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Merge remote-tracking branch 'origin/main' into sharvil10/gaudi-1.18-notebook
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+110
-87
lines changed

.github/scan/action.yml

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This file was deleted.

.github/workflows/container-ci.yaml

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# password: ${{ secrets.REGISTRY_TOKEN }}
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- name: Pull Image
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run: docker pull ${{ secrets.REGISTRY }}/${{ secrets.REPO }}:${{ matrix.container }}
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- uses: actions/cache@3624ceb22c1c5a301c8db4169662070a689d9ea8 # v4.1.1
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with:
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path: ${{ github.workspace }}/.cache/trivy
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key: ${{ github.head_ref || github.ref_name }}-trivy
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- name: Scan Container
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uses: intel/ai-containers/.github/scan@main
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uses: aquasecurity/trivy-action@915b19bbe73b92a6cf82a1bc12b087c9a19a5fe2 # v0.28.0
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with:
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cache: true
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format: sarif
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github-pat: ${{ secrets.GITHUB_TOKEN }}
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image-ref: ${{ secrets.REGISTRY }}/${{ secrets.REPO }}:${{ matrix.container }}
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output: ${{ matrix.container }}-scan.sarif
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timeout: 30m0s
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- name: Cleanup
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if: always()
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run: docker rmi -f ${{ secrets.REGISTRY }}/${{ secrets.REPO }}:${{ matrix.container }}

.github/workflows/integration-test.yaml

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with:
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pattern: test-runner-summary*
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merge-multiple: true
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- name: Check for JSON files
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- name: Find Summary
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id: summary
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shell: bash
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run: |
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if [[ -n "$(find . -maxdepth 1 -name 'test-runner-summary*.json' -print -quit)" ]]; then
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echo "has_matching_json_files=true" >> "$GITHUB_OUTPUT"
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echo "Files matching the pattern test-runner-summary*.json found in the directory"
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SUMMARY=$(find . -maxdepth 1 -name '*summary.json' -print)
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if [[ -n "$SUMMARY" ]]; then
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echo "summary=true" >> $GITHUB_OUTPUT
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echo "Files matching the pattern ./*summary.json"
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jq -s '[.[] | .[]]' ./*summary.json > combined.json
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echo "Files found in the directory"
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else
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echo "has_matching_json_files=false" >> "$GITHUB_OUTPUT"
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echo "No files matching the pattern test-runner-summary*.json found in the directory"
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echo "summary=false" >> $GITHUB_OUTPUT
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echo "No files matching the pattern ./*summary.json"
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fi
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id: check_matching_json_files
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- name: Combine JSON files
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if: ${{ steps.check_matching_json_files.outputs.has_matching_json_files == 'true' }}
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run: |
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jq -s '[.[] | .[]]' *.json > combined.json
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echo "Files found in the directory"
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- name: Generate TXT file
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if: ${{ steps.check_matching_json_files.outputs.has_matching_json_files == 'true' }}
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if: ${{ steps.summary.outputs.summary != 'false' }}
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run: |
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{
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echo "### Integration Test Results"
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fi
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} >> output.txt
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- name: PR-comment
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if: ${{ steps.check_matching_json_files.outputs.has_matching_json_files == 'true' }}
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if: ${{ steps.summary.outputs.summary != 'false' }}
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uses: marocchino/sticky-pull-request-comment@331f8f5b4215f0445d3c07b4967662a32a2d3e31 # v2.9.0
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with:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/test-runner-ci.yaml

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uses: step-security/harden-runner@91182cccc01eb5e619899d80e4e971d6181294a7 # v2.10.1
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with:
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egress-policy: audit
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- uses: coverallsapp/github-action@1134c89e4bf10443bf8f0ec69640b667cfd91041 # v2.3.1
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- uses: coverallsapp/github-action@4cdef0b2dbe0c9aa26bed48edb868db738625e79 # v2.3.3
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with:
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parallel-finished: true
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integration-test:

.gitignore

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models-perf/
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output/
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site
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test-runner-summary-output.json
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venv/

.pre-commit-config.yaml

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- hooks:
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- id: gitleaks
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repo: https://github.com/gitleaks/gitleaks
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rev: v8.20.1
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rev: v8.21.1
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- hooks:
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- args: [--license-filepath=.github/license_template.txt, --use-current-year, --detect-license-in-X-top-lines=40, --skip-license-insertion-comment=Copyright]
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files: |

classical-ml/jupyter-requirements.txt

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jupyterlab==4.2.5
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jupyterhub==5.2.0
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jupyterhub==5.2.1
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notebook==7.2.2
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jupyter-server-proxy>=4.1.2

docs/requirements.txt

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mkdocs-callouts>=1.13.2
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mkdocs-git-authors-plugin>=0.8.0
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mkdocs-git-revision-date-localized-plugin>=1.2.5
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mkdocs-material==9.5.40
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mkdocs-material==9.5.42
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mkdocs-table-reader-plugin>=2.1.0
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mkdocs==1.6.1
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pandas>=2.0.3

jax/README.md

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@@ -8,13 +8,13 @@ The images below include [JAX\*] and [Intel® Extension for OpenXLA\*].
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| Tag(s) | [JAX\*] | [Intel® Extension for OpenXLA\*] | [Flax] | Dockerfile |
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| -------------------------- | --------- | -------------------------------- | -------- | --------------- |
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| `0.4.0-pip-base`, `latest` | [v0.4.32] | [v0.4.0-jax] | [v0.9.0] | [v0.4.0] |
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| `0.4.0-pip-base`, `latest` | [v0.4.26] | [v0.4.0-jax] | [v0.8.2] | [v0.4.1] |
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The images below additionally include [Jupyter Notebook](https://jupyter.org/) server:
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| Tag(s) | [JAX\*] | [Intel® Extension for OpenXLA\*] | [Flax] | Dockerfile |
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| ------------------- | --------- | ----------------- | -------- | --------------- |
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| `0.4.0-pip-jupyter` | [v0.4.32] | [v0.4.0-jax] | [v0.9.0] | [v0.4.0] |
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| `0.4.0-pip-jupyter` | [v0.4.26] | [v0.4.0-jax] | [v0.8.2] | [v0.4.1] |
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### Run the Jupyter Container
2020

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| Tag(s) | [JAX\*] | [Intel® Extension for OpenXLA\*] | [Flax] | Dockerfile |
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| ---------------- | --------- | ----------------- | -------- | --------------- |
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| `0.4.0-idp-base` | [v0.4.32] | [v0.4.0-jax] | [v0.9.0] | [v0.4.0] |
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| `0.4.0-idp-base` | [v0.4.26] | [v0.4.0-jax] | [v0.8.2] | [v0.4.1] |
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The images below additionally include [Jupyter Notebook](https://jupyter.org/) server:
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| Tag(s) | [JAX\*] | [Intel® Extension for OpenXLA\*] | [Flax] | Dockerfile |
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| ------------------- | --------- | ----------------- | -------- | --------------- |
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| `0.4.0-idp-jupyter` | [v0.4.32] | [v0.4.0-jax] | [v0.9.0] | [v0.4.0] |
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| `0.4.0-idp-jupyter` | [v0.4.26] | [v0.4.0-jax] | [v0.8.2] | [v0.4.1] |
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## Build from Source
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[JAX\*]: https://github.com/google/jax
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[Flax]: https://github.com/google/flax
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[v0.4.32]: https://github.com/google/jax/releases/tag/jax-v0.4.32
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[v0.4.26]: https://github.com/google/jax/releases/tag/jax-v0.4.26
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[v0.4.0-jax]: https://github.com/intel/intel-extension-for-openxla/releases/tag/0.4.0
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[v0.9.0]: https://github.com/google/Flax/releases/tag/v0.9.0
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[v0.8.2]: https://github.com/google/Flax/releases/tag/v0.8.2
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[v0.4.0]: https://github.com/intel/ai-containers/blob/v0.4.0/jax/Dockerfile
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[v0.4.1]: https://github.com/intel/ai-containers/blob/main/jax/Dockerfile

