From 0d38a89c59cf1638b5fd8b4019e714e4950c397e Mon Sep 17 00:00:00 2001 From: Guilherme Caponetto <638737+caponetto@users.noreply.github.com> Date: Wed, 24 Jul 2024 11:02:12 -0300 Subject: [PATCH 1/6] Run Trivy scan FS for rocm+pytorch image due to resource constraints --- .../workflows/build-notebooks-TEMPLATE.yaml | 56 ++++++++++++++----- 1 file changed, 41 insertions(+), 15 deletions(-) diff --git a/.github/workflows/build-notebooks-TEMPLATE.yaml b/.github/workflows/build-notebooks-TEMPLATE.yaml index 02ea17e05..2e99d4880 100644 --- a/.github/workflows/build-notebooks-TEMPLATE.yaml +++ b/.github/workflows/build-notebooks-TEMPLATE.yaml @@ -22,6 +22,8 @@ jobs: env: # GitHub image registry used for storing $(CONTAINER_ENGINE)'s cache CACHE: "ghcr.io/${{ github.repository }}/workbench-images/build-cache" + # Targets (and their folder) that should be scanned using FS instead of IMAGE scan due to resource constraints + TRIVY_SCAN_FS_JSON: '{"rocm-jupyter-pytorch-ubi9-python-3.9": "jupyter/rocm/pytorch/ubi9-python-3.9"}' steps: @@ -138,27 +140,42 @@ jobs: - name: "Show podman images information" run: podman images - - name: "pull_request|schedule: resolve image name if Trivy scan should run" - id: resolve-image + - name: "pull_request|schedule: resolve target if Trivy scan should run" + id: resolve-target if: ${{ fromJson(inputs.github).event_name == 'pull_request' || fromJson(inputs.github).event_name == 'schedule' }} env: EVENT_NAME: ${{ fromJson(inputs.github).event_name }} HAS_TRIVY_LABEL: ${{ contains(fromJson(inputs.github).event.pull_request.labels.*.name, 'trivy-scan') }} + FS_SCAN_FOLDER: ${{ fromJson(env.TRIVY_SCAN_FS_JSON)[inputs.target] }} run: | if [[ "$EVENT_NAME" == "pull_request" && "$HAS_TRIVY_LABEL" == "true" ]]; then - IMAGE_NAME="localhost:5000/workbench-images:${{ inputs.target }}-${{ github.sha }}" - echo "image=$IMAGE_NAME" >> $GITHUB_OUTPUT + if [[ -n "$FS_SCAN_FOLDER" ]]; then + TARGET="$FS_SCAN_FOLDER" + TYPE="fs" + else + TARGET="localhost:5000/workbench-images:${{ inputs.target }}-${{ github.sha }}" + TYPE="image" + fi elif [[ "$EVENT_NAME" == "schedule" ]]; then - IMAGE_NAME="ghcr.io/${{ github.repository }}/workbench-images:${{ inputs.target }}-${{ github.ref_name }}_${{ github.sha }}" - echo "image=$IMAGE_NAME" >> $GITHUB_OUTPUT + if [[ -n "$FS_SCAN_FOLDER" ]]; then + TARGET="$FS_SCAN_FOLDER" + TYPE="fs" + else + TARGET="ghcr.io/${{ github.repository }}/workbench-images:${{ inputs.target }}-${{ github.ref_name }}_${{ github.sha }}" + TYPE="image" + fi fi - if [[ -z "$IMAGE_NAME" ]]; then + if [[ -n "$TARGET" ]]; then + echo "target=$TARGET" >> $GITHUB_OUTPUT + echo "type=$TYPE" >> $GITHUB_OUTPUT + echo "Trivy scan will run on $TARGET ($TYPE)" + else echo "Trivy scan won't run" fi - name: Run Trivy vulnerability scanner - if: ${{ steps.resolve-image.outputs.image }} + if: ${{ steps.resolve-target.outputs.target }} run: | TRIVY_VERSION=0.53.0 REPORT_FOLDER=${{ github.workspace }}/report @@ -168,22 +185,31 @@ jobs: mkdir -p $REPORT_FOLDER cp ci/$REPORT_TEMPLATE $REPORT_FOLDER - IMAGE_NAME=${{ steps.resolve-image.outputs.image }} - echo "Scanning $IMAGE_NAME" + SCAN_TARGET=${{ steps.resolve-target.outputs.target }} + SCAN_TYPE=${{ steps.resolve-target.outputs.type }} + echo "Scanning $SCAN_TARGET ($SCAN_TYPE)" + + if [[ "$SCAN_TYPE" == "image" ]]; then + SCAN_ARGS="--image-src podman --podman-host /var/run/podman/podman.sock" + PODMAN_ARGS="-v ${PODMAN_SOCK}:/var/run/podman/podman.sock" + elif [[ "$SCAN_TYPE" == "fs" ]]; then + WORKSPACE_FOLDER="/workspace" + SCAN_TARGET="$WORKSPACE_FOLDER/$SCAN_TARGET" + PODMAN_ARGS="-v ${{ github.workspace }}:$WORKSPACE_FOLDER" + fi # have trivy access podman socket, # https://github.com/aquasecurity/trivy/issues/580#issuecomment-666423279 podman run --rm \ - -v ${PODMAN_SOCK}:/var/run/podman/podman.sock \ + $PODMAN_ARGS \ -v ${REPORT_FOLDER}:/report \ docker.io/aquasec/trivy:$TRIVY_VERSION \ - image \ - --image-src podman \ - --podman-host /var/run/podman/podman.sock \ + $SCAN_TYPE \ + $SCAN_ARGS \ --scanners vuln --ignore-unfixed \ --exit-code 0 --timeout 30m \ --format template --template "@/report/$REPORT_TEMPLATE" -o /report/$REPORT_FILE \ - $IMAGE_NAME + $SCAN_TARGET cat $REPORT_FOLDER/$REPORT_FILE >> $GITHUB_STEP_SUMMARY From 061c6fb50a71358fa4565bdb208449513457f413 Mon Sep 17 00:00:00 2001 From: Harshad Reddy Nalla Date: Mon, 22 Jul 2024 11:10:16 -0400 Subject: [PATCH 2/6] Pinned down jupyter-server-proxy for cve fixes - Pinned kfp-tekton due the requirements changing pyyaml. - Pinned rest of the packages for dependency resolutions. Signed-off-by: Harshad Reddy Nalla --- habana/1.10.0/ubi8-python-3.8/Pipfile | 12 +- habana/1.10.0/ubi8-python-3.8/Pipfile.lock | 3196 ++++++++++---------- 2 files changed, 1682 insertions(+), 1526 deletions(-) diff --git a/habana/1.10.0/ubi8-python-3.8/Pipfile b/habana/1.10.0/ubi8-python-3.8/Pipfile index e2df2e55c..2c333ba2d 100644 --- a/habana/1.10.0/ubi8-python-3.8/Pipfile +++ b/habana/1.10.0/ubi8-python-3.8/Pipfile @@ -33,7 +33,7 @@ pybind11 = "==2.6.2" elyra-pipeline-editor-extension = "~=3.15.0" elyra-python-editor-extension = "~=3.15.0" elyra-code-snippet-extension = "~=3.15.0" -kfp-tekton = "<1.6.0" +kfp-tekton = "==1.5.7" # pinned to avoid upgrade of pyyaml which is required. boto3 = "~=1.26.165" kafka-python = "~=2.0.2" matplotlib = "~=3.6.3" @@ -45,12 +45,12 @@ scipy = "~=1.10.1" jupyter-bokeh = "~=3.0.5" jupyterlab-lsp = "~=3.10.2" jupyterlab-widgets = "~=3.0.5" -jupyter-resource-usage = "~=0.6.0" +jupyter-resource-usage = "~=0.7.2" # Parent image requirements to maintain cohesion jupyterlab = "~=3.5.3" jupyter-server = "~=2.1.0" -jupyter-server-proxy = "~=3.2.2" +jupyter-server-proxy = "~=3.2.4" jupyter-server-terminals = "~=0.4.4" jupyterlab-git = "~=0.41.0" nbdime = "~=3.1.1" @@ -58,5 +58,11 @@ nbgitpuller = "~=1.1.1" # --- wheel = "~=0.38.4" +# conflict between python-lsp-server and following packages +# due to pycodestyle dependency, pinning this, till we get +# a fix from python-lsp-server +autopep8 = "~=2.0.4" +flake8 = "~=7.0.0" + [requires] python_version = "3.8" diff --git a/habana/1.10.0/ubi8-python-3.8/Pipfile.lock b/habana/1.10.0/ubi8-python-3.8/Pipfile.lock index 1d62fecb1..45da391d7 100644 --- a/habana/1.10.0/ubi8-python-3.8/Pipfile.lock +++ b/habana/1.10.0/ubi8-python-3.8/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "f9d1627b8c94140310a4fa7d929c19b9d2ba5930b1e81263cb42c619bf9fa31b" + "sha256": "3886f50647f504b4023b69c3c8fc50ef2b3792c244dc647c0d51308e381efc36" }, "pipfile-spec": 6, "requires": { @@ -26,96 +26,85 @@ }, 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.../ubi9-python-3.9/runtime-images/datascience-ubi9-py39.json | 2 +- .../ubi9-python-3.9/runtime-images/pytorch-ubi9-py39.json | 2 +- .../ubi9-python-3.9/runtime-images/tensorflow-ubi9-py39.json | 2 +- .../datascience/ubi9-python-3.9/runtime-images/ubi9-py39.json | 2 +- 12 files changed, 12 insertions(+), 12 deletions(-) diff --git a/jupyter/datascience/anaconda-python-3.8/runtime-images/datascience-ubi8-py38.json b/jupyter/datascience/anaconda-python-3.8/runtime-images/datascience-ubi8-py38.json index c6778b6ff..2034a88bc 100644 --- a/jupyter/datascience/anaconda-python-3.8/runtime-images/datascience-ubi8-py38.json +++ b/jupyter/datascience/anaconda-python-3.8/runtime-images/datascience-ubi8-py38.json @@ -5,7 +5,7 @@ "datascience" ], "display_name": "Datascience with Python 3.8 (UBI8)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:acc9b8fed84c9778b177581455c0a5d228d1438daa629e1a476cef4440f2a91a", + "image_name": "quay.io/opendatahub/workbench-images@sha256:c33bd3365f40fcca2a0d570f3e28269c6387436f792080c5122b80c218e0cda3", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/anaconda-python-3.8/runtime-images/pytorch-ubi8-py38.json b/jupyter/datascience/anaconda-python-3.8/runtime-images/pytorch-ubi8-py38.json index cac6534be..258c7e636 100644 --- a/jupyter/datascience/anaconda-python-3.8/runtime-images/pytorch-ubi8-py38.json +++ b/jupyter/datascience/anaconda-python-3.8/runtime-images/pytorch-ubi8-py38.json @@ -5,7 +5,7 @@ "pytorch" ], "display_name": "Pytorch with CUDA and Python 3.8 (UBI8)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:a46edb1ded8d6270dbff55d3cbb824ebebbe05a095cf1d37e7972c87a4dbcd4f", + "image_name": "quay.io/opendatahub/workbench-images@sha256:0c9f5480fd6f7fceede66c6ab91277cfdb05b6032f317c0ffc411d2ef650d1ee", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/anaconda-python-3.8/runtime-images/tensorflow-ubi8-py38.json b/jupyter/datascience/anaconda-python-3.8/runtime-images/tensorflow-ubi8-py38.json index bf3d5be54..72fd1ff95 100644 --- a/jupyter/datascience/anaconda-python-3.8/runtime-images/tensorflow-ubi8-py38.json +++ b/jupyter/datascience/anaconda-python-3.8/runtime-images/tensorflow-ubi8-py38.json @@ -5,7 +5,7 @@ "tensorflow" ], "display_name": "TensorFlow with CUDA and Python 3.8 (UBI8)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:0958fffbadb5d413dd01f2f0f13bdb2b4e7f2f2c10de2d87c5449db21fdc520b", + "image_name": "quay.io/opendatahub/workbench-images@sha256:c3fb741047ebf1722f0804cd3d1146ed0be0ca5826920e25f83cd4655e074ff3", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/anaconda-python-3.8/runtime-images/ubi8-py38.json b/jupyter/datascience/anaconda-python-3.8/runtime-images/ubi8-py38.json index 93214b0ed..6a28ec775 100644 --- a/jupyter/datascience/anaconda-python-3.8/runtime-images/ubi8-py38.json +++ b/jupyter/datascience/anaconda-python-3.8/runtime-images/ubi8-py38.json @@ -5,7 +5,7 @@ "minimal" ], "display_name": "Python 3.8 (UBI8)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:98a035d355d67120fc913cf753866d7bad2227af21ccc3894148b4b679d40c3d", + "image_name": "quay.io/opendatahub/workbench-images@sha256:7a27e9aeaea8b22231eb965609b5ccc3e130a10bafe9024b75c313965b4c8502", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/ubi8-python-3.8/runtime-images/datascience-ubi8-py38.json b/jupyter/datascience/ubi8-python-3.8/runtime-images/datascience-ubi8-py38.json index c6778b6ff..2034a88bc 100644 --- a/jupyter/datascience/ubi8-python-3.8/runtime-images/datascience-ubi8-py38.json +++ b/jupyter/datascience/ubi8-python-3.8/runtime-images/datascience-ubi8-py38.json @@ -5,7 +5,7 @@ "datascience" ], "display_name": "Datascience with Python 3.8 (UBI8)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:acc9b8fed84c9778b177581455c0a5d228d1438daa629e1a476cef4440f2a91a", + "image_name": "quay.io/opendatahub/workbench-images@sha256:c33bd3365f40fcca2a0d570f3e28269c6387436f792080c5122b80c218e0cda3", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/ubi8-python-3.8/runtime-images/pytorch-ubi8-py38.json b/jupyter/datascience/ubi8-python-3.8/runtime-images/pytorch-ubi8-py38.json index cac6534be..258c7e636 100644 --- a/jupyter/datascience/ubi8-python-3.8/runtime-images/pytorch-ubi8-py38.json +++ b/jupyter/datascience/ubi8-python-3.8/runtime-images/pytorch-ubi8-py38.json @@ -5,7 +5,7 @@ "pytorch" ], "display_name": "Pytorch with CUDA and Python 3.8 (UBI8)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:a46edb1ded8d6270dbff55d3cbb824ebebbe05a095cf1d37e7972c87a4dbcd4f", + "image_name": "quay.io/opendatahub/workbench-images@sha256:0c9f5480fd6f7fceede66c6ab91277cfdb05b6032f317c0ffc411d2ef650d1ee", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/ubi8-python-3.8/runtime-images/tensorflow-ubi8-py38.json b/jupyter/datascience/ubi8-python-3.8/runtime-images/tensorflow-ubi8-py38.json index bf3d5be54..72fd1ff95 100644 --- a/jupyter/datascience/ubi8-python-3.8/runtime-images/tensorflow-ubi8-py38.json +++ b/jupyter/datascience/ubi8-python-3.8/runtime-images/tensorflow-ubi8-py38.json @@ -5,7 +5,7 @@ "tensorflow" ], "display_name": "TensorFlow with CUDA and Python 3.8 (UBI8)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:0958fffbadb5d413dd01f2f0f13bdb2b4e7f2f2c10de2d87c5449db21fdc520b", + "image_name": "quay.io/opendatahub/workbench-images@sha256:c3fb741047ebf1722f0804cd3d1146ed0be0ca5826920e25f83cd4655e074ff3", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/ubi8-python-3.8/runtime-images/ubi8-py38.json b/jupyter/datascience/ubi8-python-3.8/runtime-images/ubi8-py38.json index 93214b0ed..6a28ec775 100644 --- a/jupyter/datascience/ubi8-python-3.8/runtime-images/ubi8-py38.json +++ b/jupyter/datascience/ubi8-python-3.8/runtime-images/ubi8-py38.json @@ -5,7 +5,7 @@ "minimal" ], "display_name": "Python 3.8 (UBI8)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:98a035d355d67120fc913cf753866d7bad2227af21ccc3894148b4b679d40c3d", + "image_name": "quay.io/opendatahub/workbench-images@sha256:7a27e9aeaea8b22231eb965609b5ccc3e130a10bafe9024b75c313965b4c8502", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/ubi9-python-3.9/runtime-images/datascience-ubi9-py39.json b/jupyter/datascience/ubi9-python-3.9/runtime-images/datascience-ubi9-py39.json index 7d7fa1442..a49d7cc2a 100644 --- a/jupyter/datascience/ubi9-python-3.9/runtime-images/datascience-ubi9-py39.json +++ b/jupyter/datascience/ubi9-python-3.9/runtime-images/datascience-ubi9-py39.json @@ -5,7 +5,7 @@ "datascience" ], "display_name": "Datascience with Python 3.9 (UBI9)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:90ef43828264de9dd4247a420033e62b4c0a5b0f43fdc5717eb0faf4d75dc1b9", + "image_name": "quay.io/opendatahub/workbench-images@sha256:dc1408fde855c0cf50c54e04c865785269aaeec13d94c4e97e9aa7dc4ed3aec1", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/ubi9-python-3.9/runtime-images/pytorch-ubi9-py39.json b/jupyter/datascience/ubi9-python-3.9/runtime-images/pytorch-ubi9-py39.json index b1780c900..9a7a693f1 100644 --- a/jupyter/datascience/ubi9-python-3.9/runtime-images/pytorch-ubi9-py39.json +++ b/jupyter/datascience/ubi9-python-3.9/runtime-images/pytorch-ubi9-py39.json @@ -5,7 +5,7 @@ "pytorch" ], "display_name": "Pytorch with CUDA and Python 3.9 (UBI9)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:bafcdaab39ee7bda63781e67ceef355f290249d58f2deaced4e9159ece39e616", + "image_name": "quay.io/opendatahub/workbench-images@sha256:df9de2ece3c99d6b709c239f16b973a8747e410408dbda96643e87d8414f2347", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/ubi9-python-3.9/runtime-images/tensorflow-ubi9-py39.json b/jupyter/datascience/ubi9-python-3.9/runtime-images/tensorflow-ubi9-py39.json index 83c19daab..9f01b394b 100644 --- a/jupyter/datascience/ubi9-python-3.9/runtime-images/tensorflow-ubi9-py39.json +++ b/jupyter/datascience/ubi9-python-3.9/runtime-images/tensorflow-ubi9-py39.json @@ -5,7 +5,7 @@ "tensorflow" ], "display_name": "TensorFlow with CUDA and Python 3.9 (UBI9)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:367f3b3e3186d9bb21af68cfcc1c574e60979ac5a8a15105e2cb4ea509346c3b", + "image_name": "quay.io/opendatahub/workbench-images@sha256:97f103f55b660457ec8da8d4f98a21aa123eea07813df2e0f93bdb2893f9aaac", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" diff --git a/jupyter/datascience/ubi9-python-3.9/runtime-images/ubi9-py39.json b/jupyter/datascience/ubi9-python-3.9/runtime-images/ubi9-py39.json index 63b26aee9..bb42627df 100644 --- a/jupyter/datascience/ubi9-python-3.9/runtime-images/ubi9-py39.json +++ b/jupyter/datascience/ubi9-python-3.9/runtime-images/ubi9-py39.json @@ -5,7 +5,7 @@ "minimal" ], "display_name": "Python 3.9 (UBI9)", - "image_name": "quay.io/opendatahub/workbench-images@sha256:1d72f9e192f247c22c2b6759df47005511496eb84077f1429625cb8d07ba037a", + "image_name": "quay.io/opendatahub/workbench-images@sha256:2f2618585119753187dc666f67b05c9892eca14b050cd1df34e96153879d6e53", "pull_policy": "IfNotPresent" }, "schema_name": "runtime-image" From eedde7e6f6aa11b9517c83a88131ce66accac285 Mon Sep 17 00:00:00 2001 From: Harshad Reddy Nalla Date: Tue, 30 Jul 2024 14:03:36 -0400 Subject: [PATCH 4/6] Upgrade codeflare-sdk 0.18.0 for py3.9 content Signed-off-by: Harshad Reddy Nalla Co-authored-by: Jan Stourac --- jupyter/datascience/ubi9-python-3.9/Pipfile | 2 +- .../datascience/ubi9-python-3.9/Pipfile.lock | 1089 +++++++++-------- jupyter/pytorch/ubi9-python-3.9/Pipfile | 2 +- jupyter/pytorch/ubi9-python-3.9/Pipfile.lock | 867 ++++++------- jupyter/rocm/pytorch/ubi9-python-3.9/Pipfile | 3 +- .../rocm/pytorch/ubi9-python-3.9/Pipfile.lock | 898 +++++++------- .../rocm/tensorflow/ubi9-python-3.9/Pipfile | 2 +- .../tensorflow/ubi9-python-3.9/Pipfile.lock | 610 +++++---- jupyter/tensorflow/ubi9-python-3.9/Pipfile | 2 +- .../tensorflow/ubi9-python-3.9/Pipfile.lock | 877 ++++++------- jupyter/trustyai/ubi9-python-3.9/Pipfile | 2 +- jupyter/trustyai/ubi9-python-3.9/Pipfile.lock | 821 +++++++------ runtimes/datascience/ubi9-python-3.9/Pipfile | 2 +- .../datascience/ubi9-python-3.9/Pipfile.lock | 555 ++++----- runtimes/pytorch/ubi9-python-3.9/Pipfile | 2 +- runtimes/pytorch/ubi9-python-3.9/Pipfile.lock | 561 ++++----- runtimes/tensorflow/ubi9-python-3.9/Pipfile | 2 +- .../tensorflow/ubi9-python-3.9/Pipfile.lock | 560 ++++----- 18 files changed, 3391 insertions(+), 3466 deletions(-) diff --git a/jupyter/datascience/ubi9-python-3.9/Pipfile b/jupyter/datascience/ubi9-python-3.9/Pipfile index 573878ace..8c099c408 100644 --- a/jupyter/datascience/ubi9-python-3.9/Pipfile +++ b/jupyter/datascience/ubi9-python-3.9/Pipfile @@ -17,7 +17,7 @@ scikit-learn = "~=1.4.0" scipy = "~=1.12.0" skl2onnx = "~=1.16.0" onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf -codeflare-sdk = "~=0.16.4" +codeflare-sdk = "~=0.18.0" memray = "~=1.10.0" # any version above this would cause issue with rich package # DB connectors pymongo = "~=4.6.2" diff --git a/jupyter/datascience/ubi9-python-3.9/Pipfile.lock b/jupyter/datascience/ubi9-python-3.9/Pipfile.lock index b655259b5..21fb6e80f 100644 --- a/jupyter/datascience/ubi9-python-3.9/Pipfile.lock +++ b/jupyter/datascience/ubi9-python-3.9/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "182e5c882f08cbc5a2803d382fa99b0d2e6d7ae4f4c73e49322ab7c88c401bd8" + "sha256": "18cdcbdced89e25b92da4636e11c458edecb28208350a8fe06e0b9d6fc667169" }, "pipfile-spec": 6, "requires": { @@ -21,7 +21,7 @@ "sha256:1142fa8e80dbae46bb6339573ad4c8c0841358f79c6eb50a493dceca14621bad", "sha256:9107f1ca0b2a5553987a94a3c9959fe5b491fdf731389aa5b7b1bd0733e32de6" ], - "markers": "python_version >= '3.7' and python_version < '4.0'", + "markers": "python_version < '4' and python_full_version >= '3.7.0'", "version": "==22.1.0" }, "aiohttp": { @@ -118,7 +118,7 @@ "sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc", "sha256:f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17" ], - "markers": "python_version >= '3.7'", + "markers": "python_full_version >= '3.7.0'", "version": "==1.3.1" }, 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"python_version >= '3.7'", + "markers": "python_full_version >= '3.7.0'", "version": "==5.0.1" }, "sniffio": { @@ -3425,7 +3434,7 @@ "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2", "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc" ], - "markers": "python_version >= '3.7'", + "markers": "python_full_version >= '3.7.0'", "version": "==1.3.1" }, "snowballstemmer": { @@ -3440,7 +3449,7 @@ "sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690", "sha256:eaa337ff55a1579b6549dc679565eac1e3d000563bcb1c8ab0d0fefbc0c2cdc7" ], - "markers": "python_full_version >= '3.8.0'", + "markers": "python_version >= '3.8'", "version": "==2.5" }, "stack-data": { @@ -3455,23 +3464,23 @@ "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c", "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f" ], - "markers": "python_version >= '3.7'", + "markers": "python_full_version >= '3.7.0'", "version": "==0.9.0" }, "tenacity": { "hashes": [ - "sha256:9e6f7cf7da729125c7437222f8a522279751cdfbe6b67bfe64f75d3a348661b2", - "sha256:cd80a53a79336edba8489e767f729e4f391c896956b57140b5d7511a64bbd3ef" + "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b", + "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539" ], - "markers": "python_full_version >= '3.8.0'", - "version": "==8.4.2" + "markers": "python_version >= '3.8'", + "version": "==9.0.0" }, "termcolor": { "hashes": [ "sha256:3afb05607b89aed0ffe25202399ee0867ad4d3cb4180d98aaf8eefa6a5f7d475", "sha256:b5b08f68937f138fe92f6c089b99f1e2da0ae56c52b78bf7075fd95420fd9a5a" ], - "markers": "python_version >= '3.7'", + "markers": "python_full_version >= '3.7.0'", "version": "==2.3.0" }, "terminado": { @@ -3479,7 +3488,7 @@ "sha256:a4468e1b37bb318f8a86514f65814e1afc977cf29b3992a4500d9dd305dcceb0", "sha256:de09f2c4b85de4765f7714688fff57d3e75bad1f909b589fde880460c753fd2e" ], - "markers": "python_full_version >= '3.8.0'", + "markers": "python_version >= '3.8'", "version": "==0.18.1" }, "threadpoolctl": { @@ -3487,7 +3496,7 @@ "sha256:082433502dd922bf738de0d8bcc4fdcbf0979ff44c42bd40f5af8a282f6fa107", "sha256:56c1e26c150397e58c4926da8eeee87533b1e32bef131bd4bf6a2f45f3185467" ], - "markers": "python_full_version >= '3.8.0'", + "markers": "python_version >= '3.8'", "version": "==3.5.0" }, "tinycss2": { @@ -3495,7 +3504,7 @@ "sha256:152f9acabd296a8375fbca5b84c961ff95971fcfc32e79550c8df8e29118c54d", "sha256:54a8dbdffb334d536851be0226030e9505965bb2f30f21a4a82c55fb2a80fae7" ], - "markers": "python_full_version >= '3.8.0'", + "markers": "python_version >= '3.8'", "version": "==1.3.0" }, "tomli": { @@ -3508,11 +3517,11 @@ }, "tomlkit": { "hashes": [ - "sha256:af914f5a9c59ed9d0762c7b64d3b5d5df007448eb9cd2edc8a46b1eafead172f", - "sha256:eef34fba39834d4d6b73c9ba7f3e4d1c417a4e56f89a7e96e090dd0d24b8fb3c" + "sha256:08ad192699734149f5b97b45f1f18dad7eb1b6d16bc72ad0c2335772650d7b72", + "sha256:7075d3042d03b80f603482d69bf0c8f345c2b30e41699fd8883227f89972b264" ], - "markers": "python_version >= '3.7'", - "version": "==0.12.5" + "markers": "python_version >= '3.8'", + "version": "==0.13.0" }, "tornado": { "hashes": [ @@ -3528,7 +3537,7 @@ "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d", "sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4" ], - "markers": "python_full_version >= '3.8.0'", + "markers": "python_version >= '3.8'", "version": "==6.4.1" }, "tqdm": { @@ -3536,7 +3545,7 @@ "sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644", "sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb" ], - "markers": "python_version >= '3.7'", + "markers": "python_full_version >= '3.7.0'", "version": "==4.66.4" }, "traitlets": { @@ -3544,7 +3553,7 @@ "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7", "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f" ], - "markers": "python_full_version >= '3.8.0'", + "markers": "python_version >= '3.8'", "version": "==5.14.3" }, "types-python-dateutil": { @@ -3552,7 +3561,7 @@ "sha256:5d2f2e240b86905e40944dd787db6da9263f0deabef1076ddaed797351ec0202", "sha256:6b8cb66d960771ce5ff974e9dd45e38facb81718cc1e208b10b1baccbfdbee3b" ], - "markers": "python_full_version >= '3.8.0'", + "markers": "python_version >= '3.8'", "version": "==2.9.0.20240316" }, "typing-extensions": { @@ -3652,7 +3661,7 @@ "sha256:f8ccb77b3e40b151e20519c6ae6d89bfe3f4c14e8e210d910287f778368bb3d1", "sha256:fbd8fd427f57a03cff3ad6574b5e299131585d9727c8c366da4624a9069ed746" ], - "markers": "python_full_version >= '3.8.0'", + "markers": "python_version >= '3.8'", "version": "==5.10.0" }, "uri-template": { @@ -3712,7 +3721,7 @@ "sha256:f27279d060e2ab24c0aa98363ff906d2386aa6c4dc2f1a374655d4e02a6c5e5e", "sha256:f8affdf3c0f0466e69f5b3917cdd042f89c8c63aebdb9f7c078996f607cdb0f5" ], - "markers": "python_full_version >= '3.8.0'", + "markers": 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"ypy-websocket": { @@ -4046,7 +4055,7 @@ "sha256:43a001473f5c8abcf182f603049cf305cbc855ad8deaa9dfa0f3b5a7cea9d0ff", "sha256:b1ba0dfcc9762f0ca168d2378062d3ca1299d39076b0f145d961359121042be5" ], - "markers": "python_version >= '3.7'", + "markers": "python_full_version >= '3.7.0'", "version": "==0.8.4" }, "zipp": { diff --git a/jupyter/pytorch/ubi9-python-3.9/Pipfile b/jupyter/pytorch/ubi9-python-3.9/Pipfile index 8d04b6c45..3a90489b6 100644 --- a/jupyter/pytorch/ubi9-python-3.9/Pipfile +++ b/jupyter/pytorch/ubi9-python-3.9/Pipfile @@ -26,7 +26,7 @@ scikit-learn = "~=1.4.0" scipy = "~=1.12.0" skl2onnx = "~=1.16.0" onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf -codeflare-sdk = "~=0.16.4" +codeflare-sdk = "~=0.18.0" memray = "~=1.10.0" # any version above this would cause issue with rich package # DB connectors pymongo = "~=4.6.2" diff --git a/jupyter/pytorch/ubi9-python-3.9/Pipfile.lock b/jupyter/pytorch/ubi9-python-3.9/Pipfile.lock index 3ee7bd382..bdf59a6ca 100644 --- a/jupyter/pytorch/ubi9-python-3.9/Pipfile.lock +++ b/jupyter/pytorch/ubi9-python-3.9/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "35f918165bcc21d267c32ce5b7bbaa7c92df8fa1d371244319f1ae3e9c24a521" + "sha256": "cd3cd72c71f348f97998c2b07a135683988b051d991d95ea71b0a4fb3389b216" }, "pipfile-spec": 6, "requires": { @@ -34,7 +34,7 @@ "sha256:1142fa8e80dbae46bb6339573ad4c8c0841358f79c6eb50a493dceca14621bad", "sha256:9107f1ca0b2a5553987a94a3c9959fe5b491fdf731389aa5b7b1bd0733e32de6" ], - "markers": "python_version >= '3.7' and python_full_version < '4.0.0'", + "markers": "python_version >= '3.7' and python_version < '4.0'", "version": "==22.1.0" }, "aiohttp": { @@ -162,7 +162,7 @@ "sha256:0fca07b290282b9449590cbdb39b3461c45f2b6037523949f028ff2cba82c85e", "sha256:c2aec138a24f8462d6199c65666590dab14acb18af6c62950c82bc8d40862558" ], - "markers": "python_version >= '3.6' and python_full_version < '4.0.0'", + "markers": "python_version >= '3.6' and python_version < '4.0'", "version": "==1.1.6" }, "argon2-cffi": { @@ -210,11 +210,11 @@ }, "astroid": { "hashes": [ - "sha256:8ead48e31b92b2e217b6c9733a21afafe479d52d6e164dd25fb1a770c7c3cf94", - "sha256:e8a0083b4bb28fcffb6207a3bfc9e5d0a68be951dd7e336d5dcf639c682388c0" + "sha256:0e14202810b30da1b735827f78f5157be2bbd4a7a59b7707ca0bfc2fb4c0063a", + "sha256:413658a61eeca6202a59231abb473f932038fbcbf1666587f66d482083413a25" ], "markers": "python_version >= '3.8'", - "version": "==3.2.2" + "version": "==3.2.4" }, "asttokens": { "hashes": [ @@ -257,36 +257,36 @@ }, "bcrypt": { "hashes": [ - "sha256:01746eb2c4299dd0ae1670234bf77704f581dd72cc180f444bfe74eb80495b64", - "sha256:037c5bf7c196a63dcce75545c8874610c600809d5d82c305dd327cd4969995bf", - "sha256:094fd31e08c2b102a14880ee5b3d09913ecf334cd604af27e1013c76831f7b05", - "sha256:0d4cf6ef1525f79255ef048b3489602868c47aea61f375377f0d00514fe4a78c", - 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"pytorch"} torchvision = {version = "~=0.18.1", index = "pytorch"} # https://pytorch.org/get-started/previous-versions/#linux-and-windows-1 +pytorch-triton-rocm = {version = "~=2.3.1", index = "pytorch"} # Datascience and useful extensions boto3 = "~=1.34.50" @@ -27,7 +28,7 @@ scikit-learn = "~=1.4.0" scipy = "~=1.12.0" skl2onnx = "~=1.16.0" onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf -codeflare-sdk = "~=0.16.4" +codeflare-sdk = "~=0.18.0" memray = "~=1.10.0" # any version above this would cause issue with rich package # DB connectors diff --git a/jupyter/rocm/pytorch/ubi9-python-3.9/Pipfile.lock b/jupyter/rocm/pytorch/ubi9-python-3.9/Pipfile.lock index 3562b2087..8dbab59f5 100644 --- a/jupyter/rocm/pytorch/ubi9-python-3.9/Pipfile.lock +++ b/jupyter/rocm/pytorch/ubi9-python-3.9/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "922cc25e73cf7ddb2207c65bbb40e3878b67f151420fdf9a67003856db36a5e2" + "sha256": 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"sha256:f3d73022990ab0c8b172cce57c69fd9a89c24fd473a5e79cbce92df87e3d9c48", + "sha256:f5b8353ea1a4d7dfb59a7f45c04df66ecfd363bb5b35f33b11ea579111d4655f", + "sha256:f809a17cc78bd331e137caa25262b507225854073fd319e987bd216bed911b7c", + "sha256:f9bc4161bd3b970cd6a6fcda70583ad4afd10f2750609fb1f3ca9505050d4ef3", + "sha256:fdf4890cda3b59170009d012fca3294c00140e7f2abe1910e6a730809d0f3f9b" ], "markers": "python_version >= '3.8'", - "version": "==0.18.1" + "version": "==0.19.1" }, "rsa": { "hashes": [ "sha256:90260d9058e514786967344d0ef75fa8727eed8a7d2e43ce9f4bcf1b536174f7", "sha256:e38464a49c6c85d7f1351b0126661487a7e0a14a50f1675ec50eb34d4f20ef21" ], - "markers": "python_version >= '3.6' and python_version < '4'", + "markers": "python_version >= '3.6' and python_version < '4.0'", "version": "==4.9" }, "ruamel.yaml": { @@ -3533,14 +3535,6 @@ "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'", "version": "==1.8.3" }, - "setuptools": { - "hashes": [ - "sha256:0ff4183f8f42cd8fa3acea16c45205521a4ef28f73c6391d8a25e92893134f2e", - "sha256:c21c49fb1042386df081cb5d86759792ab89efca84cf114889191cd09aacc80c" - ], - "index": "pypi", - "version": "==69.2.0" - }, "simpervisor": { "hashes": [ "sha256:3e313318264559beea3f475ead202bc1cd58a2f1288363abb5657d306c5b8388", @@ -3620,11 +3614,11 @@ }, "tenacity": { "hashes": [ - "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78", - "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687" + "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b", + "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539" ], "markers": "python_version >= '3.8'", - "version": "==8.5.0" + "version": "==9.0.0" }, "tensorboard": { "hashes": [ @@ -3728,11 +3722,11 @@ }, "tomlkit": { "hashes": [ - "sha256:af914f5a9c59ed9d0762c7b64d3b5d5df007448eb9cd2edc8a46b1eafead172f", - "sha256:eef34fba39834d4d6b73c9ba7f3e4d1c417a4e56f89a7e96e090dd0d24b8fb3c" + "sha256:08ad192699734149f5b97b45f1f18dad7eb1b6d16bc72ad0c2335772650d7b72", + "sha256:7075d3042d03b80f603482d69bf0c8f345c2b30e41699fd8883227f89972b264" ], - "markers": "python_version >= '3.7'", - "version": "==0.12.5" + "markers": "python_version >= '3.8'", + "version": "==0.13.0" }, "tornado": { "hashes": [ @@ -3780,7 +3774,7 @@ "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d", "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8" ], - "markers": "python_version >= '3.8'", + "markers": "python_version < '3.11'", "version": "==4.12.2" }, "tzdata": { @@ -3887,7 +3881,7 @@ "sha256:37a0344459b199fce0e80b0d3569837ec6b6937435c5244e7fd73fa6006830f3", "sha256:3e3d753a8618b86d7de333b4223005f68720bcd6a7d2bcb9fbd2229ec7c1e429" ], - "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'", + "markers": "python_version < '3.10'", "version": "==1.26.19" }, "virtualenv": { @@ -3974,10 +3968,10 @@ }, "whatthepatch": { "hashes": [ - "sha256:6bc41f9f48a63384be4478d8b2d5b22185aac75be853cdcb150a2dc174ede7e1", - "sha256:7f374c172812581bc3763587525d14a143aac7fe4220bc4676ecce0d86cb8f08" + "sha256:b274b3294784f78b1e759b35b49b7ef2e8473a580aabf39e5b94a9f901e5de61", + "sha256:c0cee5975e9b5cad8a0d12a52d76f8bb567ccdec319cf08c5fcfb1efab7fa1b2" ], - "version": "==1.0.5" + "version": "==1.0.6" }, "wheel": { "hashes": [ @@ -4286,7 +4280,7 @@ "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19", "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c" ], - "markers": "python_version >= '3.8'", + "markers": "python_version < '3.10'", "version": "==3.19.2" } }, diff --git a/jupyter/tensorflow/ubi9-python-3.9/Pipfile b/jupyter/tensorflow/ubi9-python-3.9/Pipfile index be6a89abc..43d367aee 100644 --- a/jupyter/tensorflow/ubi9-python-3.9/Pipfile +++ b/jupyter/tensorflow/ubi9-python-3.9/Pipfile @@ -21,7 +21,7 @@ scikit-learn = "~=1.4.0" scipy = "~=1.12.0" skl2onnx = "~=1.16.0" onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf -codeflare-sdk = "~=0.16.4" +codeflare-sdk = "~=0.18.0" memray = "~=1.10.0" # any version above this would cause issue with rich package # DB connectors pymongo = "~=4.6.2" diff --git a/jupyter/tensorflow/ubi9-python-3.9/Pipfile.lock b/jupyter/tensorflow/ubi9-python-3.9/Pipfile.lock index 4ada43c53..5e2ea3cf2 100644 --- a/jupyter/tensorflow/ubi9-python-3.9/Pipfile.lock +++ b/jupyter/tensorflow/ubi9-python-3.9/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "53e6643520ff09797bf0e1771b3ce582c3d3c36046167b5b9f4f6b962a711483" + "sha256": "4b41a45381ebe60322008cf2b6018a898a975c9cd799b678a7461884437f0049" }, "pipfile-spec": 6, "requires": { @@ -29,7 +29,7 @@ "sha256:1142fa8e80dbae46bb6339573ad4c8c0841358f79c6eb50a493dceca14621bad", "sha256:9107f1ca0b2a5553987a94a3c9959fe5b491fdf731389aa5b7b1bd0733e32de6" ], - "markers": "python_version >= '3.7' and python_full_version < '4.0.0'", + "markers": "python_version >= '3.7' and python_version < '4'", "version": "==22.1.0" }, "aiohttp": { @@ -157,7 +157,7 @@ "sha256:0fca07b290282b9449590cbdb39b3461c45f2b6037523949f028ff2cba82c85e", "sha256:c2aec138a24f8462d6199c65666590dab14acb18af6c62950c82bc8d40862558" ], - "markers": "python_version >= '3.6' and python_full_version < '4.0.0'", + "markers": "python_version >= '3.6' and python_version < '4'", "version": "==1.1.6" }, "argon2-cffi": { @@ -205,11 +205,11 @@ }, "astroid": { "hashes": [ - "sha256:8ead48e31b92b2e217b6c9733a21afafe479d52d6e164dd25fb1a770c7c3cf94", - "sha256:e8a0083b4bb28fcffb6207a3bfc9e5d0a68be951dd7e336d5dcf639c682388c0" + "sha256:0e14202810b30da1b735827f78f5157be2bbd4a7a59b7707ca0bfc2fb4c0063a", + "sha256:413658a61eeca6202a59231abb473f932038fbcbf1666587f66d482083413a25" ], "markers": "python_version >= '3.8'", - "version": "==3.2.2" + "version": "==3.2.4" }, "asttokens": { "hashes": [ @@ -259,36 +259,36 @@ }, "bcrypt": { 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a/jupyter/trustyai/ubi9-python-3.9/Pipfile.lock +++ b/jupyter/trustyai/ubi9-python-3.9/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "4dd689dc67992d3aa80fdbe9018e7d6df9bd42b38233fe7827a5e8a44f165cd4" + "sha256": "aad2bffb6fc7e7656b825fcc3d83b15fe77b20a56b807f60df4a2103eaadd8f4" }, "pipfile-spec": 6, "requires": { @@ -21,7 +21,7 @@ "sha256:1142fa8e80dbae46bb6339573ad4c8c0841358f79c6eb50a493dceca14621bad", "sha256:9107f1ca0b2a5553987a94a3c9959fe5b491fdf731389aa5b7b1bd0733e32de6" ], - "markers": "python_version >= '3.7' and python_version < '4'", + "markers": "python_version >= '3.7' and python_version < '4.0'", "version": "==22.1.0" }, "aiohttp": { @@ -149,7 +149,7 @@ "sha256:0fca07b290282b9449590cbdb39b3461c45f2b6037523949f028ff2cba82c85e", "sha256:c2aec138a24f8462d6199c65666590dab14acb18af6c62950c82bc8d40862558" ], - "markers": "python_version < '4' and python_full_version >= '3.6.0'", + "markers": "python_version >= '3.6' and python_version < '4.0'", "version": 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ee59b7bb3..5f0fc3fca 100644 --- a/runtimes/datascience/ubi9-python-3.9/Pipfile +++ b/runtimes/datascience/ubi9-python-3.9/Pipfile @@ -16,7 +16,7 @@ plotly = "~=5.20.0" scikit-learn = "~=1.4.0" scipy = "~=1.12.0" skl2onnx = "~=1.16.0" -codeflare-sdk = "~=0.16.4" +codeflare-sdk = "~=0.18.0" memray = "~=1.10.0" # any version above this would cause issue with rich package # DB connectors pymongo = "~=4.6.2" diff --git a/runtimes/datascience/ubi9-python-3.9/Pipfile.lock b/runtimes/datascience/ubi9-python-3.9/Pipfile.lock index dd3d3fab9..f09da6146 100644 --- a/runtimes/datascience/ubi9-python-3.9/Pipfile.lock +++ b/runtimes/datascience/ubi9-python-3.9/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "88f57b623868e3e3938059f37951f29d87486177ae8faf3dbca1c3b9d3a90bd2" + "sha256": "40e26b94cf088511f0a5e070298921884a371b369d69000a51a58cb4b19aba59" }, "pipfile-spec": 6, "requires": { @@ -151,43 +151,43 @@ }, "bcrypt": { "hashes": [ - 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python_version < '4'", + "markers": "python_version >= '3.6' and python_version < '4.0'", "version": "==4.9" }, "s3transfer": { @@ -2497,7 +2471,6 @@ "sha256:ff4effe5a1d4e8fed260a83a163f7dbf4f6087b54528d8880bab1d1377bd78be" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==1.4.2" }, "scipy": { @@ -2529,17 +2502,8 @@ "sha256:f7ce148dffcd64ade37b2df9315541f9adad6efcaa86866ee7dd5db0c8f041c3" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==1.12.0" }, - "setuptools": { - "hashes": [ - "sha256:b8b8060bb426838fbe942479c90296ce976249451118ef566a5a0b7d8b78fb05", - "sha256:bd63e505105011b25c3c11f753f7e3b8465ea739efddaccef8f0efac2137bac1" - ], - "markers": "python_version >= '3.8'", - "version": "==70.2.0" - }, "six": { "hashes": [ "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926", @@ -2580,11 +2544,11 @@ }, "tenacity": { "hashes": [ - "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78", - 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-2883,7 +2844,7 @@ "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19", "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c" ], - "markers": "python_version >= '3.8'", + "markers": "python_version < '3.10'", "version": "==3.19.2" } }, diff --git a/runtimes/pytorch/ubi9-python-3.9/Pipfile b/runtimes/pytorch/ubi9-python-3.9/Pipfile index 8e75de762..ecc3800eb 100644 --- a/runtimes/pytorch/ubi9-python-3.9/Pipfile +++ b/runtimes/pytorch/ubi9-python-3.9/Pipfile @@ -25,7 +25,7 @@ plotly = "~=5.20.0" scikit-learn = "~=1.4.0" scipy = "~=1.12.0" skl2onnx = "~=1.16.0" -codeflare-sdk = "~=0.16.4" +codeflare-sdk = "~=0.18.0" memray = "~=1.10.0" # any version above this would cause issue with rich package # DB connectors pymongo = "~=4.6.2" diff --git a/runtimes/pytorch/ubi9-python-3.9/Pipfile.lock b/runtimes/pytorch/ubi9-python-3.9/Pipfile.lock index 1c31ed13b..524708dfc 100644 --- a/runtimes/pytorch/ubi9-python-3.9/Pipfile.lock +++ b/runtimes/pytorch/ubi9-python-3.9/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "bca78aac4b0f17504b0d2886abbb7d02959480a2022d952c3c3fd522c32effdf" + "sha256": "842722828751600f7fc7916164c953ee01eed3c6e968471dcccc8092a69e7821" }, "pipfile-spec": 6, "requires": { @@ -164,43 +164,43 @@ }, "bcrypt": { "hashes": [ - "sha256:01746eb2c4299dd0ae1670234bf77704f581dd72cc180f444bfe74eb80495b64", - "sha256:037c5bf7c196a63dcce75545c8874610c600809d5d82c305dd327cd4969995bf", - "sha256:094fd31e08c2b102a14880ee5b3d09913ecf334cd604af27e1013c76831f7b05", - "sha256:0d4cf6ef1525f79255ef048b3489602868c47aea61f375377f0d00514fe4a78c", - "sha256:193bb49eeeb9c1e2db9ba65d09dc6384edd5608d9d672b4125e9320af9153a15", - "sha256:2505b54afb074627111b5a8dc9b6ae69d0f01fea65c2fcaea403448c503d3991", - "sha256:2ee15dd749f5952fe3f0430d0ff6b74082e159c50332a1413d51b5689cf06623", - "sha256:31adb9cbb8737a581a843e13df22ffb7c84638342de3708a98d5c986770f2834", - 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"sha256:f3d73022990ab0c8b172cce57c69fd9a89c24fd473a5e79cbce92df87e3d9c48", + "sha256:f5b8353ea1a4d7dfb59a7f45c04df66ecfd363bb5b35f33b11ea579111d4655f", + "sha256:f809a17cc78bd331e137caa25262b507225854073fd319e987bd216bed911b7c", + "sha256:f9bc4161bd3b970cd6a6fcda70583ad4afd10f2750609fb1f3ca9505050d4ef3", + "sha256:fdf4890cda3b59170009d012fca3294c00140e7f2abe1910e6a730809d0f3f9b" ], "markers": "python_version >= '3.8'", - "version": "==0.19.0" + "version": "==0.19.1" }, "rsa": { "hashes": [ "sha256:90260d9058e514786967344d0ef75fa8727eed8a7d2e43ce9f4bcf1b536174f7", "sha256:e38464a49c6c85d7f1351b0126661487a7e0a14a50f1675ec50eb34d4f20ef21" ], - "markers": "python_version >= '3.6' and python_version < '4'", + "markers": "python_version >= '3.6' and python_version < '4.0'", "version": "==4.9" }, "s3transfer": { @@ -2628,7 +2603,6 @@ "sha256:ff4effe5a1d4e8fed260a83a163f7dbf4f6087b54528d8880bab1d1377bd78be" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==1.4.2" }, "scipy": { @@ -2660,17 +2634,8 @@ "sha256:f7ce148dffcd64ade37b2df9315541f9adad6efcaa86866ee7dd5db0c8f041c3" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==1.12.0" }, - "setuptools": { - "hashes": [ - "sha256:b8b8060bb426838fbe942479c90296ce976249451118ef566a5a0b7d8b78fb05", - "sha256:bd63e505105011b25c3c11f753f7e3b8465ea739efddaccef8f0efac2137bac1" - ], - "markers": "python_version >= '3.8'", - "version": "==70.2.0" - }, "six": { "hashes": [ "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926", @@ -2711,26 +2676,25 @@ }, "sympy": { "hashes": [ - "sha256:3b6af8f4d008b9a1a6a4268b335b984b23835f26d1d60b0526ebc71d48a25f57", - "sha256:6b0b32a4673fb91bd3cac3b55406c8e01d53ae22780be467301cc452f6680c92" + "sha256:9cebf7e04ff162015ce31c9c6c9144daa34a93bd082f54fd8f12deca4f47515f", + "sha256:db36cdc64bf61b9b24578b6f7bab1ecdd2452cf008f34faa33776680c26d66f8" ], "markers": "python_version >= '3.8'", - "version": "==1.13.0" + "version": "==1.13.1" }, "tenacity": { "hashes": [ - "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78", - "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687" + "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b", + "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539" ], "markers": "python_version >= '3.8'", - "version": "==8.5.0" + "version": "==9.0.0" }, "tensorboard": { "hashes": [ "sha256:9f2b4e7dad86667615c0e5cd072f1ea8403fc032a299f0072d6f74855775cc45" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==2.16.2" }, "tensorboard-data-server": { @@ -2812,7 +2776,6 @@ "sha256:e7d8db41c0181c80d76c982aacc442c0783a2c54d6400fe028954201a2e032fe" ], "index": "pypi", - "markers": "python_version >= '3.8'", "version": "==6.3.3" }, "tqdm": { @@ -2829,7 +2792,6 @@ "sha256:2d313cc50a42cd6c277e7d7dc8d4d7fedd06a2c215f78766ae7b1a66277e0033" ], "index": "pypi", - "markers": "python_version >= '3.7'", "version": "==5.1.1" }, "triton": { @@ -2866,7 +2828,6 @@ "sha256:f8ecc1bba5667413457c529ab955bf8c67b45db799d159066261719e328580a0" ], "index": "pypi", - "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'", "version": "==1.26.18" }, "virtualenv": { @@ -3091,7 +3052,7 @@ "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19", "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c" ], - "markers": "python_version >= '3.8'", + "markers": "python_version < '3.10'", "version": "==3.19.2" } }, diff --git a/runtimes/tensorflow/ubi9-python-3.9/Pipfile b/runtimes/tensorflow/ubi9-python-3.9/Pipfile index dc9d94330..f4e0d021e 100644 --- a/runtimes/tensorflow/ubi9-python-3.9/Pipfile +++ b/runtimes/tensorflow/ubi9-python-3.9/Pipfile @@ -21,7 +21,7 @@ scikit-learn = "~=1.4.0" scipy = "~=1.12.0" skl2onnx = "~=1.16.0" onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf -codeflare-sdk = "~=0.16.4" +codeflare-sdk = "~=0.18.0" memray = "~=1.10.0" # any version above this would cause issue with rich package # DB connectors pymongo = "~=4.6.2" diff --git a/runtimes/tensorflow/ubi9-python-3.9/Pipfile.lock b/runtimes/tensorflow/ubi9-python-3.9/Pipfile.lock index 1e30a133e..500a2389f 100644 --- a/runtimes/tensorflow/ubi9-python-3.9/Pipfile.lock +++ b/runtimes/tensorflow/ubi9-python-3.9/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "bc77845837ca116f3a410a7ecd020134280d7bcbd31a3f78cc49cfceb9995bac" + "sha256": "c57c77c757ff6b1e3b37873765b11e98487ab4f02d549cf0035076644253bc92" }, "pipfile-spec": 6, "requires": { @@ -166,43 +166,43 @@ }, "bcrypt": { "hashes": [ - "sha256:01746eb2c4299dd0ae1670234bf77704f581dd72cc180f444bfe74eb80495b64", - "sha256:037c5bf7c196a63dcce75545c8874610c600809d5d82c305dd327cd4969995bf", - "sha256:094fd31e08c2b102a14880ee5b3d09913ecf334cd604af27e1013c76831f7b05", - 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"sha256:90260d9058e514786967344d0ef75fa8727eed8a7d2e43ce9f4bcf1b536174f7", "sha256:e38464a49c6c85d7f1351b0126661487a7e0a14a50f1675ec50eb34d4f20ef21" ], - "markers": "python_version >= '3.6' and python_version < '4'", + "markers": "python_version >= '3.6' and python_full_version < '4.0.0'", "version": "==4.9" }, "s3transfer": { @@ -2632,7 +2607,6 @@ "sha256:ff4effe5a1d4e8fed260a83a163f7dbf4f6087b54528d8880bab1d1377bd78be" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==1.4.2" }, "scipy": { @@ -2664,17 +2638,8 @@ "sha256:f7ce148dffcd64ade37b2df9315541f9adad6efcaa86866ee7dd5db0c8f041c3" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==1.12.0" }, - "setuptools": { - "hashes": [ - "sha256:b8b8060bb426838fbe942479c90296ce976249451118ef566a5a0b7d8b78fb05", - "sha256:bd63e505105011b25c3c11f753f7e3b8465ea739efddaccef8f0efac2137bac1" - ], - "markers": "python_version >= '3.8'", - "version": "==70.2.0" - }, "six": { "hashes": [ "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926", @@ -2715,18 +2680,17 @@ }, "tenacity": { "hashes": [ - "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78", - "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687" + "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b", + "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539" ], "markers": "python_version >= '3.8'", - "version": "==8.5.0" + "version": "==9.0.0" }, "tensorboard": { "hashes": [ "sha256:a6f6443728064d962caea6d34653e220e34ef8df764cb06a8212c17e1a8f0622" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==2.15.2" }, "tensorboard-data-server": { @@ -2757,7 +2721,6 @@ "sha256:f8e85821317c9c0fbf1256e9f721cfb1400ba1e09becb844b3ddd91f744805fc" ], "index": "pypi", - "markers": "python_version >= '3.9'", "version": "==2.15.1" }, "tensorflow-estimator": { @@ -2842,7 +2805,6 @@ "sha256:e7d8db41c0181c80d76c982aacc442c0783a2c54d6400fe028954201a2e032fe" ], "index": "pypi", - "markers": "python_version >= '3.8'", "version": "==6.3.3" }, "tqdm": { @@ -2859,7 +2821,6 @@ "sha256:2d313cc50a42cd6c277e7d7dc8d4d7fedd06a2c215f78766ae7b1a66277e0033" ], "index": "pypi", - "markers": "python_version >= '3.7'", "version": "==5.1.1" }, "typing-extensions": { @@ -2884,7 +2845,6 @@ "sha256:f8ecc1bba5667413457c529ab955bf8c67b45db799d159066261719e328580a0" ], "index": "pypi", - "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'", "version": "==1.26.18" }, "virtualenv": { @@ -3121,7 +3081,7 @@ "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19", "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c" ], - "markers": "python_version >= '3.8'", + "markers": "python_version < '3.10'", "version": "==3.19.2" } }, From 2095eb5f00115150780262dac5d94d62f9770994 Mon Sep 17 00:00:00 2001 From: aTheo Date: Tue, 30 Jul 2024 21:19:11 +0300 Subject: [PATCH 5/6] Incorporate rocm-pytorch and rocm-tensorflow runtime images (#626) * Incorporate rocm-pytorch and rocm-tensorflow runtime images * Commit autogenerated changes from the to update the build-notebooks.yaml * Rename references of amd to rocm as more proper naming --- .github/workflows/build-notebooks.yaml | 22 + Makefile | 