diff --git a/mindspore/python/mindspore/ops/operations/math_ops.py b/mindspore/python/mindspore/ops/operations/math_ops.py
index 19dc3ea1eec..fb928855744 100644
--- a/mindspore/python/mindspore/ops/operations/math_ops.py
+++ b/mindspore/python/mindspore/ops/operations/math_ops.py
@@ -5402,7 +5402,7 @@ class Invert(Primitive):
 
     .. math::
 
-        out_i = -x_{i}
+        out_i = ~x_{i}
 
     Inputs:
         - **x** (Tensor) - The shape of tensor is :math:`(x_1, x_2, ..., x_R)`.
diff --git a/mindspore/python/mindspore/ops/operations/nn_ops.py b/mindspore/python/mindspore/ops/operations/nn_ops.py
index e0c4c654bb8..422936e9e29 100644
--- a/mindspore/python/mindspore/ops/operations/nn_ops.py
+++ b/mindspore/python/mindspore/ops/operations/nn_ops.py
@@ -6667,8 +6667,7 @@ class Dropout(PrimitiveWithCheck):
         Seed1 (int): Seed1 value for random generating. Default: 0.
 
     Inputs:
-        - **x** (Tensor) - Tensor of shape :math:`(N, *)`, where :math:`*` means, any number of
-          additional dimensions, with float16 or float32 data type.
+        - **x** (Tensor) - The input of Dropout, a Tensor of any shape with data type of float16 or float32.
 
     Outputs:
         - **output** (Tensor) - With the same shape and data type as `x`.
diff --git a/mindspore/python/mindspore/ops/operations/other_ops.py b/mindspore/python/mindspore/ops/operations/other_ops.py
index 53b66a93495..60ff20a270d 100644
--- a/mindspore/python/mindspore/ops/operations/other_ops.py
+++ b/mindspore/python/mindspore/ops/operations/other_ops.py
@@ -222,12 +222,14 @@ class CheckValid(PrimitiveWithInfer):
         specifying the valid boundary (heights x ratio, weights x ratio).
 
     Inputs:
-        - **bboxes** (Tensor) - Bounding boxes tensor with shape (N, 4). Data type must be float16 or float32.
-        - **img_metas** (Tensor) - Raw image size information with the format of (height, width, ratio).
-          Data type must be float16 or float32.
+        - **bboxes** (Tensor) - Bounding boxes tensor with shape (N, 4). "N" indicates the number of
+          bounding boxes, the value "4" indicates "x0", "x1", "y0", and "y1". Data type must be float16 or float32.
+        - **img_metas** (Tensor) - Raw image size information with the format of (height, width, ratio), specifying
+          the valid boundary(height * ratio, width * ratio). Data type must be float16 or float32.
 
     Outputs:
-        Tensor, with shape of (N,) and dtype of bool.
+        Tensor, with shape of (N,) and dtype of bool, specifying whether the bounding boxes is in the image.
+        "True" indicates valid, while "False" indicates invalid.
 
     Raises:
         TypeError: If `bboxes` or `img_metas` is not a Tensor.
@@ -609,7 +611,8 @@ class ConfusionMatrix(PrimitiveWithInfer):
 
 class PopulationCount(PrimitiveWithInfer):
     r"""
-    Calculates population count.
+    Computes element-wise population count(a.k.a bitsum, bitcount).
+    For each entry in `input` , calculates the number of 1 bits in the binary representation of that entry.
 
     Inputs:
         - **input** (Tensor) -  The data type must be int16 or uint16.