optimize comments

mindinsight/datavisual/data_transform/histogram_container.py

@@ -120,12 +120,12 @@ class HistogramContainer:
 
         It's caller's duty to ensure input is valid.
 
-        Why we need visual range for histograms? Miss aligned buckets between steps might miss-lead users about the
-        trend of a tensor. Because for given tensor, if you have thinner buckets, count of every bucket might get
-        low, however, if you have thicker buckets, count of every bucket might get high.  If there are the above two
-        kinds of histogram in one graph, user might think the histogram with thicker buckets has more values. This is
-        miss-leading. So we need to unify buckets across steps. Visual range for histogram is a technology for unifying
-        buckets.
+        Why we need visual range for histograms? Aligned buckets between steps can help users know about the trend of
+        tensors. Miss aligned buckets between steps might miss-lead users about the trend of a tensor. Because for
+        given tensor, if you have thinner buckets, count of every bucket will get lower, however, if you have
+        thicker buckets, count of every bucket will get higher.  When they are displayed together, user might think
+        the histogram with thicker buckets has more values. This is miss-leading. So we need to unify buckets across
+        steps. Visual range for histogram is a technology for unifying buckets.
 
         Args:
             max_val (float): Max value for visual histogram.

mindinsight/lineagemgr/summary/_summary_adapter.py

@@ -16,8 +16,7 @@
 import time
 
 from mindinsight.datavisual.proto_files.mindinsight_lineage_pb2 import LineageEvent
-from mindinsight.lineagemgr.common.exceptions.exceptions import LineageParamTypeError, \
-    LineageParamValueError
+from mindinsight.lineagemgr.common.exceptions.exceptions import LineageParamTypeError
 from mindinsight.lineagemgr.common.log import logger as log