template <typename... LabelType>
int64_t TFE_MonitoringCounterReader::Read(const LabelType&... labels) {
  return counter->Read(labels...);
}

TFE_MonitoringCounterReader* TFE_MonitoringNewCounterReader(const char* name) {
  auto* result = new TFE_MonitoringCounterReader(name);

  return result;
}

int64_t TFE_MonitoringReadCounter0(TFE_MonitoringCounterReader* cell_reader) {
  int64_t result = cell_reader->Read();

  TapeVSpace vspace(ctx);
  std::vector<int64_t> target_tensor_ids = MakeTensorIDList(targets);
  std::vector<int64_t> source_tensor_ids = MakeTensorIDList(sources);
  tensorflow::gtl::FlatSet<int64_t> sources_set(source_tensor_ids.begin(),
                                                source_tensor_ids.end());
  std::unordered_map<int64_t, TapeTensor> sources_that_are_targets;

    return absl::OkStatus();
  }
  absl::Status SetAttrShape(const char* attr_name, const int64_t* dims,
                            const int num_dims) override {
    PartialTensorShape shape;
    if (num_dims >= 0) {
      shape = PartialTensorShape(absl::Span<const int64_t>(
          reinterpret_cast<const int64_t*>(dims), num_dims));
    }
    op_->node_builder.Attr(attr_name, shape);
    return absl::OkStatus();

  return th;
}

TFE_TensorHandle* DoubleTestMatrixTensorHandle(TFE_Context* ctx) {
  int64_t dims[] = {2, 2};
  double data[] = {1.0, 2.0, 3.0, 4.0};
  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_DOUBLE, &dims[0],
                                        sizeof(dims) / sizeof(int64_t), status);
  memcpy(TF_TensorData(t), &data[0], TF_TensorByteSize(t));

TFE_MonitoringNewCounterReader(const char* name);

// Reads the value of a counter that was created with 0 labels.
TF_CAPI_EXPORT extern int64_t TFE_MonitoringReadCounter0(
    TFE_MonitoringCounterReader*);

// Reads the value of specific cell of a counter that was created with 1 label.
TF_CAPI_EXPORT extern int64_t TFE_MonitoringReadCounter1(
    TFE_MonitoringCounterReader*, const char* label_value);

#ifdef __cplusplus
} /* end extern "C" */

  return num_dims;
}

int64_t TFE_TensorHandleNumElements(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return -1;
  }

  int64_t num_elements = -1;
  status->status = tensorflow::unwrap(h)->NumElements(&num_elements);
  return num_elements;
}

int64_t TFE_TensorHandleDim(TFE_TensorHandle* h, int dim_index,

    TF_DeleteShapeAndTypeList(output_shapes);
  }

  absl::optional<std::vector<int64_t>> make_shape(
      std::vector<int64_t>&& dims) const {
    return absl::make_optional(dims);
  }

  absl::optional<std::vector<int64_t>> unknown_shape() const {
    return absl::nullopt;
  }

  static constexpr int64_t kUnknownDim =
      shape_inference::InferenceContext::kUnknownDim;
  TF_Status* status_;

}

void TestEncodeDecode(int line, const std::vector<std::string>& data) {
  const int64_t n = data.size();
  absl::Status status;
  for (const std::vector<int64_t>& dims :
       std::vector<std::vector<int64_t>>{{n}, {1, n}, {n, 1}, {n / 2, 2}}) {
    // Create C++ Tensor
    Tensor src(tensorflow::DT_STRING, TensorShape(dims));
    for (int64_t i = 0; i < src.NumElements(); ++i) {
      src.flat<tstring>()(i) = data[i];
    }

  int64_t num_values = 1;
  for (int i = 0; i < num_dims; ++i) {
    num_values *= dims[i];
  }
  TF_Tensor* t =
      TF_AllocateTensor(TF_INT32, dims, num_dims, sizeof(int32_t) * num_values);
  memcpy(TF_TensorData(t), values, sizeof(int32_t) * num_values);
  return t;
}

TF_Tensor* Int32Tensor(const std::vector<int32_t>& values) {
  int64_t dims = values.size();
  return Int32Tensor(&dims, 1, values.data());
}

                   int64_t value) {
  desc->node_builder.Attr(attr_name, static_cast<int64_t>(value));
}

void TF_SetAttrIntList(TF_OperationDescription* desc, const char* attr_name,
                       const int64_t* values, int num_values) {
  desc->node_builder.Attr(
      attr_name, ArraySlice<const int64_t>(
                     reinterpret_cast<const int64_t*>(values), num_values));
}