Fix the structure of cn docs paddle.t & fix the annotation display on…

… 5 cn docs (PaddlePaddle#4402) * Update t_cn.rst * Update basic_usage_cn.md * Update cumsum_cn.rst * Update InputSpec_cn.rst * Update Program_cn.rst * Update gradients_cn.rst * Update t_cn.rst * Update t_cn.rst * Update t_cn.rst * Update t_cn.rst Co-authored-by: Ligoml <[email protected]>
MarisaSparkL · Apr 20, 2022 · 23a6e2d · 23a6e2d
1 parent caad954
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diff --git a/docs/api/paddle/cumsum_cn.rst b/docs/api/paddle/cumsum_cn.rst
@@ -47,6 +47,6 @@ cumsum
 
         y = paddle.cumsum(data, dtype='float64')
         print(y.dtype)
-        # VarType.FP64
+        # paddle.float64
 
 
diff --git a/docs/api/paddle/static/InputSpec_cn.rst b/docs/api/paddle/static/InputSpec_cn.rst
@@ -30,8 +30,8 @@ InputSpec
 
     input = InputSpec([None, 784], 'float32', 'x')
     label = InputSpec([None, 1], 'int64', 'label')
-    print(input)  # InputSpec(shape=(-1, 784), dtype=VarType.FP32, name=x)
-    print(label)  # InputSpec(shape=(-1, 1), dtype=VarType.INT64, name=label)
+    print(input)  # InputSpec(shape=(-1, 784), dtype=paddle.float32, name=x)
+    print(label)  # InputSpec(shape=(-1, 1), dtype=paddle.int64, name=label)
 
 
 方法
@@ -61,7 +61,7 @@ from_tensor(tensor, name=None)
 
     x = paddle.to_tensor(np.ones([2, 2], np.float32))
     x_spec = InputSpec.from_tensor(x, name='x')
-    print(x_spec)  # InputSpec(shape=(2, 2), dtype=VarType.FP32, name=x)
+    print(x_spec)  # InputSpec(shape=(2, 2), dtype=paddle.float32, name=x)
 
 
 from_numpy(ndarray, name=None)
@@ -88,7 +88,7 @@ from_numpy(ndarray, name=None)
 
     x = np.ones([2, 2], np.float32)
     x_spec = InputSpec.from_numpy(x, name='x')
-    print(x_spec)  # InputSpec(shape=(2, 2), dtype=VarType.FP32, name=x)
+    print(x_spec)  # InputSpec(shape=(2, 2), dtype=paddle.float32, name=x)
 
 
 batch(batch_size)
@@ -112,7 +112,7 @@ batch(batch_size)
   
     x_spec = InputSpec(shape=[64], dtype='float32', name='x')
     x_spec.batch(4)
-    print(x_spec)  # InputSpec(shape=(4, 64), dtype=VarType.FP32, name=x)
+    print(x_spec)  # InputSpec(shape=(4, 64), dtype=paddle.float32, name=x)
 
 
 unbatch()
@@ -133,4 +133,4 @@ unbatch()
 
     x_spec = InputSpec(shape=[4, 64], dtype='float32', name='x')
     x_spec.unbatch()
-    print(x_spec)  # InputSpec(shape=(64,), dtype=VarType.FP32, name=x)
+    print(x_spec)  # InputSpec(shape=(64,), dtype=paddle.float32, name=x)
diff --git a/docs/api/paddle/static/Program_cn.rst b/docs/api/paddle/static/Program_cn.rst
@@ -434,8 +434,8 @@ Generator，会yield每个Program中的变量。
     for var in prog.list_vars():
         print(var)
 
-    # var img : paddle.VarType.LOD_TENSOR.shape(-1, 1, 28, 28).astype(VarType.FP32)
-    # var label : paddle.VarType.LOD_TENSOR.shape(-1, 1).astype(VarType.INT64)
+    # var img : LOD_TENSOR.shape(-1, 1, 28, 28).dtype(float32).stop_gradient(True)
+    # var label : LOD_TENSOR.shape(-1, 1).dtype(int64).stop_gradient(True)
 
 all_parameters()
 '''''''''
@@ -467,8 +467,8 @@ list[ :ref:`api_guide_parameter` ]，一个包含当前Program中所有参数的
     # Here will print all parameters in current program, in this example,
     # the result is like:
     #
-    # persist trainable param fc_0.w_0 : paddle.VarType.LOD_TENSOR.shape(13, 10).astype(VarType.FP32)
-    # persist trainable param fc_0.b_0 : paddle.VarType.LOD_TENSOR.shape(10,).astype(VarType.FP32)
+    # persist trainable param fc_0.w_0 : LOD_TENSOR.shape(13, 10).dtype(float32).stop_gradient(False)
+    # persist trainable param fc_0.b_0 : LOD_TENSOR.shape(10,).dtype(float32).stop_gradient(False)
     #
     # Here print(param) will print out all the properties of a parameter,
     # including name, type and persistable, you can access to specific

