further improvements to model loading

- code for committing config changes to models.yaml now in module
  rather than in invoke script
- model marked "default" is now loaded if model not specified on
  command line
- uncache changed models when edited, so that they reload properly
- removed liaon from models.yaml and added stable-diffusion-1.5

ldm/invoke/args.py

@@ -364,17 +364,16 @@ class Args(object):
         deprecated_group.add_argument('--laion400m')
         deprecated_group.add_argument('--weights') # deprecated
         model_group.add_argument(
-            '--conf',
+            '--config',
             '-c',
-            '-conf',
+            '-config',
             dest='conf',
             default='./configs/models.yaml',
             help='Path to configuration file for alternate models.',
         )
         model_group.add_argument(
             '--model',
-            default='stable-diffusion-1.4',
-            help='Indicates which diffusion model to load. (currently "stable-diffusion-1.4" (default) or "laion400m")',
+            help='Indicates which diffusion model to load (defaults to "default" stanza in configs/models.yaml)',
         )
         model_group.add_argument(
             '--sampler',

ldm/invoke/model_cache.py

@@ -85,6 +85,26 @@ class ModelCache(object):
             'hash': hash
         }
 
+    def default_model(self) -> str:
+        '''
+        Returns the name of the default model, or None
+        if none is defined.
+        '''
+        for model_name in self.config:
+            if self.config[model_name].get('default',False):
+                return model_name
+        return None
+
+    def set_default_model(self,model_name:str):
+        '''
+        Set the default model. The change will not take
+        effect until you call model_cache.commit()
+        '''
+        assert model_name in self.models,f"unknown model '{model_name}'"
+        for model in self.models:
+            self.models[model].pop('default',None)
+        self.models[model_name]['default'] = True
+
     def list_models(self) -> dict:
         '''
         Return a dict of models in the format:
@@ -122,22 +142,23 @@ class ModelCache(object):
             else:
                 print(line)
 
-    def del_model(self, model_name:str) ->str:
+    def del_model(self, model_name:str) ->bool:
         '''
-        Delete the named model and return the YAML
+        Delete the named model.
         '''
         omega = self.config
         del omega[model_name]
         if model_name in self.stack:
             self.stack.remove(model_name)
-        return OmegaConf.to_yaml(omega)
+        return True
 
-    def add_model(self, model_name:str, model_attributes:dict, clobber=False) ->str:
+    def add_model(self, model_name:str, model_attributes:dict, clobber=False) ->True:
         '''
         Update the named model with a dictionary of attributes. Will fail with an
         assertion error if the name already exists. Pass clobber=True to overwrite.
-        On a successful update, the config will be changed in memory and a YAML
-        string will be returned.
+        On a successful update, the config will be changed in memory and the
+        method will return True. Will fail with an assertion error if provided
+        attributes are incorrect or the model name is missing.
         '''
         omega = self.config
         # check that all the required fields are present
@@ -150,7 +171,9 @@ class ModelCache(object):
             config[field] = model_attributes[field]
 
         omega[model_name] = config
-        return OmegaConf.to_yaml(omega)
+        if clobber:
+            self._invalidate_cached_model(model_name)
+        return True
     
     def _check_memory(self):
         avail_memory = psutil.virtual_memory()[1]
@@ -230,6 +253,36 @@ class ModelCache(object):
         if self._has_cuda():
             torch.cuda.empty_cache()
 
+    def commit(self,config_file_path:str):
+        '''
+        Write current configuration out to the indicated file.
+        '''
+        yaml_str = OmegaConf.to_yaml(self.config)
+        tmpfile = os.path.join(os.path.dirname(config_file_path),'new_config.tmp')
+        with open(tmpfile, 'w') as outfile:
+            outfile.write(self.preamble())
+            outfile.write(yaml_str)
+        os.rename(tmpfile,config_file_path)
+
+    def preamble(self):
+        '''
+        Returns the preamble for the config file.
+        '''
+        return '''# This file describes the alternative machine learning models
+# available to the dream script.
+#
+# To add a new model, follow the examples below. Each
+# model requires a model config file, a weights file,
+# and the width and height of the images it
+# was trained on.
+'''
+
+    def _invalidate_cached_model(self,model_name:str):
+        self.unload_model(model_name)
+        if model_name in self.stack:
+            self.stack.remove(model_name)
+        self.models.pop(model_name,None)
+        
     def _model_to_cpu(self,model):
         if self.device != 'cpu':
             model.cond_stage_model.device = 'cpu'