for (const tensorflow::Edge* edge : control_edges) {
    graph->graph.RemoveControlEdge(edge);
  }
}

void TF_SetRequireShapeInferenceFns(TF_Graph* graph, bool require) {
  mutex_lock l(graph->mu);
  graph->refiner.set_require_shape_inference_fns(require);
}

void TF_ExtendSession(TF_Session* session, TF_Status* status) {
  ExtendSessionGraphHelper(session, status);
  session->extend_before_run = false;
}

        body_nodes->push_back(node);
      } else {
        // This node is referenced in inputs. Currently, we place an
        // artificial restriction and require that when num_opers=-1, such
        // nodes must have a single output.
        if (node->num_outputs() != 1) {
          return InvalidArgument(
              "When `num_opers` is set to -1, nodes referenced in `inputs` "

      const auto func_op = GetFunc(ctx, default_value.func(), status);
      if (!status->status.ok()) return;
      // TODO(nareshmodi): TFE_OpSetAttrFunction and TFE_OpSetAttrFunctionList
      // require TFE_Op* and just convert it internally a NameAttrValue, so
      // consider adding an overload to the C API to make this case easier.
      TFE_OpSetAttrFunction(op, attr_name, func_op);
      TFE_DeleteOp(func_op);

        int64_t bytes_transferred;
        bytes_transferred = block_fetcher_(key.first, key.second, block_size_,
                                           block->data.data(), status);
        block->mu.Lock();  // Reacquire the lock immediately afterwards
        if (TF_GetCode(status) == TF_OK) {
          block->data.resize(bytes_transferred, 0);
          // Shrink the data capacity to the actual size used.

  // root directory. Otherwise, we need to add the `<scheme>://` in front of
  // this path.
  //
  // Note that some filesystem might require a different approach here, for
  // example they might require the root directory path to be in a special
  // format, etc. When we get there, we might decide to move this class to
  // `modular_filesystem_test.h` and extend the instantiation to also take as

// TODO(ashankar): Use gmock matchers instead?
// (https://github.com/google/googletest/blob/master/googlemock/docs/CookBook.md#writing-new-parameterized-matchers-quickly)
// That will require setting up the tensorflow build with gmock.
#define EXPECT_TF_META(attr_name, expected_list_size, expected_type, \
                       expected_total_size)                          \