gpu upgrade debug

app.py

@@ -13,7 +13,7 @@ import diffusers
 import requests
 
 
-assert tuple(map(int,diffusers.__version__.split(".")))  >= (0,9,0), "Please upgrade diffusers to 0.9.0"
+# assert tuple(map(int,diffusers.__version__.split(".")))  >= (0,9,0), "Please upgrade diffusers to 0.9.0"
 
 from diffusers.configuration_utils import FrozenDict
 from diffusers import (
@@ -41,13 +41,13 @@ from enum import Enum
 from utils import *
 
 # load environment variables from the .env file
-if os.path.exists(".env"):
-    with open(".env") as f:
-        for line in f:
-            if line.startswith("#") or not line.strip():
-                continue
-            name, value = line.strip().split("=", 1)
-            os.environ[name] = value
+# if os.path.exists(".env"):
+#     with open(".env") as f:
+#         for line in f:
+#             if line.startswith("#") or not line.strip():
+#                 continue
+#             name, value = line.strip().split("=", 1)
+#             os.environ[name] = value
 
 
 # access_token = os.environ.get("HF_ACCESS_TOKEN")
@@ -221,10 +221,19 @@ parser.add_argument(
     "--local_model", type=str, help="use a model stored on your PC", default=""
 )
 
-if __name__ == "__main__":
+# original 
+# if __name__ == "__main__":
+#     args = parser.parse_args()
+# else:
+#     args = parser.parse_args(["--debug"])
+# # args = parser.parse_args(["--debug"])
+# if args.auth is not None:
+#     args.auth = tuple(args.auth)
+
+if __name__ == "__main__" and not RUN_IN_SPACE:
     args = parser.parse_args()
 else:
-    args = parser.parse_args(["--debug"])
+    args = parser.parse_args()
 # args = parser.parse_args(["--debug"])
 if args.auth is not None:
     args.auth = tuple(args.auth)
@@ -447,10 +456,17 @@ class StableDiffusionInpaint:
         selected_scheduler = scheduler_dict.get(scheduler, scheduler_dict["PLMS"])
         for item in [inpaint]:
             item.scheduler = selected_scheduler
-            if enable_safety or self.safety_checker is None:
+            if enable_safety:
                 item.safety_checker = self.safety_checker
             else:
                 item.safety_checker = lambda images, **kwargs: (images, False)
+        
+        # for item in [inpaint]:
+        #     item.scheduler = selected_scheduler
+        #     if enable_safety or self.safety_checker is None:
+        #         item.safety_checker = self.safety_checker
+        #     else:
+        #         item.safety_checker = lambda images, **kwargs: (images, False)
         width, height = image_pil.size
         sel_buffer = np.array(image_pil)
         img = sel_buffer[:, :, 0:3]
@@ -1088,16 +1104,56 @@ class StableDiffusion:
 #                 )["images"]
 #         return images
 
