return runtimeService.ListPodSandbox(ctx, filter)
}

func (*defaultImpl) StopPodSandbox(ctx context.Context, runtimeService criapi.RuntimeService, sandboxID string) error {
	return runtimeService.StopPodSandbox(ctx, sandboxID)
}

func (*defaultImpl) RemovePodSandbox(ctx context.Context, runtimeService criapi.RuntimeService, podSandboxID string) error {
	return runtimeService.RemovePodSandbox(ctx, podSandboxID)

libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,
including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could
potentially exploit a vulnerability in the TensorFlow code that handles videos,

func (kl *Kubelet) ListMetricDescriptors(ctx context.Context) ([]*runtimeapi.MetricDescriptor, error) {
	return kl.containerRuntime.ListMetricDescriptors(ctx)
}

// ListPodSandboxMetrics retrieves the metrics for all pod sandboxes.
func (kl *Kubelet) ListPodSandboxMetrics(ctx context.Context) ([]*runtimeapi.PodSandboxMetrics, error) {
	return kl.containerRuntime.ListPodSandboxMetrics(ctx)
}

	newSandboxNeeded, _, _ := runtimeutil.PodSandboxChanged(pod, podStatus)
	// if a new sandbox does not need to be created for a pod, it indicates that
	// a sandbox for the pod with networking configured already exists.
	// Otherwise, the kubelet needs to invoke the container runtime to create a
	// fresh sandbox and configure networking for the sandbox.
	if !newSandboxNeeded {
		return v1.PodCondition{
			Type:   v1.PodReadyToStartContainers,

                throw new RuntimeException("Should have been a miss");
            });

        // Produce some example output (simulate executing cacheable work in a temporary sandbox)
        Path sandboxOutputDirectory = Files.createTempDirectory("sandbox-output");
        Path sandboxOutputTxt = sandboxOutputDirectory.resolve("output.txt");
        Files.write(sandboxOutputTxt, Collections.singleton("contents"));

			containers:  []string{"1", "2"},
			shouldError: false,
		},
		{
			name:       "invalid: remove pod sandbox fails",
			containers: []string{"1"},
			prepare: func(mock *fakeImpl) {
				mock.RemovePodSandboxReturns(errTest)
			},
			shouldError: true,
		},
		{
			name:       "invalid: stop pod sandbox fails",
			containers: []string{"1"},
			prepare: func(mock *fakeImpl) {
				mock.StopPodSandboxReturns(errTest)

		expected v1.PodCondition
	}{
		"Empty pod status": {
			pod:    &v1.Pod{},
			status: &kubecontainer.PodStatus{},
			expected: v1.PodCondition{
				Status: v1.ConditionFalse,
			},
		},
		"Pod sandbox status not ready": {
			pod: &v1.Pod{},
			status: &kubecontainer.PodStatus{
				SandboxStatuses: []*runtimeapi.PodSandboxStatus{
					{
						Metadata: &runtimeapi.PodSandboxMetadata{Attempt: uint32(0)},

   
      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.

		DetectedRestoreBinary: iptablesRestoreBin,
		Version:               parsedVer,
		Legacy:                !isNft,
		ExistingRules:         existingRules,
	}, nil
}

// runInSandbox builds a lightweight sandbox ("container") to build a suitable environment to run iptables commands in.
// This is used in CNI, where commands are executed from the host but from within the container network namespace.

        return cleanOrCreate(perVersion)
    }

    private File perVersionStudioSandboxDirectory(File workingDir) {
        File studioSandboxDir = new File(workingDir, "studio-sandbox")
        return cleanOrCreate(studioSandboxDir)
    }

    private static File cleanOrCreate(File directory) {
        if (!directory.exists()) {
            directory.mkdirs()
        } else {