class ImageClassificationPytorch: def __init__(self, config): gpu_id = config['gpu_id'] os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" os.environ["CUDA_VISIBLE_DEVICES"] = gpu_id print(config) #check_config_dict(config) self.config = config self.init() def init(self): # create net self.model = ExampleModel(self.config) # load self.model.load() # create your data generator self.train_loader, self.test_loader = get_data_loader(self.config) # create logger self.logger = ExampleLogger(self.config) # create trainer and path all previous components to it self.trainer = ExampleTrainer(self.model, self.train_loader, self.test_loader, self.config, self.logger) def run(self): # here you train your model self.trainer.train() def close(self): # close self.logger.close()
def init(self): # create net self.model = ExampleModel(self.config) # load self.model.load() # create your data generator self.train_loader, self.test_loader = get_data_loader(self.config) # create logger self.logger = ExampleLogger(self.config) # create trainer and path all previous components to it self.trainer = ExampleTrainer(self.model, self.train_loader, self.test_loader, self.config, self.logger)