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Merge pull request #363 from harshad16/rsync-2024a
[release-2024a] sync release-2024a branch with upstream/2024a
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.github/workflows/code-quality.yaml

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echo "Hadolint done"
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# This simply checks that the manifests and respective kustomization.yaml finishes without an error.
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# Version of the kustomize that operator use in runtime to apply these changes is determined by:
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# https://github.com/red-hat-data-services/rhods-operator/blob/7ccc405135f99c014982d7e297b8949e970dd750/go.mod#L28-L29
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# and then to match appropriate kustomize release https://github.com/kubernetes-sigs/kustomize/releases/tag/kustomize%2Fv5.0.2
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- name: Check kustomize manifest
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id: kustomize-manifests
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run: |
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kubectl version --client=true
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KUSTOMIZE_VERSION=5.0.2
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wget "https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v${KUSTOMIZE_VERSION}/kustomize_v${KUSTOMIZE_VERSION}_linux_amd64.tar.gz"
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tar -xvf kustomize*
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./kustomize version
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echo "----------------------------------------------------------"
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echo "Starting 'kubectl kustomize manifests/base'"
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echo "Starting './kustomize build manifests/base'"
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echo "----------------------------------------------------------"
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kubectl kustomize manifests/base
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./kustomize build manifests/base
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echo "----------------------------------------------------------"
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echo "Starting 'kubectl kustomize manifests/overlays/additional'"
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echo "Starting './kustomize build manifests/overlays/additional'"
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echo "----------------------------------------------------------"
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kubectl kustomize manifests/overlays/additional
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./kustomize build manifests/overlays/additional

README.md

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Welcome to the OpenDataHub Notebooks repository! This repository provides a collection of notebooks tailored for data analysis, machine learning, research and coding within the OpenDataHub ecosystem. Designed to streamline data science workflows, these notebooks offer an integrated environment equipped with the latest tools and libraries. These notebooks were created to be used with OpenDataHub ecosystem with the ODH Notebook Controller as the launcher.
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These workbenches are available at: [quay.io/opendatahub/workbench-images](https://quay.io/opendatahub/workbench-images)
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These workbenches are available at: [quay.io/repository/opendatahub/workbench-images](https://quay.io/repository/opendatahub/workbench-images)
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## Getting Started
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For a deeper understanding of the architecture underlying this repository, please explore our wiki page [Wiki](https://github.com/opendatahub-io/notebooks/wiki/Workbenches)

habana/1.10.0/ubi8-python-3.8/Pipfile.lock

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habana/1.13.0/ubi8-python-3.8/Pipfile.lock

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intel/runtimes/ml/ubi9-python-3.9/Pipfile

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scipy = "~=1.11.2"
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scikit-learn = "~=1.3.1"
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skl2onnx = "~=1.15.0"
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codeflare-sdk = "~=0.16.3"
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codeflare-sdk = "~=0.19.1"
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# DB connectors
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pymongo = "~=4.5.0"
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psycopg = "~=3.1.10"

intel/runtimes/ml/ubi9-python-3.9/Pipfile.lock

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jupyter/datascience/ubi8-python-3.8/Pipfile.lock

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jupyter/datascience/ubi9-python-3.9/Pipfile

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scipy = "~=1.12.0"
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skl2onnx = "~=1.16.0"
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onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf
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codeflare-sdk = "~=0.18.0"
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codeflare-sdk = "~=0.19.1"
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memray = "~=1.10.0" # any version above this would cause issue with rich package
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# DB connectors
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pymongo = "~=4.6.2"
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# and to achieve compatible of pycodestyle with python-lsp-server[all]
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# pinned the below packages
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autopep8 = "~=2.0.4"
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flake8 = "~=7.0.0"
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flake8 = "~=7.1.0"
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# Base packages
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wheel = "~=0.43.0"
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setuptools = "~=69.2.0"

jupyter/datascience/ubi9-python-3.9/Pipfile.lock

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{
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"display_name": "Pytorch with ROCm and Python 3.9 (UBI9)",
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"metadata": {
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"tags": [
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"rocm-pytorch"
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],
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"display_name": "Pytorch with ROCm and Python 3.9 (UBI9)",
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"image_name": "quay.io/opendatahub/workbench-images@sha256:519b7f4ea9a16065ba2213389de4e38ee4afa3084f3b8b770157818928ad0f7a",
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"pull_policy": "IfNotPresent"
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},
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"schema_name": "runtime-image"
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}

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