fix: apply CodeRabbit auto-fixes

Fixed 2 file(s) based on 2 unresolved review comments.

Co-authored-by: CodeRabbit <noreply@coderabbit.ai>

fastvideo/configs/pipelines/kandinsky5.py

@@ -76,6 +76,12 @@ class Kandinsky5T2VConfig(PipelineConfig):
     vae_tiling: bool = True
 
     def __post_init__(self) -> None:
+        if len(self.text_encoder_configs) != 2:
+            raise ValueError(
+                f"Kandinsky5 pipeline requires exactly 2 text encoders (qwen and clip), "
+                f"but got {len(self.text_encoder_configs)} encoder(s)."
+            )
+
         self.vae_config.load_encoder = False
         self.vae_config.load_decoder = True
 

fastvideo/pipelines/stages/kandinsky5.py

@@ -2,6 +2,8 @@
 
 from __future__ import annotations
 
+import contextlib
+
 import torch
 from diffusers.utils.torch_utils import randn_tensor
 from tqdm.auto import tqdm
@@ -184,7 +186,9 @@ class Kandinsky5DenoisingStage(PipelineStage):
                     continue
 
                 t_expand = timestep.unsqueeze(0).repeat(latents.shape[0]).to(device=device, dtype=target_dtype)
-                with torch.autocast(device_type="cuda", dtype=target_dtype, enabled=autocast_enabled):
+                autocast_ctx = (torch.autocast(device_type="cuda", dtype=target_dtype, enabled=autocast_enabled)
+                                if device.type == "cuda" else contextlib.nullcontext())
+                with autocast_ctx:
                     pred_velocity = self.transformer(
                         hidden_states=latents.to(dtype=target_dtype),
                         encoder_hidden_states=prompt_embeds,