add support for controlnet & sdxl conversion - not fully working

invokeai/backend/install/invokeai_configure.py

@@ -55,6 +55,7 @@ from invokeai.frontend.install.widgets import (
 from invokeai.backend.install.legacy_arg_parsing import legacy_parser
 from invokeai.backend.install.model_install_backend import (
     hf_download_from_pretrained,
+    hf_download_with_resume,
     InstallSelections,
     ModelInstall,
 )
@@ -204,6 +205,13 @@ def download_conversion_models():
         pipeline = CLIPTextModel.from_pretrained(repo_id, subfolder="text_encoder", **kwargs)
         pipeline.save_pretrained(target_dir / 'stable-diffusion-2-clip' / 'text_encoder', safe_serialization=True)
 
+        repo_id = "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k"
+        _, model_name = repo_id.split('/')
+        tokenizer_2 = CLIPTokenizer.from_pretrained(repo_id, **kwargs)
+        tokenizer_2.save_pretrained(target_dir / model_name, safe_serialization=True)
+        # for some reason config.json never downloads
+        hf_download_with_resume(repo_id, target_dir / model_name, "config.json")
+
         # VAE
         logger.info('Downloading stable diffusion VAE')
         vae = AutoencoderKL.from_pretrained('stabilityai/sd-vae-ft-mse', **kwargs)

invokeai/backend/install/model_install_backend.py

@@ -58,7 +58,15 @@ LEGACY_CONFIGS = {
             SchedulerPredictionType.Epsilon: 'v2-inpainting-inference.yaml',
             SchedulerPredictionType.VPrediction: 'v2-inpainting-inference-v.yaml',
         }
-    }
+    },
+    
+    BaseModelType.StableDiffusionXL: {
+        ModelVariantType.Normal: 'sd_xl_base.yaml',
+    },
+    
+    BaseModelType.StableDiffusionXLRefiner: {
+        ModelVariantType.Normal: 'sd_xl_refiner.yaml',
+    },
 }
 
 @dataclass
@@ -329,6 +337,7 @@ class ModelInstall(object):
             description = str(description),
             model_format = info.format,
             )
+        legacy_conf = None
         if info.model_type == ModelType.Main:
             attributes.update(dict(variant = info.variant_type,))
             if info.format=="checkpoint":
@@ -343,11 +352,17 @@ class ModelInstall(object):
                 except KeyError:
                     legacy_conf = Path(self.config.legacy_conf_dir, 'v1-inference.yaml')  # best guess
                     
-                attributes.update(
-                    dict(
-                        config = str(legacy_conf)
-                    )
+        if info.model_type == ModelType.ControlNet and info.format=="checkpoint":
+            possible_conf = path.with_suffix('.yaml')
+            if possible_conf.exists():
+                legacy_conf = str(self.relative_to_root(possible_conf))
+
+        if legacy_conf:
+            attributes.update(
+                dict(
+                    config = str(legacy_conf)
                 )
+            )
         return attributes
 
     def relative_to_root(self, path: Path)->Path: