Recent commits broke merging

[cluder]

trying to merge models fails now because of multiple methods being called which have been removed (pass) or commented out

c1b23bd
bccf9fb

1. sd_models.read_state_dict() has been removed (pass), but its still called during merging
   see extras.py: run_modelmerger()

2. AttributeError: module 'modules.sd_models_config' has no attribute 'find_checkpoint_config_near_filename'
   find_checkpoint_config_near_filename has been commented out in: bccf9fb

the following changes seems to work for me, not sure if create_config() is needed at all after merging?

diff --git a/modules/extras.py b/modules/extras.py
index 2a310ae3..af0e2cfd 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -179,7 +179,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_

     shared.state.textinfo = f"Loading {primary_model_info.filename}..."
     print(f"Loading {primary_model_info.filename}...")
-    theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
+    theta_0 = sd_models.load_torch_file(primary_model_info.filename)^M

     print("Merging...")
     shared.state.textinfo = 'Merging A and B'
@@ -222,7 +222,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
     if bake_in_vae_filename is not None:
         print(f"Baking in VAE from {bake_in_vae_filename}")
         shared.state.textinfo = 'Baking in VAE'
-        vae_dict = sd_vae.load_vae_dict(bake_in_vae_filename, map_location='cpu')
+        vae_dict = sd_vae.load_torch_file(bake_in_vae_filename)^M

         for key in vae_dict.keys():
             theta_0_key = 'first_stage_model.' + key
@@ -321,7 +321,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
     if created_model:
         created_model.calculate_shorthash()

-    create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)
+    #create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)^M

     print(f"Checkpoint saved to {output_modelname}.")
     shared.state.textinfo = "Checkpoint saved"```

[cluder]

when the checkpoints list is populated initially, it does not contain a hash value, and a merge works.
after we close webui and run it again, the hash has been calculated, the checkpoint list now contains the checkpoint name + hash e.g. now we always get a KeyError because 'checkpoint.safetensor' cannot match 'checkpoint.safetensor [hash]'

To solve that problem, we can get the checkpoint into from the checkpoint_aliases which contains all possible key's (has only, name+hash, name only etc) for a specific model instead from the checkpoint_list: