version  *version.Info
		expected int
		errMsg   error
		isValid  bool
	}{
		{
			version:  version1_17,
			expected: 17,
			errMsg:   nil,
			isValid:  true,
		},
		{
			version:  version1_8,
			expected: 8,
			errMsg:   nil,
			isValid:  true,
		},
		{
			version:  version1_18,
			expected: 18,
			errMsg:   nil,
			isValid:  true,
		},
		{

	case bucketTaggingConfig:
		st.Tagging = madmin.MetaStatus{IsSet: true, Err: errMsg}
	case bucketQuotaConfigFile:
		st.Quota = madmin.MetaStatus{IsSet: true, Err: errMsg}
	case objectLockConfig:
		st.ObjectLock = madmin.MetaStatus{IsSet: true, Err: errMsg}
	case bucketVersioningConfig:
		st.Versioning = madmin.MetaStatus{IsSet: true, Err: errMsg}
	default:
		st.Err = errMsg
	}

                String errMsg = "Missing Javadoc file for " + link + " in " + sourceFile.getName();
                if (link.startsWith("javadoc")) {
                    errMsg += " (You may need to remove the leading `javadoc` path component)";
                }
                errorsForFile.add(new Error(lineNumber, line, errMsg));
            }

	emptyBanner = color.BgRed(strings.Repeat(" ", len(logTag))) + " "
	bannerWidth = len(logTag) + 1
)

func (f fatalMsg) pretty(msg string, args ...interface{}) {
	// Build the passed error message
	errMsg := fmt.Sprintf(msg, args...)

	tagPrinted := false

	// Print the error message: the following code takes care
	// of splitting error text and always pretty printing the

	respBytes []byte, apiErr APIError, errMsg string,
) {
	if h.forceStarted {
		_, apiErr = ahs.stopHealSequence(pathJoin(h.bucket, h.object))
		if apiErr.Code != "" {
			return respBytes, apiErr, ""
		}
	} else {
		oh, exists := ahs.getHealSequence(pathJoin(h.bucket, h.object))
		if exists && !oh.hasEnded() {
			errMsg = "Heal is already running on the given path " +

  TF_Buffer* ret = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(server_def, ret));
  return ret;
}

void TF_MakeInternalErrorStatus(TF_Status* status, const char* errMsg) {
  status->status = tensorflow::errors::Internal(errMsg);
}

struct TF_CheckpointReader : public tensorflow::checkpoint::CheckpointReader {
  using tensorflow::checkpoint::CheckpointReader::CheckpointReader;

	} else if err != nil {
		return nil, fmt.Errorf("failed to get namespace %s: %v", ns, err)
	}
	return nsObj, nil
}

func errorWithMessage(errMsg string, gwc *gateway.Gateway, err error) error {
	errorMsg := fmt.Sprintf("%s\t%v/%v", errMsg, gwc.Namespace, gwc.Name)
	if err != nil {
		errorMsg += fmt.Sprintf(": %s", err)
	}
	return errors.New(errorMsg)
}

TF_Buffer* TFE_GetServerDef(const char* text_proto, TF_Status* status);

TF_CAPI_EXPORT extern void TF_MakeInternalErrorStatus(TF_Status* status,
                                                      const char* errMsg);

// TF_NewCheckpointReader() return the CheckpointReader that can be use to
// investigate or load the variable from the checkpoint file
typedef struct TF_CheckpointReader TF_CheckpointReader;

		t.Fatalf("%s: Expected to fail since the NewMultipartUpload is initialized on a non-existent bucket.", instanceType)
	}
	if errMsg != err.Error() {
		t.Errorf("%s, Expected to fail with Error \"%s\", but instead found \"%s\".", instanceType, errMsg, err.Error())
	}

	// Create bucket before initiating NewMultipartUpload.
	err = obj.MakeBucket(context.Background(), bucket, MakeBucketOptions{})
	if err != nil {

			if authz == nil {
				// Print a warning that some policies mapped to a role are not defined.
				errMsg := fmt.Errorf(
					"The policies \"%s\" mapped to role ARN %s are not defined - this role may not work as expected.",
					unknownPoliciesSet.ToSlice(), arn.String())
				authZLogIf(ctx, errMsg, logger.WarningKind)
			}
		}
		sys.rolesMap[arn] = rolePolicies
	}
}

// Prints IAM role ARNs.