diff --git a/make_tf_record.py b/make_tf_record.py
index 26c2af7..b5a148a 100644
--- a/make_tf_record.py
+++ b/make_tf_record.py
@@ -1,32 +1,35 @@
 import argparse
+import os
 import os.path
 import sys
+from pathlib import Path
 
 # disable tensorflow warnings on import:
-import os
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
 import tensorflow as tf
-from pathlib import Path
 from tensorflow.io import TFRecordWriter
 
 
 # some code below adapted from
 # keras.io/examples/keras_recipes/creating_tfrecords
 
-def bytes_feature(value: str|bytes):
+def bytes_feature(value: str | bytes):
     """Returns a bytes_list from a string / byte."""
     if isinstance(value, str):
-        value = value.encode()
+        value = value.encode(encoding="utf-8")
 
     return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
 
+
 def int64_feature(value):
     """Returns an int64_list from a bool / enum / int / uint."""
     return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
 
+
 def create_example(source_filename: str, is_obfuscated: bool):
     # note: not all files are in utf-8, so we don't decode yet
+    # TODO print warning if file is not in UTF-8
     source_file_data = Path(source_filename).read_bytes()
 
     feature = {
@@ -36,23 +39,24 @@ def create_example(source_filename: str, is_obfuscated: bool):
     }
     return tf.train.Example(features=tf.train.Features(feature=feature))
 
+
 def main():
     arg_parser = argparse.ArgumentParser(
         description="Packs source files into tfrecord format with a label as either obfuscated or non-obfuscated"
     )
 
     arg_parser.add_argument("-d", "--dir", required=True, type=Path,
-            help="output directory for tfrecord files")
+                            help="output directory for tfrecord files")
     arg_parser.add_argument("-f", "--files", required=True, type=Path,
-            help="list of source files to process, one path per line")
+                            help="list of source files to process, one path per line")
     arg_parser.add_argument("-l", "--label", required=True, type=int,
-            help="obfuscation label for files, either 0 (non-obfuscated) or 1 (obfuscated)")
+                            help="obfuscation label for files, either 0 (non-obfuscated) or 1 (obfuscated)")
     arg_parser.add_argument("-n", "--nrecords", default="65536", type=int, metavar="NUM",
-            help="number of files to store in each tfrecord file (default 65536)")
+                            help="number of files to store in each tfrecord file (default 65536)")
     arg_parser.add_argument("-p", "--prefix", default="",
-            help="prefix to add to generated tfrecord filenames")
+                            help="prefix to add to generated tfrecord filenames")
     arg_parser.add_argument("-v", "--verbose", action="store_true", default=False,
-            help="print out verbose progress info")
+                            help="print out verbose progress info")
 
     parsed_args = arg_parser.parse_args()
 
@@ -72,41 +76,41 @@ def main():
             return 1
 
     if not os.path.exists(files_list):
-        print(f"path to file list does not exist: {non_obfuscated_js_files_list}")
+        print(f"path to file list does not exist: {files_list}")
         return 1
 
     if not record_dir.exists():
         os.mkdir(record_dir)
 
-    record_number = 1
+    record_num = 1
     with open(files_list, "rt") as source_files:
         eof = False
         while not eof:
-            record_filename = f"{prefix}{record_number}.tfrec"
+            record_filename = f"{prefix}{record_num}.tfrec"
             with TFRecordWriter(bytes(record_dir / record_filename)) as writer:
-                sample_number = 0
+                sample_num = 0
                 while not eof:
-
                     source_filename = source_files.readline().strip()
                     if not source_filename:
                         eof = True
                         break
 
                     if print_progress:
-                        print(f"[{record_filename} {sample_number % samples_per_record}/{samples_per_record}] {source_filename}")
+                        print(f"[{record_filename} {sample_num % samples_per_record}/{samples_per_record}]",
+                              source_filename)
 
                     example = create_example(source_filename, obfuscation_label)
                     writer.write(example.SerializeToString())
 
-                    sample_number += 1
-                    if sample_number % samples_per_record == 0:
+                    sample_num += 1
+                    if sample_num % samples_per_record == 0:
                         break
 
-            record_number += 1
+            record_num += 1
 
     return 0
 
+
 if __name__ == "__main__":
     ret = main()
     sys.exit(ret)
-
diff --git a/requirements.txt b/requirements.txt
index 51078cd..568a162 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -8,18 +8,18 @@ gast==0.4.0
 google-auth==2.22.0
 google-auth-oauthlib==1.0.0
 google-pasta==0.2.0
-grpcio==1.56.2
+grpcio==1.57.0
 h5py==3.9.0
 idna==3.4
 keras==2.13.1
 libclang==16.0.6
-Markdown==3.4.3
+Markdown==3.4.4
 MarkupSafe==2.1.3
 numpy==1.24.3
 oauthlib==3.2.2
 opt-einsum==3.3.0
 packaging==23.1
-protobuf==4.23.4
+protobuf==4.24.2
 pyasn1==0.5.0
 pyasn1-modules==0.3.0
 requests==2.31.0
@@ -31,9 +31,9 @@ tensorboard==2.13.0
 tensorboard-data-server==0.7.1
 tensorflow==2.13.0
 tensorflow-estimator==2.13.0
-tensorflow-io-gcs-filesystem==0.32.0
+tensorflow-io-gcs-filesystem==0.33.0
 termcolor==2.3.0
 typing_extensions==4.5.0
 urllib3==1.26.16
-Werkzeug==2.3.6
+Werkzeug==2.3.7
 wrapt==1.15.0
diff --git a/tokenizer_training.py b/tokenizer_training.py
index 91558c4..10c942b 100644
--- a/tokenizer_training.py
+++ b/tokenizer_training.py
@@ -28,7 +28,7 @@ def train_model(input_filenames: Iterable[str], verbose: bool) -> io.BytesIO:
 
     min_log_level = LogLevel.INFO if verbose else LogLevel.WARNING
 
-    def filename_to_sentence(filename: str) -> bytes:
+    def filename_to_sentence(filename: str) -> str:
         return Path(filename).read_text(errors="ignore")
 
     model = io.BytesIO()