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

## Summary

			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",

// capture some inputs and then add a node in the graph. The output tensors are
// returned through the provided TF_OutputList.
// Any active tape will observe the effects of this execution.
void TF_ExecuteOperation(TF_AbstractOp* op, int num_inputs,
                         TF_AbstractTensor* const* inputs, TF_OutputList* o,
                         TF_Status* s);

                "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
            {

// 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:...

case "${VERSION}" in
devtoolset-7)
mv "/${TARGET}/usr/lib/libstdc++.so.${LIBSTDCXX_VERSION}" \
   "/${TARGET}/usr/lib/libstdc++.so.${LIBSTDCXX_VERSION}.backup"
echo -e "OUTPUT_FORMAT(elf64-x86-64)\nINPUT ( libstdc++.so.6.0.13 -lstdc++_nonshared44 )" \
   > "/${TARGET}/usr/lib/libstdc++.so.${LIBSTDCXX_VERSION}"
cp "./x86_64-pc-linux-gnu/libstdc++-v3/src/.libs/libstdc++_nonshared44.a" \
   "/${TARGET}/usr/lib"
  ;;

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

@ElementTypesAreNonnullByDefault
public interface Interner<E> {
  /**
   * Chooses and returns the representative instance for any of a collection of instances that are
   * equal to each other. If two {@linkplain Object#equals equal} inputs are given to this method,
   * both calls will return the same instance. That is, {@code intern(a).equals(a)} always holds,
   * and {@code intern(a) == intern(b)} if and only if {@code a.equals(b)}. Note that {@code

}

void TF_ExecuteOperation(TF_AbstractOp* op, int num_inputs,
                         TF_AbstractTensor* const* inputs, TF_OutputList* o,
                         TF_Status* s) {
  for (int i = 0; i < num_inputs; i++) {
    tsl::Set_TF_Status_from_Status(s, unwrap(op)->AddInput(unwrap(inputs[i])));
    if (TF_GetCode(s) != TF_OK) {
      return;
    }
  }
  int num_outputs = unwrap(o)->expected_num_outputs;