14 + .../rocm-pytorch/ubi9-python-3.9/Dockerfile | 28 + runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile | 60 + .../rocm-pytorch/ubi9-python-3.9/Pipfile.lock | 2946 ++++++++++++++++ .../kustomize/base/kustomization.yaml | 14 + .../ubi9-python-3.9/kustomize/base/pod.yaml | 29 + .../kustomize/base/requirements-elyra.txt | 20 + .../ubi9-python-3.9/utils/bootstrapper.py | 770 ++++ .../ubi9-python-3.9/utils/pip.conf | 4 + .../utils/requirements-elyra.txt | 71 + .../ubi9-python-3.9/Dockerfile | 28 + .../rocm-tensorflow/ubi9-python-3.9/Pipfile | 54 + .../ubi9-python-3.9/Pipfile.lock | 3086 +++++++++++++++++ .../kustomize/base/kustomization.yaml | 14 + .../ubi9-python-3.9/kustomize/base/pod.yaml | 29 + .../kustomize/base/requirements-elyra.txt | 20 + .../ubi9-python-3.9/utils/bootstrapper.py | 770 ++++ .../ubi9-python-3.9/utils/pip.conf | 4 + .../utils/requirements-elyra.txt | 71 + 20 files changed, 8054 insertions(+) create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/Dockerfile create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile.lock create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/kustomization.yaml create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/pod.yaml create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/requirements-elyra.txt create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/utils/bootstrapper.py create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/utils/pip.conf create mode 100644 runtimes/rocm-pytorch/ubi9-python-3.9/utils/requirements-elyra.txt create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/Dockerfile create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/Pipfile create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/Pipfile.lock create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/kustomization.yaml create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/pod.yaml create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/requirements-elyra.txt create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/utils/bootstrapper.py create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/utils/pip.conf create mode 100644 runtimes/rocm-tensorflow/ubi9-python-3.9/utils/requirements-elyra.txt diff --git a/.github/workflows/build-notebooks.yaml b/.github/workflows/build-notebooks.yaml index ef9d9258f..dee9374c9 100644 --- a/.github/workflows/build-notebooks.yaml +++ b/.github/workflows/build-notebooks.yaml @@ -471,6 +471,28 @@ }, "secrets": "inherit" }, + "rocm-runtime-pytorch-ubi9-python-3_9": { + "needs": [ + "rocm-ubi9-python-3_9" + ], + "uses": "./.github/workflows/build-notebooks-TEMPLATE.yaml", + "with": { + "target": "rocm-runtime-pytorch-ubi9-python-3.9", + "github": "${{ toJSON(github) }}" + }, + "secrets": "inherit" + }, + "rocm-runtime-tensorflow-ubi9-python-3_9": { + "needs": [ + "rocm-ubi9-python-3_9" + ], + "uses": "./.github/workflows/build-notebooks-TEMPLATE.yaml", + "with": { + "target": "rocm-runtime-tensorflow-ubi9-python-3.9", + "github": "${{ toJSON(github) }}" + }, + "secrets": "inherit" + }, "base-anaconda-python-3_8": { "needs": [], "uses": "./.github/workflows/build-notebooks-TEMPLATE.yaml", diff --git a/Makefile b/Makefile index d3c82f736..4179e8465 100644 --- a/Makefile +++ b/Makefile @@ -277,6 +277,16 @@ rocm-jupyter-tensorflow-ubi9-python-3.9: rocm-jupyter-datascience-ubi9-python-3. rocm-jupyter-pytorch-ubi9-python-3.9: rocm-jupyter-datascience-ubi9-python-3.9 $(call image,$@,jupyter/rocm/pytorch/ubi9-python-3.9,$<) +# Build and push rocm-jupyter-runtime-pytorch-ubi9-python-3.9 image to the registry +.PHONY: rocm-runtime-pytorch-ubi9-python-3.9 +rocm-runtime-pytorch-ubi9-python-3.9: rocm-ubi9-python-3.9 + $(call image,$@,runtimes/rocm-pytorch/ubi9-python-3.9,$<) + +# Build and push rocm-jupyter-runtime-tensorflow-ubi9-python-3.9 image to the registry +.PHONY: rocm-runtime-tensorflow-ubi9-python-3.9 +rocm-runtime-tensorflow-ubi9-python-3.9: rocm-ubi9-python-3.9 + $(call image,$@,runtimes/rocm-tensorflow/ubi9-python-3.9,$<) + ####################################### Buildchain for Anaconda Python ####################################### # Build and push base-anaconda-python-3.8 image to the registry @@ -566,6 +576,10 @@ refresh-pipfilelock-files: cd runtimes/pytorch/ubi8-python-3.8 && pipenv lock cd runtimes/tensorflow/ubi8-python-3.8 && pipenv lock cd runtimes/tensorflow/ubi9-python-3.9 && pipenv lock + cd runtimes/rocm-tensorflow/ubi9-python-3.9 && pipenv lock + cd runtimes/rocm-pytorch/ubi9-python-3.9 && pipenv lock + + # This is only for the workflow action # For running manually, set the required environment variables diff --git a/runtimes/rocm-pytorch/ubi9-python-3.9/Dockerfile b/runtimes/rocm-pytorch/ubi9-python-3.9/Dockerfile new file mode 100644 index 000000000..cd1114cd9 --- /dev/null +++ b/runtimes/rocm-pytorch/ubi9-python-3.9/Dockerfile @@ -0,0 +1,28 @@ +ARG BASE_IMAGE +FROM ${BASE_IMAGE} + +LABEL name="odh-notebook-runtime-rocm-pytorch-ubi9-python-3.9" \ + summary="Runtime ROCm pytorch notebook image for ODH notebooks" \ + description="Runtime ROCm pytorch notebook image with base Python 3.9 builder image based on UBI9 for ODH notebooks" \ + io.k8s.display-name="Runtime ROCm pytorch notebook image for ODH notebooks" \ + io.k8s.description="Runtime ROCm pytorch notebook image with base Python 3.9 builder image based on UBI9 for ODH notebooks" \ + authoritative-source-url="https://github.com/opendatahub-io/notebooks" \ + io.openshift.build.commit.ref="main" \ + io.openshift.build.source-location="https://github.com/opendatahub-io/notebooks/tree/main/runtimes/rocm-pytorch/ubi9-python-3.9" \ + io.openshift.build.image="quay.io/opendatahub/workbench-images:rocm-runtime-pytorch-ubi9-python-3.9" + +WORKDIR /opt/app-root/bin + +# Install Python packages from Pipfile.lock +COPY Pipfile.lock ./ +# Copy Elyra dependencies for air-gapped enviroment +COPY utils ./utils/ + +RUN echo "Installing softwares and packages" && \ + micropipenv install && \ + rm -f ./Pipfile.lock && \ + # Fix permissions to support pip in Openshift environments \ + chmod -R g+w /opt/app-root/lib/python3.9/site-packages && \ + fix-permissions /opt/app-root -P + +WORKDIR /opt/app-root/src diff --git a/runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile b/runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile new file mode 100644 index 000000000..132e3acbe --- /dev/null +++ b/runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile @@ -0,0 +1,60 @@ +[[source]] +url = "https://pypi.org/simple" +verify_ssl = true +name = "pypi" + +[[source]] +url = "https://download.pytorch.org/whl/rocm6.0/" +verify_ssl = true +name = "pytorch" + +[dev-packages] + +[packages] +# PyTorch packages +tensorboard = "~=2.16.2" +torch = {version = "~=2.3.1", index = "pytorch"} +torchvision = {version = "~=0.18.1", index = "pytorch"} # https://pytorch.org/get-started/previous-versions/#linux-and-windows-1 + +# Datascience and useful extensions +boto3 = "~=1.34.50" +kafka-python = "~=2.0.2" +matplotlib = "~=3.8.3" +numpy = "~=1.26.4" +pandas = "~=2.2.0" +plotly = "~=5.20.0" +scikit-learn = "~=1.4.0" +scipy = "~=1.12.0" +skl2onnx = "~=1.16.0" +onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf +codeflare-sdk = "~=0.16.4" +memray = "~=1.10.0" # any version above this would cause issue with rich package + +# DB connectors +pymongo = "~=4.6.2" +psycopg = "~=3.1.18" +pyodbc = "~=5.1.0" +mysql-connector-python = "~=8.3.0" + +# This is a comprehensive list of python dependencies that Elyra requires to execute Jupyter notebooks. +ipykernel = "==6.13.0" +ipython = "==8.10.0" +ipython-genutils = "==0.2.0" +jinja2 = "==3.1.4" +jupyter-client = "==7.3.1" +jupyter-core = "==4.11.2" +MarkupSafe = "==2.1.1" +minio = "==7.1.15" +nbclient = "==0.6.3" +nbconvert = "==7.1.0" +nbformat = "==5.4.0" +papermill = "==2.3.4" +pyzmq = "==24.0.1" +prompt-toolkit = "==3.0.30" +requests = "==2.31.0" +tornado = "==6.3.3" +traitlets = "==5.1.1" +urllib3 = "==1.26.18" + +[requires] +python_version = "3.9" diff --git a/runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile.lock b/runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile.lock new file mode 100644 index 000000000..abf3ba0bc --- /dev/null +++ b/runtimes/rocm-pytorch/ubi9-python-3.9/Pipfile.lock @@ -0,0 +1,2946 @@ +{ + "_meta": { + "hash": { + "sha256": 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--git a/runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/pod.yaml b/runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/pod.yaml new file mode 100644 index 000000000..bc5343566 --- /dev/null +++ b/runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/pod.yaml @@ -0,0 +1,29 @@ +--- +apiVersion: v1 +kind: Pod +metadata: + name: pod + labels: + app: runtime-image +spec: + containers: + - name: runtime + image: runtime-workbench + command: ["/bin/sh", "-c", "while true ; do date; sleep 1; done;"] + imagePullPolicy: Always + ports: + - containerPort: 8080 + resources: + limits: + cpu: 500m + memory: 500Mi + requests: + cpu: 500m + memory: 500Mi + volumeMounts: + - name: config + mountPath: /opt/app-root/elyra + volumes: + - name: config + configMap: + name: req-config diff --git a/runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/requirements-elyra.txt b/runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/requirements-elyra.txt new file mode 100644 index 000000000..91fb8e57d --- /dev/null +++ b/runtimes/rocm-pytorch/ubi9-python-3.9/kustomize/base/requirements-elyra.txt @@ -0,0 +1,20 @@ +# This is a comprehensive list of python dependencies that Elyra requires to execute Jupyter notebooks. +# This is copied from elyra directly: https://github.com/elyra-ai/elyra/blob/main/etc/generic/requirements-elyra.txt +ipykernel==6.13.0 +ipython==8.10.0 +ipython-genutils==0.2.0 +jinja2==3.1.4 +jupyter-client==7.3.1 +jupyter-core==4.11.2 +MarkupSafe==2.1.1 +minio==7.1.15 +nbclient==0.6.3 +nbconvert==7.1.0 +nbformat==5.4.0 +papermill==2.3.4 +pyzmq==24.0.1 +prompt-toolkit==3.0.30 +requests==2.31.0 +tornado==6.3.3 +traitlets==5.1.1 +urllib3==1.26.18 diff --git a/runtimes/rocm-pytorch/ubi9-python-3.9/utils/bootstrapper.py b/runtimes/rocm-pytorch/ubi9-python-3.9/utils/bootstrapper.py new file mode 100644 index 000000000..6163cdd84 --- /dev/null +++ b/runtimes/rocm-pytorch/ubi9-python-3.9/utils/bootstrapper.py @@ -0,0 +1,770 @@ +# Copied from: https://github.com/elyra-ai/elyra/blob/main/elyra/kfp/bootstrapper.py +# +# Copyright 2018-2023 Elyra Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +from abc import ABC +from abc import abstractmethod +import glob +import json +import logging +import os +from pathlib import Path +import subprocess +import sys +from tempfile import TemporaryFile +import time +from typing import Any +from typing import Dict +from typing import Optional +from typing import Type +from typing import TypeVar +from urllib.parse import urljoin +from urllib.parse import urlparse +from urllib.parse import urlunparse + +from packaging import version + + +# Inputs and Outputs separator character. If updated, +# same-named variable in _notebook_op.py must be updated! +INOUT_SEPARATOR = ";" + +# Setup forward reference for type hint on return from class factory method. See +# https://stackoverflow.com/questions/39205527/can-you-annotate-return-type-when-value-is-instance-of-cls/39205612#39205612 +F = TypeVar("F", bound="FileOpBase") + +logger = logging.getLogger("elyra") +enable_pipeline_info = os.getenv("ELYRA_ENABLE_PIPELINE_INFO", "true").lower() == "true" +pipeline_name = None # global used in formatted logging +operation_name = None # global used in formatted logging + + +class FileOpBase(ABC): + """Abstract base class for file-based operations""" + + filepath = None + cos_client = None + cos_bucket = None + + @classmethod + def get_instance(cls: Type[F], **kwargs: Any) -> F: + """Creates an appropriate subclass instance based on the extension of the filepath (-f) argument""" + filepath = kwargs["filepath"] + if ".ipynb" in filepath: + return NotebookFileOp(**kwargs) + elif ".py" in filepath: + return PythonFileOp(**kwargs) + elif ".r" in filepath: + return RFileOp(**kwargs) + else: + raise ValueError(f"Unsupported file type: {filepath}") + + def __init__(self, **kwargs: Any) -> None: + """Initializes the FileOpBase instance""" + import minio + from minio.credentials import providers + + self.filepath = kwargs["filepath"] + self.input_params = kwargs or {} + self.cos_endpoint = urlparse(self.input_params.get("cos-endpoint")) + self.cos_bucket = self.input_params.get("cos-bucket") + + self.parameter_pass_method = self.input_params.get("parameter_pass_method") + self.pipeline_param_dict = self.convert_param_str_to_dict(self.input_params.get("pipeline_parameters")) + + # Infer secure from the endpoint's scheme. + self.secure = self.cos_endpoint.scheme == "https" + + # get minio credentials provider + if "cos-user" in self.input_params and "cos-password" in self.input_params: + cred_provider = providers.StaticProvider( + access_key=self.input_params.get("cos-user"), + secret_key=self.input_params.get("cos-password"), + ) + elif "AWS_ACCESS_KEY_ID" in os.environ and "AWS_SECRET_ACCESS_KEY" in os.environ: + cred_provider = providers.EnvAWSProvider() + elif "AWS_ROLE_ARN" in os.environ and "AWS_WEB_IDENTITY_TOKEN_FILE" in os.environ: + cred_provider = providers.IamAwsProvider() + else: + raise RuntimeError( + "No minio credentials provider can be initialised for current configs. " + "Please validate your runtime configuration details and retry." + ) + + # get minio client + self.cos_client = minio.Minio(self.cos_endpoint.netloc, secure=self.secure, credentials=cred_provider) + + @abstractmethod + def execute(self) -> None: + """Execute the operation relative to derived class""" + raise NotImplementedError("Method 'execute()' must be implemented by subclasses!") + + def process_dependencies(self) -> None: + """Process dependencies + + If a dependency archive is present, it will be downloaded from object storage + and expanded into the local directory. + + This method can be overridden by subclasses, although overrides should first + call the superclass method. + """ + OpUtil.log_operation_info("processing dependencies") + t0 = time.time() + archive_file = self.input_params.get("cos-dependencies-archive") + + self.get_file_from_object_storage(archive_file) + + inputs = self.input_params.get("inputs") + if inputs: + input_list = inputs.split(INOUT_SEPARATOR) + for file in input_list: + self.get_file_from_object_storage(file.strip()) + + subprocess.call(["tar", "-zxvf", archive_file]) + duration = time.time() - t0 + OpUtil.log_operation_info("dependencies processed", duration) + + def process_outputs(self) -> None: + """Process outputs + + If outputs have been specified, it will upload the appropriate files to object storage + + This method can be overridden by subclasses, although overrides should first + call the superclass method. + """ + OpUtil.log_operation_info("processing outputs") + t0 = time.time() + outputs = self.input_params.get("outputs") + if outputs: + output_list = outputs.split(INOUT_SEPARATOR) + for file in output_list: + self.process_output_file(file.strip()) + duration = time.time() - t0 + OpUtil.log_operation_info("outputs