boolean exists = installed.stream().map(this::getArtifactFromMap)
                        .anyMatch(a -> a.getName().equals(target.getName()) && a.getVersion().equals(target.getVersion()));
                if (!exists) {
                    ThreadUtil.sleep(500);
                    continue;
                }
                assertTrue("plugin(" + target + ") is included in " + installed, exists);
                done = true;

	\
	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 \

## Where are Packages Installed

When you install Python, it creates some directories with some files in your computer.

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

		// the CNI binary installed.
		if err = installer.Run(ctx); err != nil {
			if errors.Is(err, context.Canceled) || errors.Is(err, context.DeadlineExceeded) {
				log.Infof("installer complete: %v", err)
				// Error was caused by interrupt/termination signal
				err = nil
			} else {
				log.Errorf("installer failed: %v", err)
			}
		}

		if cleanErr := installer.Cleanup(); cleanErr != nil {
			if err != nil {

## Prerequisites

Please make sure the following packages are already installed via `dnf` or `apt`: 

- `tuned`
- `curl`

### Install `tuned.conf` performance profile

#### Step 1 - download `tuned.conf` from the referenced link
```
wget https://raw.githubusercontent.com/minio/minio/master/docs/tuning/tuned.conf
```

#### Step 2 - install tuned.conf as supported performance profile on all nodes
```

# different compilation methods. E.g. for a PR to test a new CUDA version, set
# the CACHEBUSTER to the PR number.
build --action_env=CACHEBUSTER=20220325

# Use Python 3.X as installed in container image
build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
build --python_path="/usr/local/bin/python3"

# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

# different compilation methods. E.g. for a PR to test a new CUDA version, set
# the CACHEBUSTER to the PR number.
build --action_env=CACHEBUSTER=20220325

# Use Python 3.X as installed in container image
build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
build --python_path="/usr/local/bin/python3"

# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

## Everything is Optional

Each component in the new installer is optional. Users can install the component defined in the new installer,
use the equivalent component in `istio-system`, configured with the official installer, or use a different
version or implementation.

For example, you may use your own Prometheus and Grafana installs, or you may use a specialized/custom

    ```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