import click import os import sys import pickle import numpy as np from PIL import Image import torch from configs import paths_config, hyperparameters, global_config from IPython.display import display import matplotlib.pyplot as plt from scripts.latent_editor_wrapper import LatentEditorWrapper image_dir_name = 'images' use_multi_id_training = False global_config.device = 'cuda' paths_config.e4e = 'e4e_ffhq_encode.pt' paths_config.input_data_id = image_dir_name paths_config.input_data_path = f'{image_dir_name}' paths_config.stylegan2_ada_ffhq = 'ffhq.pkl' paths_config.checkpoints_dir = '' paths_config.style_clip_pretrained_mappers = '' hyperparameters.use_locality_regularization = False hyperparameters.lpips_type = 'squeeze' from scripts.run_pti import run_PTI def tune(): model_id = run_PTI(run_name='',use_wandb=False, use_multi_id_training=False) #---------------------------------------------------------------------------- if __name__ == '__main__': tune() #----------------------------------------------------------------------------