diff --git a/tensorflow_examples/lite/model_maker/core/data_util/dataloader.py b/tensorflow_examples/lite/model_maker/core/data_util/dataloader.py
index b03a3cb7f54..f2277925d6f 100644
--- a/tensorflow_examples/lite/model_maker/core/data_util/dataloader.py
+++ b/tensorflow_examples/lite/model_maker/core/data_util/dataloader.py
@@ -53,7 +53,7 @@ def __init__(self, dataset, size=None):
         `input_data` means the raw input data, like an image, a text etc., while
         the `target` means some ground truth of the raw input data, such as the
         classification label of the image etc.
-      size: The size of the dataset. tf.data.Dataset donesn't support a function
+      size: The size of the dataset. tf.data.Dataset doesn't support a function
         to get the length directly since it's lazy-loaded and may be infinite.
     """
     self._dataset = dataset
@@ -63,9 +63,9 @@ def __init__(self, dataset, size=None):
   def size(self) -> Optional[int]:
     """Returns the size of the dataset.
 
-    Note that this function may return None becuase the exact size of the
+    Note that this function may return None because the exact size of the
     dataset isn't a necessary parameter to create an instance of this class,
-    and tf.data.Dataset donesn't support a function to get the length directly
+    and tf.data.Dataset doesn't support a function to get the length directly
     since it's lazy-loaded and may be infinite.
     In most cases, however, when an instance of this class is created by helper
     functions like 'from_folder', the size of the dataset will be preprocessed,
@@ -83,7 +83,7 @@ def gen_dataset(self,
     """Generate a shared and batched tf.data.Dataset for training/evaluation.
 
     Args:
-      batch_size: A integer, the returned dataset will be batched by this size.
+      batch_size: An integer, the returned dataset will be batched by this size.
       is_training: A boolean, when True, the returned dataset will be optionally
         shuffled and repeated as an endless dataset.
       shuffle: A boolean, when True, the returned dataset will be shuffled to
@@ -180,6 +180,7 @@ def __init__(self, dataset, size, index_to_label):
 
   @property
   def num_classes(self):
+    """Returns the number of classes of the dataset."""
     return len(self.index_to_label)
 
   def split(self, fraction):