typedef struct TFE_MonitoringCounterReader TFE_MonitoringCounterReader;

// Returns a handle to be used for reading values from streamz counter. The
// counter can have been created with any number of labels.
TF_CAPI_EXPORT extern TFE_MonitoringCounterReader*
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(

//
// The filled `device` struct and the allocated `device_info` struct may be
// passed to TFE_RegisterCustomDevice. The `device_name` arguments must match.
void AllocateParallelDevice(const char* device_name,
                            const char* const* underlying_devices,
                            int num_underlying_devices,
                            TFE_CustomDevice* device, void** device_info);

}  // namespace parallel_device

  // less synchronization than a thread pool would for this task, since Execute
  // acquires each thread in order (and so only one Execute will schedule
  // blocking collective operations at a time), and avoids some dynamic
  // allocation/scheduling.
  //
  // TODO(allenl): Keep a map from outer thread to list of inner threads rather
  // than a single list of threads so aliased nested parallel devices don't

// and sets 'device_name' accordingly.
// `device_type` must be either "GPU" or "TPU".
bool GetDeviceName(TFE_Context* ctx, tensorflow::string* device_name,
                   const char* device_type);

// Create a ServerDef with the given `job_name` and add `num_tasks` tasks in it.
tensorflow::ServerDef GetServerDef(const tensorflow::string& job_name,
                                   int num_tasks);

// Set XLA's internal BuildXlaOpsPassFlags.tf_xla_enable_lazy_compilation to the
// value of 'enabled'. Also returns the original value of that flag.
//
// Use in tests to allow XLA to fallback to TF classic. This has global effect.
TF_CAPI_EXPORT unsigned char TF_SetXlaEnableLazyCompilation(
    unsigned char enable);
TF_CAPI_EXPORT unsigned char TF_SetTfXlaCpuGlobalJit(unsigned char enable);

#ifndef TENSORFLOW_C_EAGER_DLPACK_H_
#define TENSORFLOW_C_EAGER_DLPACK_H_

#include "tensorflow/c/eager/c_api.h"

namespace tensorflow {

// PyCapsule name for DLPack Tensor
const char* const kDlTensorCapsuleName = "dltensor";

// Converts eager tensor handle to DLPack (DLManagedTensor*), and return the
// void* for further PyCapsule construction.

  virtual Status SetAttrFloat(const char* attr_name, float value) = 0;
  virtual Status SetAttrBool(const char* attr_name, bool value) = 0;
  virtual Status SetAttrType(const char* attr_name, DataType value) = 0;
  virtual Status SetAttrShape(const char* attr_name, const int64_t* dims,
                              const int num_dims) = 0;
  virtual Status SetAttrShape(const char* attr_name,

TF_CAPI_EXPORT extern TF_AttrType TFE_OpNameGetAttrType(
    TFE_Context* ctx, const char* op_or_function_name, const char* attr_name,
    unsigned char* is_list, TF_Status* status);

TF_CAPI_EXPORT extern void TFE_OpSetAttrString(TFE_Op* op,
                                               const char* attr_name,
                                               const void* value,

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) {
    counter = absl::WrapUnique(tensorflow::monitoring::Counter<NumLabels>::New(
        name, description, label...));
  }

}

// Exercises tensorflow's C API.
int main(int argc, char** argv) {
  TF_InitMain(argv[0], &argc, &argv);

  struct TF_StringStream* s = TF_GetLocalTempDirectories();
  const char* path;

  if (!TF_StringStreamNext(s, &path)) {
    fprintf(stderr, "TF_GetLocalTempDirectories returned no results\n");
    return 1;
  }

  char file_name[100];
  time_t t = time(NULL);