def __getstate__(self):
state_dict = {}
for k, v in self.__dict__.items():
if callable(v):
state_dict[k] = serialize_fn(v)
else:
state_dict[k] = v
return state_dict
def __getstate__(self):
if IterDataPipe.getstate_hook is not None:
return IterDataPipe.getstate_hook(self)
state_dict = {}
for k, v in self.__dict__.items():
if callable(v):
state_dict[k] = serialize_fn(v)
else:
state_dict[k] = v
return state_dict
def __getstate__(self):
# TODO: Fix `dill` circular dependency - https://github.com/pytorch/data/issues/237
if DILL_AVAILABLE:
state_dict = {}
for k, v in self.__dict__.items():
if callable(v):
state_dict[k] = serialize_fn(v)
else:
state_dict[k] = v
return state_dict
else:
return self.__dict__
def __getstate__(self):
if IterDataPipe.getstate_hook is not None:
return IterDataPipe.getstate_hook(self)
serialized_fn_with_method = serialize_fn(self.classifier_fn)
state = (
self.main_datapipe,
self.num_instances,
self.buffer_size,
serialized_fn_with_method,
self.drop_none,
)
return state
def __getstate__(self):
if IterDataPipe.getstate_hook is not None:
return IterDataPipe.getstate_hook(self)
state = (
self.main_datapipe,
self.num_instances,
self.buffer_size,
serialize_fn(self.classifier_fn)
if DILL_AVAILABLE else self.classifier_fn,
self.drop_none,
)
return state