fix error format of docstrings for some api comments.

mindspore/common/initializer.py

@@ -229,10 +229,10 @@ class XavierUniform(Initializer):
     Initialize the array with xavier uniform algorithm, and from a uniform distribution collect samples within
     U[-boundary, boundary] The boundary is defined as :
 
-                    where :math:`boundary = gain * \sqrt{\frac{6}{n_{in} + n_{out}}}`.
+    where :math:`boundary = gain * \sqrt{\frac{6}{n_{in} + n_{out}}}`.
 
-    where :math:`n_{in}` is the number of input units in the weight tensor.
-    where :math:`n_{out}` is the number of output units in the weight tensor.
+    - where :math:`n_{in}` is the number of input units in the weight tensor.
+    - where :math:`n_{out}` is the number of output units in the weight tensor.
 
     Args:
         gain (Array): The array to be assigned. Default: 1.
@@ -259,7 +259,7 @@ class HeUniform(Initializer):
     Initialize the array with He kaiming uniform algorithm, and from a uniform distribution collect samples within
     U[-boundary, boundary] The boundary is defined as :
 
-                    where :math:`boundary = \sqrt{\frac{6}{(1 + a^2) \times \text{fan_in}}}`.
+    where :math:`boundary = \sqrt{\frac{6}{(1 + a^2) \times \text{fan_in}}}`.
 
     Args:
         negative_slope (int, float, bool): Default: 0, used when nonlinearity is 'leaky_relu'.

mindspore/context.py

@@ -682,11 +682,11 @@ class ParallelMode:
     There are five kinds of parallel modes, "STAND_ALONE", "DATA_PARALLEL",
     "HYBRID_PARALLEL", "SEMI_AUTO_PARALLEL" and "AUTO_PARALLEL". Default: "STAND_ALONE".
 
-        - STAND_ALONE: Only one processor is working.
-        - DATA_PARALLEL: Distributes the data across different processors.
-        - HYBRID_PARALLEL: Achieves data parallelism and model parallelism manually.
-        - SEMI_AUTO_PARALLEL: Achieves data parallelism and model parallelism by setting parallel strategies.
-        - AUTO_PARALLEL: Achieves parallelism automatically.
+    - STAND_ALONE: Only one processor is working.
+    - DATA_PARALLEL: Distributes the data across different processors.
+    - HYBRID_PARALLEL: Achieves data parallelism and model parallelism manually.
+    - SEMI_AUTO_PARALLEL: Achieves data parallelism and model parallelism by setting parallel strategies.
+    - AUTO_PARALLEL: Achieves parallelism automatically.
 
     MODE_LIST: The list of all supported parallel modes.
     """

mindspore/train/callback/_summary_collector.py

@@ -138,7 +138,7 @@ class SummaryCollector(Callback):
             - tensor_format (Union[str, None]): Customize the export tensor format. Supports ["npy", None].
               Default: None, it means that the tensor is not exported.
 
-                - npy: export tensor as npy file.
+              - npy: export tensor as npy file.
 
     Raises:
         ValueError: If the parameter value is not expected.

mindspore/train/summary/summary_record.py

@@ -123,7 +123,7 @@ class SummaryRecord:
             - tensor_format (Union[str, None]): Customize the export tensor format. Supports ["npy", None].
               Default: None, it means that the tensor is not exported.
 
-                - npy: export tensor as npy file.
+              - npy: export tensor as npy file.
 
     Raises:
         TypeError: If the parameter type is incorrect.