diff --git a/docs/api/paddle/static/gradients_cn.rst b/docs/api/paddle/static/gradients_cn.rst
@@ -40,4 +40,5 @@ list[Tensor]，包含与输入对应的梯度。如果一个输入不影响目
             y = paddle.static.nn.conv2d(x, 4, 1, bias_attr=False)
             y = F.relu(y)
             z = paddle.static.gradients([y], x)
-            print(z) # [var x@GRAD : fluid.VarType.LOD_TENSOR.shape(-1L, 2L, 8L, 8L).astype(VarType.FP32)]
+            print(z) 
+            # [var x@GRAD : LOD_TENSOR.shape(-1, 2, 8, 8).dtype(float32).stop_gradient(False)]
diff --git a/docs/api/paddle/t_cn.rst b/docs/api/paddle/t_cn.rst
@@ -5,51 +5,18 @@ t
 
 .. py:function:: paddle.t(input, name=None)
 
-
-
-
-该OP对小于等于2维的Tensor进行数据转置。0维和1维Tensor返回本身，2维Tensor等价于perm设置为0，1的 :ref:`cn_api_fluid_layers_transpose` 函数。
+对小于等于2维的Tensor进行数据转置。0维和1维Tensor返回本身，2维Tensor等价于perm设置为0，1的 :ref:`cn_api_fluid_layers_transpose` 函数。
 
 参数
-:::::::::
-
-    - **input** (Tensor) - 输入：N维(N<=2)Tensor，可选的数据类型为float16, float32, float64, int32, int64。
-    - **name** (str, 可选)- 该参数供开发人员打印调试信息时使用，具体用法请参见 :ref:`api_guide_Name` ，默认值为None
+::::::::
+    - **input** (Tensor) - 输入：N维(N<=2)Tensor，可选的数据类型为float16、float32、float64、int32、int64，默认值为None。
+    - **name** (str，可选)- 该参数供开发人员打印调试信息时使用，具体用法请参见 :ref:`api_guide_Name` ，默认值为None。
 
 返回
-:::::::::
- N维Tensor
-
-
-代码示例
-:::::::::
-
-.. code-block:: text
-
-        # 例1 (0-D tensor)
-        x = tensor([0.79])
-        paddle.t(x) = tensor([0.79])
-
-        # 例2 (1-D tensor)
-        x = tensor([0.79, 0.84, 0.32])
-        paddle.t(x) = tensor([0.79, 0.84, 0.32])
-
-        # 例3 (2-D tensor)
-        x = tensor([0.79, 0.84, 0.32],
-                    [0.64, 0.14, 0.57])
-        paddle.t(x) = tensor([0.79, 0.64],
-                            [0.84, 0.14],
-                            [0.32, 0.57])
-
+::::::::
+Tensor，0维和1维Tensor返回本身，2维Tensor返回转置Tensor。
 
 代码示例
-::::::::::::
-
-.. code-block:: python
-
-    import paddle
-    x = paddle.ones(shape=[2, 3], dtype='int32')
-    x_transposed = paddle.t(x)
-    print(x_transposed.shape)
-    # [3, 2]
+::::::::
 
+COPY-FROM: <paddle.t>:<code-example>
diff --git a/docs/guides/04_dygraph_to_static/basic_usage_cn.md b/docs/guides/04_dygraph_to_static/basic_usage_cn.md
@@ -150,8 +150,8 @@ from paddle.static import InputSpec
 x = InputSpec([None, 784], 'float32', 'x')
 label = InputSpec([None, 1], 'int64', 'label')
 
-print(x)      # InputSpec(shape=(-1, 784), dtype=VarType.FP32, name=x)
-print(label)  # InputSpec(shape=(-1, 1), dtype=VarType.INT64, name=label)
+print(x)      # InputSpec(shape=(-1, 784), dtype=paddle.float32, name=x)
+print(label)  # InputSpec(shape=(-1, 1), dtype=paddle.int64, name=label)
 ```
 
 
@@ -166,7 +166,7 @@ from paddle.static import InputSpec
 
 x = paddle.to_tensor(np.ones([2, 2], np.float32))
 x_spec = InputSpec.from_tensor(x, name='x')
-print(x_spec)  # InputSpec(shape=(2, 2), dtype=VarType.FP32, name=x)
+print(x_spec)  # InputSpec(shape=(2, 2), dtype=paddle.float32, name=x)
 ```
 
 > 注：若未在 ``from_tensor`` 中指定新的 ``name``，则默认使用与源 Tensor 相同的 ``name``。
@@ -182,7 +182,7 @@ from paddle.static import InputSpec
 
 x = np.ones([2, 2], np.float32)
 x_spec = InputSpec.from_numpy(x, name='x')
-print(x_spec)  # InputSpec(shape=(2, 2), dtype=VarType.FP32, name=x)
+print(x_spec)  # InputSpec(shape=(2, 2), dtype=paddle.float32, name=x)
 ```
 
 > 注：若未在 ``from_numpy`` 中指定新的 ``name``，则默认使用 ``None`` 。