[tf.data] Bug fix: make_csv_dataset should not modify mutable parameters passed into it

Fixes #39186.

PiperOrigin-RevId: 310462826
Change-Id: I8b8dd6f16f9fab6b1e02410dc6e8c91f748772f6

tensorflow/python/data/experimental/kernel_tests/csv_dataset_test.py

@@ -41,9 +41,9 @@ class CsvDatasetTest(test_base.DatasetTestBase, parameterized.TestCase):
 
   def _setup_files(self, inputs, linebreak='\n', compression_type=None):
     filenames = []
-    for i, ip in enumerate(inputs):
+    for i, file_rows in enumerate(inputs):
       fn = os.path.join(self.get_temp_dir(), 'temp_%d.csv' % i)
-      contents = linebreak.join(ip).encode('utf-8')
+      contents = linebreak.join(file_rows).encode('utf-8')
       if compression_type is None:
         with open(fn, 'wb') as f:
           f.write(contents)
@@ -580,6 +580,13 @@ class CsvDatasetTest(test_base.DatasetTestBase, parameterized.TestCase):
           inputs, [[0, 0, 0, 0], [1, 1, 1, 0], [0, 2, 2, 2]],
           record_defaults=record_defaults)
 
+  def testCsvDataset_immutableParams(self):
+    inputs = [['a,b,c', '1,2,3', '4,5,6']]
+    filenames = self._setup_files(inputs)
+    select_cols = ['a', 'c']
+    _ = readers.make_csv_dataset(
+        filenames, batch_size=1, select_columns=select_cols)
+    self.assertAllEqual(select_cols, ['a', 'c'])
 
 if __name__ == '__main__':
   test.main()

tensorflow/python/data/experimental/ops/readers.py

@@ -183,24 +183,30 @@ def _get_sorted_col_indices(select_columns, column_names):
   """Transforms select_columns argument into sorted column indices."""
   names_to_indices = {n: i for i, n in enumerate(column_names)}
   num_cols = len(column_names)
-  for i, v in enumerate(select_columns):
+
+  results = []
+  for v in select_columns:
+    # If value is already an int, check if it's valid.
     if isinstance(v, int):
       if v < 0 or v >= num_cols:
         raise ValueError(
             "Column index %d specified in select_columns out of valid range." %
             v)
-      continue
-    if v not in names_to_indices:
+      results.append(v)
+    # Otherwise, check that it's a valid column name and convert to the
+    # the relevant column index.
+    elif v not in names_to_indices:
       raise ValueError(
           "Value '%s' specified in select_columns not a valid column index or "
           "name." % v)
-    select_columns[i] = names_to_indices[v]
+    else:
+      results.append(names_to_indices[v])
 
   # Sort and ensure there are no duplicates
-  result = sorted(set(select_columns))
-  if len(result) != len(select_columns):
+  results = sorted(set(results))
+  if len(results) != len(select_columns):
     raise ValueError("select_columns contains duplicate columns")
-  return result
+  return results
 
 
 def _maybe_shuffle_and_repeat(