* </ul>
 *
 * <p>This class uses (possibly repeated) invocations of {@link java.lang.System#gc()} to cause
 * finalization to happen. However, a call to {@code System.gc()} is specified to be no more than a
 * hint, so this technique may fail at the whim of the JDK implementation, for example if a user
 * specified the JVM flag {@code -XX:+DisableExplicitGC}. But in practice, it works very well for
 * ordinary tests.
 *

//   1. DENSE: each coordinate in this dimension is stored implicitly.
//   2. SPARSE_CSR: only the coordinates with non-zero elements are stored. The
//      compression technique is the same what CSR uses.
// More types like a sparse dimension with a different compression technique
// could be added to the list in the future.
enum DimensionType : byte {
  DENSE = 0,
  SPARSE_CSR = 1,
}

table Int32Vector {
  values:[int];
}

        p.setProperty("jcifs.smb.client.soTimeout", "1800000");
        p.setProperty("jcifs.netbios.cachePolicy", "1200");
        /*
         * The Filter can only work with NTLMv1 as it uses a man-in-the-middle
         * technique that NTLMv2 specifically thwarts. A real NTLM Filter would
         * need to do a NETLOGON RPC that JCIFS will likely never implement
         * because it requires a lot of extra crypto not used by CIFS.
         */

 * </ul>
 *
 * <p>This class uses (possibly repeated) invocations of {@link java.lang.System#gc()} to cause
 * finalization to happen. However, a call to {@code System.gc()} is specified to be no more than a
 * hint, so this technique may fail at the whim of the JDK implementation, for example if a user
 * specified the JVM flag {@code -XX:+DisableExplicitGC}. But in practice, it works very well for
 * ordinary tests.
 *

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// Package lzw implements the Lempel-Ziv-Welch compressed data format,
// described in T. A. Welch, “A Technique for High-Performance Data
// Compression”, Computer, 17(6) (June 1984), pp 8-19.
//
// In particular, it implements LZW as used by the GIF and PDF file
// formats, which means variable-width codes up to 12 bits and the first

// are merged together into a single JSON key, also
// to remove any extraneous JSON bodies.
//
// Go stdlib doesn't support parsing JSON with duplicate
// keys, so we need to use this technique to merge the
// keys.
func sanitizePolicy(r io.Reader) (io.Reader, error) {
	var buf bytes.Buffer
	e := json.NewEncoder(&buf)
	d := jstream.NewDecoder(r, 0).ObjectAsKVS()
	sset := set.NewStringSet()

//   1. DENSE: each coordinate in this dimension is stored implicitly.
//   2. SPARSE_CSR: only the coordinates with non-zero elements are stored. The
//      compression technique is the same what CSR uses.
// More types like a sparse dimension with a different compression technique
// could be added to the list in the future.
enum DimensionType : byte {
  DENSE = 0,
  SPARSE_CSR = 1,
}

table Int32Vector {
  values:[int];
}

    You can set `schema_extra` with a `dict` containing any additional data you would like to show up in the generated JSON Schema, including `examples`.

!!! tip
    You could use the same technique to extend the JSON Schema and add your own custom extra info.

    For example you could use it to add metadata for a frontend user interface, etc.

!!! info

        return HEADER_LENGTH;
    }
    boolean isResponse() {
        return ( flags & FLAGS_RESPONSE ) == FLAGS_RESPONSE;
    }

    /* 
     * For this packet deconstruction technique to work for
     * other networking protocols the InputStream may need
     * to be passed to the readXxxWireFormat methods. This is
     * actually purer. However, in the case of smb we know the

  /*
   * Leaving K and V as upper bounds rather than the actual key and value types allows type
   * parameters to be left implicit more often. CacheBuilder uses the same technique.
   */

  private MultimapBuilder() {}

  private static final int DEFAULT_EXPECTED_KEYS = 8;

  /** Uses a hash table to map keys to value collections. */