assertTrue("plugin(" + target + ") is included in " + installed, exists);
                done = true;
                break;
            }
            assertTrue("plugin(" + target + ") is installed.", done);
        }
        // Delete
        {
            checkDeleteMethod(targetMap).then().body("response.status", equalTo(0));

            boolean done = false;
            for (int i = 0; i < 60; i++) {

	\
	Write-Host 'Verifying install ...'; \
	Write-Host '  python --version'; C:\python312\python.exe --version; \
	\
	Write-Host 'Verifying pip install ...'; \
	C:\python312\python.exe -m pip --version; \
	\
	Write-Host 'Removing ...'; \
	Remove-Item C:\tmp\pyinstall.exe -Force; \
	\
	Write-Host 'Complete.';

# Install pip packages.
RUN python -m pip install --ignore-installed --force-reinstall --upgrade \

### Installing xl-meta

To install, [Go](https://golang.org/dl/) must be installed. Once installed, execute this to install the binary:

```bash
go install github.com/minio/minio/docs/debugging/xl-meta@latest
```

### Using xl-meta

## Where are Packages Installed { #where-are-packages-installed }

 * The local repository serves as a cache for downloaded remote artifacts and storage
 * for locally installed artifacts. This manager provides services to determine the
 * appropriate paths for artifacts within the local repository structure.
 *
 * <p>The LocalRepositoryManager is responsible for:
 * <ul>
 *   <li>Determining the storage path for locally installed artifacts</li>
 *   <li>Managing the layout and organization of cached remote artifacts</li>

# "TFCI_MACOS_PYENV_INSTALL_ENABLE" controls whether to use Pyenv to install
# the Python version set in "TFCI_PYTHON_VERSION" and use it as default.
# We enable this in the nightly and release builds because before uploading the
# wheels, we install them in a virtual environment and run some smoke tests on
# it. TFCI Mac VMs only have one Python version installed so we need to install
# the other versions manually.

    /**
     * Retrieves the list of installed plugins.
     *
     * @return JSON response containing installed plugin list
     */
    // GET /api/admin/plugin/installed
    @Execute
    public JsonResponse<ApiResult> get$installed() {
        final List<Map<String, String>> list = getAllInstalledArtifacts();

        return ComponentUtil.getPluginHelper().getArtifact(values[0], values[1]);
    }

    /**
     * Installs the specified artifact in a background thread.
     * Also removes any previously installed versions of the same plugin.
     *
     * @param artifact the artifact to install
     */
    public static void installArtifact(final Artifact artifact) {
        new Thread(() -> {

    ```bash
    python tf_doctest.py --file=<file_path>
    ```

    This will run it using your installed version of TensorFlow. To be sure
    you're running the same code that you're testing:

    *   Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/)
        `pip install -U tf-nightly`
    *   Rebase your pull request onto a recent pull from

     * correctly installed
     *
     * <p>{@link #transitioned}: is set by {@link #transitionService} to indicate that some
     * transition has been performed.
     *
     * <p>Together, they allow us to enforce that all services have their listeners installed prior
     * to any service performing a transition, then we can fail in the ServiceManager constructor