graph_def->length));
  TF_Buffer graph_def_buffer;
  graph_def_buffer.data = reinterpret_cast<const void*>(&graph_def_proto);
  graph_def_buffer.length = sizeof(tensorflow::GraphDef*);
  TF_ImportGraphDefResults* results =
      TF_GraphImportGraphDefWithResultsNoSerialization(graph, &graph_def_buffer,
                                                       opts, s);

  const int BUFFER_SIZE = 10;
  char buffer[BUFFER_SIZE];
  std::strncpy(buffer, "VALID", BUFFER_SIZE);
  TFE_OpSetAttrString(op, "padding", buffer, std::strlen(buffer));
  // Overwriting value in "buffer", should be fine since TFE_Op
  // shouldn't be holding on to it.
  std::strncpy(buffer, "NHWC", BUFFER_SIZE);
  TFE_OpSetAttrString(op, "data_format", buffer, std::strlen(buffer));

  void (*cleanup)(TF_WritableFile* file);

  /// Appends `buffer` of size `n` to `*file`.
  ///
  /// Core TensorFlow owns `buffer` and guarantees at least `n` bytes of storage
  /// that can be used to write data.
  ///
  /// Note: the `buffer` argument is NOT a null terminated string!
  ///
  /// Plugins:

  // Test we can retrieve function OpDef from graph
  TF_Buffer* buffer = TF_NewBuffer();
  TF_GraphGetOpDef(host_graph_, func_name_, buffer, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Sanity check returned OpDef
  string data(static_cast<const char*>(buffer->data), buffer->length);
  OpDef op_def;
  op_def.ParseFromString(data);

//
// Params:
//  op_list_buffer - TF_Buffer instance containing serialized OpList
//    protocol buffer. (See
//    https://www.tensorflow.org/code/tensorflow/core/framework/op_def.proto
//    for the OpList proto definition).
//  status - Set to OK on success and an appropriate error on failure.
TF_CAPI_EXPORT extern TF_ApiDefMap* TF_NewApiDefMap(TF_Buffer* op_list_buffer,