import org.jspecify.annotations.NullUnmarked;

/**
 * A generator of {@code TestSuite} instances for testing {@code CharSink} implementations.
 * Generates tests of all methods on a {@code CharSink} given various inputs written to it.
 *
 * @author Colin Decker
 */
@AndroidIncompatible // TODO(b/230620681): Make this available (even though we won't run it).
@NullUnmarked

    for (int i = 0; i < inputs.size(); i++) {
      GraphTensor* t = dyn_cast<GraphTensor>(inputs[i]);
      if (!t) {
        return tensorflow::errors::InvalidArgument(
            "Unable to cast input to GraphTensor");
      }
      tf_outputs[i] = t->output_;
    }
    TF_AddInputList(op_.get(), tf_outputs.data(), tf_outputs.size());
    return absl::OkStatus();
  }

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["header", "tool"],
            "msg": "Extra inputs are not permitted",
            "input": "plumbus",
        }
    ]
}
```

## 밑줄 변환 비활성화하기 { #disable-convert-underscores }

일반적인 헤더 매개변수와 마찬가지로, 매개변수 이름에 밑줄 문자가 있으면 **자동으로 하이픈으로 변환**됩니다.

    private final String input;

    /** The new stopword, if updated. */
    private String newInput;

    /**
     * Constructs a new stopword item.
     *
     * @param id    The unique identifier of the item.
     * @param input The stopword.
     */
    public StopwordsItem(final long id, final String input) {
        this.id = id;
        this.input = input;

        if (id == 0) {

    }

    @ParameterizedTest
    @ValueSource(strings = { "", "password", "pässwörd", "1234567890abcdef" })
    @DisplayName("nTOWFv1 equals getNTHash across inputs")
    void testNTOWFv1_delegatesToGetNTHash(String password) {
        // Act
        byte[] h1 = NtlmUtil.nTOWFv1(password);
        byte[] h2 = NtlmUtil.getNTHash(password);

        // Assert

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["header", "tool"],
            "msg": "Extra inputs are not permitted",
            "input": "plumbus",
        }
    ]
}
```

## Disable Convert Underscores { #disable-convert-underscores }

  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,
                             /*opers=*/nullptr, 1, inputs, 1, outputs,
                             /*output_names=*/nullptr,
                             /*opts=*/nullptr, description, s.get());

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

他们将收到一条错误响应，表明字段 `extra` 不被允许：

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

## 总结 { #summary }

	cfg.APIKey = strings.TrimSpace(env.Get(config.EnvMinIOSubnetAPIKey, kvs.Get(config.APIKey)))
	cfg.Proxy = proxy

	if transport == nil {
		// when transport is nil, it means we are just validating the
		// inputs not performing any network calls.
		return cfg, nil
	}

	// Make sure to clone the transport before editing the ProxyURL
	if proxyURL != nil {
		if tr, ok := transport.(*http.Transport); ok {