if (values.size() != num_underlying_devices()) {
    TF_SetStatus(
        status, TF_INVALID_ARGUMENT,
        "Number of values did not match number of underlying devices.");
    return nullptr;
  }
  TF_DataType datatype_enum(
      static_cast<TF_DataType>(DataTypeToEnum<DataType>().value));
  for (int device_index = 0; device_index < num_underlying_devices();
       ++device_index) {

// (for now at least).
// Implementations of the context may contain some state e.g. an execution
// environment, a traced representation etc.
class AbstractContext {
 protected:
  enum AbstractContextKind { kGraph, kMlir, kEager, kTfrt, kTape, kOpHandler };
  explicit AbstractContext(AbstractContextKind kind) : kind_(kind) {}
  virtual ~AbstractContext() {}

 public:

#include "_cgo_export.h"

static void*
addThread(void *p)
{
	int i, max;
	
	max = *(int*)p;
	for(i=0; i<max; i++)
		Add(i);
	return 0;
}

void
doAdd(int max, int nthread)
{
	enum { MaxThread = 20 };
	int i;
	pthread_t thread_id[MaxThread];
	
	if(nthread > MaxThread)
		nthread = MaxThread;
	for(i=0; i<nthread; i++)
		pthread_create(&thread_id[i], 0, addThread, &max);

// representation between various supported formats e.g. FunctionDef and Mlir
// function.
class AbstractFunction : public core::RefCounted {
 protected:
  enum AbstractFunctionKind { kGraph, kMlir };
  explicit AbstractFunction(AbstractFunctionKind kind) : kind_(kind) {}

 public:
  // Returns which subclass is this instance of.

  virtual Status SetAttrTypeList(const char* attr_name, const DataType* values,
                                 int num_values) = 0;
  virtual Status SetAttrBoolList(const char* attr_name,
                                 const unsigned char* values,
                                 int num_values) = 0;
  virtual Status SetAttrShapeList(const char* attr_name, const int64_t** dims,

                                                 TF_Status* s);
void TF_DeleteExecutionContext(TF_ExecutionContext*);

// Represents a (partially-defined) shape.
typedef struct TF_Shape {
  int num_dims;  // Must be >= -1; -1 represents unknown rank.
  int64_t* dim_sizes;
} TF_Shape;

// Add a new parameter to a TensorFlow Function.
TF_AbstractTensor* TF_AddFunctionParameter(TF_ExecutionContext* func,

// Custom devices must use TFE_NewCustomDeviceTensorHandle instead.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandleFromDeviceMemory(
    TFE_Context* ctx, const char* device_name, TF_DataType, const int64_t* dims,
    int num_dims, void* data, size_t len,
    void (*deallocator)(void* data, size_t len, void* arg),
    void* deallocator_arg, TF_Status* status);

// Retrieves the address space (i.e. job, replia, task) of the local host and

    TF_Status* status);

// Controls how to act when we try to run an operation on a given device but
// some input tensors are not on that device.
// LINT.IfChange
// Note: Keep in sync with internal copy of enum in eager/context.h.
typedef enum TFE_ContextDevicePlacementPolicy {
  // Running operations with input tensors on the wrong device will fail.
  TFE_DEVICE_PLACEMENT_EXPLICIT = 0,
  // Copy the tensor to the right device but log a warning.

namespace tensorflow {

// Abstract interface to a Tensor handle in either tracing or immediate
// execution mode.
class AbstractTensorHandle : public core::RefCounted {
 protected:
  enum AbstractTensorHandleKind { kGraph, kMlir, kEager, kTfrt, kCustomDevice };
  explicit AbstractTensorHandle(AbstractTensorHandleKind kind) : kind_(kind) {}
  ~AbstractTensorHandle() override {}

 public:

namespace tensorflow {
class EagerExecutor;
class EagerContext;
class CustomDevice;
class CustomDeviceOpHandler;
class Device;

// LINT.IfChange
// Note: Keep in sync with exported copy of enum in eager/c_api.h.
enum ContextDevicePlacementPolicy {
  // Running operations with input tensors on the wrong device will fail.
  DEVICE_PLACEMENT_EXPLICIT = 0,
  // Copy the tensor to the right device but log a warning.