// 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,
                                           TF_DataType dtype, TF_Shape shape,

// Monitoring Sampler APIs.
// These APIs de-templated monitoring Sampler for swig.

typedef struct TFE_MonitoringSamplerCell TFE_MonitoringSamplerCell;

// Atomically add the value of the cell.
TF_CAPI_EXPORT extern void TFE_MonitoringSamplerCellAdd(
    TFE_MonitoringSamplerCell* cell, double value);

// Retrieves the current value of the cell. The return value is a HistogramProto

// 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);

// Create a ServerDef with job name "localhost" and add `num_tasks` tasks in it.
tensorflow::ServerDef GetServerDef(int num_tasks);

// Create a multi-client ServerDef with the given `job_name`, add `num_tasks`

// * int is used as an index into arrays.
// * Deletion functions are safe to call on nullptr.
//
// Questions left to address:
// * Might at some point need a way for callers to provide their own Env.
// * Maybe add TF_TensorShape that encapsulates dimension info.
//
// Design decisions made:
// * Backing store for tensor memory has an associated deallocation
//   function.  This deallocation function will point to client code

                                              TF_Status* out_status);

// Sets the attribute attr_name to be a function specified by 'function'.
//
// TODO(ashankar,iga): Add this functionality to the C API for graph
// construction. Perhaps we want an AttrValueMap equivalent in the C API?
TF_CAPI_EXPORT extern void TFE_OpSetAttrFunction(TFE_Op* op,

#define WIN32_LEAN_AND_MEAN
#include <windows.h>
#include <process.h>
#include "_cgo_export.h"

__stdcall
static unsigned int
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;
	uintptr_t thread_id[MaxThread];
	
	if(nthread > MaxThread)
		nthread = MaxThread;
	for(i=0; i<nthread; i++)

#include <pthread.h>
#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++)

// Caller must call TF_DeleteTensor() over the returned tensor. If the queue is
// empty, this call is blocked.
//
// Tensors are enqueued via the corresponding TF enqueue op.
// TODO(hongm): Add support for `timeout_ms`.
TF_CAPI_EXPORT extern TF_Tensor* TF_DequeueNamedTensor(TF_Session* session,
                                                       int tensor_id,

  // Runs forward autodiff. Should be called whenever a new operation is
  // available and the accumulator is active.
  //
  // Like GradientTape::RecordOperation, this method takes the operation type
  // `op_type` (e.g. "Add"), the operation's inputs (`input_tensors`,
  // `input_tensor_id`, and `input_dtypes`; the latter two are somewhat
  // redundant but taken as arguments to avoid repeatedly fetching these values

                          const char* name = "scalar");

TF_Operation* Add(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                  TF_Status* s, const char* name = "add");

TF_Operation* AddNoCheck(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                         TF_Status* s, const char* name = "add");

TF_Operation* AddWithCtrlDependency(TF_Operation* l, TF_Operation* r,