def __getitem__(self, index):
ind = self.pairs[index]
# Graph 1
node_labels1, am1 = create_graph_letter(
self.root + self.graphs[ind[0]],
representation=self.representation)
target1 = self.labels[ind[0]]
node_labels1 = torch.FloatTensor(node_labels1)
am1 = torch.FloatTensor(am1)
if self.normalization:
node_labels1 = du.normalize_mean(node_labels1)
# Graph 2
node_labels2, am2 = create_graph_letter(
self.root + self.graphs[ind[1]],
representation=self.representation)
target2 = self.labels[ind[1]]
node_labels2 = torch.FloatTensor(node_labels2)
am2 = torch.FloatTensor(am2)
if self.normalization:
node_labels2 = du.normalize_mean(node_labels2)
target = torch.FloatTensor(
[1.0]) if target1 == target2 else torch.FloatTensor([0.0])
return node_labels1, am1, node_labels2, am2, target
def __getitem__(self, index):
node_labels, am = create_graph_histo(
self.root + self.graphs[index], representation=self.representation)
target = self.labels[index]
node_labels = torch.FloatTensor(node_labels)
if self.normalization:
node_labels = du.normalize_mean(node_labels)
am = torch.FloatTensor(am)
return node_labels, am, target