Spaces:
Running
on
A10G
Running
on
A10G
File size: 1,930 Bytes
251e479 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
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)
|