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lmms_eval/models/llava_sglang.py

@@ -97,7 +97,7 @@ def _collate(x):
         pbar = tqdm(total=num_iters, disable=(self.rank != 0), desc="Model Responding")
         for chunk in chunks:
             contexts, all_gen_kwargs, doc_to_visuals, doc_id, tasks, splits = zip(*chunk)
-            batched_visuals = [doc_to_visual(self.task_dict[task][split][ids]) for ids,task,split,doc_to_visual in zip(doc_id, tasks, splits, doc_to_visuals)]  # [B, N]
+            batched_visuals = [doc_to_visual(self.task_dict[task][split][ids]) for ids, task, split, doc_to_visual in zip(doc_id, tasks, splits, doc_to_visuals)]  # [B, N]
             # we assume all gen kwargs in the batch are the same
             # this is safe to assume because the `grouper` object ensures it.
             gen_kwargs = all_gen_kwargs[0]