diff --git a/tests/data/test_text_data.py b/tests/data/test_text_data.py
index f72a04a040..398eb2ae8b 100644
--- a/tests/data/test_text_data.py
+++ b/tests/data/test_text_data.py
@@ -2,33 +2,43 @@
 # SPDX-License-Identifier: Apache-2.0
 import os
 import pathlib
-from streaming import MDSWriter
-from llmfoundry.data import StreamingTextDataset
-import pytest
+
 import numpy as np
+import pytest
 import torch
+from streaming import MDSWriter
+
+from llmfoundry.data import StreamingTextDataset
+
 
 @pytest.mark.parametrize('token_encoding_type', ['int16', 'int32', 'int64'])
 @pytest.mark.parametrize('samples', [10])
 @pytest.mark.parametrize('max_seq_len', [2048])
 @pytest.mark.parametrize('vocab_size', [10000])
-def test_encoding_types(tmp_path: pathlib.Path,
-                        token_encoding_type: str,
-                        samples: int,
-                        max_seq_len: int,
-                        vocab_size: int):
+def test_encoding_types(
+    tmp_path: pathlib.Path,
+    token_encoding_type: str,
+    samples: int,
+    max_seq_len: int,
+    vocab_size: int,
+):
     dataset_local_path = str(tmp_path)
     encoding_dtype = getattr(np, token_encoding_type)
 
     columns = {
-        'tokens': 'ndarray:'+token_encoding_type,
+        'tokens': 'ndarray:' + token_encoding_type,
     }
-    
+
     with MDSWriter(out=dataset_local_path, columns=columns) as writer:
         for _ in range(samples):
-            tokens = np.random.randint(0, vocab_size, max_seq_len, dtype=encoding_dtype)
+            tokens = np.random.randint(
+                0,
+                vocab_size,
+                max_seq_len,
+                dtype=encoding_dtype,
+            )
             writer.write({'tokens': tokens})
-    
+
     print('Dataset local path:', dataset_local_path)
     print(os.listdir(dataset_local_path))
 
@@ -45,7 +55,11 @@ def test_encoding_types(tmp_path: pathlib.Path,
         assert sample.dtype == getattr(torch, token_encoding_type)
         assert sample.shape == (max_seq_len,)
 
-@pytest.mark.parametrize('token_encoding_type', ['int17', 'float32', 'complex', 'int8'])
+
+@pytest.mark.parametrize(
+    'token_encoding_type',
+    ['int17', 'float32', 'complex', 'int8'],
+)
 def test_unsupported_encoding_type(token_encoding_type: str):
     with pytest.raises(ValueError, match='The token_encoding_type*'):
         StreamingTextDataset(
@@ -54,4 +68,4 @@ def test_unsupported_encoding_type(token_encoding_type: str):
             max_seq_len=2048,
             local='dataset/path',
             batch_size=1,
-        )
\ No newline at end of file
+        )