import sys import os assert len(sys.argv) == 3, 'Args are wrong.' input_path = sys.argv[1] output_path = sys.argv[2] assert os.path.exists(input_path), 'Input model does not exist.' assert not os.path.exists(output_path), 'Output filename already exists.' assert os.path.exists(os.path.dirname(output_path)), 'Output path is not valid.' import torch from share import * from cldm.model import create_model def get_node_name(name, parent_name): if len(name) <= len(parent_name): return False, '' p = name[:len(parent_name)] if p != parent_name: return False, '' return True, name[len(parent_name):] model = create_model(config_path='./models/cldm_v15-mask.yaml') pretrained_weights = torch.load(input_path) if 'state_dict' in pretrained_weights: pretrained_weights = pretrained_weights['state_dict'] scratch_dict = model.state_dict() target_dict = {} for k in scratch_dict.keys(): is_control, name = get_node_name(k, 'control_') if is_control: copy_k = 'model.diffusion_' + name else: copy_k = k if copy_k in pretrained_weights: target_dict[k] = pretrained_weights[copy_k].clone() else: target_dict[k] = scratch_dict[k].clone() print(f'These weights are newly added: {k}') model.load_state_dict(target_dict, strict=True) torch.save(model.state_dict(), output_path) print('Done.')