fix The first round of evaluation (#47256)

* fix paddle.get_default_dtype 

Chinese and English return values are inconsistent

* fix paddle.matmul 文档评估 #4407

把函数的输出改成正确的

* fix paddle.std文档评估 #4370

增加了一个unbiased=False的代码示例，没有增加numpy,怕引起误会。

* fix paddle.load文档测评 #4455 

只把代码拆分了5段

* try

* try

* try

* Update io.py

* Update io.py

* Update creation.py

* Update creation.py

* [Docs]add name description

* [Docs]fix broadcasting issue

Co-authored-by: Ligoml <[email protected]>

Author: coderbullbull

python/paddle/framework/io.py

@@ -669,6 +669,7 @@ def save(obj, path, protocol=4, **configs):
 
     Examples:
         .. code-block:: python
+            :name: code-example-1
 
             # example 1: dynamic graph
             import paddle
@@ -690,7 +691,11 @@ def save(obj, path, protocol=4, **configs):
             # save weight of emb
             paddle.save(emb.weight, "emb.weight.pdtensor")
 
+        .. code-block:: python
+            :name: code-example-2
+
             # example 2: Save multiple state_dict at the same time
+            import paddle
             from paddle import nn
             from paddle.optimizer import Adam
 
@@ -700,6 +705,8 @@ def save(obj, path, protocol=4, **configs):
             path = 'example/model.pdparams'
             paddle.save(obj, path)
 
+        .. code-block:: python
+            :name: code-example-3
 
             # example 3: static graph
             import paddle
@@ -728,6 +735,9 @@ def save(obj, path, protocol=4, **configs):
             path_state_dict = 'temp/model.pdparams'
             paddle.save(prog.state_dict("param"), path_tensor)
 
+        .. code-block:: python
+            :name: code-example-4
+
             # example 4: save program
             import paddle
 
@@ -740,6 +750,8 @@ def save(obj, path, protocol=4, **configs):
             path = "example/main_program.pdmodel"
             paddle.save(main_program, path)
 
+        .. code-block:: python
+            :name: code-example-5
 
             # example 5: save object to memory
             from io import BytesIO
@@ -918,6 +930,7 @@ def load(path, **configs):
 
     Examples:
         .. code-block:: python
+            :name: code-example-1
 
             # example 1: dynamic graph
             import paddle
@@ -946,8 +959,11 @@ def load(path, **configs):
             # load weight of emb
             load_weight = paddle.load("emb.weight.pdtensor")
 
+        .. code-block:: python
+            :name: code-example-2
 
             # example 2: Load multiple state_dict at the same time
+            import paddle
             from paddle import nn
             from paddle.optimizer import Adam
 
@@ -958,6 +974,8 @@ def load(path, **configs):
             paddle.save(obj, path)
             obj_load = paddle.load(path)
 
+        .. code-block:: python
+            :name: code-example-3
 
             # example 3: static graph
             import paddle
@@ -988,6 +1006,8 @@ def load(path, **configs):
             paddle.save(prog.state_dict("param"), path_tensor)
             load_state_dict = paddle.load(path_tensor)
 
+        .. code-block:: python
+            :name: code-example-4
 
             # example 4: load program
             import paddle
@@ -1003,6 +1023,8 @@ def load(path, **configs):
             load_main = paddle.load(path)
             print(load_main)
 
+        .. code-block:: python
+            :name: code-example-5
 
             # example 5: save object to memory
             from io import BytesIO

python/paddle/tensor/creation.py

@@ -1174,7 +1174,7 @@ def triu(x, diagonal=0, name=None):
 
 def meshgrid(*args, **kwargs):
     """
-    Takes a list of N tensors as input *args, each of which is 1-dimensional vector, and creates N-dimensional grids.
+    Takes a list of N tensors as input :attr:`*args`, each of which is 1-dimensional vector, and creates N-dimensional grids.
 
     Args:
         *args(Tensor|list of Tensor) : tensors (tuple(list) of tensor): the shapes of input k tensors are (N1,),

python/paddle/tensor/linalg.py

@@ -183,9 +183,9 @@ def matmul(x, y, transpose_x=False, transpose_y=False, name=None):
     Args:
         x (Tensor): The input tensor which is a Tensor.
         y (Tensor): The input tensor which is a Tensor.
-        transpose_x (bool): Whether to transpose :math:`x` before multiplication.
-        transpose_y (bool): Whether to transpose :math:`y` before multiplication.
-        name(str|None): A name for this layer(optional). If set None, the layer
+        transpose_x (bool, optional): Whether to transpose :math:`x` before multiplication.
+        transpose_y (bool, optional): Whether to transpose :math:`y` before multiplication.
+        name(str, optional): A name for this layer(optional). If set None, the layer
             will be named automatically.
 
     Returns:
@@ -202,35 +202,35 @@ def matmul(x, y, transpose_x=False, transpose_y=False, name=None):
             y = paddle.rand([10])
             z = paddle.matmul(x, y)
             print(z.shape)
-            # [1]
+            # (1,)
 
             # matrix * vector
             x = paddle.rand([10, 5])
             y = paddle.rand([5])
             z = paddle.matmul(x, y)
             print(z.shape)
-            # [10]
+            # (10,)
 
             # batched matrix * broadcasted vector
             x = paddle.rand([10, 5, 2])
             y = paddle.rand([2])
             z = paddle.matmul(x, y)
             print(z.shape)
-            # [10, 5]
+            # (10, 5)
 
             # batched matrix * batched matrix
             x = paddle.rand([10, 5, 2])
             y = paddle.rand([10, 2, 5])
             z = paddle.matmul(x, y)
             print(z.shape)
-            # [10, 5, 5]
+            # (10, 5, 5)
 
             # batched matrix * broadcasted matrix
             x = paddle.rand([10, 1, 5, 2])
             y = paddle.rand([1, 3, 2, 5])
             z = paddle.matmul(x, y)
             print(z.shape)
-            # [10, 3, 5, 5]
+            # (10, 3, 5, 5)
 
     """
     if in_dygraph_mode():
@@ -639,9 +639,9 @@ def p_matrix_norm(input, porder=1.0, axis=axis, keepdim=False, name=None):
 def dist(x, y, p=2, name=None):
     r"""
 
-    This OP returns the p-norm of (x - y). It is not a norm in a strict sense, only as a measure
+    Returns the p-norm of (x - y). It is not a norm in a strict sense, only as a measure
     of distance. The shapes of x and y must be broadcastable. The definition is as follows, for
-    details, please refer to the `numpy's broadcasting <https://docs.scipy.org/doc/numpy/user/basics.broadcasting.html>`_:
+    details, please refer to the `Introduction to Tensor <../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor>`_:
 
     - Each input has at least one dimension.
     - Match the two input dimensions from back to front, the dimension sizes must either be equal, one of them is 1, or one of them does not exist.
@@ -695,6 +695,8 @@ def dist(x, y, p=2, name=None):
         x (Tensor): 1-D to 6-D Tensor, its data type is float32 or float64.
         y (Tensor): 1-D to 6-D Tensor, its data type is float32 or float64.
         p (float, optional): The norm to be computed, its data type is float32 or float64. Default: 2.
+        name (str, optional): The default value is `None`. Normally there is no need for
+            user to set this property. For more information, please refer to :ref:`api_guide_Name`.
 
     Returns:
         Tensor: Tensor that is the p-norm of (x - y).

python/paddle/tensor/search.py

@@ -384,7 +384,7 @@ def nonzero(x, as_tuple=False):
 
     Args:
         x (Tensor): The input tensor variable.
-        as_tuple (bool): Return type, Tensor or tuple of Tensor.
+        as_tuple (bool, optional): Return type, Tensor or tuple of Tensor.
 
     Returns:
         Tensor. The data type is int64.

python/paddle/tensor/stat.py

@@ -206,8 +206,11 @@ def std(x, axis=None, unbiased=True, keepdim=False, name=None):
             x = paddle.to_tensor([[1.0, 2.0, 3.0], [1.0, 4.0, 5.0]])
             out1 = paddle.std(x)
             # [1.63299316]
-            out2 = paddle.std(x, axis=1)
+            out2 = paddle.std(x, unbiased=False)
+            # [1.49071205]
+            out3 = paddle.std(x, axis=1)
             # [1.       2.081666]
+
     """
     if not paddle.in_dynamic_mode():
         check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'std')