remove half

app.py

@@ -29,14 +29,14 @@ def get_modelscope_pipeline(
     mcm_variant: Optional[str] = "WebVid",
 ):
     model_id = "ali-vilab/text-to-video-ms-1.7b"
-    if torch.cuda.is_available():
-        pipe = DiffusionPipeline.from_pretrained(
-            model_id, torch_dtype=torch.float16, variant="fp16"
-        )
-    else:
-        pipe = DiffusionPipeline.from_pretrained(
-            model_id
-        )
+    # if torch.cuda.is_available():
+    #     pipe = DiffusionPipeline.from_pretrained(
+    #         model_id, torch_dtype=torch.float16, variant="fp16"
+    #     )
+    # else:
+    pipe = DiffusionPipeline.from_pretrained(
+        model_id
+    )
     scheduler = LCMScheduler.from_pretrained(
         model_id,
         subfolder="scheduler",
@@ -87,23 +87,23 @@ def get_animatediff_pipeline(
     else:
         raise ValueError(f"Unknown real_variant {real_variant}")
 
-    if torch.cuda.is_available():
-        adapter = MotionAdapter.from_pretrained(
-            motion_module_path, torch_dtype=torch.float16
-        )
-        pipe = AnimateDiffPipeline.from_pretrained(
-            model_id,
-            motion_adapter=adapter,
-            torch_dtype=torch.float16,
-        )
-    else:
-        adapter = MotionAdapter.from_pretrained(
-            motion_module_path
-        )
-        pipe = AnimateDiffPipeline.from_pretrained(
-            model_id,
-            motion_adapter=adapter,
-        )
+    # if torch.cuda.is_available():
+    #     adapter = MotionAdapter.from_pretrained(
+    #         motion_module_path, torch_dtype=torch.float16
+    #     )
+    #     pipe = AnimateDiffPipeline.from_pretrained(
+    #         model_id,
+    #         motion_adapter=adapter,
+    #         torch_dtype=torch.float16,
+    #     )
+    # else:
+    adapter = MotionAdapter.from_pretrained(
+        motion_module_path
+    )
+    pipe = AnimateDiffPipeline.from_pretrained(
+        model_id,
+        motion_adapter=adapter,
+    )
     scheduler = LCMScheduler.from_pretrained(
         model_id,
         subfolder="scheduler",
@@ -214,7 +214,7 @@ def infer(
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
-    generator = torch.Generator().manual_seed(seed)
+    generator = torch.Generator("cpu").manual_seed(seed)
 
     output = cache_pipeline["pipeline"](
         prompt=prompt,