assertThat(endpointPair.source()).isEqualTo(node);
        assertThat(endpointPair.target()).isEqualTo(endpointPair.adjacentNode(node));
      }

      for (Integer adjacentNode : network.adjacentNodes(node)) {
        Set<String> edges = network.edgesConnecting(node, adjacentNode);
        Set<String> antiParallelEdges = network.edgesConnecting(adjacentNode, node);

        assertThat(endpointPair.source()).isEqualTo(node);
        assertThat(endpointPair.target()).isEqualTo(endpointPair.adjacentNode(node));
      }

      for (Integer adjacentNode : network.adjacentNodes(node)) {
        Set<String> edges = network.edgesConnecting(node, adjacentNode);
        Set<String> antiParallelEdges = network.edgesConnecting(adjacentNode, node);

     * @param session the {@link Session}, must not be {@code null}
     * @param node the {@link Node} to flatten, must not be {@code null}
     * @param scope an optional {@link PathScope} to filter out dependencies
     * @return the flattened list of node
     * @throws DependencyResolverException
     */
    List<Node> flatten(@Nonnull Session session, @Nonnull Node node, @Nullable PathScope scope)
            throws DependencyResolverException;

  @CheckForNull
  V putEdgeValue(EndpointPair<N> endpoints, V value);

  /**
   * Removes {@code node} if it is present; all edges incident to {@code node} will also be removed.
   *
   * @return {@code true} if the graph was modified as a result of this call
   */
  @CanIgnoreReturnValue
  boolean removeNode(N node);

  /**
   * Removes the edge connecting {@code nodeU} to {@code nodeV}, if it is present.
   *

  // implementation will use to handle pods of this class. The possible values
  // are specific to the node & CRI configuration.  It is assumed that all
  // handlers are available on every node, and handlers of the same name are
  // equivalent on every node.
  // For example, a handler called "runc" might specify that the runc OCI
  // runtime (using native Linux containers) will be used to run the containers

  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each
  // value records whether the graph has been mutated since the corresponding

                        final Node node = nodeList.get(i);
                        strList.add(node.getTextContent());
                    }
                    buf.append(getResultDataBody(entry.getKey(), strList));
                    break;
                case NODE:
                    final Node node = (Node) xObj.value();

 * implement it:
 *
 * <pre>{@code
 * // won't work
 * TreeTraverser<NodeType> traverser = node -> node.getChildNodes();
 * }</pre>
 *
 * Instead, you can pass a lambda expression to the {@code using} factory method:
 *
 * <pre>{@code
 * TreeTraverser<NodeType> traverser = TreeTraverser.using(node -> node.getChildNodes());
 * }</pre>
 *
 * @author Louis Wasserman
 * @since 15.0

  // A list of node selector requirements by node's fields.
  // +optional
  repeated NodeSelectorRequirement matchFields = 2;
}

// NodeSpec describes the attributes that a node is created with.
message NodeSpec {
  // PodCIDR represents the pod IP range assigned to the node.
  // +optional
  optional string podCIDR = 1;

  // podCIDRs represents the IP ranges assigned to the node for usage by Pods on that node. If this

    discussions(categoryId: $category_id, first: 100) {
      nodes {
        title
        id
        number
        labels(first: 10) {
          edges {
            node {
              id
              name
            }
          }
        }
      }
    }
  }
}
"""

translation_discussion_query = """
query Q($after: String, $discussion_number: Int!) {