diff --git a/docs/api/api_python/ops/mindspore.ops.StridedSlice.rst b/docs/api/api_python/ops/mindspore.ops.StridedSlice.rst
index 5a7c2ddce6f..1d65f67c0c3 100644
--- a/docs/api/api_python/ops/mindspore.ops.StridedSlice.rst
+++ b/docs/api/api_python/ops/mindspore.ops.StridedSlice.rst
@@ -3,15 +3,18 @@
 
 .. py:class:: mindspore.ops.StridedSlice(begin_mask=0, end_mask=0, ellipsis_mask=0, new_axis_mask=0, shrink_axis_mask=0)
 
-    输入Tensor根据步长和索引进行切片提取。
+    对输入Tensor根据步长和索引进行切片提取。
 
-    给定一个输入Tensor，此操作会插入长度为1的维度。从给定的 `input_tensor` 中提取大小为 `(end-begin)/stride` 的片段。从起始位置开始，根据步长和索引进行提取，直到所有维度都不小于结束位置为止。
+    该算子在给定的 `input_tensor` 中提取大小为 `(end-begin)/stride` 的片段。从起始位置开始，根据步长和索引进行提取，直到所有维度的都不小于结束位置为止。
 
     给定一个 `input_x[m1, m2, ...、mn]` 。 `begin` 、 `end` 和 `strides` 是长度为n的向量。
 
-    在每个掩码字段中（`begin_mask`、`end_mask`、`ellipsis_mask`、`new_axis_mask`、`shrink_ax_mask`)，第i位将对应于第i个m。
+    在每个掩码字段中（`begin_mask`、`end_mask`、`ellipsis_mask`、`new_axis_mask`、`shrink_axis_mask`)，第i位将对应于第i个m。
 
-    如果设置了 `begin_mask` 的第i位，则忽略 `begin[i]` ，而使用该维度中最有可能的取值范围。除了结尾的取值范围， `end_mask` 是类似的。
+    对于每个特定的mask，内部先将其转化为二进制表示， 然后倒序排布后进行计算。比如说对于一个5*6*7的Tensor，mask设置为3， 3转化为二进制表示为ob011， 倒序
+    后为ob110， 则该mask只在第0维和第1维产生作用， 下面各自举例说明。
+
+    如果设置了 `begin_mask` 的第i位，则忽略 `begin[i]`，而使用该维度的最大可能取值范围， `begin_mask` 使用方法与之类似。
 
     对于5*6*7的Tensor， `x[2:,:3,:]` 等同于 `x[2:5,0:3,0:7]` 。
 
@@ -21,11 +24,11 @@
 
     如果设置了 `new_axis_mask` 的第i位，则忽略 `begin` 、 `end` 和 `strides` ，并在输出Tensor的指定位置添加新的长度为1的维度。
 
-    对于5*6*7的Tensor， `x[:2, newaxis, :6]` 将产生一个shape为 :math:`(2, 1, 7)` 的Tensor。
+    对于5*6*7的Tensor， `x[:2, newaxis, :6]` 将产生一个shape为 :math:`(2, 1, 6, 7)` 的Tensor。
 
-    如果设置了 `shrink_axis_mask` 的第i位，则第i个大小将维度收缩1，并忽略 `begin[i]` 、 `end[i]` 和 `strides[i]` 索引处的值。
+    如果设置了 `shrink_axis_mask` 的第i位，则第i维被收缩掉，并忽略 `begin[i]` 、 `end[i]` 和 `strides[i]` 索引处的值。
 
-    对于5*6*7的Tensor， `x[:, 5, :]` 将使得 `shrink_axis_mask` 等于4。
+    对于5*6*7的Tensor， `x[:, 5, :]` 相当于将 `shrink_axis_mask` 设置为2, 使得输出shape为:math:`(5, 7)` 。
 
     .. note::
         步长可能为负值，这会导致反向切片。 `begin` 、 `end` 和 `strides` 的shape必须相同。 `begin` 和 `end` 是零索引。 `strides` 的元素必须非零。
diff --git a/mindspore/core/ops/sign.cc b/mindspore/core/ops/sign.cc
index f7dd2ee1758..e6a28b4370e 100644
--- a/mindspore/core/ops/sign.cc
+++ b/mindspore/core/ops/sign.cc
@@ -54,7 +54,9 @@ AbstractBasePtr SignInfer(const abstract::AnalysisEnginePtr &, const PrimitivePt
   const int64_t input_num = 1;
   CheckAndConvertUtils::CheckInputArgs(input_args, kEqual, input_num, primitive->name());
 
