with:
          version: "0.4.15"
          enable-cache: true
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
      - name: Install Dependencies
        run: uv pip install -r requirements-github-actions.txt -r requirements-translations.txt
      # Allow debugging with tmate
      - name: Setup tmate session
        uses: mxschmitt/action-tmate@v3

    }
    TesterRequirements requirements;
    try {
      requirements = FeatureUtil.getTesterRequirements(method);
    } catch (ConflictingRequirementsException e) {
      throw new RuntimeException(e);
    }
    if (!features.containsAll(requirements.getPresentFeatures())) {
      if (logger.isLoggable(FINER)) {
        Set<Feature<?>> missingFeatures = copyToSet(requirements.getPresentFeatures());

---> 100%
```

</div>

////

### Install from `requirements.txt` { #install-from-requirements-txt }

If you have a `requirements.txt`, you can now use it to install its packages.

//// tab | `pip`

<div class="termy">

```console
$ pip install -r requirements.txt
---> 100%
```

</div>

////

//// tab | `uv`

     * If error still persists then, apparently your CPU model does not support AVX instruction sets.
       * Refer [hardware requirements](https://www.tensorflow.org/install/pip#hardware-requirements).
   
   -----------------------------------------------------------------------------------------------
   
   **2. Installing **TensorFlow** (TF) CPU prebuilt binaries**
   
   

        uses: astral-sh/setup-uv@v6
        with:
          version: "0.4.15"
          enable-cache: true
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
      - name: Install Dependencies
        run: uv pip install -r requirements-github-actions.txt
      # Allow debugging with tmate
      - name: Setup tmate session
        uses: mxschmitt/action-tmate@v3

        uses: astral-sh/setup-uv@v6
        with:
          version: "0.4.15"
          enable-cache: true
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
      - name: Install Dependencies
        run: uv pip install -r requirements-github-actions.txt
      # Allow debugging with tmate
      - name: Setup tmate session
        uses: mxschmitt/action-tmate@v3

acknowledged by the Bazel requirements updater command as well. For example, if
you wish the updater to consider pre-release versions simply pass `--pre`
argument to the bazel command:

```
bazel run //ci/official/requirements_updater:requirements.update --repo_env=HERMETIC_PYTHON_VERSION=3.12 -- --pre
```

If you need to upgrade all of the packages in requirements lock file, just pass
the `--upgrade` parameter:

      uses: astral-sh/setup-uv@v6
      with:
        version: "0.4.15"
        enable-cache: true
        cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
    - name: Install GitHub Actions dependencies
      run: uv pip install -r requirements-github-actions.txt
    - name: Label Approved
      run: python ./scripts/label_approved.py
      env:
        TOKEN: ${{ secrets.GITHUB_TOKEN }}

        uses: astral-sh/setup-uv@v6
        with:
          version: "0.4.15"
          enable-cache: true
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
      - name: Install GitHub Actions dependencies
        run: uv pip install -r requirements-github-actions.txt
      - name: Update Topic Repos
        run: python ./scripts/topic_repos.py
        env:

This is necessary to avoid compiler and linker conflicts. Adding
a "vendor/" prefix also maintains the invariant that standard
library packages begin with a dotless path element.

The module requirements of std and cmd do not influence version
selection in other modules. They are only considered when running
module commands like 'go get' and 'go mod vendor' from a directory
in GOROOT/src.

Maintaining vendor directories