// added since the last TF_SessionRun() call.
      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();

using tensorflow::FunctionDef;
using tensorflow::Node;
using tensorflow::NodeBuilder;
using tensorflow::Status;
using tensorflow::errors::InvalidArgument;

namespace {
typedef std::unique_ptr<TF_Function, decltype(&TF_DeleteFunction)>
    UniqueFuncPtr;
}

// struct TF_Operation { tensorflow::Node node; };
static TF_Operation* ToTF_Operation(Node* node) {
  return static_cast<TF_Operation*>(static_cast<void*>(node));

}

TEST_P(CppGradients, TestMatMulGrad) {
  // TODO(vnvo2409): Figure out why `gradient_checker` does not work very
  // well with `MatMul` and remove `TestMatMul*` in
  // `mnist_gradients_test` when done.
  GTEST_SKIP();

  float A_vals[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f};
  int64_t A_dims[] = {3, 3};
  AbstractTensorHandlePtr A;
  {
    AbstractTensorHandle* A_raw;

  EXPECT_NE(TF_GetCode(status.get()), TF_CANCELLED);
  EXPECT_EQ(TF_GetCode(status.get()), TF_INVALID_ARGUMENT);
  EXPECT_THAT(TF_Message(status.get()), HasSubstr("assertion failed"));

  // Note that future collectives with the same context do not work at the
  // moment; once canceled, the collective executor requires the program to be
  // restarted / context to be reset.
}

    }
  }
  return found_dtype && found_value;
}

bool IsAddN(const tensorflow::NodeDef& node_def, int n) {
  if (node_def.op() != "AddN" || node_def.name() != "add" ||
      node_def.input_size() != n) {
    return false;
  }
  bool found_t = false;
  bool found_n = false;
  for (const auto& attr : node_def.attr()) {
    if (attr.first == "T") {
      if (attr.second.type() == tensorflow::DT_INT32) {

  options->guard_size = 0;
  options->numa_node = -1;
}

TF_Thread* TF_StartThread(const TF_ThreadOptions* options,
                          const char* thread_name, void (*work_func)(void*),
                          void* param) {
  ::tensorflow::ThreadOptions cc_options;
  cc_options.stack_size = options->stack_size;
  cc_options.guard_size = options->guard_size;
  cc_options.numa_node = options->numa_node;

// accessing local paths). This test suite tests exactly one scheme for each
// invocation. By default, we are testing all schemes available but this can be
// restricted by using `--schemes` to specify a set of schemes to test.
//
// Example invocation:
//  bazel test //tensorflow/c/experimental/filesystem:modular_filesystem_test \\
//  --test_arg=--dso=/path/to/one.so --test_arg=--dso=/path/to/another.so \\

  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());

  TF_DeleteAbstractOp(add_op);

  TF_AbstractFunction* func =
      TF_FinalizeFunction(graph_ctx, add_outputs, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  // Note: TF_OutputList does not own the underlying AbstractTensors, those
  // need to be deleted explicitly.
  TF_DeleteAbstractTensor(TF_OutputListGet(add_outputs, 0));

  // Build eager context.

    TF_EXCLUSIVE_LOCKS_REQUIRED(fn_body->mu) {
  if (num_opers == -1) {
    for (const Node* node : fn_body->graph.op_nodes()) {
      const auto& iter = input_nodes.find(node);
      if (iter == input_nodes.end()) {
        // This node is not referenced in inputs. Add it to the body.
        body_nodes->push_back(node);
      } else {
        // This node is referenced in inputs. Currently, we place an