matrix.python_version }}-torch${{ matrix.pytorch_version }}
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timeout-minutes: 85
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timeout-minutes: 95
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# report failure to Slack
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- name: Slack notification
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file: dockers/base-conda/Dockerfile
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push: ${{ env.PUSH_TO_HUB }}
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tags: pytorchlightning/pytorch_lightning:base-conda-py${{ matrix.python_version }}-torch${{ matrix.pytorch_version }}
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timeout-minutes: 85
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timeout-minutes: 95
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# report failure to Slack
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- name: Slack notification

dockers/base-conda/Dockerfile

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@@ -72,16 +72,15 @@ COPY environment.yml environment.yml
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# conda init
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RUN conda update -n base -c defaults conda && \
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conda install mamba -n base -c conda-forge && \
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mamba create -y --name $CONDA_ENV python=${PYTHON_VERSION} pytorch=${PYTORCH_VERSION} torchvision torchtext cudatoolkit=${CUDA_VERSION} -c nvidia -c pytorch -c pytorch-test -c pytorch-nightly && \
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conda create -y --name $CONDA_ENV python=${PYTHON_VERSION} pytorch=${PYTORCH_VERSION} torchvision torchtext cudatoolkit=${CUDA_VERSION} -c nvidia -c pytorch -c pytorch-test -c pytorch-nightly && \
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conda init bash && \
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# NOTE: this requires that the channel is presented in the yaml before packages \
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printf "import re;\nfname = 'environment.yml';\nreq = open(fname).read();\nfor n in ['python', 'pytorch', 'torchtext', 'torchvision']:\n req = re.sub(rf'- {n}[>=]+', f'# - {n}=', req);\nopen(fname, 'w').write(req)" > prune.py && \
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python prune.py && \
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rm prune.py && \
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cat environment.yml && \
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mamba env update --name $CONDA_ENV --file environment.yml && \
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mamba clean -ya && \
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conda env update --name $CONDA_ENV --file environment.yml && \
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conda clean -ya && \
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rm environment.yml
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ENV \

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