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

configs/models.yaml

@@ -6,15 +6,15 @@
 # and the width and height of the images it
 # was trained on.
 
-laion400m:
-    config:  configs/latent-diffusion/txt2img-1p4B-eval.yaml
-    weights: models/ldm/text2img-large/model.ckpt
-    description: Latent Diffusion LAION400M model
-    width: 256
-    height: 256
 stable-diffusion-1.4:
     config:  configs/stable-diffusion/v1-inference.yaml
     weights: models/ldm/stable-diffusion-v1/model.ckpt
     description: Stable Diffusion inference model version 1.4
     width: 512
     height: 512
+stable-diffusion-1.5:
+    config:  configs/stable-diffusion/v1-inference.yaml
+    weights: models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
+    description: Stable Diffusion inference model version 1.5
+    width: 512
+    height: 512

ldm/generate.py

@@ -35,6 +35,9 @@ from ldm.invoke.devices import choose_torch_device, choose_precision
 from ldm.invoke.conditioning import get_uc_and_c
 from ldm.invoke.model_cache import ModelCache
 
+# this is fallback model in case no default is defined
+FALLBACK_MODEL_NAME='stable-diffusion-1.4'
+
 def fix_func(orig):
     if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
         def new_func(*args, **kw):
@@ -127,7 +130,7 @@ class Generate:
 
     def __init__(
             self,
-            model                 = 'stable-diffusion-1.4',
+            model                 = None,
             conf                  = 'configs/models.yaml',
             embedding_path        = None,
             sampler_name          = 'k_lms',
@@ -143,7 +146,6 @@ class Generate:
             free_gpu_mem=False,
     ):
         mconfig             = OmegaConf.load(conf)
-        self.model_name     = model
         self.height         = None
         self.width          = None
         self.model_cache    = None
@@ -188,6 +190,8 @@ class Generate:
 
         # model caching system for fast switching
         self.model_cache = ModelCache(mconfig,self.device,self.precision)
+        print(f'DEBUG: model={model}, default_model={self.model_cache.default_model()}')
+        self.model_name  = model or self.model_cache.default_model() or FALLBACK_MODEL_NAME
 
         # for VRAM usage statistics
         self.session_peakmem = torch.cuda.max_memory_allocated() if self._has_cuda else None

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'

scripts/invoke.py

@@ -341,6 +341,7 @@ def main_loop(gen, opt, infile):
 
     print('goodbye!')
 
+    # to do: this is ugly, fix
 def do_command(command:str, gen, opt:Args, completer) -> tuple:
     operation = 'generate'   # default operation, alternative is 'postprocess'
 
@@ -455,7 +456,10 @@ def add_weights_to_config(model_path:str, gen, opt, completer):
                 done = True
             except:
                 print('** Please enter a valid integer between 64 and 2048')
-    if write_config_file(opt.conf, gen, model_name, new_config):
+
+    make_default = input('Make this the default model? [n] ') in ('y','Y')
+    
+    if write_config_file(opt.conf, gen, model_name, new_config, make_default=make_default):
         completer.add_model(model_name)
 
 def del_config(model_name:str, gen, opt, completer):
@@ -488,14 +492,17 @@ def edit_config(model_name:str, gen, opt, completer):
         completer.linebuffer = str(conf[field]) if field in conf else ''
         new_value = input(f'{field}: ')
         new_config[field] = int(new_value) if field in ('width','height') else new_value
+    make_default = input('Make this the default model? [n] ') in ('y','Y')
     completer.complete_extensions(None)
-    write_config_file(opt.conf, gen, model_name, new_config, clobber=True)
+    write_config_file(opt.conf, gen, model_name, new_config, clobber=True, make_default=make_default)
     
-def write_config_file(conf_path, gen, model_name, new_config, clobber=False):
+def write_config_file(conf_path, gen, model_name, new_config, clobber=False, make_default=False):
     current_model = gen.model_name
     
     op = 'modify' if clobber else 'import'
     print('\n>> New configuration:')
+    if make_default:
+        new_config['default'] = True
     print(yaml.dump({model_name:new_config}))
     if input(f'OK to {op} [n]? ') not in ('y','Y'):
         return False
@@ -509,10 +516,11 @@ def write_config_file(conf_path, gen, model_name, new_config, clobber=False):
         gen.model_cache.del_model(model_name)
         return False
 
-    tmpfile = os.path.join(os.path.dirname(conf_path),'new_config.tmp')
-    with open(tmpfile, 'w') as outfile:
-        outfile.write(yaml_str)
-    os.rename(tmpfile,conf_path)
+    if make_default:
+        print('making this default')
+        gen.model_cache.set_default_model(model_name)
+
+    gen.model_cache.commit(conf_path)
     
     do_switch = input(f'Keep model loaded? [y]')
     if len(do_switch)==0 or do_switch[0] in ('y','Y'):