-
+# ORIGINAL 
+# def get_model(token="", model_choice="", model_path=""):
+#     if "model" not in model:
+#         model_name = ""
+#         if args.local_model:
+#             print(f"Using local_model: {args.local_model}")
+#             model_path = args.local_model
+#         elif args.remote_model:
+#             print(f"Using remote_model: {args.remote_model}")
+#             model_name = args.remote_model
+#         if model_choice == ModelChoice.INPAINTING.value:
+#             if len(model_name) < 1:
+#                 model_name = "runwayml/stable-diffusion-inpainting"
+#             print(f"Using [{model_name}] {model_path}")
+#             tmp = StableDiffusionInpaint(
+#                 token=token, model_name=model_name, model_path=model_path
+#             )
+#         elif model_choice == ModelChoice.INPAINTING2.value:
+#             if len(model_name) < 1:
+#                 model_name = "stabilityai/stable-diffusion-2-inpainting"
+#             print(f"Using [{model_name}] {model_path}")
+#             tmp = StableDiffusionInpaint(
+#                 token=token, model_name=model_name, model_path=model_path
+#             )
+#         elif model_choice == ModelChoice.INPAINTING_IMG2IMG.value:
+#             print(
+#                 f"Note that {ModelChoice.INPAINTING_IMG2IMG.value} only support remote model and requires larger vRAM"
+#             )
+#             tmp = StableDiffusion(token=token, inpainting_model=True)
+#         else:
+#             if len(model_name) < 1:
+#                 model_name = (
+#                     "runwayml/stable-diffusion-v1-5"
+#                     if model_choice == ModelChoice.MODEL_1_5.value
+#                     else "CompVis/stable-diffusion-v1-4"
+#                 )
+#                 if model_choice == ModelChoice.MODEL_2_0.value:
+#                     model_name = "stabilityai/stable-diffusion-2-base"
+#                 elif model_choice == ModelChoice.MODEL_2_0_V.value:
+#                     model_name = "stabilityai/stable-diffusion-2"
+#                 elif model_choice == ModelChoice.MODEL_2_1.value:
+#                     model_name = "stabilityai/stable-diffusion-2-1-base"
+#             tmp = StableDiffusion(
+#                 token=token, model_name=model_name, model_path=model_path
+#             )
+#         model["model"] = tmp
+#     return model["model"]
 def get_model(token="", model_choice="", model_path=""):
     if "model" not in model:
         model_name = ""
-        if args.local_model:
-            print(f"Using local_model: {args.local_model}")
-            model_path = args.local_model
-        elif args.remote_model:
-            print(f"Using remote_model: {args.remote_model}")
-            model_name = args.remote_model
         if model_choice == ModelChoice.INPAINTING.value:
             if len(model_name) < 1:
                 model_name = "runwayml/stable-diffusion-inpainting"
@@ -1105,18 +1161,11 @@ def get_model(token="", model_choice="", model_path=""):
             tmp = StableDiffusionInpaint(
                 token=token, model_name=model_name, model_path=model_path
             )
-        elif model_choice == ModelChoice.INPAINTING2.value:
-            if len(model_name) < 1:
-                model_name = "stabilityai/stable-diffusion-2-inpainting"
-            print(f"Using [{model_name}] {model_path}")
-            tmp = StableDiffusionInpaint(
-                token=token, model_name=model_name, model_path=model_path
-            )
         elif model_choice == ModelChoice.INPAINTING_IMG2IMG.value:
             print(
                 f"Note that {ModelChoice.INPAINTING_IMG2IMG.value} only support remote model and requires larger vRAM"
             )
-            tmp = StableDiffusion(token=token, inpainting_model=True)
+            tmp = StableDiffusion(token=token, model_name="runwayml/stable-diffusion-v1-5", inpainting_model=True)
         else:
             if len(model_name) < 1:
                 model_name = (
@@ -1124,19 +1173,12 @@ def get_model(token="", model_choice="", model_path=""):
                     if model_choice == ModelChoice.MODEL_1_5.value
                     else "CompVis/stable-diffusion-v1-4"
                 )
-                if model_choice == ModelChoice.MODEL_2_0.value:
-                    model_name = "stabilityai/stable-diffusion-2-base"
-                elif model_choice == ModelChoice.MODEL_2_0_V.value:
-                    model_name = "stabilityai/stable-diffusion-2"
-                elif model_choice == ModelChoice.MODEL_2_1.value:
-                    model_name = "stabilityai/stable-diffusion-2-1-base"
             tmp = StableDiffusion(
                 token=token, model_name=model_name, model_path=model_path
             )
         model["model"] = tmp
     return model["model"]
 
-
 def run_outpaint(
     sel_buffer_str,
     prompt_text,
@@ -1298,7 +1340,7 @@ with blocks as demo:
             # model_choices_lst.insert(0, "local_model")
         elif args.remote_model:
             model_path_input_val = args.remote_model
-            model_choices_lst.insert(0, "remote_model")
+            # model_choices_lst.insert(0, "remote_model")
 
         sd_prompt = gr.Textbox(
             label="Prompt", placeholder="input your prompt here!", lines=2