DL-Art-School/codes/scripts/byol_extract_wrapped_model.py

20 lines
630 B
Python

import torch
from models.spinenet_arch import SpineNet
if __name__ == '__main__':
pretrained_path = '../../experiments/byol_discriminator.pth'
output_path = '../../experiments/byol_discriminator_extracted.pth'
wrap_key = 'online_encoder.net.'
sd = torch.load(pretrained_path)
sdo = {}
for k,v in sd.items():
if wrap_key in k:
sdo[k.replace(wrap_key, '')] = v
#model = SpineNet('49', in_channels=3, use_input_norm=True).to('cuda')
#model.load_state_dict(sdo, strict=True)
print("Validation succeeded, dumping state dict to output path.")
torch.save(sdo, output_path)