def collate()

in data_loaders.py [0:0]

• 16 lines of code
• 13 McCabe index (conditional complexity)

	def collate(self, batch):
		data = {}
		data['names'] = [item['names'] for item in batch]
		data['class'] = [item['class'] for item in batch]
		data['samples'] = torch.cat([item['samples'].unsqueeze(0) for item in batch])
		data['sim_touch'] = torch.cat([item['sim_touch'].unsqueeze(0) for item in batch])
		data['empty'] = torch.cat([item['empty'].unsqueeze(0) for item in batch])
		data['depth'] = torch.cat([item['depth'].unsqueeze(0) for item in batch])
		data['ref'] = {}
		data['ref']['rot'] = torch.cat([item['rot'].unsqueeze(0) for item in batch])
		data['ref']['rot_M'] = torch.cat([item['rot_M'].unsqueeze(0) for item in batch])
		data['ref']['pos'] = torch.cat([item['pos'].unsqueeze(0) for item in batch])
		data['good_touch'] = [item['good_touch'] for item in batch]
		data['save_dir'] = [item['save_dir'] for item in batch]
		data['num_samples'] = [item['num_samples'] for item in batch]

		return data