Update app.py

app.py

@@ -142,45 +142,45 @@ def import_custom_nodes() -> None:
 from nodes import NODE_CLASS_MAPPINGS
 
 #TO be added to "model_loaders" as it loads a model
-downloadandloadcogvideomodel = NODE_CLASS_MAPPINGS[
-    "DownloadAndLoadCogVideoModel"
-]()
-downloadandloadcogvideomodel_1 = downloadandloadcogvideomodel.loadmodel(
-    model="THUDM/CogVideoX-5b",
-    precision="bf16",
-    quantization="disabled",
-    enable_sequential_cpu_offload=True,
-    attention_mode="sdpa",
-    load_device="main_device",
-)
-loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
-cliploader = NODE_CLASS_MAPPINGS["CLIPLoader"]()
-cliploader_20 = cliploader.load_clip(
-    clip_name="t5/google_t5-v1_1-xxl_encoderonly-fp8_e4m3fn.safetensors",
-    type="sd3",
-    device="default",
-)
-emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
-
-cogvideotextencode = NODE_CLASS_MAPPINGS["CogVideoTextEncode"]()
-cogvideosampler = NODE_CLASS_MAPPINGS["CogVideoSampler"]()
-cogvideodecode = NODE_CLASS_MAPPINGS["CogVideoDecode"]()
-reactorfaceswap = NODE_CLASS_MAPPINGS["ReActorFaceSwap"]()
-cr_upscale_image = NODE_CLASS_MAPPINGS["CR Upscale Image"]()
-vhs_videocombine = NODE_CLASS_MAPPINGS["VHS_VideoCombine"]()
-
-#Add all the models that load a safetensors file
-model_loaders = [downloadandloadcogvideomodel_1, cliploader_20]
-
-# Check which models are valid and how to best load them
-valid_models = [
-    getattr(loader[0], 'patcher', loader[0]) 
-    for loader in model_loaders
-    if not isinstance(loader[0], dict) and not isinstance(getattr(loader[0], 'patcher', None), dict)
-]
-
-#Finally loads the models
-model_management.load_models_gpu(valid_models)
+# downloadandloadcogvideomodel = NODE_CLASS_MAPPINGS[
+#     "DownloadAndLoadCogVideoModel"
+# ]()
+# downloadandloadcogvideomodel_1 = downloadandloadcogvideomodel.loadmodel(
+#     model="THUDM/CogVideoX-5b",
+#     precision="bf16",
+#     quantization="disabled",
+#     enable_sequential_cpu_offload=True,
+#     attention_mode="sdpa",
+#     load_device="main_device",
+# )
+# loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
+# cliploader = NODE_CLASS_MAPPINGS["CLIPLoader"]()
+# cliploader_20 = cliploader.load_clip(
+#     clip_name="t5/google_t5-v1_1-xxl_encoderonly-fp8_e4m3fn.safetensors",
+#     type="sd3",
+#     device="default",
+# )
+# emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
+
+# cogvideotextencode = NODE_CLASS_MAPPINGS["CogVideoTextEncode"]()
+# cogvideosampler = NODE_CLASS_MAPPINGS["CogVideoSampler"]()
+# cogvideodecode = NODE_CLASS_MAPPINGS["CogVideoDecode"]()
+# reactorfaceswap = NODE_CLASS_MAPPINGS["ReActorFaceSwap"]()
+# cr_upscale_image = NODE_CLASS_MAPPINGS["CR Upscale Image"]()
+# vhs_videocombine = NODE_CLASS_MAPPINGS["VHS_VideoCombine"]()
+
+# #Add all the models that load a safetensors file
+# model_loaders = [downloadandloadcogvideomodel_1, cliploader_20]
+
+# # Check which models are valid and how to best load them
+# valid_models = [
+#     getattr(loader[0], 'patcher', loader[0]) 
+#     for loader in model_loaders
+#     if not isinstance(loader[0], dict) and not isinstance(getattr(loader[0], 'patcher', None), dict)
+# ]
+
+# #Finally loads the models
+# model_management.load_models_gpu(valid_models)
 
 #Run ComfyUI Workflow
 @spaces.GPU(duration=60)
@@ -192,39 +192,39 @@ def generate_video(positive_prompt, num_frames, input_image):
 
     import_custom_nodes()
     with torch.inference_mode():
-        # downloadandloadcogvideomodel = NODE_CLASS_MAPPINGS[
-        #     "DownloadAndLoadCogVideoModel"
-        # ]()
-        # downloadandloadcogvideomodel_1 = downloadandloadcogvideomodel.loadmodel(
-        #     model="THUDM/CogVideoX-5b",
-        #     precision="bf16",
-        #     quantization="disabled",
-        #     enable_sequential_cpu_offload=True,
-        #     attention_mode="sdpa",
-        #     load_device="main_device",
-        # )
-
-        # loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
+        downloadandloadcogvideomodel = NODE_CLASS_MAPPINGS[
+            "DownloadAndLoadCogVideoModel"
+        ]()
+        downloadandloadcogvideomodel_1 = downloadandloadcogvideomodel.loadmodel(
+            model="THUDM/CogVideoX-5b",
+            precision="bf16",
+            quantization="disabled",
+            enable_sequential_cpu_offload="disabled",
+            attention_mode="sdpa",
+            load_device="main_device",
+        )
+
+        loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
         loadimage_8 = loadimage.load_image(image=input_image)
 
-        # cliploader = NODE_CLASS_MAPPINGS["CLIPLoader"]()
-        # cliploader_20 = cliploader.load_clip(
-        #     clip_name="t5/google_t5-v1_1-xxl_encoderonly-fp8_e4m3fn.safetensors",
-        #     type="sd3",
-        #     device="default",
-        # )
+        cliploader = NODE_CLASS_MAPPINGS["CLIPLoader"]()
+        cliploader_20 = cliploader.load_clip(
+            clip_name="t5/google_t5-v1_1-xxl_encoderonly-fp8_e4m3fn.safetensors",
+            type="sd3",
+            device="default",
+        )
 
-        # emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
+        emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
         emptylatentimage_161 = emptylatentimage.generate(
             width=720, height=480, batch_size=1
         )
 
-        # cogvideotextencode = NODE_CLASS_MAPPINGS["CogVideoTextEncode"]()
-        # cogvideosampler = NODE_CLASS_MAPPINGS["CogVideoSampler"]()
-        # cogvideodecode = NODE_CLASS_MAPPINGS["CogVideoDecode"]()
-        # reactorfaceswap = NODE_CLASS_MAPPINGS["ReActorFaceSwap"]()
-        # cr_upscale_image = NODE_CLASS_MAPPINGS["CR Upscale Image"]()
-        # vhs_videocombine = NODE_CLASS_MAPPINGS["VHS_VideoCombine"]()
+        cogvideotextencode = NODE_CLASS_MAPPINGS["CogVideoTextEncode"]()
+        cogvideosampler = NODE_CLASS_MAPPINGS["CogVideoSampler"]()
+        cogvideodecode = NODE_CLASS_MAPPINGS["CogVideoDecode"]()
+        reactorfaceswap = NODE_CLASS_MAPPINGS["ReActorFaceSwap"]()
+        cr_upscale_image = NODE_CLASS_MAPPINGS["CR Upscale Image"]()
+        vhs_videocombine = NODE_CLASS_MAPPINGS["VHS_VideoCombine"]()
 
         for q in range(1):
             cogvideotextencode_30 = cogvideotextencode.process(