There is a problem with the pre-training weights

[softalter]

scripts/train.py --dataset_type cars_encode --exp_dir directory --use_w_pool --w_discriminator_lambda 0.1 --progressive_start 20000 --id_lambda 0.5 --val_interval 10000 --start_from_latent_avg --max_steps 200000 --stylegan_size 512 --stylegan_weights a/stylegan2-ffhq-config-f.pt --workers 8 --batch_size 8 --test_batch_size 4 --test_workers 4 {'batch_size': 8, 'board_interval': 50, 'checkpoint_path': None, 'd_reg_every': 16, 'dataset_type': 'cars_encode', 'delta_norm': 2, 'delta_norm_lambda': 0.0002, 'encoder_type': 'Encoder4Editing', 'exp_dir': 'directory', 'id_lambda': 0.5, 'image_interval': 100, 'keep_optimizer': False, 'l2_lambda': 1.0, 'learning_rate': 0.0001, 'lpips_lambda': 0.8, 'lpips_type': 'alex', 'max_steps': 200000, 'optim_name': 'ranger', 'progressive_start': 20000, 'progressive_step_every': 2000, 'progressive_steps': [0, 20000, 22000, 24000, 26000, 28000, 30000, 32000, 34000, 36000, 38000, 40000, 42000, 44000, 46000, 48000], 'r1': 10, 'resume_training_from_ckpt': None, 'save_interval': None, 'save_training_data': False, 'start_from_latent_avg': True, 'stylegan_size': 512, 'stylegan_weights': 'a/stylegan2-ffhq-config-f.pt', 'sub_exp_dir': None, 'test_batch_size': 4, 'test_workers': 4, 'train_decoder': False, 'update_param_list': None, 'use_w_pool': True, 'val_interval': 10000, 'w_discriminator_lambda': 0.1, 'w_discriminator_lr': 2e-05, 'w_pool_size': 50, 'workers': 8} Loading encoders weights from irse50! Loading decoder weights from pretrained! Traceback (most recent call last): File "/root/test/encoder4editing-main/encoder4editing-main/scripts/train.py", line 87, in main() File "/root/test/encoder4editing-main/encoder4editing-main/scripts/train.py", line 28, in main coach = Coach(opts, previous_train_ckpt) File "../training/coach.py", line 42, in init self.lpips_loss = LPIPS(net_type=self.opts.lpips_type).to(self.device).eval() File "../criteria/lpips/lpips.py", line 23, in init self.net = get_network(net_type).to("cuda") File "../criteria/lpips/networks.py", line 14, in get_network return AlexNet() File "../criteria/lpips/networks.py", line 81, in init self.layers = models.alexnet(True).features File "/root/miniconda3/lib/python3.8/site-packages/torchvision/models/alexnet.py", line 63, in alexnet state_dict = load_state_dict_from_url(model_urls['alexnet'], File "/root/miniconda3/lib/python3.8/site-packages/torch/hub.py", line 528, in load_state_dict_from_url return torch.load(cached_file, map_location=map_location) File "/root/miniconda3/lib/python3.8/site-packages/torch/serialization.py", line 593, in load return _legacy_load(opened_file, map_location, pickle_module, pickle_load_args) File "/root/miniconda3/lib/python3.8/site-packages/torch/serialization.py", line 762, in _legacy_load magic_number = pickle_module.load(f, pickle_load_args) _pickle.UnpicklingError: unpickling stack underflow

Process finished with exit code 1