std::move(t), device, device, context));
}

// This function will block till the operation that produces `h` has
// completed. This is only valid on local TFE_TensorHandles. Returns the size in
// bytes of the memory pointed to by the device pointer returned above.
size_t TFE_TensorHandleDeviceMemorySize(TFE_TensorHandle* h,
                                        TF_Status* status) {
  if (h == nullptr) {

-# endif
 #else
 /* These are a few types we need for the optimizations if we cannot
    use unaligned memory accesses.  */
@@ -94,148 +72,11 @@ __STRING2_COPY_TYPE (8);
 
 /* Set N bytes of S to C.  */
 #if !defined _HAVE_STRING_ARCH_memset
-# if !__GNUC_PREREQ (3, 0)
-#  if _STRING_ARCH_unaligned
-#   define memset(s, c, n) \
-  (__extension__ (__builtin_constant_p (n) && (n) <= 16			      \

*   `tensorflow.experimental.tensorrt`:

    *   `conversion_params` is now deprecated inside `TrtGraphConverterV2` in
        favor of direct arguments: `max_workspace_size_bytes`, `precision_mode`,
        `minimum_segment_size`, `maximum_cached_engines`, `use_calibration` and
        `allow_build_at_runtime`.
    *   Added a new parameter called `save_gpu_specific_engines` to the

    if (file_size != content.size())
      TF_SetStatus(
          status_, TF_DATA_LOSS,
          std::string("expected " + std::to_string(file_size) + " got " +
                      std::to_string(content.size()) + " bytes")
              .c_str());
    return content;
  }

 protected:
  TF_Filesystem* filesystem_;
  TF_Status* status_;

 private:
  std::string root_dir_;
};