Spaces:
Runtime error
Runtime error
| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # All rights reserved. | |
| # This source code is licensed under the license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| """ | |
| Functions for downloading pre-trained DiT models | |
| """ | |
| from torchvision.datasets.utils import download_url | |
| import torch | |
| import os | |
| pretrained_models = {'DiT-XL-2-512x512.pt', 'DiT-XL-2-256x256.pt'} | |
| def find_model(model_name): | |
| """ | |
| Finds a pre-trained G.pt model, downloading it if necessary. Alternatively, loads a model from a local path. | |
| """ | |
| if model_name in pretrained_models: # Find/download our pre-trained G.pt checkpoints | |
| return download_model(model_name) | |
| else: # Load a custom DiT checkpoint: | |
| assert os.path.isfile(model_name), f'Could not find DiT checkpoint at {model_name}' | |
| return torch.load(model_name, map_location=lambda storage, loc: storage) | |
| def download_model(model_name): | |
| """ | |
| Downloads a pre-trained DiT model from the web. | |
| """ | |
| assert model_name in pretrained_models | |
| local_path = f'pretrained_models/{model_name}' | |
| if not os.path.isfile(local_path): | |
| os.makedirs('pretrained_models', exist_ok=True) | |
| web_path = f'https://dl.fbaipublicfiles.com/DiT/models/{model_name}' | |
| download_url(web_path, 'pretrained_models') | |
| model = torch.load(local_path, map_location=lambda storage, loc: storage) | |
| return model | |
| if __name__ == "__main__": | |
| # Download all DiT checkpoints | |
| for model in pretrained_models: | |
| download_model(model) | |
| print('Done.') | |