diff --git a/mmengine/evaluator/evaluator.py b/mmengine/evaluator/evaluator.py
index a435a4ce..930ce930 100644
--- a/mmengine/evaluator/evaluator.py
+++ b/mmengine/evaluator/evaluator.py
@@ -104,12 +104,6 @@ class Evaluator:
         """
 
         # support chunking iterable objects
-        if data is not None:
-            assert len(data_samples) == len(data), (
-                'outputs and data should have the same length, but got '
-                f'outputs length: {len(data_samples)} '
-                f'data length: {len(data)}')
-
         def get_chunks(seq: Iterator, chunk_size=1):
             stop = False
             while not stop:
@@ -123,10 +117,17 @@ class Evaluator:
                 if chunk:
                     yield chunk
 
+        if data is not None:
+            assert len(data_samples) == len(data), (
+                'data_samples and data should have the same length, but got '
+                f'data_samples length: {len(data_samples)} '
+                f'data length: {len(data)}')
+            data = get_chunks(iter(data), chunk_size)
+
         size = 0
         for output_chunk in get_chunks(iter(data_samples), chunk_size):
             if data is not None:
-                data_chunk = pseudo_collate(data[size:size + chunk_size])
+                data_chunk = pseudo_collate(next(data))  # type: ignore
             else:
                 data_chunk = None
             size += len(output_chunk)
diff --git a/tests/test_evaluator/test_evaluator.py b/tests/test_evaluator/test_evaluator.py
index fb02167e..29dc60cf 100644
--- a/tests/test_evaluator/test_evaluator.py
+++ b/tests/test_evaluator/test_evaluator.py
@@ -247,7 +247,7 @@ class TestEvaluator(TestCase):
         all_data = [dict() for _ in range(9)]
         with self.assertRaisesRegex(
                 AssertionError,
-                'outputs and data should have the same length'):
+                'data_samples and data should have the same length'):
             evaluator.offline_evaluate(all_predictions, all_data)
 
     @unittest.skipUnless(torch.cuda.is_available(), 'can only run with gpu')