|
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/anydoor.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 'control_model.input_blocks.0.0' in k: |
|
print('skipped key: ', k) |
|
continue |
|
|
|
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=False) |
|
torch.save(model.state_dict(), output_path) |
|
print('Done.') |
|
|