r0.3.3

.github/pull_request_template.md

@@ -15,6 +15,7 @@
 <!-- Explain how the changes have been tested, including the testing environment and any relevant test cases. -->
 
 - [ ] I have tested any changes in container groups locally with `/test-runner/test_runner.py` with all existing tests passing, and I have added new tests where necessary.
-- [ ] Automated Validation (Do not edit, check to begin Validation)
-
-command: /test-group group_dir: my-container-group, runner_label: test-runner
+
+### Automated Testing
+
+Leave a PR comment in the following format: `/test-group group_dir: <my-container-group>, runner_label: <my-runner-label>` to run automated tests.

.github/workflows/bandit.yaml

@@ -3,6 +3,8 @@ on:
   pull_request_review:
     types: [submitted]
 
+permissions: read-all
+
 jobs:
   scan-bandit:
     if: github.event.review.state == 'approved'

.github/workflows/container-pipeline-tester.yaml

@@ -1,4 +1,7 @@
 name: Container Pipeline Tester
+
+permissions: read-all
+
 on:
   workflow_dispatch:
     inputs:
@@ -89,7 +92,7 @@ jobs:
       - uses: actions/checkout@v4
       - name: Get Recipes
         id: recipes
-        run: echo "RECIPES=$(find ${{ inputs.group_dir }} -type f -name 'tests.yaml' -exec dirname {} \; | awk -F/ '{print $NF}' | jq -R -s -c 'split("\n")[:-1]')" >> $GITHUB_OUTPUT
+        run: echo "RECIPES=$(find ${{ inputs.group_dir }} -type f -name 'tests.yaml' -exec dirname {} \; | jq -R -s -c 'split("\n")[:-1]')" >> $GITHUB_OUTPUT
   test-containers:
     needs: [ setup-test ]
     if: ${{ needs.setup-test.outputs.recipes != '[]' }}
@@ -111,5 +114,5 @@ jobs:
         with:
           mlops_repo: ${{ vars.MLOPS_REPO }}
           registry: ${{ vars.REGISTRY }}
-          test_dir: ${{ inputs.group_dir }}/${{ matrix.recipe }}
+          test_dir: ${{ matrix.recipe }}
           token: ${{ github.token }}

.github/workflows/dockerfile-builder.yml

@@ -1,4 +1,7 @@
 name: Dockerfile Builder
+
+permissions: read-all
+
 on: 
   workflow_dispatch:
 

.github/workflows/review-trigger.yml

@@ -3,6 +3,22 @@ name: Review Pipeline Validation
 on:
   pull_request_review:
     types: [submitted, edited]
+
+permissions:
+  actions: read
+  checks: read
+  contents: read
+  deployments: read
+  discussions: read
+  id-token: write
+  issues: read
+  packages: read
+  pages: read
+  pull-requests: write
+  repository-projects: read
+  security-events: read
+  statuses: read
+
 jobs:
   check-review:
     runs-on: [ k8-runners ]

.github/workflows/unit-test.yaml

@@ -4,6 +4,8 @@ on:
     branches:
       - develop
 
+permissions: read-all
+
 jobs:
   unit-test:
     runs-on: [ test-runner ]

README.md

@@ -1,4 +1,5 @@
 # Intel® AI Containers
+[![OpenSSF Best Practices](https://www.bestpractices.dev/projects/8270/badge)](https://www.bestpractices.dev/projects/8270)
 
 This repository contains Dockerfiles, scripts, yaml files, Helm charts, etc. used to scale out AI containers with versions of TensorFlow and PyTorch that have been optimized for Intel platforms. Scaling is done with python, Docker, kubernetes, kubeflow, cnvrg.io, Helm, and other container orchestration frameworks for use in the cloud and on-premise.
 

preset/classical-ml/docker-compose.yaml

@@ -0,0 +1,57 @@
+# 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.
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# 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
+#
+# Copyright (c) 2023 Intel Corporation
+#
+# -*- coding: utf-8 -*-
+#
+
+version: '3'
+services:
+  classical-ml:
+    build:
+      args:
+        BASE_IMAGE: ${BASE_IMAGE:-ubuntu}
+        BASE_TAG: ${BASE_TAG:-22.04}
+        DAAL4PY_VERSION: ${DAAL4PY_VERSION:-2024.0.1}
+        DEVICE: ${DEVICE:-flex}
+        DPCPP_VER: ${DPCPP_VER:-2024.0.0-49819}
+        LEVEL_ZERO_DEV_VER: 1.14.0-744~22.04
+        LEVEL_ZERO_GPU_VER: 1.3.27191.42-775~22.04
+        LEVEL_ZERO_VER: 1.14.0-744~22.04
+        ICD_VER: 23.35.27191.42-775~22.04
+        IDP_VERSION: ${IDP_VERSION:-2024.0.0}
+        INTEL_CHANNEL: ${INTEL_CHANNEL:-intel}
+        MINICONDA_VERSION: ${MINICONDA_VERSION:-latest-Linux-x86_64}
+        MKL_VER: ${MKL_VER:-2024.0.0-49656}
+        MODIN_VERSION: ${MODIN_VERSION:-0.24.1}
+        PYTHON_VERSION: ${PYTHON_VERSION:-3.10}
+        SCIKIT_VERSION: ${SCIKIT_VERSION:-2024.0.1}
+        XGBOOST_VERSION: ${XGBOOST_VERSION:-1.7.3}
+        http_proxy: ${http_proxy}
+        https_proxy: ${https_proxy}
+        no_proxy: ''
+      context: .
+      target: classical-ml-jupyter
+    command: |
+      bash -c "conda run -n classical-ml python -c 'import sklearn; import xgboost; print(\"SciKit:\", sklearn.__version__, \" XGBoost:\",xgboost.__version__)' && \
+      conda run -n classical-ml python -c 'import modin.pandas as pd, modin.config as cfg; cfg.Engine.put(\"Ray\"); df = pd.DataFrame([1]);print(df+1)'"
+    image: ${REGISTRY}/aiops/mlops-ci:b-${GITHUB_RUN_NUMBER:-0}-classical-ml-${IDP_VERSION:-2024.0.0}-py${PYTHON_VERSION:-3.10}
+    devices:
+      - /dev/dri:/dev/dri
+    environment:
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+    network_mode: host
+    shm_size: 12GB
+    volumes:
+      - /dev/dri/by-path:/dev/dri/by-path

preset/data-analytics/.actions.json

@@ -0,0 +1,4 @@
+{
+    "PYTHON_VERSION": ["3.9", "3.10"],
+    "experimental": [true]
+}