struct TFE_MonitoringCounterReader {
  explicit TFE_MonitoringCounterReader(const char* name) {
    counter = std::make_unique<
        ::tensorflow::monitoring::testing::CellReader<int64_t>>(name);
  }
  template <typename... LabelType>
  int64_t Read(const LabelType&... labels);
  std::unique_ptr<::tensorflow::monitoring::testing::CellReader<int64_t>>
      counter;
};

// TODO(fishx): Move these monitoring APIs into a separate file.
// -----------------------------------------------------------------------------
// Monitoring Counter APIs.
// These APIs de-templated monitoring Counter for swig.

typedef struct TFE_MonitoringCounterCell TFE_MonitoringCounterCell;

// Atomically increments the value of the cell. The value must be non-negative.

TFE_TensorHandle* TestTensorHandleWithDimsInt(TFE_Context* ctx, int data[],
                                              int64_t dims[], int num_dims);

// Return a tensor handle with given type, values and dimensions.
template <class T, TF_DataType datatype>
TFE_TensorHandle* TestTensorHandleWithDims(TFE_Context* ctx, const T* data,
                                           const int64_t* dims, int num_dims) {
  TF_Status* status = TF_NewStatus();

                                                       TF_Status* status) const;

  // Construct a parallel tensor consisting of the scalar values from `values`.
  template <typename DataType>
  std::unique_ptr<ParallelTensor> ScalarsFromSequence(
      absl::Span<const DataType> values, TFE_Context* context,
      TF_Status* status) const;

// (also known as adjoint function) to compute, given downstream gradients,
// upstream gradients.
//
// TODO(apassos) provide concrete template instantiations for TFE_TensorHandle
// specialization, which is blocked by quite a few things needing to loop back
// into python now.
template <typename Gradient, typename BackwardFunction, typename TapeTensor>
class VSpace {
 public:
  virtual ~VSpace() {}

#include "tensorflow/core/lib/monitoring/sampler.h"
#include "tensorflow/core/platform/types.h"

struct TFE_MonitoringCounterCell {
  tensorflow::monitoring::CounterCell cell;
};

template <int NumLabels>
struct TFE_MonitoringCounter {
  template <typename... LabelDesc>
  TFE_MonitoringCounter(const char* name, const char* description,
                        LabelDesc&&... label) {

                absl::Span<AbstractTensorHandle*> outputs, bool use_function);

Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx);

// Return a tensor handle with given type, values and dimensions.
template <class T, TF_DataType datatype>
Status TestTensorHandleWithDims(AbstractContext* ctx, const T* data,
                                const int64_t* dims, int num_dims,
                                AbstractTensorHandle** tensor) {