Therefore, if you run a `tf.train.Server` in your network, anybody with access
to the network can execute arbitrary code with the privileges of the user
running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized
in taking those formats, modifying them, and/or converting them to intermediate

			description:       "Invalid command args - missing valid input spec",
			args:              strings.Split("entry configure --name foo -o temp --clusterID cid", " "),
			expectedException: true,
			expectedOutput:    "Error: expecting a WorkloadGroup artifact file or the name and namespace of an existing WorkloadGroup\n",
		},
		{
			description:       "Invalid command args - missing valid input spec",

    TFE_TensorHandle* input = TFE_OpGetFlatInput(original_op, j, s);
    if (TF_GetCode(s) != TF_OK) return;
    const char* input_device = TFE_TensorHandleDeviceName(input, s);
    if (TF_GetCode(s) != TF_OK) return;
    if (dev->device_name == input_device) {
      LoggedTensor* t = reinterpret_cast<LoggedTensor*>(
          TFE_TensorHandleDevicePointer(input, s));
      if (TF_GetCode(s) != TF_OK) return;

                "detail": [
                    {
                        "type": "extra_forbidden",
                        "loc": ["cookie", "extra"],
                        "msg": "Extra inputs are not permitted",
                        "input": "track-me-here-too",
                    }
                ]
            }
        )
        | IsDict(
            # TODO: remove when deprecating Pydantic v1
            {

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["body", "extra"],
            "msg": "Extra inputs are not permitted",
            "input": "Mr. Poopybutthole"
        }
    ]
}
```

## Summary

                IsDict(
                    {
                        "type": "extra_forbidden",
                        "loc": ["header", "tool"],
                        "msg": "Extra inputs are not permitted",
                        "input": "plumbus",
                    }
                )
                | IsDict(
                    # TODO: remove when deprecating Pydantic v1
                    {

ame:"dimension",validatorFunction:function(b,d,e,g,h){if(c){var i=e.get(0).files||[],j=this;e.attr("data-validation").indexOf("mime")===-1?(alert("You should validate file type being jpg, gif or png on input "+e[0].name),b(!1)):i.length>1?(alert("Validating image dimensions does not support inputs allowing multiple files"),b(!1)):0===i.length?b(!0):f(i[0],function(c){var d=!1;e.valAttr("dimension")&&(d=a.formUtils.checkImageDimension(c,e.valAttr("dimension"),h)),!d&&e.valAttr("ratio")&&(d=a.form...

     *
     * @param    input    input block
     * @param    offset    start of meaningful bytes in input
     * @param    len        count of bytes in input block to consider
     */
    public void engineUpdate (byte[] input, int offset, int len) {
        // make sure we don't exceed input's allocated size/length
        if (offset < 0 || len < 0 || (long)offset + len > input.length)

// TPUReplicatedInput and TPUReplicatedOutput respectively. For example, with
// two component devices, running `x = TPUReplicatedInput(inputs=[a, b])` on the
// parallel device creates a parallel tensor `x` with `a` on the first of
// `underlying_devices` and `b` on the second. Running `a_unpacked, b_unpacked =
// TPUReplicatedOutput(input=x, num_replicas=2)` un-packs the parallel tensor
// into its components.
//

0;\n}\n\n.input-group > .input-group-append > .btn,\n.input-group > .input-group-append > .input-group-text,\n.input-group > .input-group-prepend:not(:first-child) > .btn,\n.input-group > .input-group-prepend:not(:first-child) > .input-group-text,\n.input-group > .input-group-prepend:first-child > .btn:not(:first-child),\n.input-group > .input-group-prepend:first-child > .input-group-text:not(:first-child) {\n  border-top-left-radius: 0;\n  border-bottom-left-radius: 0;\n}\n\n.custom-control {\n  position:...