!45347 [MS][DOC]export some primitive doc

Merge pull request !45347 from mengyuanli/code_docs_export_primitive

docs/api/api_python/mindspore.ops.rst

@@ -132,6 +132,9 @@ MindSpore中 `mindspore.ops` 接口与上一版本相比，新增、删除和支
     mindspore.ops.Adam
     mindspore.ops.AdamWeightDecay
     mindspore.ops.AdaptiveAvgPool2D
+    mindspore.ops.AdaptiveAvgPool3D
+    mindspore.ops.AdaptiveMaxPool2D
+    mindspore.ops.AdaptiveMaxPool3D
     mindspore.ops.ApplyAdadelta
     mindspore.ops.ApplyAdagrad
     mindspore.ops.ApplyAdagradDA
@@ -185,6 +188,7 @@ MindSpore中 `mindspore.ops` 接口与上一版本相比，新增、删除和支
     :nosignatures:
     :template: classtemplate.rst
     
+    mindspore.ops.AdjustHue
     mindspore.ops.BoundingBoxDecode
     mindspore.ops.BoundingBoxEncode
     mindspore.ops.CheckValid

docs/api/api_python/ops/mindspore.ops.AdaptiveAvgPool3D.rst

@@ -0,0 +1,8 @@
+mindspore.ops.AdaptiveAvgPool3D
+================================
+
+.. py:class:: mindspore.ops.AdaptiveAvgPool3D(output_size)
+
+    三维自适应平均池化。
+
+    更多参考详见 :func:`mindspore.ops.adaptive_avg_pool3d`。

docs/api/api_python/ops/mindspore.ops.AdaptiveMaxPool2D.rst

@@ -0,0 +1,8 @@
+mindspore.ops.AdaptiveMaxPool2D
+===============================
+
+.. py:class:: mindspore.ops.AdaptiveMaxPool2D(output_size)
+
+    二维自适应最大值池化。
+
+    更多参考详见 :func:`mindspore.ops.adaptive_max_pool2d`。

docs/api/api_python/ops/mindspore.ops.AdjustHue.rst

@@ -0,0 +1,23 @@
+mindspore.ops.AdjustHue
+=======================
+
+.. py:class:: mindspore.ops.AdjustHue()
+
+    调整 RGB 图像的色调。
+
+    .. note::
+        该运算是种将 RGB 图像转换为浮点表示的便捷方法。通过将图像转换为HSV色彩空间并移动色调通道中的强度来调整图像，然后转换回原始数据模式。
+        当多个调整依次进行时尽量减少冗余转换的数量。
+
+    输入：
+        - **image** (Tensor) - 输入的Tensor。shape的最后一个维度的必须为3。dtype需要是float16或float32。Tensor的维度至少是3维。
+        - **delta** (Tensor) - 色调通道的添加值。dtype需要是float32。Tensor必须是0维的。
+
+    输出：
+        Tensor，具有与 `image` 相同的shape和dtype。
+
+    异常：
+        - **TypeError** - 如果 `image` 或 `delta` 不是Tensor。
+        - **TypeError** - 如果 `image` 的dtype不是：float32或float16。
+        - **TypeError** - 如果 `delta` 的dtype不是：float32。
+        - **ValueError** - 如果 `image` 的维度低于3维。

docs/api/api_python_en/mindspore.ops.rst

@@ -132,6 +132,9 @@ Optimizer
     mindspore.ops.Adam
     mindspore.ops.AdamWeightDecay
     mindspore.ops.AdaptiveAvgPool2D
+    mindspore.ops.AdaptiveAvgPool3D
+    mindspore.ops.AdaptiveMaxPool2D
+    mindspore.ops.AdaptiveMaxPool3D
     mindspore.ops.ApplyAdadelta
     mindspore.ops.ApplyAdagrad
     mindspore.ops.ApplyAdagradDA
@@ -185,6 +188,7 @@ Image Processing
     :nosignatures:
     :template: classtemplate.rst
     
