#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_macros.h"
#include "tensorflow/c/tf_status.h"

// --------------------------------------------------------------------------
// C API for Graph. The API is under active development and eventually
// should allow registering a plugin graph optimizer with TensorFlow.
//
// Conventions:
//   * Struct prefix indicates whether struct fields should be filled by the

// TF_ExecuteOperation will, if in eager mode, execute, if in graph mode, maybe
// capture some inputs and then add a node in the graph. The output tensors are
// returned through the provided TF_OutputList.
// Any active tape will observe the effects of this execution.
void TF_ExecuteOperation(TF_AbstractOp* op, int num_inputs,
                         TF_AbstractTensor* const* inputs, TF_OutputList* o,
                         TF_Status* s);

  // TODO(b/172877902): These helper functions are currently used to support
  // PyFuncOp on TFRT, and might be useful for ops that directly use low
  // level TF APIs. Remove/replace the following functions when TFRT native
  // ops are implemented.
  //===--------------------------------------------------------------------===//
  // Create an abstract tensor handle from tensorflow::Tensor.

#define TENSORFLOW_C_EAGER_C_API_H_

// C API extensions to experiment with eager execution of kernels.
// WARNING: Unlike tensorflow/c/c_api.h, the API here is not guaranteed to be
// stable and can change without notice.

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

#ifdef __cplusplus
extern "C" {
#endif

typedef struct TFE_ContextOptions TFE_ContextOptions;

// Return a new options object.

#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/c/tf_status.h"
#include "xla/pjrt/c/pjrt_c_api.h"

// --------------------------------------------------------------------------
// C API for device. The API is under active development and eventually
// should allow registering a plugin device with TensorFlow.

#ifdef __cplusplus
extern "C" {
#endif

// TF_Device is a C wrapper to the C++ TF Device class. This is to be passed

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each
  // value records whether the graph has been mutated since the corresponding
  // session has been run (this is detected in RecordMutation function). If the

  // Tensor associated with `tensor_id` is deleted.
  void DeleteGradient(int64_t 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