// `src_names` are owned by and have the lifetime of `results`.
TF_CAPI_EXPORT extern void TF_ImportGraphDefResultsMissingUnusedInputMappings(
    TF_ImportGraphDefResults* results, int* num_missing_unused_input_mappings,
    const char*** src_names, int** src_indexes);

// Deletes a results object returned by TF_GraphImportGraphDefWithResults().

  // Blocks until the previous `StartExecute` has run `TFE_Execute` on each
  // device. If is_async=false (constructor argument) this means the ops have
  // run and have results. If is_async=true it means that all of the
  // device-specific executors have scheduled the op.
  //
  // Accepts inferred shapes for outputs (`expected_output_shapes`), which if

  TF_InitMain(argv[0], &argc, &argv);

  struct TF_StringStream* s = TF_GetLocalTempDirectories();
  const char* path;

  if (!TF_StringStreamNext(s, &path)) {
    fprintf(stderr, "TF_GetLocalTempDirectories returned no results\n");
    return 1;
  }

  char file_name[100];
  time_t t = time(NULL);
  snprintf(file_name, sizeof(file_name), "test-%d-%ld.txt", getpid(), t);

  size_t length = 2 + strlen(path) + strlen(file_name);

//     op for shape inference.
//   - The types need not be set in `input_shapes` as it is not used.
//   - The number of `input_tensors` should be the same as the number of items
//     in `input_shapes`.
//
// The results are returned in `output_shapes` and
// `output_resource_shapes_and_types`. The caller is responsible for freeing the
// memory in these buffers by calling `TF_DeleteShapeAndTypeList`.
TF_CAPI_EXPORT extern void TFE_InferShapes(

  // to compute the jvp, which will waste computation when executing eagerly.
  //
  // Unlike GradientTape::RecordOperation, Accumulate runs gradient computation
  // immediately. It stores the results, which feed into Accumulate for future
  // operations and may be fetched by calling FetchJVP. ForwardAccumulator
  // maintains a reference to these JVPs: if an `output_tensors` Tensor is

                              TF_DataType value, TF_Status* s);

void TF_DeleteAbstractTensor(TF_AbstractTensor*);

// TF_OutputList holds the list of TF_AbstractTensor that results from executing
// an operation, or provided to create a function.
// When executing an operation in an eager context, the expected number of
// outputs must be set beforehand with `TF_OutputListSetNumOutputs`.

#include "tensorflow/c/tf_status.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/casts.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {

// Represents the results of the execution of an operation.
struct OutputList {
  std::vector<AbstractTensorHandle*> outputs;
  int expected_num_outputs = -1;
};

namespace tracing {

                     std::vector<std::string>* result) override;
  Status GetMatchingPaths(const std::string& pattern, TransactionToken* token,
                          std::vector<std::string>* results) override;
  Status DeleteFile(const std::string& fname, TransactionToken* token) override;
  Status DeleteRecursively(const std::string& dirname, TransactionToken* token,
                           int64_t* undeleted_files,

  ///
  /// This is accomplished by traversing directory tree rooted at `path` and
  /// deleting entries as they are encountered, from leaves to root. Each plugin
  /// is free to choose a different approach which obtains similar results.
  ///
  /// On successful deletion, `status` must be `TF_OK` and `*undeleted_files`
  /// and `*undeleted_dirs` must be 0. On unsuccessful deletion, `status` must