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