def setup_layer_structure(self):
"""
Creating the layer structure (3 convolutional upper layers, 3 bottom layers) and dense final.
"""
self.upper_layers = [SparseNGCNLayer(self.feature_number, self.args.layers_1[i-1], i, self.args.dropout) for i in range(1, self.order_1+1)]
self.upper_layers = ListModule(*self.upper_layers)
self.bottom_layers = [DenseNGCNLayer(self.abstract_feature_number_1, self.args.layers_2[i-1], i, self.args.dropout) for i in range(1, self.order_2+1)]
self.bottom_layers = ListModule(*self.bottom_layers)
self.fully_connected = torch.nn.Linear(self.abstract_feature_number_2, self.class_number)
def setup_layer_structure(self):
"""
Creating the layer structure (3 convolutional layers) and dense final.
"""
self.main_layers = [SparseNGCNLayer(self.feature_number, self.args.layers_1[i-1], i, self.args.dropout) for i in range(1, self.order+1)]
self.main_layers = ListModule(*self.main_layers)
self.fully_connected = torch.nn.Linear(sum(self.args.layers_1), self.class_number)
def _setup_base_layers(self):
"""
Creating GCN layers.
"""
self.base_layers = [GCNConv(self.number_of_features, self.args.gcn_filters)]
for layer in range(self.args.gcn_layers-1):
self.base_layers.append(GCNConv( self.args.gcn_filters, self.args.gcn_filters))
self.base_layers = ListModule(*self.base_layers)
def _setup_layers(self):
"""
Creating layers of model.
1. GCN layers.
2. Primary capsules.
3. Attention
4. Graph capsules.
5. Class capsules.
"""
self.base_layers = [GCNConv(self.number_of_features, self.args.gcn_filters)]
for layer in range(self.args.gcn_layers-1):
self.base_layers.append(GCNConv( self.args.gcn_filters, self.args.gcn_filters))
self.base_layers = ListModule(*self.base_layers)
self.first_capsule = PrimaryCapsuleLayer(self.args.gcn_filters, self.args.gcn_layers, self.args.gcn_layers, self.args.capsule_dimensions)
self.attention = Attention(self.args.gcn_layers* self.args.gcn_filters*self.args.capsule_dimensions, self.args.inner_attention_dimension)
self.graph_capsule = SecondaryCapsuleLayer(self.args.gcn_layers*self.args.gcn_filters, self.args.capsule_dimensions, self.args.number_of_capsules, self.args.capsule_dimensions)
self.class_capsule = SecondaryCapsuleLayer(self.args.capsule_dimensions,self.args.number_of_capsules, self.number_of_targets, self.args.capsule_dimensions)