#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/platform/intrusive_ptr.h"
#include "tensorflow/core/platform/refcount.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class FunctionRecord;

// A traced function: this hides the complexity of converting the serialized
// representation between various supported formats e.g. FunctionDef and Mlir
// function.

#define TENSORFLOW_C_EAGER_GRAPH_FUNCTION_H_

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/refcount.h"
namespace tensorflow {
namespace tracing {
namespace graph {
using tensorflow::AbstractFunction;
// Thin wrapper around a FunctionDef.
class GraphFunction : public AbstractFunction {
 public:
  explicit GraphFunction(FunctionDef fdef);

#include "tensorflow/core/lib/gtl/flatmap.h"
#include "tensorflow/core/lib/gtl/flatset.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace eager {

// Represents an entry in the tape.
template <typename BackwardFunction, typename TapeTensor>
struct OpTapeEntry {
  string op_type;
  std::vector<TapeTensor> output_tensor_info;

#define TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_DISTRIBUTED_MANAGER_H_

#include <cstdint>
#include <string>

#include "tensorflow/core/platform/status.h"

namespace tsl {
class CoordinationServiceAgent;
}

namespace tensorflow {
class ImmediateExecutionContext;
class ServerDef;
class WorkerEnv;
class WorkerCacheInterface;

class ImmediateExecutionDistributedManager {
 public:

#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Builds and returns a `TracingContext` using the default tracing impl.
AbstractContext* BuildFunction(const char* fn_name);

// Creates parameters (placeholders) in the tracing `ctx` using the shape and