node_def.set_name(op->Name());
  node_def.set_op(op->Name());
  for (int i = 0; i < num_inputs; ++i) {
    node_def.add_input("dummy_input");
  }
  OperationFromInterface(op)->Attrs().FillAttrValueMap(node_def.mutable_attr());

  const tensorflow::OpRegistrationData* op_reg_data;
  status->status =
      tensorflow::OpRegistry::Global()->LookUp(node_def.op(), &op_reg_data);

      "      }"
      "    }"
      "    node_def {"
      "      name: 'read0'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"
      "      device: '/job:localhost/replica:0/task:0/device:CPU:0'"
      "      attr {"
      "        key: 'dtype'"
      "        value {"
      "          type: DT_FLOAT"
      "        }"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read1'"

    for (const NodeDef& node_def : fdef.node_def()) {
      for (int i = 0; i < node_def.input_size(); ++i) {
        const string& in = node_def.input(i);
        const auto& v =
            a_edges.insert({in, strings::StrCat(node_def.name(), ":", i)});
        ASSERT_TRUE(v.second) << "Duplicate edge " << in << " -> "
                              << strings::StrCat(node_def.name(), ":", i)

  EXPECT_TRUE(neg == neg2);
  NodeDef node_def2;
  ASSERT_TRUE(GetNodeDef(neg2, &node_def2));
  EXPECT_EQ(node_def.DebugString(), node_def2.DebugString());

  TF_Operation* feed2 = TF_GraphOperationByName(graph, "feed");
  EXPECT_TRUE(feed == feed2);
  ASSERT_TRUE(GetNodeDef(feed, &node_def));
  ASSERT_TRUE(GetNodeDef(feed2, &node_def2));
  EXPECT_EQ(node_def.DebugString(), node_def2.DebugString());

#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/framework/graph_to_functiondef.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/tensor.pb.h"  // NOLINT
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/graph/graph.h"

// Changes an attr value in the node_def Protocol Buffer and sets a status upon
// completion.
TF_CAPI_EXPORT extern void TF_SetAttr(TF_Graph* graph, TF_Operation* op,
                                      const char* attr_name,
                                      TF_Buffer* attr_value_proto,
                                      TF_Status* status);

// Clears the attr in the node_def Protocol Buffer and sets a status upon

      "    signature {"
      "      name: 'FunctionWith__OP_NAME__'"
      "      output_arg {"
      "        name: 'out'"
      "        type: DT_STRING"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'error_op'"
      "      op: '__OP_NAME__'"
      "    }"
      "    ret {"
      "      key: 'out'"
      "      value: 'error_op:out'"
      "    }";

      for (auto id = session->last_num_graph_nodes; id < num_nodes; ++id) {
        Node* const node = graph.FindNodeId(id);
        if (node != nullptr && node->IsOp()) {
          NodeDef* const node_def = graph_def.add_node();
          *node_def = node->def();
        }
      }
      *graph_def.mutable_library() = graph.flib_def().ToProto();
      if (flags::Global().more_stack_traces.value()) {

                                                     const TF_DataType* values,
                                                     int num_values);

// Checks the tensorflow::NodeDef built via the methods above to see if it can
// run on device_type.
TF_CAPI_EXPORT extern void TF_AttrBuilderCheckCanRunOnDevice(
    TF_AttrBuilder* builder, const char* device_type, TF_Status* status);

*   `uniform_unit_scaling_initializer()` no longer takes a `full_shape` arg,
    instead relying on the partition info passed to the initializer function
    when it's called.
*   The NodeDef protocol message is now defined in its own file `node_def.proto`
    `instead of graph.proto`.
*   `ops.NoGradient` was renamed `ops.NotDifferentiable`. `ops.NoGradient` will
    be removed soon.