!26738 fix comments in metric

Merge pull request !26738 from liutongtong9/code_docs_fixmetric

mindspore/nn/metrics/mean_surface_distance.py

@@ -36,7 +36,7 @@ class MeanSurfaceDistance(Metric):
         AvgSurDis(B\rightarrow A) = \frac{\sum_{s_{B}  \in S(B)}^{} {\text{dis}  \
         left ( s_{B}, S(A) \right )} } {\left | S(B) \right |}
 
-    Where the ||*|| denotes a distance measure. |*| denotes the number of elements.
+    Where the \|\|\*\|\| denotes a distance measure. \|\*\| denotes the number of elements.
 
     The mean of surface distance form set(B) to set(A) and from set(A) to set(B) is:
 

mindspore/nn/metrics/root_mean_square_surface_distance.py

@@ -35,7 +35,7 @@ class RootMeanSquareDistance(Metric):
         RmsSurDis(B \rightarrow A) = \sqrt{\frac{\sum_{s_{B}  \in S(B)}^{} {\text{dis}^2  \left ( s_{B}, S(A)
         \right )} }{\left | S(B) \right |}}
 
-    Where the ||\*|| denotes a distance measure. |\*| denotes the number of elements.
+    Where the \|\|\*\|\| denotes a distance measure.\ |\*\| denotes the number of elements.
 
     The Root Mean Square Surface Distance form set(B) to set(A) and from set(A) to set(B) is:
 

mindspore/nn/metrics/topk.py

@@ -68,7 +68,7 @@ class TopKCategoricalAccuracy(Metric):
         Updates the internal evaluation result `y_pred` and `y`.
 
         Args:
-            inputs: Input `y_pred` and `y`. ` y_pred` and `y` are Tensor, list or numpy.ndarray.
+            inputs: Input `y_pred` and `y`. `y_pred` and `y` are Tensor, list or numpy.ndarray.
                 `y_pred` is in most cases (not strictly) a list of floating numbers in range :math:`[0, 1]`
                 and the shape is :math:`(N, C)`, where :math:`N` is the number of cases and :math:`C`
                 is the number of categories. `y` contains values of integers. The shape is :math:`(N, C)`