TF_CAPI_EXPORT extern void TF_DeleteGraphProperties(
    TF_GraphProperties* graph_properties);

// Infer tensor shapes through abstract interpretation.
// If assume_valid_feeds is true, it can help infer shapes in the fanout of fed
// nodes. This may cause incorrectness in graph analyses, but is useful for
// simulation or scheduling.
// If aggressive_shape_inference is true, nodes are executed on the host to

                                                           TF_DeleteStatus);

  TF_Operation* feed = Placeholder(func_graph.get(), s.get());
  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,

   * (Applicable also to display devices and the skip function on punched cards.)
   *
   * @since 8.0
   */
  public static final byte HT = 9;

  /**
   * Line Feed ('\n'): A format effector which controls the movement of the printing position to the
   * next printing line. (Applicable also to display devices.) Where appropriate, this character may

            protected PathMappingHelper getPathMappingHelper() {
                return new PathMappingHelper();
            }
        };
        fessXpathTransformer.init();
        fessXpathTransformer.convertUrlMap.put("feed:", "http:");

        List<RequestData> urlList = new ArrayList<>();

        urlList = fessXpathTransformer.convertChildUrlList(urlList);
        assertEquals(0, urlList.size());

        urlList.clear();

   * (Applicable also to display devices and the skip function on punched cards.)
   *
   * @since 8.0
   */
  public static final byte HT = 9;

  /**
   * Line Feed ('\n'): A format effector which controls the movement of the printing position to the
   * next printing line. (Applicable also to display devices.) Where appropriate, this character may

 *
 * <p>Hasher accepts primitive data types, but can also accept any Object of type {@code T} provided
 * that you implement a {@link Funnel}{@code <T>} to specify how to "feed" data from that object
 * into the function. (See {@linkplain Hasher#putObject an example} of this.)
 *
 * <p><b>Compatibility note:</b> Throughout this API, multibyte values are always interpreted in

 *       {@code Number}, and primitive varargs are supported.
 *   <li>Or, to avoid storing up all the data first, create a {@link StatsAccumulator} instance,
 *       feed values to it as you get them, then call {@link StatsAccumulator#snapshot}.
 * </ul>
 *
 * <p>Static convenience methods called {@code meanOf} are also provided for users who wish to
 * calculate <i>only</i> the mean.
 *

  TF_Operation* op;
  Split3Helper(input, graph, s, name, &op);
  return op;
}

bool IsPlaceholder(const tensorflow::NodeDef& node_def) {
  if (node_def.op() != "Placeholder" || node_def.name() != "feed") {
    return false;
  }
  bool found_dtype = false;
  bool found_shape = false;
  for (const auto& attr : node_def.attr()) {
    if (attr.first == "dtype") {

//
// Gradient is the type returned by gradient functions. In Python TF it's either
// Tensor or IndexedSlices or None, which here we map to nullptr. Gradients need
// to allow their size to be computed and they need to be passable to a backward
// function and deleted (as the backprop code creates lots of gradients the user
// is not interested in).
//

   * omitted} or {@linkplain #withPadChar(char) replaced}.
   *
   * <p>No line feeds are added by default, as per <a
   * href="http://tools.ietf.org/html/rfc4648#section-3.1">RFC 4648 section 3.1</a>, Line Feeds in
   * Encoded Data. Line feeds may be added using {@link #withSeparator(String, int)}.
   */
  public static BaseEncoding base64() {
    return BASE64;
  }