diff --git a/.gitignore b/.gitignore index 330172c..5bd9b70 100644 --- a/.gitignore +++ b/.gitignore @@ -8,7 +8,7 @@ training/ *.safetensors gradio_pose2image_private.py -tool_transfer_control.py +gradio_canny2image_private.py # Byte-compiled / optimized / DLL files __pycache__/ diff --git a/tool_transfer_control.py b/tool_transfer_control.py new file mode 100644 index 0000000..b84442c --- /dev/null +++ b/tool_transfer_control.py @@ -0,0 +1,59 @@ +path_sd15 = './models/v1-5-pruned.ckpt' +path_sd15_with_control = './models/control_sd15_openpose.pth' +path_input = './models/anything-v3-full.safetensors' +path_output = './models/control_any3_openpose.pth' + + +import os + + +assert os.path.exists(path_sd15), 'Input path_sd15 does not exists!' +assert os.path.exists(path_sd15_with_control), 'Input path_sd15_with_control does not exists!' +assert os.path.exists(path_input), 'Input path_input does not exists!' +assert os.path.exists(os.path.dirname(path_output)), 'Output folder not exists!' + + +import torch +from share import * +from cldm.model import load_state_dict + + +sd15_state_dict = load_state_dict(path_sd15) +sd15_with_control_state_dict = load_state_dict(path_sd15_with_control) +input_state_dict = load_state_dict(path_input) + + +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):] + + +keys = sd15_with_control_state_dict.keys() + +final_state_dict = {} +for key in keys: + is_first_stage, _ = get_node_name(key, 'first_stage_model') + is_cond_stage, _ = get_node_name(key, 'cond_stage_model') + if is_first_stage or is_cond_stage: + final_state_dict[key] = input_state_dict[key] + continue + p = sd15_with_control_state_dict[key] + is_control, node_name = get_node_name(key, 'control_') + if is_control: + sd15_key_name = 'model.diffusion_' + node_name + else: + sd15_key_name = key + if sd15_key_name in input_state_dict: + p_new = p + input_state_dict[sd15_key_name] - sd15_state_dict[sd15_key_name] + # print(f'Offset clone from [{sd15_key_name}] to [{key}]') + else: + p_new = p + # print(f'Direct clone to [{key}]') + final_state_dict[key] = p_new + +torch.save(final_state_dict, path_output) +print('Transferred model saved at ' + path_output)