def train_loader(self, index):
labels = self.graph.node_label[index]
sequence = SBVATSampleSequence([self.cache.X, self.cache.A],
labels,
out_weight=index,
neighbors=self.cache.neighbors,
sizes=self.cfg.fit.sizes,
device=self.data_device)
return sequence
def train_sequence(self, index):
labels = self.graph.node_label[index]
sequence = SBVATSampleSequence([self.cache.X, self.cache.A],
labels,
out_weight=index,
neighbors=self.cache.neighbors,
num_samples=self.cfg.train.num_samples,
device=self.device)
return sequence
def train_sequence(self, index):
labels = self.graph.node_label[index]
sequence = SBVATSampleSequence([self.cache.X, self.cache.A, index],
labels,
neighbors=self.cache.neighbors,
n_samples=self.cache.n_samples,
device=self.device)
return sequence
def train_sequence(self, index):
index = T.asintarr(index)
labels = self.graph.labels[index]
sequence = SBVATSampleSequence(
[self.feature_inputs, self.structure_inputs, index],
labels,
neighbors=self.neighbors,
n_samples=self.n_samples,
device=self.device)
return sequence
def train_sequence(self, index):
labels = self.graph.node_label[index]
sequence = SBVATSampleSequence(
[self.feature_inputs, self.structure_inputs, index],
labels,
neighbors=self.neighbors,
n_samples=self.n_samples,
device=self.device)
return sequence