                                "default": False,
                                "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 cost."})
          argument_list.append({"opts": ("-pp", "--ping-pong"),
                                "action": "store_true",
                                "dest": "pingpong",
                                "default": False,
                                "help": "[Nvidia only] Enable ping pong training. Trains one side "
 
</s> remove                               "help": "Sets allow_growth option of Tensorflow "
                                      "to spare memory on some configs"})
 </s> add                               "help": "Sets allow_growth option of Tensorflow to spare memory "
                                      "on some configurations."}) </s> remove                               "help": "Draw landmarks on the ouput faces for "
                                      "debug"})
 </s> add                               "help": "Draw landmarks on the ouput faces for debugging purposes."}) </s> remove                               "help": "Skip frames that already have "
                                      "detected faces in the alignments "
                                      "file"})
 </s> add                               "help": "Skip frames that already have detected faces in the "
                                      "alignments file"}) </s> remove                               "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of B "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-A parameter."})
 </s> add                               "help": "Optional for creating a timelapse. Timelapse will save an "
                                      "image of your selected faces into the timelapse-output "
                                      "folder at every save iteration. This should be the "
                                      "input folder of 'B' faces that you would like to use for "
                                      "creating the timelapse. You must also supply a "
                                      "--timelapse-output and a --timelapse-input-A parameter."})
        argument_list.append({"opts": ("-to", "--timelapse-output"),
                              "action": DirFullPaths,
                              "dest": "timelapse_output",
                              "default": None,
                              "help": "Optional for creating a timelapse. Timelapse will save an "
                                      "image of your selected faces into the timelapse-output "
                                      "folder at every save iteration. If the input folders are "
                                      "supplied but no output folder, it will default to your "
                                      "model folder /timelapse/"})
        argument_list.append({"opts": ("-m", "--model-dir"),
                              "action": DirFullPaths,
                              "dest": "model_dir",
                              "required": True,
                              "help": "Model directory. This is where the training data will be "
                                      "stored. You should always specify a new folder for new "
                                      "models. If starting a new model, select either an empty "
                                      "folder, or a folder which does not exist (which will be "
                                      "created). If continuing to train an existing model, "
                                      "specify the location of the existing model."}) </s> remove                               "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of A "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-B parameter."})
 </s> add                               "help": "Optional for creating a timelapse. Timelapse will save an "
                                      "image of your selected faces into the timelapse-output "
                                      "folder at every save iteration. This should be the "
                                      "input folder of 'A' faces that you would like to use for "
                                      "creating the timelapse. You must also supply a "
                                      "--timelapse-output and a --timelapse-input-B parameter."})
                                      "speed/system RAM cost."})
                                "default": False,
                                "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."})
          argument_list.append({"opts": ("-pp", "--ping-pong"),
                                "action": "store_true",
                                "dest": "pingpong",
                                "default": False,
                                "help": "[Nvidia only] Enable ping pong training. Trains one side "
keep keep keep keep replace keep keep keep keep keep
 Clarification of helptext in cli.py 
lib/cli.py