ruff

server/lorax_server/models/causal_lm.py

@@ -596,11 +596,11 @@ def generate_token(self, batch: CausalLMBatch) -> Tuple[List[Generation], Option
         # TODO(travis): don't update this if indices haven't changed
         # Use prefill=True in all cases to force use of SGMV, as the batch is heterogenous
         adapter_data = AdapterBatchData.from_meta(
-            meta=batch.adapter_meta, 
-            weights=self.layer_to_adapter_weights, 
+            meta=batch.adapter_meta,
+            weights=self.layer_to_adapter_weights,
             layer_to_lora_weights={},
             punica_wrapper=None,
-            prefill=True, 
+            prefill=True,
             prefill_head_indices=None,
         )
 

server/lorax_server/models/flash_qwen2.py

@@ -122,11 +122,11 @@ def embed(self, batch) -> torch.Tensor:
         adapter_meta = batch.adapter_meta
         prefill = False
         adapter_data = AdapterBatchData.from_meta(
-            meta=adapter_meta, 
-            weights=self.layer_to_adapter_weights, 
+            meta=adapter_meta,
+            weights=self.layer_to_adapter_weights,
             layer_to_lora_weights={},
             punica_wrapper=None,
-            prefill=prefill, 
+            prefill=prefill,
             prefill_head_indices=batch.prefill_head_indices,
         )
         embedding, _ = self.forward(batch, adapter_data=adapter_data)

server/lorax_server/models/flash_roberta.py

@@ -210,11 +210,11 @@ def forward(self, batch: FlashEmbeddingClassificationBatch):
     @tracer.start_as_current_span("embed")
     def embed(self, batch: FlashEmbeddingClassificationBatch) -> Embedding:
         adapter_data = AdapterBatchData.from_meta(
-            meta=batch.adapter_meta, 
-            weights=self.layer_to_adapter_weights, 
+            meta=batch.adapter_meta,
+            weights=self.layer_to_adapter_weights,
             layer_to_lora_weights={},
             punica_wrapper=None,
-            prefill=False, 
+            prefill=False,
             prefill_head_indices=None,
         )