processed", duration) + + def process_metrics_and_metadata(self) -> None: + """Process metrics and metadata + + This method exposes metrics/metadata that the processed + notebook | script produces in the KFP UI. + + This method should not be overridden by subclasses. + """ + + OpUtil.log_operation_info("processing metrics and metadata") + t0 = time.time() + + # Location where the KFP specific output files will be stored + # in the environment where the bootsrapper is running. + # Defaults to '/tmp' if not specified. + output_path = Path(os.getenv("ELYRA_WRITABLE_CONTAINER_DIR", "/tmp")) + + # verify that output_path exists, is a directory + # and writable by creating a temporary file in that location + try: + with TemporaryFile(mode="w", dir=output_path) as t: + t.write("can write") + except Exception: + # output_path doesn't meet the requirements + # treat this as a non-fatal error and log a warning + logger.warning(f'Cannot create files in "{output_path}".') + OpUtil.log_operation_info("Aborted metrics and metadata processing", time.time() - t0) + return + + # Name of the proprietary KFP UI metadata file. + # Notebooks | scripts might (but don't have to) produce this file + # as documented in + # https://www.kubeflow.org/docs/pipelines/sdk/output-viewer/ + # Each ExecuteFileOp must declare this as an output file or + # the KFP UI won't pick up the information. + kfp_ui_metadata_filename = "mlpipeline-ui-metadata.json" + + # Name of the proprietary KFP metadata file. + # Notebooks | scripts might (but don't have to) produce this file + # as documented in + # https://www.kubeflow.org/docs/pipelines/sdk/pipelines-metrics/ + # Each ExecuteFileOp must declare this as an output file or + # the KFP UI won't pick up the information. + kfp_metrics_filename = "mlpipeline-metrics.json" + + # If the notebook | Python script produced one of the files + # copy it to the target location where KFP is looking for it. + for filename in [kfp_ui_metadata_filename, kfp_metrics_filename]: + try: + src = Path(".") / filename + logger.debug(f"Processing {src} ...") + # try to load the file, if one was created by the + # notebook or script + with open(src, "r") as f: + metadata = json.load(f) + + # the file exists and contains valid JSON + logger.debug(f"File content: {json.dumps(metadata)}") + + target = output_path / filename + # try to save the file in the destination location + with open(target, "w") as f: + json.dump(metadata, f) + except FileNotFoundError: + # The script | notebook didn't produce the file + # we are looking for. This is not an error condition + # that needs to be handled. + logger.debug(f"{self.filepath} produced no file named {src}") + except ValueError as ve: + # The file content could not be parsed. Log a warning + # and treat this as a non-fatal error. + logger.warning(f"Ignoring incompatible {str(src)} produced by {self.filepath}: {ve} {str(ve)}") + except Exception as ex: + # Something is wrong with the user-generated metadata file. + # Log a warning and treat this as a non-fatal error. + logger.warning(f"Error processing {str(src)} produced by {self.filepath}: {ex} {str(ex)}") + + # + # Augment kfp_ui_metadata_filename with Elyra-specific information: + # - link to object storage where input and output artifacts are + # stored + ui_metadata_output = output_path / kfp_ui_metadata_filename + try: + # re-load the file + with open(ui_metadata_output, "r") as f: + metadata = json.load(f) + except Exception: + # ignore all errors + metadata = {} + + # Assure the 'output' property exists and is of the correct type + if metadata.get("outputs", None) is None or not isinstance(metadata["outputs"], list): + metadata["outputs"] = [] + + # Define HREF for COS bucket: + # // + bucket_url = urljoin( + urlunparse(self.cos_endpoint), f"{self.cos_bucket}/{self.input_params.get('cos-directory', '')}/" + ) + + # add Elyra metadata to 'outputs' + metadata["outputs"].append( + { + "storage": "inline", + "source": f"## Inputs for {self.filepath}\n" + f"[{self.input_params['cos-dependencies-archive']}]({bucket_url})", + "type": "markdown", + } + ) + + # print the content of the augmented metadata file + logger.debug(f"Output UI metadata: {json.dumps(metadata)}") + + logger.debug(f"Saving UI metadata file as {ui_metadata_output} ...") + + # Save [updated] KFP UI metadata file + with open(ui_metadata_output, "w") as f: + json.dump(metadata, f) + + duration = time.time() - t0 + OpUtil.log_operation_info("metrics and metadata processed", duration) + + def get_object_storage_filename(self, filename: str) -> str: + """Function to pre-pend cloud storage working dir to file name + + :param filename: the local file + :return: the full path of the object storage file + """ + return os.path.join(self.input_params.get("cos-directory", ""), filename) + + def get_file_from_object_storage(self, file_to_get: str) -> None: + """Utility function to get files from an object storage + + :param file_to_get: filename + """ + + object_to_get = self.get_object_storage_filename(file_to_get) + t0 = time.time() + self.cos_client.fget_object(bucket_name=self.cos_bucket, object_name=object_to_get, file_path=file_to_get) + duration = time.time() - t0 + OpUtil.log_operation_info( + f"downloaded {file_to_get} from bucket: {self.cos_bucket}, object: {object_to_get}", duration + ) + + def put_file_to_object_storage(self, file_to_upload: str, object_name: Optional[str] = None) -> None: + """Utility function to put files into an object storage + + :param file_to_upload: filename + :param object_name: remote filename (used to rename) + """ + + object_to_upload = object_name + if not object_to_upload: + object_to_upload = file_to_upload + + object_to_upload = self.get_object_storage_filename(object_to_upload) + t0 = time.time() + self.cos_client.fput_object(bucket_name=self.cos_bucket, object_name=object_to_upload, file_path=file_to_upload) + duration = time.time() - t0 + OpUtil.log_operation_info( + f"uploaded {file_to_upload} to bucket: {self.cos_bucket} object: {object_to_upload}", duration + ) + + def has_wildcard(self, filename): + wildcards = ["*", "?"] + return bool(any(c in filename for c in wildcards)) + + def process_output_file(self, output_file): + """Puts the file to object storage. Handles wildcards and directories.""" + + matched_files = [output_file] + if self.has_wildcard(output_file): # explode the wildcarded file + matched_files = glob.glob(output_file) + + for matched_file in matched_files: + if os.path.isdir(matched_file): + for file in os.listdir(matched_file): + self.process_output_file(os.path.join(matched_file, file)) + else: + self.put_file_to_object_storage(matched_file) + + def convert_param_str_to_dict(self, pipeline_parameters: Optional[str] = None) -> Dict[str, Any]: + """Convert INOUT-separated string of pipeline parameters into a dictionary.""" + parameter_dict = {} + if pipeline_parameters: + parameter_list = pipeline_parameters.split(INOUT_SEPARATOR) + for parameter in parameter_list: + param_name, value = parameter.split("=", 1) + if self.parameter_pass_method == "env" and (not value or not isinstance(value, str)): + continue # env vars must be non-empty strings + parameter_dict[param_name] = value + return parameter_dict + + def set_parameters_in_env(self) -> None: + """Make pipeline parameters available as environment variables.""" + for name, value in self.pipeline_param_dict.items(): + if name in os.environ: + continue # avoid overwriting env vars with the same name + os.environ[name] = value + + +class NotebookFileOp(FileOpBase): + """Perform Notebook File Operation""" + + def execute(self) -> None: + """Execute the Notebook and upload results to object storage""" + notebook = os.path.basename(self.filepath) + notebook_name = notebook.replace(".ipynb", "") + notebook_output = f"{notebook_name}-output.ipynb" + notebook_html = f"{notebook_name}.html" + + try: + OpUtil.log_operation_info(f"executing notebook using 'papermill {notebook} {notebook_output}'") + t0 = time.time() + # Include kernel selection in execution time + kernel_name = NotebookFileOp.find_best_kernel(notebook) + + kwargs = {} + if self.parameter_pass_method == "env": + self.set_parameters_in_env() + + import papermill + + papermill.execute_notebook(notebook, notebook_output, kernel_name=kernel_name, **kwargs) + duration = time.time() - t0 + OpUtil.log_operation_info("notebook execution completed", duration) + + NotebookFileOp.convert_notebook_to_html(notebook_output, notebook_html) + self.put_file_to_object_storage(notebook_output, notebook) + self.put_file_to_object_storage(notebook_html) + self.process_outputs() + except Exception as ex: + # log in case of errors + logger.error(f"Unexpected error: {sys.exc_info()[0]}") + + NotebookFileOp.convert_notebook_to_html(notebook_output, notebook_html) + self.put_file_to_object_storage(notebook_output, notebook) + self.put_file_to_object_storage(notebook_html) + raise ex + + @staticmethod + def convert_notebook_to_html(notebook_file: str, html_file: str) -> str: + """Function to convert a Jupyter notebook file (.ipynb) into an html file + + :param notebook_file: object storage client + :param html_file: name of what the html output file should be + :return: html_file: the converted notebook in html format + """ + import nbconvert + import nbformat + + OpUtil.log_operation_info(f"converting from {notebook_file} to {html_file}") + t0 = time.time() + nb = nbformat.read(notebook_file, as_version=4) + html_exporter = nbconvert.HTMLExporter() + data, resources = html_exporter.from_notebook_node(nb) + with open(html_file, "w") as f: + f.write(data) + f.close() + + duration = time.time() - t0 + OpUtil.log_operation_info(f"{notebook_file} converted to {html_file}", duration) + return html_file + + @staticmethod + def find_best_kernel(notebook_file: str) -> str: + """Determines the best kernel to use via the following algorithm: + + 1. Loads notebook and gets kernel_name and kernel_language from NB metadata. + 2. Gets the list of configured kernels using KernelSpecManager. + 3. If notebook kernel_name is in list, use that, else + 4. If not found, load each configured kernel.json file and find a language match. + 5. On first match, log info message regarding the switch and use that kernel. + 6. If no language match is found, revert to notebook kernel and log warning message. + """ + from jupyter_client.kernelspec import KernelSpecManager + import nbformat + + nb = nbformat.read(notebook_file, 4) + + nb_kspec = nb.metadata.kernelspec + nb_kernel_name = nb_kspec.get("name") + nb_kernel_lang = nb_kspec.get("language") + + kernel_specs = KernelSpecManager().find_kernel_specs() + + # see if we have a direct match... + if nb_kernel_name in kernel_specs.keys(): + return nb_kernel_name + + # no match found for kernel, try matching language... + for name, file in kernel_specs.items(): + # load file (JSON) and pick out language, if match, use first found + with open(os.path.join(file, "kernel.json")) as f: + kspec = json.load(f) + if kspec.get("language").lower() == nb_kernel_lang.lower(): + matched_kernel = os.path.basename(file) + logger.info( + f"Matched kernel by language ({nb_kernel_lang}), using kernel " + f"'{matched_kernel}' instead of the missing kernel '{nb_kernel_name}'." + ) + return matched_kernel + + # no match found for language, return notebook kernel and let execution fail + logger.warning( + f"Reverting back to missing notebook kernel '{nb_kernel_name}' since no " + f"language match ({nb_kernel_lang}) was found in current kernel specifications." + ) + return nb_kernel_name + + +class PythonFileOp(FileOpBase): + """Perform Python File Operation""" + + def execute(self) -> None: + """Execute the Python script and upload results to object storage""" + python_script = os.path.basename(self.filepath) + python_script_name = python_script.replace(".py", "") + # python_script_output = f"{python_script_name}.log" + + try: + OpUtil.log_operation_info( + f"executing python script using 'python3 {python_script}'" + ) + t0 = time.time() + + run_args = ["python3", python_script] + if self.parameter_pass_method == "env": + self.set_parameters_in_env() + + logger.info("----------------------Python logs start----------------------") + # Removing support for the s3 storage of python script logs + # with open(python_script_output, "w") as log_file: + # process = subprocess.Popen(run_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + process = subprocess.Popen(run_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + + for line in iter(process.stdout.readline, b''): + sys.stdout.write(line.decode()) + + process.stdout.close() + return_code = process.wait() + logger.info("----------------------Python logs ends----------------------") + if return_code: + raise subprocess.CalledProcessError(return_code, run_args) + duration = time.time() - t0 + OpUtil.log_operation_info("python script execution completed", duration) + + # self.put_file_to_object_storage(python_script_output, python_script_output) + self.process_outputs() + except Exception as ex: + # log in case of errors + logger.error(f"Unexpected error: {sys.exc_info()[0]}") + logger.error(f"Error details: {ex}") + + # self.put_file_to_object_storage(python_script_output, python_script_output) + raise ex + + +class RFileOp(FileOpBase): + """Perform R File Operation""" + + def execute(self) -> None: + """Execute the R script and upload results to object storage""" + r_script = os.path.basename(self.filepath) + r_script_name = r_script.replace(".r", "") + # r_script_output = f"{r_script_name}.log" + + try: + OpUtil.log_operation_info(f"executing R script using 'Rscript {r_script}'") + t0 = time.time() + + run_args = ["Rscript", r_script] + if self.parameter_pass_method == "env": + self.set_parameters_in_env() + + logger.info("----------------------R script logs start----------------------") + # Removing support for the s3 storage of R script logs + # with open(r_script_output, "w") as log_file: + # process = subprocess.Popen(run_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + process = subprocess.Popen(run_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + + for line in iter(process.stdout.readline, b''): + sys.stdout.write(line.decode()) + + process.stdout.close() + return_code = process.wait() + logger.info("----------------------R script logs ends----------------------") + if return_code: + raise subprocess.CalledProcessError(return_code, run_args) + + duration = time.time() - t0 + OpUtil.log_operation_info("R script execution completed", duration) + + # self.put_file_to_object_storage(r_script_output, r_script_output) + self.process_outputs() + except Exception as ex: + # log in case of errors + logger.error(f"Unexpected error: {sys.exc_info()[0]}") + logger.error(f"Error details: {ex}") + + # self.put_file_to_object_storage(r_script_output, r_script_output) + raise ex + + +class OpUtil(object): + """Utility functions for preparing file execution.""" + + @classmethod + def package_install(cls, user_volume_path) -> None: + OpUtil.log_operation_info("Installing packages") + t0 = time.time() + requirements_file = cls.determine_elyra_requirements() + elyra_packages = cls.package_list_to_dict(requirements_file) + current_packages = cls.package_list_to_dict("requirements-current.txt") + to_install_list = [] + + for package, ver in elyra_packages.items(): + if package in current_packages: + if current_packages[package] is None: + logger.warning( + f"WARNING: Source package '{package}' found already installed as an " + "editable package. This may conflict with the required version: " + f"{ver} . Skipping..." + ) + continue + try: + version.Version(current_packages[package]) + except version.InvalidVersion: # current version is not PEP-440 compliant + logger.warning( + f"WARNING: Source package '{package}' found already installed from " + f"{current_packages[package]}. This may conflict with the required " + f"version: {ver} . Skipping..." + ) + continue + if version.Version(ver) > version.Version(current_packages[package]): + logger.info(f"Updating {package} package from version {current_packages[package]} to {ver}...") + to_install_list.append(f"{package}=={ver}") + elif version.Version(ver) < version.Version(current_packages[package]): + logger.info( + f"Newer {package} package with version {current_packages[package]} " + f"already installed. Skipping..." + ) + else: + logger.info(f"Package not found. Installing {package} package with version {ver}...") + to_install_list.append(f"{package}=={ver}") + + if to_install_list: + if user_volume_path: + to_install_list.insert(0, f"--target={user_volume_path}") + to_install_list.append("--no-cache-dir") + + subprocess.run([sys.executable, "-m", "pip", "install"] + to_install_list, check=True) + + if user_volume_path: + os.environ["PIP_CONFIG_FILE"] = f"{user_volume_path}/pip.conf" + + subprocess.run([sys.executable, "-m", "pip", "freeze"]) + duration = time.time() - t0 + OpUtil.log_operation_info("Packages installed", duration) + + @classmethod + def determine_elyra_requirements(cls) -> Any: + if sys.version_info.major == 3: + if sys.version_info.minor in [8, 9, 10, 11]: + return "requirements-elyra.txt" + logger.error( + f"This version of Python '{sys.version_info.major}.