                                        "the model to stop automatically at a set number of "
                                        "iterations, you can set that value here."})
          argument_list.append({"opts": ("-g", "--gpus"),
                                "type": int,
                                "action": Slider,
                                "min_max": (1, 10),
                                "rounding": 1,
                                "default": 1,
                                "help": "Number of GPUs to use for training"})
          argument_list.append({"opts": ("-ps", "--preview-scale"),
 
</s> remove                                       "then alignment (2 passes). Useful if VRAM is at a premium. "
                                      "Only has an effect if both the aligner and detector use "
                                      "the GPU, otherwise this is automatically off. NB: AMD "
                                      "cards do not support parallel processing, so if both "
                                      "aligner and detector use an AMD GPU this will "
                                      "automatically be enabled."})
 </s> add                                       "then alignment (2 passes). Useful if VRAM is at a "
                                      "premium."}) </s> remove                               "help": "[Nvidia only] To save VRAM some optimizer gradient "
                                      "calculations can be performed on the CPU rather than the "
                                      "GPU. This allows you to increase batchsize at a training "
                                      "speed/system RAM cost."})
 </s> add                               "backend": "nvidia",
                              "help": "To save VRAM some optimizer gradient calculations can be "
                                      "performed on the CPU rather than the GPU. This allows you "
                                      "to increase batchsize at a training speed/system RAM "
                                      "cost."}) </s> remove                               "help": "[Nvidia only] Trades off VRAM usage against computation "
                                      "time. Can fit larger models into memory at a cost of "
                                      "slower training speed. 50%%-150%% batch size increase for "
                                      "20%%-50%% longer training time. NB: Launch time will be "
                                      "significantly delayed. Switching sides using ping-pong "
                                      "training will take longer."})
 </s> add                               "backend": "nvidia",
                              "help": "Trades off VRAM usage against computation time. Can fit "
                                      "larger models into memory at a cost of slower training "
                                      "speed. 50%%-150%% batch size increase for 20%%-50%% longer "
                                      "training time. NB: Launch time will be significantly "
                                      "delayed. Switching sides using ping-pong training will "
                                      "take longer."})
                              "backend": "nvidia",
                                        "the model to stop automatically at a set number of "
                                        "iterations, you can set that value here."})
          argument_list.append({"opts": ("-g", "--gpus"),
                                "type": int,
                              "backend": "nvidia",
                                "action": Slider,
                                "min_max": (1, 10),
                                "rounding": 1,
                                "default": 1,
                                "help": "Number of GPUs to use for training"})
          argument_list.append({"opts": ("-ps", "--preview-scale"),
keep keep keep add keep keep keep keep keep keep
 More seamless AMD Integration

- utils.py: Set FS backend if .faceswap config file doesn't exist
- setup.py: set .faceswap config on setup
- Dynamically load options for AMD/CPU/NVIDIA backends 
lib/cli.py