// provided inputs automatically.
// Note(bmzhao): This class is mainly intended to house low-level reusable
// function logic between SignatureDefFunction and ConcreteFunction, which
// present higher level interfaces. This type does *not* hold any "function
// metadata".
class FlatTensorFunction {
 public:
  // Factory for creating a FlatTensorFunction.
  //
  // Params:

                                                      const char* function_path,
                                                      TF_Status* status) {
  tensorflow::ConcreteFunction* result = nullptr;
  tensorflow::Status get_function_status =
      tensorflow::unwrap(model)->GetFunction(function_path, &result);
  status->status.Update(get_function_status);
  if (!get_function_status.ok()) {

#define TENSORFLOW_C_EXPERIMENTAL_SAVED_MODEL_PUBLIC_SAVED_MODEL_API_H_

#include "tensorflow/c/c_api_macros.h"
#include "tensorflow/c/experimental/saved_model/public/concrete_function.h"
#include "tensorflow/c/experimental/saved_model/public/concrete_function_list.h"
#include "tensorflow/c/experimental/saved_model/public/signature_def_function.h"
#include "tensorflow/c/tf_status.h"

#ifdef __cplusplus

* Introducing `tf.types.experimental.AtomicFunction` as the fastest way to perform TF computations in Python.

    * Can be accessed through `inference_fn` property of `ConcreteFunction`s
    * Does not support gradients.