+    mindspore.ops.AdjustHue
     mindspore.ops.BoundingBoxDecode
     mindspore.ops.BoundingBoxEncode
     mindspore.ops.CheckValid

mindspore/python/mindspore/ops/operations/image_ops.py

@@ -131,7 +131,7 @@ class AdjustHue(Primitive):
 
     Inputs:
         - **image** (Tensor): RGB image or images. The size of the last dimension must be 3.
-          the dtype is float16 or float32.  At least 3-D.
+          the dtype is float16 or float32. At least 3-D.
         - **delta** (Tensor): How much to add to the hue channel, the dtype is float32. Must be 0-D.
 
     Output:
@@ -139,9 +139,9 @@ class AdjustHue(Primitive):
 
     Raises:
         TypeError: If neither `image` nor `delta` is a tensor.
-        TypeError: If the dtype of image not float16 or float32.
+        TypeError: If the dtype of `image` is neither float16 nor float32.
-        TypeError: If the dtype of delta not float32.
+        TypeError: If the dtype of `delta` not float32.
-        ValueError: If image have at less than 3 dimensions.
+        ValueError: If the dimension of `image` is less than 3.
 
     Supported Platforms:
         ``Ascend`` ``GPU`` ``CPU``

mindspore/python/mindspore/ops/operations/nn_ops.py

@@ -375,55 +375,9 @@ class AdaptiveAvgPool2D(AdaptiveAvgPool2DV1):
 
 class AdaptiveMaxPool2D(Primitive):
     r"""
-    AdaptiveMaxPool2D operation.
+    Applies a 2D adaptive max pooling over an input signal composed of several input planes.
 
-    This operator applies a 2D adaptive max pooling to an input signal composed of multiple input planes.
+    Refer to :func:`mindspore.ops.adaptive_max_pool2d` for more details.
-    That is, for any input size, the size of the specified output is H x W.
-    The number of output features is equal to the number of input planes.
-
-    The input and output data format can be "NCHW" and "CHW". N is the batch size, C is the number of channels,
-    H is the feature height, and W is the feature width.
-
-    For max adaptive pool2d:
-
-    .. math::
-
-        \begin{align}
-        h_{start} &= floor(i * H_{in} / H_{out})\\
-        h_{end} &= ceil((i + 1) * H_{in} / H_{out})\\
-        w_{start} &= floor(j * W_{in} / W_{out})\\
-        w_{end} &= ceil((j + 1) * W_{in} / W_{out})\\
-        Output(i,j) &= {\max Input[h_{start}:h_{end}, w_{start}:w_{end}]}
-        \end{align}
-
-    Note:
-        In Ascend, the second output `argmax` is invalid, please ignore it.
-
-    Args:
-        output_size (Union[int, tuple]): The target output size is H x W.
-            ouput_size can be a tuple, or a single H for H x H, and H and W can be int or None
-            which means the output size is the same as the input.
-
-        return_indices (bool): If `return_indices` is True, the indices of max value would be output.
-            Default: False.
-
-    Inputs:
-        - **input_x** (Tensor) - The input of AdaptiveMaxPool2D, which is a 3D or 4D tensor,
-          with float16, float32 or float64 data type.
-
-    Outputs:
-        Tensor, with the same type as the `input_x`.
-
-        Shape of the output is `input_x_shape[:len(input_x_shape) - len(out_shape)] + out_shape`.
-
-    Raises:
-        TypeError: If `output_size` is not int or tuple.
-        TypeError: If `input_x` is not a tensor.
-        TypeError: If `return_indices` is not a bool.
-        TypeError: If dtype of `input_x` is not float16, float32 or float64.
-        ValueError: If `output_size` is a tuple and the length of `output_size` is not 2.
-        ValueError: If the dimension of `input_x` is not NCHW or CHW.
-        ValueError: If `output_size` is less than -1.
 
     Supported Platforms:
         ``Ascend`` ``GPU`` ``CPU``