diff --git a/src/mindspore2022/mindspore/python/mindspore/_extends/graph_kernel/expanders/bias_add_grad.py b/src/mindspore2022/mindspore/python/mindspore/_extends/graph_kernel/expanders/bias_add_grad.py
index 161f33c0..8e8394dd 100644
--- a/src/mindspore2022/mindspore/python/mindspore/_extends/graph_kernel/expanders/bias_add_grad.py
+++ b/src/mindspore2022/mindspore/python/mindspore/_extends/graph_kernel/expanders/bias_add_grad.py
@@ -13,37 +13,64 @@
 # limitations under the License.
 # ===========================================================================
 """generate json desc for bias_add"""
+# 导入MindSpore的DataFormat类
 from mindspore._extends.graph_kernel.model.model import DataFormat as DF
+# 导入Expander和ExpanderInfoValidator类
 from ._utils import Expander, ExpanderInfoValidator as VLD
 
 
+# 为BiasAddGrad类添加DF.DEFAULT、DF.NHWC、DF.NCHW、DF.FRAC_NZ格式的验证
 @VLD.add_format(DF.DEFAULT)
 @VLD.add_format(DF.NHWC)
 @VLD.add_format(DF.NCHW)
 @VLD.add_format(DF.FRAC_NZ)
+# 定义BiasAddGrad类，继承自Expander类
 class BiasAddGrad(Expander):
     """BiasAddGrad expander"""
 
     def _expand(self, graph_builder):
+        """
+        内部方法，用于扩展输入张量的维度。
+
+        Args:
+            graph_builder (GraphBuilder): 图构建器对象，用于生成图操作。
+
+        Returns:
+            Tensor: 扩展维度后的张量。
+
+        """
+        # 获取输入张量
         x = self.inputs[0]
 
+        # 定义reduce_axis，用于指定求和的维度
         reduce_axis = ()
+        # 如果输入张量的数据格式为NHWC，则reduce_axis为(0, 1, 2)
         if x.data_format == DF.NHWC:
             reduce_axis = (0, 1, 2)
+        # 如果输入张量的数据格式为NCHW，则reduce_axis为(0, 2, 3)
         elif x.data_format == DF.NCHW:
             reduce_axis = (0, 2, 3)
+        # 如果输入张量的数据格式为FRAC_NZ，则reduce_axis为(-2, -3)
         elif x.data_format == DF.FRAC_NZ:
             reduce_axis = (-2, -3)
+        # 如果输入张量的数据格式为DefaultFormat，则根据shape的长度确定reduce_axis
         else:
             # DefaultFormat shape's length should be from 2 to 4
+            # 如果x的维度为2，则reduce_axis为(0,)
             if len(x.shape) == 2:
                 reduce_axis = (0,)
+            # 如果x的维度为3，则reduce_axis为(0, 1)
             elif len(x.shape) == 3:
                 reduce_axis = (0, 1)
+            # 否则，reduce_axis为(0, 2, 3)
             else:
                 reduce_axis = (0, 2, 3)
+        # 发射ReduceSum操作，计算x的reduce_sum，reduce_axis为reduce_axis，keep_dims为False
         result = graph_builder.emit('ReduceSum', [x], attrs={'reduce_axis': reduce_axis, 'keep_dims': False})
+        # 如果x的数据格式为DF.FRAC_NZ，则将result的shape改为x.shape[:-4] + [x.shape[-1] * x.shape[-4]]
         if x.data_format == DF.FRAC_NZ:
             out_shape = x.shape[:-4] + [x.shape[-1] * x.shape[-4]]
+            # 发射Reshape操作，将result的shape改为out_shape
             result = graph_builder.emit('Reshape', [result], attrs={'shape': out_shape})
+        # 返回result
         return result