upload new config changer

adapt_config.py

@@ -43,17 +43,22 @@ def is_index_stable_diffusion_like(config_dict):
 
 
 def convert_single(model_id: str, folder: str) -> List["CommitOperationAdd"]:
-    config_file = "scheduler/scheduler_config.json"
-    os.makedirs(os.path.join(folder, "scheduler"), exist_ok=True)
+    config_file = "model_index.json"
+    # os.makedirs(os.path.join(folder, "scheduler"), exist_ok=True)
     model_index_file = hf_hub_download(repo_id=model_id, filename="model_index.json")
 
     with open(model_index_file, "r") as f:
         index_dict = json.load(f)
-        if not is_index_stable_diffusion_like(index_dict):
-            print(f"{model_id} is not of type stable diffusion.")
+        if index_dict.get("feature_extractor", None) is None:
+            print(f"{model_id} has no feature extractor")
             return False, False
 
-    old_config_file = hf_hub_download(repo_id=model_id, filename=config_file)
+        if index_dict["feature_extractor"][-1] != "CLIPFeatureExtractor":
+            print(f"{model_id} is not out of date or is not CLIP")
+            return False, False
+
+    # old_config_file = hf_hub_download(repo_id=model_id, filename=config_file)
+    old_config_file = model_index_file
 
     new_config_file = os.path.join(folder, config_file)
     success = convert_file(old_config_file, new_config_file)
@@ -72,45 +77,18 @@ def convert_file(
     with open(old_config, "r") as f:
         old_dict = json.load(f)
 
-    if "clip_sample" not in old_dict:
-        print("Make scheduler DDIM compatible")
-        old_dict["clip_sample"] = False
-    else:
-        print("No matching config")
-        return False
+    old_dict["feature_extractor"][-1] = "CLIPImageProcessor"
+    # if "clip_sample" not in old_dict:
+    #     print("Make scheduler DDIM compatible")
+    #     old_dict["clip_sample"] = False
+    # else:
+    #     print("No matching config")
+    #     return False
 
-#    is_stable_diffusion = "down_block_types" in old_dict and list(old_dict["down_block_types"]) == ["CrossAttnDownBlock2D", "CrossAttnDownBlock2D", "CrossAttnDownBlock2D", "DownBlock2D"]
-#
-#    is_stable_diffusion_1 = is_stable_diffusion and ("use_linear_projection" not in old_dict or old_dict["use_linear_projection"] is False)
-#    is_stable_diffusion_2 = is_stable_diffusion and ("use_linear_projection" in old_dict and old_dict["use_linear_projection"] is True)
-#
-#    if not is_stable_diffusion_1 and not is_stable_diffusion_2:
-#        print("No matching config")
-#        return False
-#
-#    if is_stable_diffusion_1:
-#        if old_dict["sample_size"] == 64:
-#            print("Dict correct")
-#            return False
-#
-#        print("Correct stable diffusion 1")
-#        old_dict["sample_size"] = 64
-#
-#    if is_stable_diffusion_2:
-#        if old_dict["sample_size"] == 96:
-#            print("Dict correct")
-#            return False
-#
-#        print("Correct stable diffusion 2")
-#        old_dict["sample_size"] = 96
-#
     with open(new_config, 'w') as f:
         json_str = json.dumps(old_dict, indent=2, sort_keys=True) + "\n"
         f.write(json_str)
 
-#
-#    return "Stable Diffusion 1" if is_stable_diffusion_1 else "Stable Diffusion 2"
-
     return "Stable Diffusion"
 
 
@@ -126,17 +104,17 @@ def previous_pr(api: "HfApi", model_id: str, pr_title: str) -> Optional["Discuss
 
 def convert(api: "HfApi", model_id: str, force: bool = False) -> Optional["CommitInfo"]:
 #    pr_title = "Correct `sample_size` of {}'s unet to have correct width and height default"
-    pr_title = "Add `clip_sample=False` to scheduler to make model compatible with DDIM." 
+    pr_title = "Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`."
     info = api.model_info(model_id)
     filenames = set(s.rfilename for s in info.siblings)
 
-    if "unet/config.json" not in filenames:
-        print(f"Model: {model_id} has no 'unet/config.json' file to change")
+    if "model_index.json" not in filenames:
+        print(f"Model: {model_id} has no model_index.json file to change")
         return
 
-    if "vae/config.json" not in filenames:
-        print(f"Model: {model_id} has no 'vae/config.json' file to change")
-        return
+    # if "vae/config.json" not in filenames:
+    #     print(f"Model: {model_id} has no 'vae/config.json' file to change")
+    #     return
 
     with TemporaryDirectory() as d:
         folder = os.path.join(d, repo_folder_name(repo_id=model_id, repo_type="models"))
@@ -166,7 +144,11 @@ def convert(api: "HfApi", model_id: str, force: bool = False) -> Optional["Commi
 #                )
                 contributor = model_id.split("/")[0]
                 pr_description = (
-                    f"Hey {contributor} 👋, \n\n Your model repository seems to contain a stable diffusion checkpoint. We have noticed that your scheduler config currently does not correctly work with the [DDIMScheduler](https://huggingface.co/docs/diffusers/main/en/api/schedulers#diffusers.DDIMScheduler) because `clip_sample` is not set to False and will therefore [incorrectly default to True](https://github.com/huggingface/diffusers/blob/3ce6380d3a2ec5c3e3f4f48889d380d657b151bc/src/diffusers/schedulers/scheduling_ddim.py#L127). \n The official stable diffusion checkpoints have `clip_sample=False` so that the scheduler config works will **all** schedulers, see: https://huggingface.co/stabilityai/stable-diffusion-2-1-base/blob/main/scheduler/scheduler_config.json#L7. \n\n We strongly recommend that you merge this PR to make sure your model works correctly with DDIM. \n\n Diffusingly, \n Patrick."
+                        f"Hey {contributor} 👋, \n\n Your model repository seems to contain logic to load a feature extractor that is deprecated, which you should notice by seeing the warning: "
+                        "\n\n ```\ntransformers/models/clip/feature_extraction_clip.py:28: FutureWarning: The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. "
+                        f"Please use CLIPImageProcessor instead. warnings.warn(\n``` \n\n when running `pipe = DiffusionPipeline.from_pretrained({model_id})`."
+                        "This PR makes sure that the warning does not show anymore by replacing `CLIPFeatureExtractor` with `CLIPImageProcessor`. This will certainly not change or break your checkpoint, but only" 
+                        "make sure that everything is up to date. \n\n Best, the 🧨 Diffusers team."
                 )
                 new_pr = api.create_commit(
                     repo_id=model_id,