def _create_uncollate_postprocessors(self, stage: RunningStage) -> _PostProcessor:
save_per_sample = None
save_fn = None
postprocess: Postprocess = self._postprocess_pipeline
func_names: Dict[str, str] = {
k: self._resolve_function_hierarchy(k, postprocess, stage, object_type=Postprocess)
for k in self.POSTPROCESS_FUNCS
}
# since postprocessing is exclusive for prediction, we don't have to check the resolution hierarchy here.
if postprocess._save_path:
save_per_sample: bool = self._is_overriden_recursive(
"save_sample", postprocess, Postprocess, prefix=_STAGES_PREFIX[stage]
)
if save_per_sample:
save_per_sample: Callable = getattr(postprocess, func_names["save_sample"])
else:
save_fn: Callable = getattr(postprocess, func_names["save_data"])
return _PostProcessor(
getattr(postprocess, func_names["uncollate"]),
getattr(postprocess, func_names["per_batch_transform"]),
getattr(postprocess, func_names["per_sample_transform"]),
serializer=self._serializer,
save_fn=save_fn,
save_per_sample=save_per_sample
)
def _create_uncollate_postprocessors(self) -> _PostProcessor:
save_per_sample = None
save_fn = None
# since postprocessing is exclusive for prediction, we don't have to check the resolution hierarchy here.
if self._postprocess_pipeline._save_path:
save_per_sample = self._is_overriden('save_sample',
self._postprocess_pipeline,
Postprocess)
if save_per_sample:
save_per_sample = self._postprocess_pipeline._save_sample
else:
save_fn = self._postprocess_pipeline._save_data
return _PostProcessor(self._postprocess_pipeline.uncollate,
self._postprocess_pipeline.per_batch_transform,
self._postprocess_pipeline.per_sample_transform,
save_fn=save_fn,
save_per_sample=save_per_sample)