def __getitem__(self, idx: int) -> Union[Graph, List[Graph]]:
r"""
Takes in an integer (or a list of integers)
returns a single Graph object (a subset of graphs).
Args:
idx: index to be selected from graphs.
Returns:
Union[:class:`deepsnap.graph.Graph`, List[:class:`deepsnap.graph.Graph`]]: A single
:class:`deepsnap.graph.Graph` object or subset of :class:`deepsnap.graph.Graph` objects.
"""
if self.task == 'link_pred' and self._resample_negatives:
# resample negative examples
for graph in self.graphs:
if type(graph) == Graph:
graph._create_neg_sampling(
self.edge_negative_sampling_ratio, resample=True)
elif type(graph) == HeteroGraph:
graph._create_neg_sampling(
self.edge_negative_sampling_ratio, split_types=self._split_types, resample=True)
# TODO: add the hetero graph equivalent of these functions ?
if self.graphs is None:
graph = self.generator.generate()
if not isinstance(graph, Graph):
graph = Graph(graph)
# generated an networkx graph
if self.otf_device is not None:
graph.to(self.otf_device)
return graph
elif isinstance(idx, int):
return self.graphs[idx]
else:
return self._index_select(idx)
def __getitem__(self, idx: int) -> Union[Graph, List[Graph]]:
r"""
Takes in an integer (or a list of integers)
returns a single Graph object (a subset of graphs).
Args:
idx: index to be selected from graphs.
Returns:
Union[:class:`deepsnap.graph.Graph`, List[:class:`deepsnap.graph.Graph`]]: A single
:class:`deepsnap.graph.Graph` object or subset of :class:`deepsnap.graph.Graph` objects.
"""
# TODO: add the hetero graph equivalent of these functions ?
if self.graphs is None:
graph = self.generator.generate()
if not isinstance(graph, Graph):
graph = Graph(graph)
# generated an networkx graph
if self.otf_device is not None:
graph.to(self.otf_device)
# return graph
elif isinstance(idx, int):
graph = self.graphs[idx]
else:
graph = self._index_select(idx)
if self.task == "link_pred" and self._resample_negatives:
# resample negative examples
if isinstance(graph, Graph):
if isinstance(graph, HeteroGraph):
if self.negative_edges_mode == "random":
graph._create_neg_sampling(
self.edge_negative_sampling_ratio,
split_types=self._split_types,
resample=True)
elif self.negative_edges_mode == "custom":
raise NotImplementedError()
else:
if self.negative_edges_mode == "random":
graph._create_neg_sampling(
self.edge_negative_sampling_ratio, resample=True)
elif self.negative_edges_mode == "custom":
graph._custom_create_neg_sampling(
self.edge_negative_sampling_ratio, resample=True)
else:
raise TypeError("element in self.graphs of unexpected type.")
return graph
def __getitem__(self, idx: int) -> Union[Graph, List[Graph]]:
r"""
Takes in an integer (or a list of integers)
returns a single Graph object (a subset of graphs).
Args:
idx: index to be selected from graphs.
Returns:
Union[:class:`deepsnap.graph.Graph`, List[:class:`deepsnap.graph.Graph`]]: A single
:class:`deepsnap.graph.Graph` object or subset of :class:`deepsnap.graph.Graph` objects.
"""
# TODO: add the hetero graph equivalent of these functions ?
if self.graphs is None:
graph = self.generator.generate()
if not isinstance(graph, Graph):
graph = Graph(graph)
# generated an networkx graph
if self.otf_device is not None:
graph.to(self.otf_device)
elif isinstance(idx, int):
graph = self.graphs[idx]
else:
# sliceing of dataset
dataset = self._index_select(idx)
return dataset
# TODO: remove self.task check by add corresponding checker in the __init__
if (self.task == "link_pred" and self.edge_train_mode == "disjoint"
and self.resample_disjoint and graph.is_train):
if not hasattr(graph, "resample_disjoint_period"):
graph.resample_disjoint_period = self.resample_disjoint_period
if isinstance(graph, Graph):
if isinstance(graph, HeteroGraph):
graph = graph.resample_disjoint(
split_types=self._split_types,
message_ratio=self.edge_message_ratio)
else:
graph = graph.resample_disjoint(self.edge_message_ratio)
else:
raise TypeError("element in self.graphs of unexpected type.")
if self.task == "link_pred" and self.resample_negatives:
resample_negative_flag = True
# after graph just resampled disjoint training data
# graph.edge_label is reset to original state,
# the negative sampling process needs to utilize
# resample=False mode.
if (hasattr(graph, "_resample_disjoint_flag")
and graph._resample_disjoint_flag):
resample_negative_flag = False
# resample negative examples
if isinstance(graph, Graph):
if isinstance(graph, HeteroGraph):
if self.negative_edges_mode == "random":
graph._create_neg_sampling(
self.edge_negative_sampling_ratio,
split_types=self._split_types,
resample=resample_negative_flag)
elif self.negative_edges_mode == "custom":
graph._custom_create_neg_sampling(
self.edge_negative_sampling_ratio,
split_types=self._split_types,
resample=resample_negative_flag)
else:
if self.negative_edges_mode == "random":
graph._create_neg_sampling(
self.edge_negative_sampling_ratio,
resample=resample_negative_flag)
elif self.negative_edges_mode == "custom":
graph._custom_create_neg_sampling(
self.edge_negative_sampling_ratio,
resample=resample_negative_flag)
else:
raise TypeError("element in self.graphs of unexpected type.")
if self.graphs is not None and isinstance(idx, int):
self.graphs[idx] = graph
return graph
