Fix lint: formatting in RoPE and golden test

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Signed-off-by: Justin Chu <justinchu@microsoft.com>

Author: justinchuby

src/mobius/components/_rotary_embedding.py

@@ -150,9 +150,7 @@ def _cast_embeddings(
         return cos, sin
 
     def forward(self, op: builder.OpBuilder, position_ids: ir.Value):
-        cos, sin = get_rotary_pos_emb(
-            op, position_ids, self.cos_cache, self.sin_cache
-        )
+        cos, sin = get_rotary_pos_emb(op, position_ids, self.cos_cache, self.sin_cache)
         return self._cast_embeddings(op, cos, sin)
 
 
@@ -306,9 +304,7 @@ def forward(self, op: builder.OpBuilder, position_ids: ir.Value):
             )
             offset = op.Mul(use_long, self.original_max_position_embeddings)
             position_ids = op.Add(position_ids, offset)
-        cos, sin = get_rotary_pos_emb(
-            op, position_ids, self.cos_cache, self.sin_cache
-        )
+        cos, sin = get_rotary_pos_emb(op, position_ids, self.cos_cache, self.sin_cache)
         return self._cast_embeddings(op, cos, sin)
 
 
@@ -394,9 +390,7 @@ def find_correction_dim(num_rotations):
         self._llama4_original_max_pos = float(original_max_pos)
 
     def forward(self, op: builder.OpBuilder, position_ids: ir.Value):
-        cos, sin = get_rotary_pos_emb(
-            op, position_ids, self.cos_cache, self.sin_cache
-        )
+        cos, sin = get_rotary_pos_emb(op, position_ids, self.cos_cache, self.sin_cache)
         cos, sin = self._cast_embeddings(op, cos, sin)
         if self._llama4_beta is None:
             return cos, sin

tests/e2e_golden_test.py

@@ -155,7 +155,6 @@ def _use_temp_hf_cache(tmp_path):
     "text-generation/helium-1-2b": "Helium decode loop diverges from HF after first token",
     "text-generation/nanochat-d20": "NanoChat decode loop diverges from HF after first token",
     "text-generation/ernie4_5-0_3b": "ERNIE 4.5 decode loop diverges from HF after first token",
-
     # MLA compressed KV cache dimensions not yet handled by OnnxGenerator
     "text-generation/youtu-2b": "Youtu MLA KV cache dims differ from standard attention (v_head_dim != head_dim)",
 }