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60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
path_sd15 = './models/v1-5-pruned.ckpt'
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path_sd15_with_control = './models/control_sd15_openpose.pth'
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path_input = './models/anything-v3-full.safetensors'
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path_output = './models/control_any3_openpose.pth'
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import os
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assert os.path.exists(path_sd15), 'Input path_sd15 does not exists!'
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assert os.path.exists(path_sd15_with_control), 'Input path_sd15_with_control does not exists!'
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assert os.path.exists(path_input), 'Input path_input does not exists!'
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assert os.path.exists(os.path.dirname(path_output)), 'Output folder not exists!'
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import torch
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from share import *
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from cldm.model import load_state_dict
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sd15_state_dict = load_state_dict(path_sd15)
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sd15_with_control_state_dict = load_state_dict(path_sd15_with_control)
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input_state_dict = load_state_dict(path_input)
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def get_node_name(name, parent_name):
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if len(name) <= len(parent_name):
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return False, ''
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p = name[:len(parent_name)]
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if p != parent_name:
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return False, ''
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return True, name[len(parent_name):]
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keys = sd15_with_control_state_dict.keys()
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final_state_dict = {}
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for key in keys:
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is_first_stage, _ = get_node_name(key, 'first_stage_model')
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is_cond_stage, _ = get_node_name(key, 'cond_stage_model')
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if is_first_stage or is_cond_stage:
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final_state_dict[key] = input_state_dict[key]
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continue
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p = sd15_with_control_state_dict[key]
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is_control, node_name = get_node_name(key, 'control_')
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if is_control:
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sd15_key_name = 'model.diffusion_' + node_name
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else:
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sd15_key_name = key
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if sd15_key_name in input_state_dict:
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p_new = p + input_state_dict[sd15_key_name] - sd15_state_dict[sd15_key_name]
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# print(f'Offset clone from [{sd15_key_name}] to [{key}]')
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else:
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p_new = p
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# print(f'Direct clone to [{key}]')
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final_state_dict[key] = p_new
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torch.save(final_state_dict, path_output)
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print('Transferred model saved at ' + path_output)
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