ruff checks

comfy/autoregressive_sampling.py

@@ -14,10 +14,10 @@ import comfy.model_management
 class CacheLayerParent(ABC):
     def __init__(self):
         self.keys, self.values = None, None
-    
+
     @abstractmethod
     def lazy_init(self, key_states): ...
-    
+
     @abstractmethod
     def update(self, key_states, value_states, cache_kwargs = None): ...
 
@@ -40,7 +40,7 @@ class Cache:
         if layer_idx >= len(self.layers):
             return 0
         return self.layers[layer_idx].get_seq_length()
-    
+
     def get_max_cache_shape(self, layer_idx = 0):
         if layer_idx >= len(self.layers): # for future dynamic cache impl.
             return -1
@@ -52,7 +52,7 @@ class Cache:
     def update(self, key_states, value_states, layer_idx, cache_kwargs):
         keys, values = self.layers[layer_idx].update(key_states, value_states, cache_kwargs)
         return keys, values
-    
+
     @property
     def max_cache_len(self):
         values = [layer.max_cache_len for layer in self.layers]
@@ -73,7 +73,7 @@ class StaticLayer(CacheLayerParent):
 
         self.max_batch_size, self.num_heads, _, self.head_dim = key_states.shape
         self.dtype, self.device = key_states.dtype, key_states.device
-        
+
         self.keys = torch.zeros(
             (self.max_batch_size, self.num_heads, self.max_cache_len, self.head_dim),
             dtype=self.dtype,
@@ -87,7 +87,7 @@ class StaticLayer(CacheLayerParent):
         )
 
     def update(self, key_states, value_states, cache_kwargs = None):
-        
+
         if self.keys is None:
             self.lazy_init(key_states)
 
@@ -104,7 +104,7 @@ class StaticLayer(CacheLayerParent):
             self.keys[:, :, cache_position] = key_states
             self.values[:, :, cache_position] = value_states
         return self.keys, self.values
-    
+
 class StaticCache(Cache):
     def __init__(self, config, max_cache_len):
         self.layers = [StaticLayer(max_cache_len) for _ in range(config.num_hidden_layers)]