def __init__(self,
config,
dataset,
sampler,
kg_sampler,
neg_sample_args,
batch_size=1,
dl_format=InputType.POINTWISE,
shuffle=False):
# using sampler
self.general_dataloader = GeneralNegSampleDataLoader(
config=config,
dataset=dataset,
sampler=sampler,
neg_sample_args=neg_sample_args,
batch_size=batch_size,
dl_format=dl_format,
shuffle=shuffle)
# using kg_sampler and dl_format is pairwise
self.kg_dataloader = KGDataLoader(config,
dataset,
kg_sampler,
batch_size=batch_size,
dl_format=InputType.PAIRWISE,
shuffle=shuffle)
self.main_dataloader = self.general_dataloader
super().__init__(config,
dataset,
batch_size=batch_size,
dl_format=dl_format,
shuffle=shuffle)
class KnowledgeBasedDataLoader(AbstractDataLoader):
""":class:`KnowledgeBasedDataLoader` is used for knowledge based model.
It has three states, which is saved in :attr:`state`.
In different states, :meth:`~_next_batch_data` will return different :class:`~recbole.data.interaction.Interaction`.
Detailed, please see :attr:`~state`.
Args:
config (Config): The config of dataloader.
dataset (Dataset): The dataset of dataloader.
sampler (Sampler): The sampler of dataloader.
kg_sampler (KGSampler): The knowledge graph sampler of dataloader.
neg_sample_args (dict): The neg_sample_args of dataloader.
batch_size (int, optional): The batch_size of dataloader. Defaults to ``1``.
dl_format (InputType, optional): The input type of dataloader. Defaults to
:obj:`~recbole.utils.enum_type.InputType.POINTWISE`.
shuffle (bool, optional): Whether the dataloader will be shuffle after a round. Defaults to ``False``.
Attributes:
state (KGDataLoaderState):
This dataloader has three states:
- :obj:`~recbole.utils.enum_type.KGDataLoaderState.RS`
- :obj:`~recbole.utils.enum_type.KGDataLoaderState.KG`
- :obj:`~recbole.utils.enum_type.KGDataLoaderState.RSKG`
In the first state, this dataloader would only return the triplets with negative examples in a knowledge graph.
In the second state, this dataloader would only return the user-item interaction.
In the last state, this dataloader would return both knowledge graph information
and user-item interaction information.
"""
def __init__(self,
config,
dataset,
sampler,
kg_sampler,
neg_sample_args,
batch_size=1,
dl_format=InputType.POINTWISE,
shuffle=False):
# using sampler
self.general_dataloader = GeneralNegSampleDataLoader(
config=config,
dataset=dataset,
sampler=sampler,
neg_sample_args=neg_sample_args,
batch_size=batch_size,
dl_format=dl_format,
shuffle=shuffle)
# using kg_sampler and dl_format is pairwise
self.kg_dataloader = KGDataLoader(config,
dataset,
kg_sampler,
batch_size=batch_size,
dl_format=InputType.PAIRWISE,
shuffle=shuffle)
self.main_dataloader = self.general_dataloader
super().__init__(config,
dataset,
batch_size=batch_size,
dl_format=dl_format,
shuffle=shuffle)
@property
def pr(self):
"""Pointer of :class:`KnowledgeBasedDataLoader`. It would be affect by self.state.
"""
return self.main_dataloader.pr
@pr.setter
def pr(self, value):
self.main_dataloader.pr = value
def __iter__(self):
if not hasattr(self, 'state') or not hasattr(self, 'main_dataloader'):
raise ValueError(
'The dataloader\'s state and main_dataloader must be set '
'when using the kg based dataloader')
return super().__iter__()
def _shuffle(self):
if self.state == KGDataLoaderState.RSKG:
self.general_dataloader._shuffle()
self.kg_dataloader._shuffle()
else:
self.main_dataloader._shuffle()
def __next__(self):
if self.pr >= self.pr_end:
if self.state == KGDataLoaderState.RSKG:
self.general_dataloader.pr = 0
self.kg_dataloader.pr = 0
else:
self.pr = 0
raise StopIteration()
return self._next_batch_data()
def __len__(self):
return len(self.main_dataloader)
@property
def pr_end(self):
return self.main_dataloader.pr_end
def _next_batch_data(self):
if self.state == KGDataLoaderState.KG:
return self.kg_dataloader._next_batch_data()
elif self.state == KGDataLoaderState.RS:
return self.general_dataloader._next_batch_data()
elif self.state == KGDataLoaderState.RSKG:
if self.kg_dataloader.pr >= self.kg_dataloader.pr_end:
self.kg_dataloader.pr = 0
kg_data = self.kg_dataloader._next_batch_data()
rec_data = self.general_dataloader._next_batch_data()
rec_data.update(kg_data)
return rec_data
def set_mode(self, state):
"""Set the mode of :class:`KnowledgeBasedDataLoader`, it can be set to three states:
- KGDataLoaderState.RS
- KGDataLoaderState.KG
- KGDataLoaderState.RSKG
The state of :class:`KnowledgeBasedDataLoader` would affect the result of _next_batch_data().
Args:
state (KGDataLoaderState): the state of :class:`KnowledgeBasedDataLoader`.
"""
if state not in set(KGDataLoaderState):
raise NotImplementedError(
'kg data loader has no state named [{}]'.format(self.state))
self.state = state
if self.state == KGDataLoaderState.RS:
self.main_dataloader = self.general_dataloader
elif self.state == KGDataLoaderState.KG:
self.main_dataloader = self.kg_dataloader
else: # RSKG
kgpr = self.kg_dataloader.pr_end
rspr = self.general_dataloader.pr_end
self.main_dataloader = self.general_dataloader if rspr < kgpr else self.kg_dataloader