python/requirements.txt

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numpy==1.26.4
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setuptools>=70.0.0
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psutil==6.0.0
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psutil==6.1.0
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mkl==2024.2.2
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mkl-include==2024.2.2
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intel-openmp==2024.2.1

pytorch/jupyter-requirements.txt

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jupyterlab==4.3.0b2
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jupyterhub==5.2.0
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notebook==7.3.0a1
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jupyterlab==4.3.0rc0
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jupyterhub==5.2.1
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notebook==7.3.0b0
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jupyter-server-proxy>=4.1.2

pytorch/venv-requirements.txt

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setuptools>=70.0.0
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psutil==6.0.0
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psutil==6.1.0
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mkl==2024.2.2
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mkl-include==2024.2.2
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intel-openmp==2024.2.1

tensorflow/jupyter-requirements.txt

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jupyterlab>=4.2.4
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jupyterhub==5.2.0
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jupyterhub==5.2.1
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notebook>=7.1.3
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jupyter-server-proxy>=4.1.2

tensorflow/requirements.txt

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tensorflow==2.15.1
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intel-extension-for-tensorflow[cpu]>=2.15,<2.16
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tensorflow-hub==0.16.1
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pillow==10.4.0
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pillow==11.0.0

tensorflow/serving/requirements.txt

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numpy==2.1.2
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pillow==10.4.0
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pillow==11.0.0
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requests==2.32.3
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tensorflow==2.17.0
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tensorflow-serving-api==2.17.0

test-runner/action.yml

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if: always()
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with:
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name: test-runner-summary ${{ env.test }}
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path: test-runner-summary*.json
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path: ${{ inputs.test_dir }}/logs/*summary.json
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overwrite: true

test-runner/test_runner.py

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break
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summary.append([idx + 1, test.name, "PASS"])
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json_summary.append({"Group": test_group, "Test": test.name, "Status": "PASS"})
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json_summary_path = f"test-runner-summary-{test_group}.json"
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json_summary_path = f"{args.logs_path}/{test_group.replace('/', '-')}-summary.json"
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with open(json_summary_path, "w", encoding="utf-8") as file:
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json.dump(json_summary, file, indent=4)

workflows/charts/tensorflow-serving/Chart.yaml

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# limitations under the License.
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apiVersion: v2
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name: tensorflow-serving-on-intel
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name: tensorflow-serving
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description: TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. TensorFlow Serving makes it easy to deploy new algorithms and experiments, while keeping the same server architecture and APIs. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data.
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# A chart can be either an 'application' or a 'library' chart.

workflows/charts/tensorflow-serving/README.md

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# tensorflow-serving-on-intel
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# TensorFlow Serving on Intel GPU
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TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. TensorFlow Serving makes it easy to deploy new algorithms and experiments, while keeping the same server architecture and APIs. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data.
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![Version: 0.1.0](https://img.shields.io/badge/Version-0.1.0-informational?style=flat-square) ![Type: application](https://img.shields.io/badge/Type-application-informational?style=flat-square) ![AppVersion: 1.16.0](https://img.shields.io/badge/AppVersion-1.16.0-informational?style=flat-square)
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TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. TensorFlow Serving makes it easy to deploy new algorithms and experiments, while keeping the same server architecture and APIs. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data.
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## Installation
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## Maintainers
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```bash
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helm repo add intel https://intel.github.io/helm-charts
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helm install my-tgi intel/text-generation-inference
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```
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| Name | Email | Url |
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| ---- | ------ | --- |
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| tylertitsworth | <tyler.titsworth@intel.com> | <https://github.com/tylertitsworth> |
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Then, follow the installation notes to test the deployment
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## Values
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# TensorFlow Serving on Intel GPU
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{{ template "chart.description" . }}
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{{ template "chart.versionBadge" . }}{{ template "chart.typeBadge" . }}{{ template "chart.appVersionBadge" . }}
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## Installation
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```bash
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helm repo add intel https://intel.github.io/helm-charts
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helm install my-tgi intel/text-generation-inference
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```
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Then, follow the installation notes to test the deployment
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{{ template "chart.valuesSection" . }}
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{{ template "helm-docs.versionFooter" . }}

workflows/charts/tgi/Chart.yaml workflows/charts/text-generation-inference/Chart.yaml

