input_tensors.empty()
                        ? nullptr
                        : const_cast<TF_Tensor**>(input_tensors.data()),
                    /*input_tensors_as_shapes*/ nullptr,
                    /*input_resource_shapes_and_types*/ nullptr, &output_shapes,
                    /*output_resource_shapes_and_types*/ nullptr, status_);
    CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);

namespace tensorflow {
namespace checkpoint {

class TensorSliceReader;

CheckpointReader::CheckpointReader(const string& filename, TF_Status* status)
    : reader_(nullptr),
      v2_reader_(nullptr),
      var_to_shape_map_(nullptr),
      var_to_data_type_map_(nullptr) {
  // Depending on whether this is a V2 ckpt, initializes "reader_" or
  // "v2_reader_".
  std::vector<string> v2_path;

  if (!s.ok()) {
    return nullptr;
  }
  s = op->AddInputList(gradient_tensors);
  if (!s.ok()) {
    return nullptr;
  }

  int num_outputs = 1;
  std::vector<AbstractTensorHandle*> outputs(num_outputs);
  s = op->Execute(absl::Span<AbstractTensorHandle*>(outputs), &num_outputs);
  if (!s.ok()) {
    return nullptr;
  }
  return outputs[0];
}

  TF_Status* status = TF_NewStatus();

  TF_DeleteStatus(nullptr);
  TF_DeleteBuffer(nullptr);
  TF_DeleteTensor(nullptr);
  TF_DeleteSessionOptions(nullptr);
  TF_DeleteGraph(nullptr);
  TF_DeleteImportGraphDefOptions(nullptr);
  TF_DeleteImportGraphDefResults(nullptr);
  TF_DeleteFunction(nullptr);
  TF_DeleteSession(nullptr, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  func_ = TF_GraphToFunction(
      func_graph.get(), "func", /*append_hash_to_fn_name=*/false, -1,
      /*opers=*/nullptr, 0, nullptr, 3, outputs,
      /*output_names=*/nullptr,
      /*opts=*/nullptr, /*description=*/nullptr, s.get());
  ASSERT_EQ(TF_OK, TF_GetCode(s.get())) << TF_Message(s.get());
  ASSERT_NE(func_, nullptr);

  // Verify that FunctionDef has 2 attributes, "v1" and "v2".

  LoggingDevice* dev = reinterpret_cast<LoggingDevice*>(device_info);
  TFE_TensorHandle* t = TFE_TensorHandleCopyToDevice(
      tensor, context, dev->underlying_device.c_str(), status);
  if (TF_GetCode(status) != TF_OK) return nullptr;
  auto dst = std::make_unique<LoggedTensor>(t);
  *(dev->arrived_flag) = true;
  return MakeLoggedTensorHandle(context, dev->device_name, std::move(dst),
                                status);
}

                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,
            std::unique_ptr<TensorSliceReader::VarToDataTypeMap> >
  BuildV2VarMaps();

// all be equal to `num_shapes_and_types`. If `ranks[i] != -1`, (i.e., if the
// rank is known), then it must be equal to the length of `shapes[i]`; if
// `ranks[i] == 1`, then `shapes[i]` may be nullptr.
//
// TODO(akshayka): Implement a corresponding getter method.
void TF_GraphSetOutputHandleShapesAndTypes(TF_Graph* graph, TF_Output output,
                                           int num_shapes_and_types,

*   Fixes an undefined behavior arising from reference binding to nullptr in
    `RaggedTensorToSparse`
    ([CVE-2021-37656](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-37656))
*   Fixes an undefined behavior arising from reference binding to nullptr in
    `MatrixDiagV*` ops
    ([CVE-2021-37657](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-37657))