def forward()

in vision_charts/models.py [0:0]

• 18 lines of code
• 2 McCabe index (conditional complexity)

	def forward(self, img_occ, img_unocc,  cur_vertices):
		# double size due to legacy decision
		if self.args.use_unoccluded:
			x = torch.cat((img_unocc, img_unocc), dim = 1)
		elif self.args.use_occluded:
			x = torch.cat((img_occ, img_occ), dim=1)
		else:
			x = torch.cat((img_occ, img_unocc), dim=1)

		features = []
		layer_selections = [len(self.layers) - 1 -  (i+1)*self.args.num_img_layers for i in range(3)]
		for e, layer in enumerate(self.layers):
			if x.shape[-1] < self.args.size_img_ker:
				break
			x = layer(x)
			# collect feature maps
			if e in layer_selections:
				features.append(x)
		features.append(x)
		# get vertex features from selected feature maps
		vert_image_features = self.pooling(features, cur_vertices)
		return vert_image_features