modify nn annotation

mindspore/nn/layer/container.py

@@ -259,8 +259,13 @@ class CellList(_CellListBase, Cell):
         >>> cell_ls.append(relu)
         >>> cell_ls
         CellList<
-          (0): Conv2d<input_channels=100, ..., bias_init=None>
-          (1): BatchNorm2d<num_features=20, ..., moving_variance=Parameter (name=variance)>
+          (0): Conv2d<input_channels=100, output_channels=20, kernel_size=(3, 3),stride=(1, 1),  pad_mode=same,
+          padding=0, dilation=(1, 1), group=1, has_bias=Falseweight_init=normal, bias_init=zeros, format=NCHW>
+          (1): BatchNorm2d<num_features=20, eps=1e-05, momentum=0.09999999999999998, gamma=Parameter (name=1.gamma,
+          shape=(20,), dtype=Float32, requires_grad=True), beta=Parameter (name=1.beta, shape=(20,), dtype=Float32,
+          requires_grad=True), moving_mean=Parameter (name=1.moving_mean, shape=(20,), dtype=Float32,
+          requires_grad=False), moving_variance=Parameter (name=1.moving_variance, shape=(20,), dtype=Float32,
+          requires_grad=False)>
           (2): ReLU<>
           >
     """

mindspore/nn/loss/loss.py

@@ -512,7 +512,7 @@ class MultiClassDiceLoss(_Loss):
         >>> y = Tensor(np.array([[0, 1], [1, 0], [0, 1]]), mstype.float32)
         >>> output = loss(y_pred, y)
         >>> print(output)
-        [0.3283009]
+        0.3283009
     """
     def __init__(self, weights=None, ignore_indiex=None, activation="softmax"):
         super(MultiClassDiceLoss, self).__init__()