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.tekton/universal-image-py312-cuda128-torch280-pull-request.yaml

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- name: netrc
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workspace: netrc
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- name: build-container
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timeout: 8h
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params:
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- name: IMAGE
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value: $(params.output-image)

.tekton/universal-image-py312-cuda128-torch280-push.yaml

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- name: revision
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value: '{{revision}}'
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- name: output-image
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value: quay.io/opendatahub/odh-training-cuda128-torch28-py312-rhel9:{{revision}}
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value: quay.io/opendatahub/odh-training-cuda128-torch28-py312-rhel9:latest
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- name: dockerfile
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value: /images/universal/training/py312-cuda128-torch280/Dockerfile
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pipelineSpec:
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- name: netrc
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workspace: netrc
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- name: build-container
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timeout: 8h
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- name: IMAGE
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images/universal/training/py312-cuda128-torch280/Dockerfile

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io.k8s.display-name="Universal CUDA 12.8 Python 3.12 (Workbench + Runtime)" \
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io.k8s.description="Universal image: Jupyter workbench by default; runtime when command provided. Includes RDMA/IB libs, Torch 2.8.0 cu128, FlashAttention 2.8.3."
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## TODO: Add license file
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# COPY LICENSE.md /licenses/cuda-license.md
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COPY ./images/universal/training/py312-cuda128-torch280/LICENSE.md /licenses/cuda-license.md
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# For OS installs we need elevated privileges; base may default to 1001
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USER 0
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(v. September 14, 2021)
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# Universal Training Container Image
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CUDA enabled container image for Training Workbench and Training Runtime in OpenShift AI.
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It includes the following layers:
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* UBI 9
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* Python 3.12
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* CUDA 12.8
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* PyTorch 2.8.0

renovate.json

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{
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"enabled": false
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}

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