new Predicate<Field>() {
              @Override
              public boolean apply(Field input) {
                int modifiers = input.getModifiers();
                return isPublic(modifiers)
                    && isStatic(modifiers)
                    && isFinal(modifiers)
                    && MediaType.class.equals(input.getType());
              }
            });
  }

  @J2ktIncompatible

    return RESULT_DATA;
  }

  private class ChainingFunction implements AsyncFunction<Integer, String> {
    @Override
    public ListenableFuture<String> apply(Integer input) throws Exception {
      switch (input) {
        case VALID_INPUT_DATA:
          outputFuture.set(RESULT_DATA);
          break;
        case SLOW_OUTPUT_VALID_INPUT_DATA:
          break; // do nothing to the result

    return RESULT_DATA;
  }

  private class ChainingFunction implements AsyncFunction<Integer, String> {
    @Override
    public ListenableFuture<String> apply(Integer input) throws Exception {
      switch (input) {
        case VALID_INPUT_DATA:
          outputFuture.set(RESULT_DATA);
          break;
        case SLOW_OUTPUT_VALID_INPUT_DATA:
          break; // do nothing to the result

foo_is_missing = {
    "detail": [
        IsDict(
            {
                "loc": ["query", "foo"],
                "msg": "Field required",
                "type": "missing",
                "input": None,
            }
        )
        # TODO: remove when deprecating Pydantic v1
        | IsDict(
            {
                "loc": ["query", "foo"],
                "msg": "field required",

# Using TensorFlow Securely

This document discusses the TensorFlow security model. It describes the security
risks to consider when using models, checkpoints or input data for training or
serving. We also provide guidelines on what constitutes a vulnerability in
TensorFlow and how to report them.

This document applies to other repositories in the TensorFlow organization,
covering security practices for the entirety of the TensorFlow ecosystem.

 * }</pre>
 *
 * <p>For separator-based splitters that do not use {@code omitEmptyStrings}, an input string
 * containing {@code n} occurrences of the separator naturally yields an iterable of size {@code n +
 * 1}. So if the separator does not occur anywhere in the input, a single substring is returned
 * containing the entire input. Consequently, all splitters split the empty string to {@code [""]}
 * (note: even fixed-length splitters).
 *

}

func testGetBucketLocationHandler(obj ObjectLayer, instanceType, bucketName string, apiRouter http.Handler,
	credentials auth.Credentials, t *testing.T,
) {
	// test cases with sample input and expected output.
	testCases := []struct {
		bucketName string
		accessKey  string
		secretKey  string
		// expected Response.
		expectedRespStatus int
		locationResponse   []byte

    validations:
      required: true

  - type: textarea
    id: since
    attributes:
      label: Since when has it been failing?
    validations:
      required: true

  - type: input
    id: testgrid
    attributes:
      label: Testgrid link

  - type: textarea
    id: reason
    attributes:
      label: Reason for failure (if possible)

  - type: textarea
    id: additional

		{"X-Amz-Content-Sha256", "", false},
	}

	for i, testCase := range testCases {
		// creating an input HTTP request.
		// Only the query parameters are relevant for this particular test.
		inputReq, err := http.NewRequest(http.MethodGet, "http://example.com", nil)
		if err != nil {
			t.Fatalf("Error initializing input HTTP request: %v", err)
		}
		q := inputReq.URL.Query()

func splitZipExtensionPath(input string) (zipPath, object string, err error) {
	idx := strings.Index(input, archivePattern)
	if idx < 0 {
		// Should never happen
		return "", "", errors.New("unable to parse zip path")
	}
	return input[:idx+len(archivePattern)-1], input[idx+len(archivePattern):], nil
}

// getObjectInArchiveFileHandler - GET Object in the archive file