`minimum_segment_size`, `maximum_cached_engines`, `use_calibration` and
        `allow_build_at_runtime`.
    *   Added a new parameter called `save_gpu_specific_engines` to the
        `.save()` function inside `TrtGraphConverterV2`. When `False`, the
        `.save()` function won't save any TRT engines that have been built. When
        `True` (default), the original behavior is preserved.

// setting functional attributes of other composite ops e.g. control flow.
typedef struct TF_AbstractFunction TF_AbstractFunction;

// This allows the client to swap the implementation of the tracing engine.
// Any future call to TF_CreateFunction will use the implementation defined
// here.
void TF_SetTracingImplementation(const char* name, TF_Status*);

  string name_;
};

static TracingContext* GraphTracingFactory(const char* name, TF_Status* s) {
  return new GraphContext(name);
}

// Register the tracing implemented in this file as the default tracing engine.
static bool register_tracing = [] {
  RegisterTracingEngineFactory("graphdef", GraphTracingFactory);
  SetDefaultTracingEngine("graphdef").IgnoreError();
  return true;
}();

}  // namespace graph

namespace tensorflow {
namespace {

// The tests are parameterized on:
// - a string representing the tracing implementation: "mlir" or "graphdef".
// - a boolean that when true enables TFRT as the execution engine.
class UnifiedCAPI
    : public ::testing::TestWithParam<std::tuple<const char*, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());

  auto entry = GetFactories().find(name);
  if (entry != GetFactories().end()) {
    default_factory = GetFactories().find(name)->second;
    return absl::OkStatus();
  }
  string msg = absl::StrCat(
      "No tracing engine factory has been registered with the key '", name,
      "' (available: ");
  // Ensure deterministic (sorted) order in the error message
  std::set<string> factories_sorted;
  for (const auto& factory : GetFactories())

[community](https://www.tensorflow.org/community) resources that lets
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TensorFlow was originally developed by researchers and engineers working within
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used in other areas as well.

-   we have to use the name `__mempcpy'.  */
-#   define mempcpy(dest, src, n) __mempcpy (dest, src, n)
-#  endif
-
-#  if !__GNUC_PREREQ (3, 0) || defined _FORCE_INLINES
-#   if _STRING_ARCH_unaligned
-#    ifndef _FORCE_INLINES
-#     define __mempcpy_args(src) \
-     ((const char *) (src))[0], ((const char *) (src))[2],		      \
-     ((const char *) (src))[4], ((const char *) (src))[6],		      \