{sys.version_info.minor}' " + f"is not supported for Elyra generic components" + ) + return None + + @classmethod + def package_list_to_dict(cls, filename: str) -> dict: + package_dict = {} + with open(filename) as fh: + for line in fh: + if line[0] != "#": + if " @ " in line: + package_name, package_version = line.strip("\n").split(sep=" @ ") + elif "===" in line: + package_name, package_version = line.strip("\n").split(sep="===") + elif "==" in line: + package_name, package_version = line.strip("\n").split(sep="==") + elif line.startswith("-e ") or line.startswith("--editable "): + package_name = line.strip("\n").replace("-e ", "").replace("--editable ", "") + if "#egg=" in package_name: # editable package from version control system + package_name = package_name.split("=")[-1] + elif "/" in package_name: # editable package from local directory + package_name = os.path.basename(package_name) + package_version = None + else: + # Tolerate other formats but do not add to package list + continue + + package_dict[package_name] = package_version + + return package_dict + + @classmethod + def parse_arguments(cls, args) -> dict: + import argparse + + global pipeline_name, operation_name + + logger.debug("Parsing Arguments.....") + parser = argparse.ArgumentParser() + parser.add_argument( + "-e", "--cos-endpoint", dest="cos-endpoint", help="Cloud object storage endpoint", required=True + ) + parser.add_argument( + "-b", "--cos-bucket", dest="cos-bucket", help="Cloud object storage bucket to use", required=True + ) + parser.add_argument( + "-d", + "--cos-directory", + dest="cos-directory", + help="Working directory in cloud object storage bucket to use", + required=True, + ) + parser.add_argument( + "-t", + "--cos-dependencies-archive", + dest="cos-dependencies-archive", + help="Archive containing notebook and dependency artifacts", + required=True, + ) + parser.add_argument("-f", "--file", dest="filepath", help="File to execute", required=True) + parser.add_argument("-o", "--outputs", dest="outputs", help="Files to output to object store", required=False) + parser.add_argument("-i", "--inputs", dest="inputs", help="Files to pull in from parent node", required=False) + parser.add_argument( + "-p", + "--user-volume-path", + dest="user-volume-path", + help="Directory in Volume to install python libraries into", + required=False, + ) + parser.add_argument( + "-n", + "--pipeline-name", + dest="pipeline-name", + help="Pipeline name", + required=True, + ) + parser.add_argument( + "-r", + "--pipeline-parameters", + dest="pipeline_parameters", + help="Pipeline parameters that apply to this node", + required=False, + ) + parser.add_argument( + "-m", + "--parameter-pass-method", + dest="parameter_pass_method", + choices=["env"], + help="The method by which pipeline parameters should be applied to this node.", + required=False, + ) + parsed_args = vars(parser.parse_args(args)) + + # set pipeline name as global + pipeline_name = parsed_args.get("pipeline-name") + # operation/node name is the basename of the non-suffixed filepath, set as global + operation_name = os.path.basename(os.path.splitext(parsed_args.get("filepath"))[0]) + + return parsed_args + + @classmethod + def log_operation_info(cls, action_clause: str, duration_secs: Optional[float] = None) -> None: + """Produces a formatted log INFO message used entirely for support purposes. + + This method is intended to be called for any entries that should be captured across aggregated + log files to identify steps within a given pipeline and each of its operations. As a result, + calls to this method should produce single-line entries in the log (no embedded newlines). + Each entry is prefixed with the pipeline name. + + General logging should NOT use this method but use logger.() statements directly. + + :param action_clause: str representing the action that is being logged + :param duration_secs: optional float value representing the duration of the action being logged + """ + global pipeline_name, operation_name + if enable_pipeline_info: + duration_clause = f"({duration_secs:.3f} secs)" if duration_secs else "" + logger.info(f"'{pipeline_name}':'{operation_name}' - {action_clause} {duration_clause}") + + +def main(): + # Configure logger format, level + logging.basicConfig( + format="[%(levelname)1.1s %(asctime)s.%(msecs).03d] %(message)s", datefmt="%H:%M:%S", level=logging.DEBUG + ) + # Setup packages and gather arguments + input_params = OpUtil.parse_arguments(sys.argv[1:]) + OpUtil.log_operation_info("starting operation") + t0 = time.time() + OpUtil.package_install(user_volume_path=input_params.get("user-volume-path")) + + # Create the appropriate instance, process dependencies and execute the operation + file_op = FileOpBase.get_instance(**input_params) + + file_op.process_dependencies() + + file_op.execute() + + # Process notebook | script metrics and KFP UI metadata + file_op.process_metrics_and_metadata() + + duration = time.time() - t0 + OpUtil.log_operation_info("operation completed", duration) + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/runtimes/rocm-pytorch/ubi9-python-3.9/utils/pip.conf b/runtimes/rocm-pytorch/ubi9-python-3.9/utils/pip.conf new file mode 100644 index 000000000..69a2baf4c --- /dev/null +++ b/runtimes/rocm-pytorch/ubi9-python-3.9/utils/pip.conf @@ -0,0 +1,4 @@ +# Copied from: https://github.com/elyra-ai/elyra/blob/main/etc/kfp/pip.conf + +[global] +target=/opt/app-root/src/jupyter-work-dir/python3/ diff --git a/runtimes/rocm-pytorch/ubi9-python-3.9/utils/requirements-elyra.txt b/runtimes/rocm-pytorch/ubi9-python-3.9/utils/requirements-elyra.txt new file mode 100644 index 000000000..ddf75d0c5 --- /dev/null +++ b/runtimes/rocm-pytorch/ubi9-python-3.9/utils/requirements-elyra.txt @@ -0,0 +1,71 @@ +# Copied from: https://github.com/elyra-ai/elyra/blob/main/etc/generic/requirements-elyra.txt + +# This is a comprehensive list of python dependencies that Elyra requires to execute Jupyter notebooks. +ipykernel==6.13.0 +ipython==8.10.0 +ipython-genutils==0.2.0 +jinja2==3.1.4 +jupyter-client==7.3.1 +jupyter-core==4.11.2 +MarkupSafe==2.1.1 +minio==7.1.15 +nbclient==0.6.3 +nbconvert==7.1.0 +nbformat==5.4.0 +papermill==2.3.4 +pyzmq==24.0.1 +prompt-toolkit==3.0.30 +requests==2.31.0 +tornado==6.3.3 +traitlets==5.1.1 +urllib3==1.26.9 +# +# These excluded are transitive dependencies of the included python packages. +#ansiwrap==0.8.4 +#appnope==0.1.3 +#asttokens==2.0.5 +#attrs==21.4.0 +#backcall==0.2.0 +#beautifulsoup4==4.11.1 +#bleach==5.0.0 +#certifi==2021.10.8 +#charset-normalizer==2.0.12 +#click==8.1.3 +#debugpy==1.6.0 +#decorator==5.1.1 +#defusedxml==0.7.1 +#entrypoints==0.4 +#executing==0.8.3 +#fastjsonschema==2.15.3 +#idna==3.3 +#importlib-resources==5.7.1 +#jedi==0.18.1 +#jsonschema==4.5.1 +#jupyterlab-pygments==0.2.2 +#matplotlib-inline==0.1.3 +#mistune==0.8.4 +#nest-asyncio==1.5.5 +#packaging==21.3 +#pandocfilters==1.5.0 +#parso==0.8.3 +#pexpect==4.8.0 +#pickleshare==0.7.5 +#psutil==5.9.0 +#ptyprocess==0.7.0 +#pure-eval==0.2.2 +#Pygments==2.12.0 +#pyparsing==3.0.9 +#pyrsistent==0.18.1 +#python-dateutil==2.8.2 +#PyYAML==6.0 +#six==1.16.0 +#soupsieve==2.3.2.post1 +#stack-data==0.2.0 +#tenacity==8.0.1 +#textwrap3==0.9.2 +#tinycss2==1.1.1 +#tqdm==4.64.0 +#wcwidth==0.2.5 +#webencodings==0.5.1 +#zipp==3.8.0 +# diff --git a/runtimes/rocm-tensorflow/ubi9-python-3.9/Dockerfile b/runtimes/rocm-tensorflow/ubi9-python-3.9/Dockerfile new file mode 100644 index 000000000..4e0b753d0 --- /dev/null +++ b/runtimes/rocm-tensorflow/ubi9-python-3.9/Dockerfile @@ -0,0 +1,28 @@ +ARG BASE_IMAGE +FROM ${BASE_IMAGE} + +LABEL name="odh-notebook-rocm-runtime-tensorflow-ubi9-python-3.9" \ + summary="Runtime ROCm tensorflow notebook image for ODH notebooks" \ + description="Runtime ROCm tensorflow notebook image with base Python 3.9 builder image based on UBI9 for ODH notebooks" \ + io.k8s.display-name="Runtime ROCm tensorflow notebook image for ODH notebooks" \ + io.k8s.description="Runtime ROCm tensorflow notebook image with base Python 3.9 builder image based on UBI9 for ODH notebooks" \ + authoritative-source-url="https://github.com/opendatahub-io/notebooks" \ + io.openshift.build.commit.ref="main" \ + io.openshift.build.source-location="https://github.com/opendatahub-io/notebooks/tree/main/runtimes/rocm-tensorflow/ubi9-python-3.9" \ + io.openshift.build.image="quay.io/opendatahub/workbench-images:rocm-runtime-tensorflow-ubi9-python-3.9" + +WORKDIR /opt/app-root/bin + +# Install Python packages from Pipfile.lock +COPY Pipfile.lock ./ +# Copy Elyra dependencies for air-gapped enviroment +COPY utils ./utils/ + +RUN echo "Installing softwares and packages" && \ + micropipenv install && \ + rm -f ./Pipfile.lock && \ + # Fix permissions to support pip in Openshift environments \ + chmod -R g+w /opt/app-root/lib/python3.9/site-packages && \ + fix-permissions /opt/app-root -P + +WORKDIR /opt/app-root/src diff --git a/runtimes/rocm-tensorflow/ubi9-python-3.9/Pipfile b/runtimes/rocm-tensorflow/ubi9-python-3.9/Pipfile new file mode 100644 index 000000000..38f393b0f --- /dev/null +++ b/runtimes/rocm-tensorflow/ubi9-python-3.9/Pipfile @@ -0,0 +1,54 @@ +[[source]] +url = "https://pypi.org/simple" +verify_ssl = true +name = "pypi" + +[dev-packages] + +[packages] +tensorflow_rocm = {file = "https://repo.radeon.com/rocm/manylinux/rocm-rel-6.1/tensorflow_rocm-2.15.0-cp39-cp39-manylinux2014_x86_64.whl"} +tensorboard = "~=2.15.2" +tf2onnx = "~= 1.16.1" + +# Datascience and useful extensions +boto3 = "~=1.34.50" +kafka-python = "~=2.0.2" +matplotlib = "~=3.8.3" +numpy = "~=1.26.4" +pandas = "~=2.2.0" +plotly = "~=5.20.0" +scikit-learn = "~=1.4.0" +scipy = "~=1.12.0" +skl2onnx = "~=1.16.0" +onnxconverter-common = "~=1.13.0" # Required for skl2onnx, as upgraded version is not compatible with protobuf +codeflare-sdk = "~=0.16.4" +memray = "~=1.10.0" # any version above this would cause issue with rich package + +# DB connectors +pymongo = "~=4.6.2" +psycopg = "~=3.1.18" +pyodbc = "~=5.1.0" +mysql-connector-python = "~=8.3.0" + +# This is a comprehensive list of python dependencies that Elyra requires to execute Jupyter notebooks. +ipykernel = "==6.13.0" +ipython = "==8.10.0" +ipython-genutils = "==0.2.0" +jinja2 = "==3.1.4" +jupyter-client = "==7.3.1" +jupyter-core = "==4.11.2" +MarkupSafe = "==2.1.1" +minio = "==7.1.15" +nbclient = "==0.6.3" +nbconvert = "==7.1.0" +nbformat = "==5.4.0" +papermill = "==2.3.4" +pyzmq = "==24.0.1" +prompt-toolkit = "==3.0.30" 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b/runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/kustomization.yaml @@ -0,0 +1,14 @@ +--- +apiVersion: kustomize.config.k8s.io/v1beta1 +kind: Kustomization +namePrefix: runtime- +resources: + - pod.yaml +images: + - name: runtime-workbench + newName: quay.io/opendatahub/workbench-images + newTag: runtime-rocm-tensorflow-ubi9-python-3.9 +configMapGenerator: + - name: req-config + files: + - requirements-elyra.txt diff --git a/runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/pod.yaml b/runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/pod.yaml new file mode 100644 index 000000000..bc5343566 --- /dev/null +++ b/runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/pod.yaml @@ -0,0 +1,29 @@ +--- +apiVersion: v1 +kind: Pod +metadata: + name: pod + labels: + app: runtime-image +spec: + containers: + - name: runtime + image: runtime-workbench + command: ["/bin/sh", "-c", "while true ; do date; sleep 1; done;"] + imagePullPolicy: Always + ports: + - containerPort: 8080 + resources: + limits: + cpu: 500m + memory: 500Mi + requests: + cpu: 500m + memory: 500Mi + volumeMounts: + - name: config + mountPath: /opt/app-root/elyra + volumes: + - name: config + configMap: + name: req-config diff --git a/runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/requirements-elyra.txt b/runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/requirements-elyra.txt new file mode 100644 index 000000000..91fb8e57d --- /dev/null +++ b/runtimes/rocm-tensorflow/ubi9-python-3.9/kustomize/base/requirements-elyra.txt @@ -0,0 +1,20 @@ +# This is a comprehensive list of python dependencies that Elyra requires to execute Jupyter notebooks. +# This is copied from elyra directly: https://github.com/elyra-ai/elyra/blob/main/etc/generic/requirements-elyra.txt +ipykernel==6.13.0 +ipython==8.10.0 +ipython-genutils==0.2.0 +jinja2==3.1.4 +jupyter-client==7.3.1 +jupyter-core==4.11.2 +MarkupSafe==2.1.1 +minio==7.1.15 +nbclient==0.6.3 +nbconvert==7.1.0 +nbformat==5.4.0 +papermill==2.3.4 +pyzmq==24.0.1 +prompt-toolkit==3.0.30 +requests==2.31.0 +tornado==6.3.3 +traitlets==5.1.1 +urllib3==1.26.18 diff --git a/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/bootstrapper.py b/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/bootstrapper.py new file mode 100644 index 000000000..6163cdd84 --- /dev/null +++ b/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/bootstrapper.py @@ -0,0 +1,770 @@ +# Copied from: https://github.com/elyra-ai/elyra/blob/main/elyra/kfp/bootstrapper.py +# +# Copyright 2018-2023 Elyra Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# +from abc import ABC +from abc import abstractmethod +import glob +import json +import logging +import