allow having at half precision when there is only one checkpoint in merger tab

modules/extras.py

@@ -278,6 +278,13 @@ def create_config(ckpt_result, config_source, a, b, c):
 chckpoint_dict_skip_on_merge = ["cond_stage_model.transformer.text_model.embeddings.position_ids"]
 
 
+def to_half(tensor, enable):
+    if enable and tensor.dtype == torch.float:
+        return tensor.half()
+
+    return tensor
+
+
 def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae):
     shared.state.begin()
     shared.state.job = 'model-merge'
@@ -400,8 +407,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
             else:
                 theta_0[key] = theta_func2(a, b, multiplier)
 
-            if save_as_half:
-                theta_0[key] = theta_0[key].half()
+            theta_0[key] = to_half(theta_0[key], save_as_half)
 
         shared.state.sampling_step += 1
 
@@ -416,10 +422,14 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
         for key in vae_dict.keys():
             theta_0_key = 'first_stage_model.' + key
             if theta_0_key in theta_0:
-                theta_0[theta_0_key] = vae_dict[key].half() if save_as_half else vae_dict[key]
+                theta_0[theta_0_key] = to_half(vae_dict[key], save_as_half)
 
         del vae_dict
 
+    if save_as_half and not theta_func2:
+        for key in theta_0.keys():
+            theta_0[key] = to_half(theta_0[key], save_as_half)
+
     ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
 
     filename = filename_generator() if custom_name == '' else custom_name