Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a
[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are
reachable and exploitable through production-grade, benign models.

### Compilation

   
      * 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.

### Pod Startup Implementation

The key mechanism to maintain this property is the CNI plugin.
The CNI plugin is executed synchronously  during the creation of the Pod sandbox by the container runtime, before processes or containers are run within the Pod.
This ensures we can setup the network configuration and start Ztunnel.

        "search": ["testSearch"],
        "options": ["testOption"]
    },
    "prevResult": {
        "cniversion": "%s",
        "interfaces": [
            {
                "name": "%s",
                "sandbox": "%s"
            }
        ],
        "ips": [
            {
                "version": "4",
                "address": "10.0.0.2/24",
                "gateway": "10.0.0.1",
                "interface": 0

   * Supports-Loading-Mode}</a> header field name. This can be used to specify, for example, <a
   * href="https://developer.chrome.com/docs/privacy-sandbox/fenced-frame/#server-opt-in">fenced
   * frames</a>.
   *
   * @since 32.0.0
   */
  public static final String SUPPORTS_LOADING_MODE = "Supports-Loading-Mode";

  /**

- `kubeadm`: now shows a warning message when detecting that the sandbox image of the container runtime is inconsistent with that used by kubeadm ([#115610](https://github.com/kubernetes/kubernetes/pull/115610), [@SataQiu](https://github.com/SataQiu))

    and
    [`tf.keras.layers.CuDNNLSTM`](https://www.tensorflow.org/versions/r1.9/api_docs/python/tf/keras/layers/CuDNNLSTM)
    layers.
    [Try it](https://colab.sandbox.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb?linkId=53292082).
*   Adding support of core