fixed causvid scheduler

flux/flux_main.py

@@ -72,10 +72,7 @@ class model_factory:
             if self._interrupt:
                 return None
 
-            rng = torch.Generator(device="cuda")
-            if seed is None:
-                seed = rng.seed()
-
+            device="cuda"
             if input_ref_images != None and len(input_ref_images) > 0: 
                 image_ref = input_ref_images[0]
                 w, h = image_ref.size
@@ -91,7 +88,7 @@ class model_factory:
                 target_height=height,
                 bs=batch_size,
                 seed=seed,
-                device="cuda",
+                device=device,
             )
 
             inp.pop("img_cond_orig")
@@ -103,7 +100,7 @@ class model_factory:
             if x==None: return None
             # decode latents to pixel space
             x = unpack_latent(x)
-            with torch.autocast(device_type="cuda", dtype=torch.bfloat16):
+            with torch.autocast(device_type=device, dtype=torch.bfloat16):
                 x = self.vae.decode(x)
 
             x = x.clamp(-1, 1)

flux/sampling.py

@@ -30,8 +30,8 @@ def get_noise(
         2 * math.ceil(height / 16),
         2 * math.ceil(width / 16),
         dtype=dtype,
-        generator=torch.Generator(device="cuda").manual_seed(seed),
-    ).to(device)
+        generator=torch.Generator(device=device).manual_seed(seed),
+    )
 
 
 def prepare(t5: HFEmbedder, clip: HFEmbedder, img: Tensor, prompt: str | list[str]) -> dict[str, Tensor]:

preprocessing/depth_anything_v2/layers/attention.py

@@ -15,13 +15,7 @@ from torch import nn
 
 logger = logging.getLogger("dinov2")
 
-try:
-    from xformers.ops import memory_efficient_attention, unbind, fmha
-
-    XFORMERS_AVAILABLE = True
-except ImportError:
-    logger.warning("xFormers not available")
-    XFORMERS_AVAILABLE = False
+XFORMERS_AVAILABLE = False
 
 
 class Attention(nn.Module):

preprocessing/depth_anything_v2/layers/block.py

@@ -23,14 +23,7 @@ from .mlp import Mlp
 logger = logging.getLogger("dinov2")
 
 
-try:
-    from xformers.ops import fmha
-    from xformers.ops import scaled_index_add, index_select_cat
-
-    XFORMERS_AVAILABLE = True
-except ImportError:
-    # logger.warning("xFormers not available")
-    XFORMERS_AVAILABLE = False
+XFORMERS_AVAILABLE = False
 
 
 class Block(nn.Module):

wan/utils/basic_flowmatch.py

@@ -53,7 +53,7 @@ class FlowMatchScheduler():
         else:
             sigma_ = self.sigmas[timestep_id + 1].reshape(-1, 1, 1, 1)
         prev_sample = sample + model_output * (sigma_ - sigma)
-        return prev_sample
+        return [prev_sample]
 
     def add_noise(self, original_samples, noise, timestep):
         """

wan/utils/utils.py

@@ -493,10 +493,10 @@ def extract_audio_tracks(source_video, verbose=False, query_only= False):
         
     except ffmpeg.Error as e:
         print(f"FFmpeg error during audio extraction: {e}")
-        return []
+        return 0 if query_only else []
     except Exception as e:
         print(f"Error during audio extraction: {e}")
-        return []
+        return 0 if query_only else []
 
 def combine_video_with_audio_tracks(target_video, audio_tracks, output_video, verbose=False):
     """