os +from pathlib import Path +import subprocess +import sys +from tempfile import TemporaryFile +import time +from typing import Any +from typing import Dict +from typing import Optional +from typing import Type +from typing import TypeVar +from urllib.parse import urljoin +from urllib.parse import urlparse +from urllib.parse import urlunparse + +from packaging import version + + +# Inputs and Outputs separator character. If updated, +# same-named variable in _notebook_op.py must be updated! +INOUT_SEPARATOR = ";" + +# Setup forward reference for type hint on return from class factory method. See +# https://stackoverflow.com/questions/39205527/can-you-annotate-return-type-when-value-is-instance-of-cls/39205612#39205612 +F = TypeVar("F", bound="FileOpBase") + +logger = logging.getLogger("elyra") +enable_pipeline_info = os.getenv("ELYRA_ENABLE_PIPELINE_INFO", "true").lower() == "true" +pipeline_name = None # global used in formatted logging +operation_name = None # global used in formatted logging + + +class FileOpBase(ABC): + """Abstract base class for file-based operations""" + + filepath = None + cos_client = None + cos_bucket = None + + @classmethod + def get_instance(cls: Type[F], **kwargs: Any) -> F: + """Creates an appropriate subclass instance based on the extension of the filepath (-f) argument""" + filepath = kwargs["filepath"] + if ".ipynb" in filepath: + return NotebookFileOp(**kwargs) + elif ".py" in filepath: + return PythonFileOp(**kwargs) + elif ".r" in filepath: + return RFileOp(**kwargs) + else: + raise ValueError(f"Unsupported file type: {filepath}") + + def __init__(self, **kwargs: Any) -> None: + """Initializes the FileOpBase instance""" + import minio + from minio.credentials import providers + + self.filepath = kwargs["filepath"] + self.input_params = kwargs or {} + self.cos_endpoint = urlparse(self.input_params.get("cos-endpoint")) + self.cos_bucket = self.input_params.get("cos-bucket") + + self.parameter_pass_method = self.input_params.get("parameter_pass_method") + self.pipeline_param_dict = self.convert_param_str_to_dict(self.input_params.get("pipeline_parameters")) + + # Infer secure from the endpoint's scheme. + self.secure = self.cos_endpoint.scheme == "https" + + # get minio credentials provider + if "cos-user" in self.input_params and "cos-password" in self.input_params: + cred_provider = providers.StaticProvider( + access_key=self.input_params.get("cos-user"), + secret_key=self.input_params.get("cos-password"), + ) + elif "AWS_ACCESS_KEY_ID" in os.environ and "AWS_SECRET_ACCESS_KEY" in os.environ: + cred_provider = providers.EnvAWSProvider() + elif "AWS_ROLE_ARN" in os.environ and "AWS_WEB_IDENTITY_TOKEN_FILE" in os.environ: + cred_provider = providers.IamAwsProvider() + else: + raise RuntimeError( + "No minio credentials provider can be initialised for current configs. " + "Please validate your runtime configuration details and retry." + ) + + # get minio client + self.cos_client = minio.Minio(self.cos_endpoint.netloc, secure=self.secure, credentials=cred_provider) + + @abstractmethod + def execute(self) -> None: + """Execute the operation relative to derived class""" + raise NotImplementedError("Method 'execute()' must be implemented by subclasses!") + + def process_dependencies(self) -> None: + """Process dependencies + + If a dependency archive is present, it will be downloaded from object storage + and expanded into the local directory. + + This method can be overridden by subclasses, although overrides should first + call the superclass method. + """ + OpUtil.log_operation_info("processing dependencies") + t0 = time.time() + archive_file = self.input_params.get("cos-dependencies-archive") + + self.get_file_from_object_storage(archive_file) + + inputs = self.input_params.get("inputs") + if inputs: + input_list = inputs.split(INOUT_SEPARATOR) + for file in input_list: + self.get_file_from_object_storage(file.strip()) + + subprocess.call(["tar", "-zxvf", archive_file]) + duration = time.time() - t0 + OpUtil.log_operation_info("dependencies processed", duration) + + def process_outputs(self) -> None: + """Process outputs + + If outputs have been specified, it will upload the appropriate files to object storage + + This method can be overridden by subclasses, although overrides should first + call the superclass method. + """ + OpUtil.log_operation_info("processing outputs") + t0 = time.time() + outputs = self.input_params.get("outputs") + if outputs: + output_list = outputs.split(INOUT_SEPARATOR) + for file in output_list: + self.process_output_file(file.strip()) + duration = time.time() - t0 + OpUtil.log_operation_info("outputs processed", duration) + + def process_metrics_and_metadata(self) -> None: + """Process metrics and metadata + + This method exposes metrics/metadata that the processed + notebook | script produces in the KFP UI. + + This method should not be overridden by subclasses. + """ + + OpUtil.log_operation_info("processing metrics and metadata") + t0 = time.time() + + # Location where the KFP specific output files will be stored + # in the environment where the bootsrapper is running. + # Defaults to '/tmp' if not specified. + output_path = Path(os.getenv("ELYRA_WRITABLE_CONTAINER_DIR", "/tmp")) + + # verify that output_path exists, is a directory + # and writable by creating a temporary file in that location + try: + with TemporaryFile(mode="w", dir=output_path) as t: + t.write("can write") + except Exception: + # output_path doesn't meet the requirements + # treat this as a non-fatal error and log a warning + logger.warning(f'Cannot create files in "{output_path}".') + OpUtil.log_operation_info("Aborted metrics and metadata processing", time.time() - t0) + return + + # Name of the proprietary KFP UI metadata file. + # Notebooks | scripts might (but don't have to) produce this file + # as documented in + # https://www.kubeflow.org/docs/pipelines/sdk/output-viewer/ + # Each ExecuteFileOp must declare this as an output file or + # the KFP UI won't pick up the information. + kfp_ui_metadata_filename = "mlpipeline-ui-metadata.json" + + # Name of the proprietary KFP metadata file. + # Notebooks | scripts might (but don't have to) produce this file + # as documented in + # https://www.kubeflow.org/docs/pipelines/sdk/pipelines-metrics/ + # Each ExecuteFileOp must declare this as an output file or + # the KFP UI won't pick up the information. + kfp_metrics_filename = "mlpipeline-metrics.json" + + # If the notebook | Python script produced one of the files + # copy it to the target location where KFP is looking for it. + for filename in [kfp_ui_metadata_filename, kfp_metrics_filename]: + try: + src = Path(".") / filename + logger.debug(f"Processing {src} ...") + # try to load the file, if one was created by the + # notebook or script + with open(src, "r") as f: + metadata = json.load(f) + + # the file exists and contains valid JSON + logger.debug(f"File content: {json.dumps(metadata)}") + + target = output_path / filename + # try to save the file in the destination location + with open(target, "w") as f: + json.dump(metadata, f) + except FileNotFoundError: + # The script | notebook didn't produce the file + # we are looking for. This is not an error condition + # that needs to be handled. + logger.debug(f"{self.filepath} produced no file named {src}") + except ValueError as ve: + # The file content could not be parsed. Log a warning + # and treat this as a non-fatal error. + logger.warning(f"Ignoring incompatible {str(src)} produced by {self.filepath}: {ve} {str(ve)}") + except Exception as ex: + # Something is wrong with the user-generated metadata file. + # Log a warning and treat this as a non-fatal error. + logger.warning(f"Error processing {str(src)} produced by {self.filepath}: {ex} {str(ex)}") + + # + # Augment kfp_ui_metadata_filename with Elyra-specific information: + # - link to object storage where input and output artifacts are + # stored + ui_metadata_output = output_path / kfp_ui_metadata_filename + try: + # re-load the file + with open(ui_metadata_output, "r") as f: + metadata = json.load(f) + except Exception: + # ignore all errors + metadata = {} + + # Assure the 'output' property exists and is of the correct type + if metadata.get("outputs", None) is None or not isinstance(metadata["outputs"], list): + metadata["outputs"] = [] + + # Define HREF for COS bucket: + # // + bucket_url = urljoin( + urlunparse(self.cos_endpoint), f"{self.cos_bucket}/{self.input_params.get('cos-directory', '')}/" + ) + + # add Elyra metadata to 'outputs' + metadata["outputs"].append( + { + "storage": "inline", + "source": f"## Inputs for {self.filepath}\n" + f"[{self.input_params['cos-dependencies-archive']}]({bucket_url})", + "type": "markdown", + } + ) + + # print the content of the augmented metadata file + logger.debug(f"Output UI metadata: {json.dumps(metadata)}") + + logger.debug(f"Saving UI metadata file as {ui_metadata_output} ...") + + # Save [updated] KFP UI metadata file + with open(ui_metadata_output, "w") as f: + json.dump(metadata, f) + + duration = time.time() - t0 + OpUtil.log_operation_info("metrics and metadata processed", duration) + + def get_object_storage_filename(self, filename: str) -> str: + """Function to pre-pend cloud storage working dir to file name + + :param filename: the local file + :return: the full path of the object storage file + """ + return os.path.join(self.input_params.get("cos-directory", ""), filename) + + def get_file_from_object_storage(self, file_to_get: str) -> None: + """Utility function to get files from an object storage + + :param file_to_get: filename + """ + + object_to_get = self.get_object_storage_filename(file_to_get) + t0 = time.time() + self.cos_client.fget_object(bucket_name=self.cos_bucket, object_name=object_to_get, file_path=file_to_get) + duration = time.time() - t0 + OpUtil.log_operation_info( + f"downloaded {file_to_get} from bucket: {self.cos_bucket}, object: {object_to_get}", duration + ) + + def put_file_to_object_storage(self, file_to_upload: str, object_name: Optional[str] = None) -> None: + """Utility function to put files into an object storage + + :param file_to_upload: filename + :param object_name: remote filename (used to rename) + """ + + object_to_upload = object_name + if not object_to_upload: + object_to_upload = file_to_upload + + object_to_upload = self.get_object_storage_filename(object_to_upload) + t0 = time.time() + self.cos_client.fput_object(bucket_name=self.cos_bucket, object_name=object_to_upload, file_path=file_to_upload) + duration = time.time() - t0 + OpUtil.log_operation_info( + f"uploaded {file_to_upload} to bucket: {self.cos_bucket} object: {object_to_upload}", duration + ) + + def has_wildcard(self, filename): + wildcards = ["*", "?"] + return bool(any(c in filename for c in wildcards)) + + def process_output_file(self, output_file): + """Puts the file to object storage. Handles wildcards and directories.""" + + matched_files = [output_file] + if self.has_wildcard(output_file): # explode the wildcarded file + matched_files = glob.glob(output_file) + + for matched_file in matched_files: + if os.path.isdir(matched_file): + for file in os.listdir(matched_file): + self.process_output_file(os.path.join(matched_file, file)) + else: + self.put_file_to_object_storage(matched_file) + + def convert_param_str_to_dict(self, pipeline_parameters: Optional[str] = None) -> Dict[str, Any]: + """Convert INOUT-separated string of pipeline parameters into a dictionary.""" + parameter_dict = {} + if pipeline_parameters: + parameter_list = pipeline_parameters.split(INOUT_SEPARATOR) + for parameter in parameter_list: + param_name, value = parameter.split("=", 1) + if self.parameter_pass_method == "env" and (not value or not isinstance(value, str)): + continue # env vars must be non-empty strings + parameter_dict[param_name] = value + return parameter_dict + + def set_parameters_in_env(self) -> None: + """Make pipeline parameters available as environment variables.""" + for name, value in self.pipeline_param_dict.items(): + if name in os.environ: + continue # avoid overwriting env vars with the same name + os.environ[name] = value + + +class NotebookFileOp(FileOpBase): + """Perform Notebook File Operation""" + + def execute(self) -> None: + """Execute the Notebook and upload results to object storage""" + notebook = os.path.basename(self.filepath) + notebook_name = notebook.replace(".ipynb", "") + notebook_output = f"{notebook_name}-output.ipynb" + notebook_html = f"{notebook_name}.html" + + try: + OpUtil.log_operation_info(f"executing notebook using 'papermill {notebook} {notebook_output}'") + t0 = time.time() + # Include kernel selection in execution time + kernel_name = NotebookFileOp.find_best_kernel(notebook) + + kwargs = {} + if self.parameter_pass_method == "env": + self.set_parameters_in_env() + + import papermill + + papermill.execute_notebook(notebook, notebook_output, kernel_name=kernel_name, **kwargs) + duration = time.time() - t0 + OpUtil.log_operation_info("notebook execution completed", duration) + + NotebookFileOp.convert_notebook_to_html(notebook_output, notebook_html) + self.put_file_to_object_storage(notebook_output, notebook) + self.put_file_to_object_storage(notebook_html) + self.process_outputs() + except Exception as ex: + # log in case of errors + logger.error(f"Unexpected error: {sys.exc_info()[0]}") + + NotebookFileOp.convert_notebook_to_html(notebook_output, notebook_html) + self.put_file_to_object_storage(notebook_output, notebook) + self.put_file_to_object_storage(notebook_html) + raise ex + + @staticmethod + def convert_notebook_to_html(notebook_file: str, html_file: str) -> str: + """Function to convert a Jupyter notebook file (.ipynb) into an html file + + :param notebook_file: object storage client + :param html_file: name of what the html output file should be + :return: html_file: the converted notebook in html format + """ + import nbconvert + import nbformat + + OpUtil.log_operation_info(f"converting from {notebook_file} to {html_file}") + t0 = time.time() + nb = nbformat.read(notebook_file, as_version=4) + html_exporter = nbconvert.HTMLExporter() + data, resources = html_exporter.from_notebook_node(nb) + with open(html_file, "w") as f: + f.write(data) + f.close() + + duration = time.time() - t0 + OpUtil.log_operation_info(f"{notebook_file} converted to {html_file}", duration) + return html_file + + @staticmethod + def find_best_kernel(notebook_file: str) -> str: + """Determines the best kernel to use via the following algorithm: + + 1. Loads notebook and gets kernel_name and kernel_language from NB metadata. + 2. Gets the list of configured kernels using KernelSpecManager. + 3. If notebook kernel_name is in list, use that, else + 4. If not found, load each configured kernel.json file and find a language match. + 5. On first match, log info message regarding the switch and use that kernel. + 6. If no language match is found, revert to notebook kernel and log warning message. + """ + from jupyter_client.kernelspec import KernelSpecManager + import nbformat + + nb = nbformat.read(notebook_file, 4) + + nb_kspec = nb.metadata.kernelspec + nb_kernel_name = nb_kspec.get("name") + nb_kernel_lang = nb_kspec.get("language") + + kernel_specs = KernelSpecManager().find_kernel_specs() + + # see if we have a direct match... + if nb_kernel_name in kernel_specs.keys(): + return nb_kernel_name + + # no match found for kernel, try matching language... + for name, file in kernel_specs.items(): + # load file (JSON) and pick out language, if match, use first found + with open(os.path.join(file, "kernel.json")) as f: + kspec = json.load(f) + if kspec.get("language").lower() == nb_kernel_lang.lower(): + matched_kernel = os.path.basename(file) + logger.info( + f"Matched kernel by language ({nb_kernel_lang}), using kernel " + f"'{matched_kernel}' instead of the missing kernel '{nb_kernel_name}'." + ) + return matched_kernel + + # no match found for language, return notebook kernel and let execution fail + logger.warning( + f"Reverting back to missing notebook kernel '{nb_kernel_name}' since no " + f"language match ({nb_kernel_lang}) was found in current kernel specifications." + ) + return nb_kernel_name + + +class PythonFileOp(FileOpBase): + """Perform Python File Operation""" + + def execute(self) -> None: + """Execute the Python script and upload results to object storage""" + python_script = os.path.basename(self.filepath) + python_script_name = python_script.replace(".py", "") + # python_script_output = f"{python_script_name}.log" + + try: + OpUtil.log_operation_info( + f"executing python script using 'python3 {python_script}'" + ) + t0 = time.time() + + run_args = ["python3", python_script] + if self.parameter_pass_method == "env": + self.set_parameters_in_env() + + logger.info("----------------------Python logs start----------------------") + # Removing support for the s3 storage of python script logs + # with open(python_script_output, "w") as log_file: + # process = subprocess.Popen(run_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + process = subprocess.Popen(run_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + + for line in iter(process.stdout.readline, b''): + sys.stdout.write(line.decode()) + + process.stdout.close() + return_code = process.wait() + logger.info("----------------------Python logs ends----------------------") + if return_code: + raise subprocess.CalledProcessError(return_code, run_args) + duration = time.time() - t0 + OpUtil.log_operation_info("python script execution completed", duration) + + # self.put_file_to_object_storage(python_script_output, python_script_output) + self.process_outputs() + except Exception as ex: + # log in case of errors + logger.error(f"Unexpected error: {sys.exc_info()[0]}") + logger.error(f"Error details: {ex}") + + # self.put_file_to_object_storage(python_script_output, python_script_output) + raise ex + + +class RFileOp(FileOpBase): + """Perform R File Operation""" + + def execute(self) -> None: + """Execute the R script and upload results to object storage""" + r_script = os.path.basename(self.filepath) + r_script_name = r_script.replace(".r", "") + # r_script_output = f"{r_script_name}.log" + + try: + OpUtil.log_operation_info(f"executing R script using 'Rscript {r_script}'") + t0 = time.time() + + run_args = ["Rscript", r_script] + if self.parameter_pass_method == "env": + self.set_parameters_in_env() + + logger.info("----------------------R script logs start----------------------") + # Removing support for the s3 storage of R script logs + # with open(r_script_output, "w") as log_file: + # process = subprocess.Popen(run_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + process = subprocess.Popen(run_args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + + for line in iter(process.stdout.readline, b''): + sys.stdout.write(line.decode()) + + process.stdout.close() + return_code = process.wait() + logger.info("----------------------R script logs ends----------------------") + if return_code: + raise subprocess.CalledProcessError(return_code, run_args) + + duration = time.time() - t0 + OpUtil.log_operation_info("R script execution completed", duration) + + # self.put_file_to_object_storage(r_script_output, r_script_output) + self.process_outputs() + except Exception as ex: + # log in case of errors + logger.error(f"Unexpected error: {sys.exc_info()[0]}") + logger.error(f"Error details: {ex}") + + # self.put_file_to_object_storage(r_script_output, r_script_output) + raise ex + + +class OpUtil(object): + """Utility functions for preparing file execution.""" + + @classmethod + def package_install(cls, user_volume_path) -> None: + OpUtil.log_operation_info("Installing packages") + t0 = time.time() + requirements_file = cls.determine_elyra_requirements() + elyra_packages = cls.package_list_to_dict(requirements_file) + current_packages = cls.package_list_to_dict("requirements-current.txt") + to_install_list = [] + + for package, ver in elyra_packages.items(): + if package in current_packages: + if current_packages[package] is None: + logger.warning( + f"WARNING: Source package '{package}' found already installed as an " + "editable package. This may conflict with the required version: " + f"{ver} . Skipping..." + ) + continue + try: + version.Version(current_packages[package]) + except version.InvalidVersion: # current version is not PEP-440 compliant + logger.warning( + f"WARNING: Source package '{package}' found already installed from " + f"{current_packages[package]}. This may conflict with the required " + f"version: {ver} . Skipping..." + ) + continue + if version.Version(ver) > version.Version(current_packages[package]): + logger.info(f"Updating {package} package from version {current_packages[package]} to {ver}...") + to_install_list.append(f"{package}=={ver}") + elif version.Version(ver) < version.Version(current_packages[package]): + logger.info( + f"Newer {package} package with version {current_packages[package]} " + f"already installed. Skipping..." + ) + else: + logger.info(f"Package not found. Installing {package} package with version {ver}...") + to_install_list.append(f"{package}=={ver}") + + if to_install_list: + if user_volume_path: + to_install_list.insert(0, f"--target={user_volume_path}") + to_install_list.append("--no-cache-dir") + + subprocess.run([sys.executable, "-m", "pip", "install"] + to_install_list, check=True) + + if user_volume_path: + os.environ["PIP_CONFIG_FILE"] = f"{user_volume_path}/pip.conf" + + subprocess.run([sys.executable, "-m", "pip", "freeze"]) + duration = time.time() - t0 + OpUtil.log_operation_info("Packages installed", duration) + + @classmethod + def determine_elyra_requirements(cls) -> Any: + if sys.version_info.major == 3: + if sys.version_info.minor in [8, 9, 10, 11]: + return "requirements-elyra.txt" + logger.error( + f"This version of Python '{sys.version_info.major}.{sys.version_info.minor}' " + f"is not supported for Elyra generic components" + ) + return None + + @classmethod + def package_list_to_dict(cls, filename: str) -> dict: + package_dict = {} + with open(filename) as fh: + for line in fh: + if line[0] != "#": + if " @ " in line: + package_name, package_version = line.strip("\n").split(sep=" @ ") + elif "===" in line: + package_name, package_version = line.strip("\n").split(sep="===") + elif "==" in line: + package_name, package_version = line.strip("\n").split(sep="==") + elif line.startswith("-e ") or line.startswith("--editable "): + package_name = line.strip("\n").replace("-e ", "").replace("--editable ", "") + if "#egg=" in package_name: # editable package from version control system + package_name = package_name.split("=")[-1] + elif "/" in package_name: # editable package from local directory + package_name = os.path.basename(package_name) + package_version = None + else: + # Tolerate other formats but do not add to package list + continue + + package_dict[package_name] = package_version + + return package_dict + + @classmethod + def parse_arguments(cls, args) -> dict: + import argparse + + global pipeline_name, operation_name + + logger.debug("Parsing Arguments.....") + parser = argparse.ArgumentParser() + parser.add_argument( + "-e", "--cos-endpoint", dest="cos-endpoint", help="Cloud object storage endpoint", required=True + ) + parser.add_argument( + "-b", "--cos-bucket", dest="cos-bucket", help="Cloud object storage bucket to use", required=True + ) + parser.add_argument( + "-d", + "--cos-directory", + dest="cos-directory", + help="Working directory in cloud object storage bucket to use", + required=True, + ) + parser.add_argument( + "-t", + "--cos-dependencies-archive", + dest="cos-dependencies-archive", + help="Archive containing notebook and dependency artifacts", + required=True, + ) + parser.add_argument("-f", "--file", dest="filepath", help="File to execute", required=True) + parser.add_argument("-o", "--outputs", dest="outputs", help="Files to output to object store", required=False) + parser.add_argument("-i", "--inputs", dest="inputs", help="Files to pull in from parent node", required=False) + parser.add_argument( + "-p", + "--user-volume-path", + dest="user-volume-path", + help="Directory in Volume to install python libraries into", + required=False, + ) + parser.add_argument( + "-n", + "--pipeline-name", + dest="pipeline-name", + help="Pipeline name", + required=True, + ) + parser.add_argument( + "-r", + "--pipeline-parameters", + dest="pipeline_parameters", + help="Pipeline parameters that apply to this node", + required=False, + ) + parser.add_argument( + "-m", + "--parameter-pass-method", + dest="parameter_pass_method", + choices=["env"], + help="The method by which pipeline parameters should be applied to this node.", + required=False, + ) + parsed_args = vars(parser.parse_args(args)) + + # set pipeline name as global + pipeline_name = parsed_args.get("pipeline-name") + # operation/node name is the basename of the non-suffixed filepath, set as global + operation_name = os.path.basename(os.path.splitext(parsed_args.get("filepath"))[0]) + + return parsed_args + + @classmethod + def log_operation_info(cls, action_clause: str, duration_secs: Optional[float] = None) -> None: + """Produces a formatted log INFO message used entirely for support purposes. + + This method is intended to be called for any entries that should be captured across aggregated + log files to identify steps within a given pipeline and each of its operations. As a result, + calls to this method should produce single-line entries in the log (no embedded newlines). + Each entry is prefixed with the pipeline name. + + General logging should NOT use this method but use logger.() statements directly. + + :param action_clause: str representing the action that is being logged + :param duration_secs: optional float value representing the duration of the action being logged + """ + global pipeline_name, operation_name + if enable_pipeline_info: + duration_clause = f"({duration_secs:.3f} secs)" if duration_secs else "" + logger.info(f"'{pipeline_name}':'{operation_name}' - {action_clause} {duration_clause}") + + +def main(): + # Configure logger format, level + logging.basicConfig( + format="[%(levelname)1.1s %(asctime)s.%(msecs).03d] %(message)s", datefmt="%H:%M:%S", level=logging.DEBUG + ) + # Setup packages and gather arguments + input_params = OpUtil.parse_arguments(sys.argv[1:]) + OpUtil.log_operation_info("starting operation") + t0 = time.time() + OpUtil.package_install(user_volume_path=input_params.get("user-volume-path")) + + # Create the appropriate instance, process dependencies and execute the operation + file_op = FileOpBase.get_instance(**input_params) + + file_op.process_dependencies() + + file_op.execute() + + # Process notebook | script metrics and KFP UI metadata + file_op.process_metrics_and_metadata() + + duration = time.time() - t0 + OpUtil.log_operation_info("operation completed", duration) + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/pip.conf b/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/pip.conf new file mode 100644 index 000000000..69a2baf4c --- /dev/null +++ b/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/pip.conf @@ -0,0 +1,4 @@ +# Copied from: https://github.com/elyra-ai/elyra/blob/main/etc/kfp/pip.conf + +[global] +target=/opt/app-root/src/jupyter-work-dir/python3/ diff --git a/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/requirements-elyra.txt b/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/requirements-elyra.txt new file mode 100644 index 000000000..ddf75d0c5 --- /dev/null +++ b/runtimes/rocm-tensorflow/ubi9-python-3.9/utils/requirements-elyra.txt @@ -0,0 +1,71 @@ +# Copied from: https://github.com/elyra-ai/elyra/blob/main/etc/generic/requirements-elyra.txt + +# This is a comprehensive list of python dependencies that Elyra requires to execute Jupyter notebooks. +ipykernel==6.13.0 +ipython==8.10.0 +ipython-genutils==0.2.0 +jinja2==3.1.4 +jupyter-client==7.3.1 +jupyter-core==4.11.2 +MarkupSafe==2.1.1 +minio==7.1.15 +nbclient==0.6.3 +nbconvert==7.1.0 +nbformat==5.4.0 +papermill==2.3.4 +pyzmq==24.0.1 +prompt-toolkit==3.0.30 +requests==2.31.0 +tornado==6.3.3 +traitlets==5.1.1 +urllib3==1.26.9 +# +# These excluded are transitive dependencies of the included python packages. +#ansiwrap==0.8.4 +#appnope==0.1.3 +#asttokens==2.0.5 +#attrs==21.4.0 +#backcall==0.2.0 +#beautifulsoup4==4.11.1 +#bleach==5.0.0 +#certifi==2021.10.8 +#charset-normalizer==2.0.12 +#click==8.1.3 +#debugpy==1.6.0 +#decorator==5.1.1 +#defusedxml==0.7.1 +#entrypoints==0.4 +#executing==0.8.3 +#fastjsonschema==2.15.3 +#idna==3.3 +#importlib-resources==5.7.1 +#jedi==0.18.1 +#jsonschema==4.5.1 +#jupyterlab-pygments==0.2.2 +#matplotlib-inline==0.1.3 +#mistune==0.8.4 +#nest-asyncio==1.5.5 +#packaging==21.3 +#pandocfilters==1.5.0 +#parso==0.8.3 +#pexpect==4.8.0 +#pickleshare==0.7.5 +#psutil==5.9.0 +#ptyprocess==0.7.0 +#pure-eval==0.2.2 +#Pygments==2.12.0 +#pyparsing==3.0.9 +#pyrsistent==0.18.1 +#python-dateutil==2.8.2 +#PyYAML==6.0 +#six==1.16.0 +#soupsieve==2.3.2.post1 +#stack-data==0.2.0 +#tenacity==8.0.1 +#textwrap3==0.9.2 +#tinycss2==1.1.1 +#tqdm==4.64.0 +#wcwidth==0.2.5 +#webencodings==0.5.1 +#zipp==3.8.0 +# From fb58f366bab287a2a11be44091209a5c99036ea0 Mon Sep 17 00:00:00 2001 From: Guilherme Caponetto <638737+caponetto@users.noreply.github.com> Date: Wed, 31 Jul 2024 06:38:43 -0300 Subject: [PATCH 6/6] Sanitize ref name before using it as container tag --- .github/workflows/build-notebooks-TEMPLATE.yaml | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/.github/workflows/build-notebooks-TEMPLATE.yaml b/.github/workflows/build-notebooks-TEMPLATE.yaml index 02ea17e05..67697d8eb 100644 --- a/.github/workflows/build-notebooks-TEMPLATE.yaml +++ b/.github/workflows/build-notebooks-TEMPLATE.yaml @@ -113,10 +113,12 @@ jobs: # https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows#push - name: "push|schedule: make ${{ inputs.target }}" - run: "make ${{ inputs.target }}" + run: | + SANITIZED_REF_NAME=$(echo "${{ github.ref_name }}" | sed 's/[^a-zA-Z0-9._-]/_/g') + export IMAGE_TAG="${SANITIZED_REF_NAME}_${{ github.sha }}" + make ${{ inputs.target }} if: ${{ fromJson(inputs.github).event_name == 'push' || fromJson(inputs.github).event_name == 'schedule' }} env: - IMAGE_TAG: "${{ github.ref_name }}_${{ github.sha }}" IMAGE_REGISTRY: "ghcr.io/${{ github.repository }}/workbench-images" CONTAINER_BUILD_CACHE_ARGS: "--cache-from ${{ env.CACHE }} --cache-to ${{ env.CACHE }}"