refine format

torchbenchmark/models/pytorch_CycleGAN_and_pix2pix/__init__.py

@@ -35,18 +35,18 @@ def __init__(self, test, device, batch_size=None, extra_args=[]):
         results_arg = f"--results_dir {results_dir}"
         data_root = os.path.join(DATA_PATH, "pytorch_CycleGAN_and_pix2pix_inputs")
         device_arg = ""
-        device_type = f"--device_type {self.device}"
+        device_type_arg = f"--device_type {self.device}"
         if self.device == "cpu":
             device_arg = "--gpu_ids -1"
         else:
             device_arg = "--gpu_ids 0"
 
         if self.test == "train":
             train_args = f"--tb_device {self.device} --dataroot {data_root}/datasets/horse2zebra --name horse2zebra --model cycle_gan --display_id 0 --n_epochs 3 " + \
-                         f"--n_epochs_decay 3 {device_type} {device_arg} {checkpoints_arg}"
+                         f"--n_epochs_decay 3 {device_type_arg} {device_arg} {checkpoints_arg}"
             self.training_loop = prepare_training_loop(train_args.split(' '))
         args = f"--dataroot {data_root}/datasets/horse2zebra/testA --name horse2zebra_pretrained --model test " + \
-               f"--no_dropout {device_type} {device_arg} {checkpoints_arg} {results_arg}"
+               f"--no_dropout {device_type_arg} {device_arg} {checkpoints_arg} {results_arg}"
         self.model, self.input = get_model(args, self.device)
 
     def get_module(self):