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# limitations under the License.
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apiVersion: v2
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name: tgi-on-intel
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name: text-generation-inference
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description: A Rust, Python and gRPC server for text generation inference by huggingface on Intel GPUs.
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# A chart can be either an 'application' or a 'library' chart.

workflows/charts/tgi/README.md workflows/charts/text-generation-inference/README.md

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![Version: 0.2.1](https://img.shields.io/badge/Version-0.2.1-informational?style=flat-square) ![Type: application](https://img.shields.io/badge/Type-application-informational?style=flat-square) ![AppVersion: 1.16.0](https://img.shields.io/badge/AppVersion-1.16.0-informational?style=flat-square)
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## Installation
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```bash
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helm repo add intel https://intel.github.io/helm-charts
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helm install my-tgi intel/text-generation-inference
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```
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Then, follow the installation notes to test the deployment
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## Values
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| Key | Type | Default | Description |

workflows/charts/tgi/README.md.gotmpl workflows/charts/text-generation-inference/README.md.gotmpl

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{{ template "chart.versionBadge" . }}{{ template "chart.typeBadge" . }}{{ template "chart.appVersionBadge" . }}
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{{ template "chart.requirementsSection" . }}
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## Installation
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```bash
15+
helm repo add intel https://intel.github.io/helm-charts
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helm install my-tgi intel/text-generation-inference
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```
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Then, follow the installation notes to test the deployment
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{{ template "chart.valuesSection" . }}
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workflows/charts/torchserve/Chart.yaml

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# limitations under the License.
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apiVersion: v2
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name: torchserve-on-intel
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description: TorchServe on Intel is a performant, flexible and easy to use tool for serving PyTorch models in production.
16+
name: torchserve
17+
description: TorchServe is a performant, flexible and easy to use tool for serving PyTorch models in production on Intel GPUs.
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# A chart can be either an 'application' or a 'library' chart.
2020
#

workflows/charts/torchserve/README.md

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# TorchServe with Intel Optimizations
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TorchServe on Intel is a performant, flexible and easy to use tool for serving PyTorch models in production.
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TorchServe is a performant, flexible and easy to use tool for serving PyTorch models in production on Intel GPUs.
44

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For more information about how to use TorchServe with Intel Optimizations, check out the [container documentation](../../../pytorch/serving/README.md).
5+
For more information about how to use TorchServe with Intel Optimizations, check out the [container documentation](https://github.com/intel/ai-containers/blob/main/pytorch/serving/README.md).
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![Version: 0.1.0](https://img.shields.io/badge/Version-0.1.0-informational?style=flat-square) ![Type: application](https://img.shields.io/badge/Type-application-informational?style=flat-square) ![AppVersion: 1.16.0](https://img.shields.io/badge/AppVersion-1.16.0-informational?style=flat-square)
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## Installation
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```bash
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helm repo add intel https://intel.github.io/helm-charts
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helm install my-tgi intel/text-generation-inference
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```
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Then, follow the installation notes to test the deployment
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## Values
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| Key | Type | Default | Description |

workflows/charts/torchserve/README.md.gotmpl

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{{ template "chart.description" . }}
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For more information about how to use TorchServe with Intel Optimizations, check out the [container documentation](../../../pytorch/serving/README.md).
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For more information about how to use TorchServe with Intel Optimizations, check out the [container documentation](https://github.com/intel/ai-containers/blob/main/pytorch/serving/README.md).
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{{ template "chart.versionBadge" . }}{{ template "chart.typeBadge" . }}{{ template "chart.appVersionBadge" . }}
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{{ template "chart.requirementsSection" . }}
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## Installation
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```bash
12+
helm repo add intel https://intel.github.io/helm-charts
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helm install my-tgi intel/text-generation-inference
14+
```
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Then, follow the installation notes to test the deployment
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{{ template "chart.valuesSection" . }}
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