Modify the results in the dicelos example and the example of occlusion sensitivity

mindspore/nn/loss/loss.py

@@ -436,7 +436,7 @@ class DiceLoss(_Loss):
         >>> y = Tensor(np.array([[0, 1], [1, 0], [0, 1]]), mstype.float32)
         >>> output = loss(y_pred, y)
         >>> print(output)
-        [0.38596618]
+        0.38596618
     """
     def __init__(self, smooth=1e-5):
         super(DiceLoss, self).__init__()

mindspore/nn/metrics/occlusion_sensitivity.py

@@ -52,7 +52,7 @@ class OcclusionSensitivity(Metric):
     Example:
         >>> class DenseNet(nn.Cell):
         ...     def __init__(self):
-        ...         super(DenseNet, self).init()
+        ...         super(DenseNet, self).__init__()
         ...         w = np.array([[0.1, 0.8, 0.1, 0.1],[1, 1, 1, 1]]).astype(np.float32)
         ...         b = np.array([0.3, 0.6]).astype(np.float32)
         ...         self.dense = nn.Dense(4, 2, weight_init=Tensor(w), bias_init=Tensor(b))