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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()
#----------------------------------------------------------------------------
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