Addressed doc issues (#13165)

* Addressed doc issues

* Update optimizer.py

python/mxnet/gluon/nn/basic_layers.py

@@ -663,20 +663,21 @@ class HybridLambda(HybridBlock):
     ----------
     function : str or function
         Function used in lambda must be one of the following:
-        1) the name of an operator that is available in both symbol and ndarray. For example::
+        1) The name of an operator that is available in both symbol and ndarray. For example::
 
             block = HybridLambda('tanh')
 
-        2) a function that conforms to "def function(F, data, *args)". For example::
+        2) A function that conforms to ``def function(F, data, *args)``. For example::
 
             block = HybridLambda(lambda F, x: F.LeakyReLU(x, slope=0.1))
 
     Inputs:
-        - ** *args **: one or more input data. First argument must be symbol or ndarray.
-        Their shapes depend on the function.
+        - ** *args **: one or more input data. First argument must be symbol or ndarray. Their \
+            shapes depend on the function.
 
     Output:
         - ** *outputs **: one or more output data. Their shapes depend on the function.
+
     """
     def __init__(self, function, prefix=None):
         super(HybridLambda, self).__init__(prefix=prefix)

python/mxnet/ndarray/ndarray.py

@@ -998,7 +998,7 @@ def reshape(self, *shape, **kwargs):
 
               Example::
 
-              - without reverse=1, for input shape = (10,5,4), shape = (-1,0), output shape would be
+              - without reverse=1, for input shape = (10,5,4), shape = (-1,0), output shape would be \
                 (40,5).
               - with reverse=1, output shape will be (50,4).