fix: api comment format

mindspore/mindrecord/tools/tfrecord_to_mr.py

@@ -105,21 +105,21 @@ class TFRecordToMR:
         source (str): the TFRecord file to be transformed.
         destination (str): the MindRecord file path to tranform into.
         feature_dict (dict): a dictionary than states the feature type, i.e.
-            feature_dict = {"xxxx": tf.io.FixedLenFeature([], tf.string),
+            feature_dict = {"xxxx": tf.io.FixedLenFeature([], tf.string), \
                             "yyyy": tf.io.FixedLenFeature([], tf.int64)}
-            ****** follow case which uses VarLenFeature not support ******
-            feature_dict = {"context": {"xxxx": tf.io.FixedLenFeature([], tf.string),
-                                        "yyyy": tf.io.VarLenFeature(tf.int64)},
+
+            **Follow case which uses VarLenFeature not support**
+
+            feature_dict = {"context": {"xxxx": tf.io.FixedLenFeature([], tf.string), \
+                                        "yyyy": tf.io.VarLenFeature(tf.int64)}, \
                             "sequence": {"zzzz": tf.io.FixedLenSequenceFeature([], tf.float32)}}
         bytes_fields (list): the bytes fields which are in feature_dict.
 
     Rasies:
-        ValueError, when:
-            1) parameter TFRecord is not string.
-            2) parameter MindRecord is not string.
-            3) feature_dict is not FixedLenFeature.
-            4) parameter bytes_field is not list(str) or not in feature_dict
-        Exception, when tensorflow module not found or version is not correct.
+        ValueError: the following condition will cause ValueError, 1) parameter TFRecord is not string, 2) parameter
+            MindRecord is not string, 3) feature_dict is not FixedLenFeature, 4) parameter bytes_field is not list(str)
+            or not in feature_dict.
+        Exception: when tensorflow module not found or version is not correct.
     """
     def __init__(self, source, destination, feature_dict, bytes_fields=None):
         if not tf: