[in] uint16_t level,
			[in,out] uint32_t *count);

	[op(0x2c)]
	int LsarOpenPolicy2([in,string,unique] wchar_t *system_name,
			[in] LsarObjectAttributes *object_attributes,
			[in] uint32_t desired_access,
			[out] policy_handle *policy_handle);

	[op(0x2e)]
	int LsarQueryInformationPolicy2([in] policy_handle *handle,
			[in] uint16_t level,
			[out,switch_is(level),unique] LsarPolicyInfo *info);

import jcifs.context.SingletonContext;


/**
 * This class now contains only utilities for config parsing.
 * 
 * We strongly suggest that you create an explicit {@link jcifs.context.CIFSContextWrapper}
 * with your desired config. It's base implementation {@link jcifs.context.BaseContext}
 * should be sufficient for most needs.
 * 
 * If you want to retain the classic singleton behavior you can use

     *     </ul>
     *   </li>
     * </ul>
     *
     * This method must be invoked before {@link #addDependency(Node, Dependency, Predicate, Path, PathModularizationCache)}
     * if output directories are desired on the class-path or module-path.
     * This method can be invoked at most once.
     *
     * @param main the main output directory, or {@code null} if none

  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 1;

  // `spec` is the specification of the desired behavior of a FlowSchema.
  // More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#spec-and-status
  // +optional
  optional FlowSchemaSpec spec = 2;

  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 1;

  // `spec` is the specification of the desired behavior of a FlowSchema.
  // More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#spec-and-status
  // +optional
  optional FlowSchemaSpec spec = 2;

import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * A queue which forwards all its method calls to another queue. Subclasses should override one or
 * more methods to modify the behavior of the backing queue as desired per the <a
 * href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingQueue} forward <b>indiscriminately</b> to the

/**
 * A {@link BlockingDeque} which forwards all its method calls to another {@code BlockingDeque}.
 * Subclasses should override one or more methods to modify the behavior of the backing deque as
 * desired per the <a href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingBlockingDeque} forward <b>indiscriminately</b>

        }
        sb.append(comp);
        append = true;
      }
      dummy ^= sb.toString().length();
    }
    return dummy;
  }

  /**
   * Starts with an empty delimiter and changes to the desired value at the end of the iteration.
   */
  @Benchmark
  int assignDelimiter(int reps) {
    int dummy = 0;
    for (int i = 0; i < reps; i++) {
      StringBuilder sb = new StringBuilder();

import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * A set which forwards all its method calls to another set. Subclasses should override one or more
 * methods to modify the behavior of the backing set as desired per the <a
 * href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingSet} forward <b>indiscriminately</b> to the

apply fixes to bugs or security vulnerabilities:

*   Clone the TensorFlow repo and switch to the corresponding branch for your
    desired TensorFlow version, for example, branch `r2.8` for version 2.8.
*   Apply (that is, cherry-pick) the desired changes and resolve any code
    conflicts.
*   Run TensorFlow tests and ensure they pass.
*   [Build](https://www.tensorflow.org/install/source) the TensorFlow pip