!14393 Solve the example problem in comments

From: @lijiaqi0612
Reviewed-by: @kisnwang,@zh_qh
Signed-off-by: @zh_qh

mindspore/nn/loss/loss.py

@@ -452,7 +452,7 @@ class DiceLoss(_Loss):
         single_dice_coeff = (2 * intersection) / (unionset + self.smooth)
         dice_loss = 1 - single_dice_coeff
 
-        return dice_loss.mean()
+        return dice_loss
 
 
 @constexpr
@@ -1078,7 +1078,7 @@ class FocalLoss(_Loss):
         >>> focalloss = nn.FocalLoss(weight=Tensor([1, 2]), gamma=2.0, reduction='mean')
         >>> output = focalloss(predict, target)
         >>> print(output)
-        1.6610543
+        0.12516622
     """
 
     def __init__(self, weight=None, gamma=2.0, reduction='mean'):

mindspore/nn/metrics/bleu_score.py

@@ -38,7 +38,7 @@ class BleuScore(Metric):
         >>> metric.clear()
         >>> metric.update(candidate_corpus, reference_corpus)
         >>> bleu_score = metric.eval()
-        >>> print(output)
+        >>> print(bleu_score)
         0.5946035575013605
     """
     def __init__(self, n_gram=4, smooth=False):

mindspore/nn/metrics/confusion_matrix.py

@@ -182,7 +182,7 @@ class ConfusionMatrixMetric(Metric):
         >>> y = Tensor(np.array([[[0], [1]], [[1], [0]]]))
         >>> avg_output = metric.eval()
         >>> print(avg_output)
-        [0.75]
+        [0.5]
     """
     def __init__(self,
                  skip_channel=True,