feat: update tool_transfer_control.py to support cli args

tool_transfer_control.py

@@ -1,28 +1,12 @@
-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 argparse
 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 sys
 
 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, ''
@@ -31,29 +15,57 @@ def get_node_name(name, parent_name):
         return False, ''
     return True, name[len(parent_name):]
 
+def parse_args():
+    parser = argparse.ArgumentParser(description='Transfer weights from one model to another')
+
+    parser.add_argument('--path_sd15', required=True, type=str, help='Path to sd15 model')
+    parser.add_argument('--path_sd15_with_control', required=True, type=str, help='Path to sd15 model with control')
+    parser.add_argument('--path_input', required=True, type=str, help='Path to input model')
+    parser.add_argument('--path_output', required=True, type=str, help='Path to output transferred model')
+
+    return parser.parse_args()
+
+
+def main():
+    args = parse_args()
+
+    for path in [args.path_sd15, args.path_sd15_with_control, args.path_input]:
+        if not os.path.exists(path):
+            print(f"Error: Input path '{path}' does not exist!")
+            sys.exit(1)
+
+    if not os.path.exists(os.path.dirname(args.path_output)):
+        print("Error: Output folder does not exist!")
+        sys.exit(1)
+
+    sd15_state_dict = load_state_dict(args.path_sd15)
+    sd15_with_control_state_dict = load_state_dict(args.path_sd15_with_control)
+    input_state_dict = load_state_dict(args.path_input)
+
+    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]
+        else:
+            p_new = p
+        final_state_dict[key] = p_new
+
+    torch.save(final_state_dict, args.path_output)
+    print(f'Transferred model saved at {args.path_output}')
+
 
-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)
+if __name__ == '__main__':
+    main()