-  return abstract::MakeAbstract(SignInferShape(primitive, input_args), SignInferType(primitive, input_args));
+  auto infer_type = SignInferType(primitive, input_args);
+  auto infer_shape = SignInferShape(primitive, input_args);
+  return abstract::MakeAbstract(infer_shape, infer_type);
 }
 REGISTER_PRIMITIVE_EVAL_IMPL(Sign, prim::kPrimSign, SignInfer, nullptr, true);
 }  // namespace ops
diff --git a/mindspore/python/mindspore/ops/operations/array_ops.py b/mindspore/python/mindspore/ops/operations/array_ops.py
index fb4a8e72a12..7685ee0f728 100755
--- a/mindspore/python/mindspore/ops/operations/array_ops.py
+++ b/mindspore/python/mindspore/ops/operations/array_ops.py
@@ -3129,7 +3129,6 @@ class StridedSlice(PrimitiveWithInfer):
 
     Extracts a strided slice of a tensor.
 
-    Given an input tensor, this operation inserts a dimension of length 1 at the dimension.
     This operation extracts a fragment of size (end-begin)/stride from the given 'input_tensor'.
     Starting from the beginning position, the fragment continues adding stride to the index until
     all dimensions are not less than the ending position.
@@ -3139,26 +3138,32 @@ class StridedSlice(PrimitiveWithInfer):
     In each mask field (`begin_mask`, `end_mask`, `ellipsis_mask`, `new_axis_mask`, `shrink_axis_mask`)
     the ith bit will correspond to the ith m.
 
+    For each specific mask, it will be converted to a binary representation internally, and then
+    reverse the result to start the calculation. For a 5*6*7 tensor with a given mask value of 3 which
+    can be represented as ob011. Reverse that we get ob110, which implies the first and second dim of the
+    original tensor will be effected by this mask. See examples below:
+
     If the ith bit of `begin_mask` is set, `begin[i]` is ignored and the fullest possible range in that dimension
     is used instead. `end_mask` is analogous, except with the end range.
 
-    As for a 5*6*7 tensor, `x[2:,:3,:]` is equivalent to `x[2:5,0:3,0:7]`.
+    For a 5*6*7 tensor, `x[2:,:3,:]` is equivalent to `x[2:5,0:3,0:7]`.
 
     If the ith bit of `ellipsis_mask` is set, as many unspecified dimensions as needed will be inserted between
     other dimensions. Only one non-zero bit is allowed in `ellipsis_mask`.
 
-    As for a 5*6*7*8 tensor, `x[2:,...,:6]` is equivalent to `x[2:5,:,:,0:6]`.
+    For a 5*6*7*8 tensor, `x[2:,...,:6]` is equivalent to `x[2:5,:,:,0:6]`.
     `x[2:,...]` is equivalent to `x[2:5,:,:,:]`.
 
     If the ith bit of `new_axis_mask` is set, `begin`, `end` and `strides` are ignored and a new length 1
     dimension is added at the specified position in the output tensor.
 
-    As for a 5*6*7 tensor, `x[:2, newaxis, :6]` will produce a tensor with shape :math:`(2, 1, 7)` .
+    For a 5*6*7 tensor, `x[:2, newaxis, :6]` will produce a tensor with shape :math:`(2, 1, 6, 7)` .
 
-    If the ith bit of `shrink_axis_mask` is set, ith size shrinks the dimension by 1, taking on the value
+    If the ith bit of `shrink_axis_mask` is set, dimension i will be shrunk to 0, taking on the value
     at index `begin[i]`, `end[i]` and `strides[i]` are ignored.
 
-    As for a 5*6*7 tensor, `x[:, 5, :]` will result in `shrink_axis_mask` equal to 4.
+    For a 5*6*7 tensor, `x[:, 5, :]` is equivalent to setting the `shrink_axis_mask` to 2 and results in
+    an output shape of :math:`(5, 7)`.
 
     Note:
         The stride may be negative value, which causes reverse slicing.