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)