!13019 The API comments should be fixed.

From: @zhang_yi2020
Reviewed-by: @gemini524,@liangchenghui,@wuxuejian
Signed-off-by: @liangchenghui

mindspore/train/model.py

@@ -76,6 +76,7 @@ class Model:
                              to other metric. Default: None.
         amp_level (str): Option for argument `level` in `mindspore.amp.build_train_network`, level for mixed
             precision training. Supports ["O0", "O2", "O3", "auto"]. Default: "O0".
+
             - O0: Do not change.
             - O2: Cast network to float16, keep batchnorm run in float32, using dynamic loss scale.
             - O3: Cast network to float16, with additional property 'keep_batchnorm_fp32=False'.

mindspore/train/serialization.py

@@ -580,6 +580,7 @@ def export(net, *inputs, file_name, file_format='AIR', **kwargs):
         inputs (Tensor): Inputs of the `net`.
         file_name (str): File name of the model to be exported.
         file_format (str): MindSpore currently supports 'AIR', 'ONNX' and 'MINDIR' format for exported model.
+
             - AIR: Ascend Intermediate Representation. An intermediate representation format of Ascend model.
               Recommended suffix for output file is '.air'.
             - ONNX: Open Neural Network eXchange. An open format built to represent machine learning models.
@@ -589,6 +590,7 @@ def export(net, *inputs, file_name, file_format='AIR', **kwargs):
               Recommended suffix for output file is '.mindir'.
 
         kwargs (dict): Configuration options dictionary.
+
             - quant_mode: The mode of quant.
             - mean: Input data mean. Default: 127.5.
             - std_dev: Input data variance. Default: 127.5.