<div class="wrapper">
    <jsp:include page="/WEB-INF/view/common/admin/header.jsp"></jsp:include>
    <jsp:include page="/WEB-INF/view/common/admin/sidebar.jsp">
        <jsp:param name="menuCategoryType" value="log"/>
        <jsp:param name="menuType" value="jobLog"/>
    </jsp:include>
    <div class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">

				}
				tag.Key = s
				keyAlreadyParsed = true
			case "Value":
				if valueAlreadyParsed {
					return errDuplicatedXMLTag
				}
				tag.Value = s
				valueAlreadyParsed = true
			default:
				return errUnknownXMLTag
			}
		}
	}

	return nil
}

func (tag Tag) String() string {
	return tag.Key + "=" + tag.Value
}

// IsEmpty returns whether this tag is empty or not.

Instead, you want to provide a different dependency that will be used only during tests (possibly only some specific tests), and will provide a value that can be used where the value of the original dependency was used.

### Use cases: external service

An example could be that you have an external authentication provider that you need to call.

fun buildScanTagParam(tag: String) = """-Dscan.tag.$tag"""
fun buildScanCustomValueParam(key: String, value: String) = """-Dscan.value.$key=$value"""

fun TestCoverage.asBuildScanCustomValue() =
    "${testType.name.toCapitalized()}${testJvmVersion.name.toCapitalized()}${vendor.displayName}${os.asName()}${arch.asName()}"

// Generates a build scan custom value "PartOf=X,Y,Z"
// where X, Y, Z are all the stages including current stage

      field.setAccessible(true);
    }

    void set(T instance, Object value) {
      try {
        field.set(instance, value);
      } catch (IllegalAccessException impossible) {
        throw new AssertionError(impossible);
      }
    }

    void set(T instance, int value) {
      try {
        field.set(instance, value);
      } catch (IllegalAccessException impossible) {

  auto s = tensorflow::unwrap(op)->SetAttrFloat(attr_name, value);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

void TFE_OpSetAttrBool(TFE_Op* op, const char* attr_name, unsigned char value) {
  auto s = tensorflow::unwrap(op)->SetAttrBool(attr_name,
                                               (value == 0) ? false : true);
  if (!s.ok()) {

        this.normalizer = normalizer;
    }

    @Override
    public Object execute(String expression, Object value) {
        if (value != null && URL_EXPRESSIONS.contains(expression)) {
            return normalizer.normalize(value.toString());
        }

        return null;
    }

  }

  /** Returns the associated value type. */
  @GwtIncompatible
  public Class<V> valueType() {
    return valueTypeOrObjectUnderJ2cl;
  }

  @Override
  K checkKey(K key) {
    return checkNotNull(key);
  }

  @Override
  V checkValue(V value) {
    return checkNotNull(value);
  }

  /**

  }

  /** Returns the associated value type. */
  @GwtIncompatible
  public Class<V> valueType() {
    return valueTypeOrObjectUnderJ2cl;
  }

  @Override
  K checkKey(K key) {
    return checkNotNull(key);
  }

  @Override
  V checkValue(V value) {
    return checkNotNull(value);
  }

  /**

        format(prop.additionalValues[0].title) == 'inherited'
        format(prop.additionalValues[0].value) == 'specific1'
        format(prop.additionalValues[1].title) == 'overridden'
        format(prop.additionalValues[1].value) == 'specific3'
        format(prop.additionalValues[2].title) == 'added'
        format(prop.additionalValues[2].value) == 'specific2'

        def prop2 = doc.classProperties[1]
        prop2.name == 'b'