fix doc of data,matmul,dot,cholesky,scatter,divide,remainder,inverse,sign (#28665)

python/paddle/fluid/layers/nn.py

@@ -8545,7 +8545,8 @@ def scatter_nd_add(ref, index, updates, name=None):
         .. code-block:: python
 
             import paddle.fluid as fluid
-
+            import paddle
+            paddle.enable_static()
             ref = fluid.data(name='ref', shape=[3, 5, 9, 10], dtype='float32')
             index = fluid.data(name='index', shape=[3, 2], dtype='int32')
             updates = fluid.data(name='update', shape=[3, 9, 10], dtype='float32')

python/paddle/static/input.py

@@ -57,6 +57,7 @@ def data(name, shape, dtype=None, lod_level=0):
 
           import numpy as np
           import paddle
+          paddle.enable_static()
 
           # Creates a variable with fixed size [3, 2, 1]
           # User can only feed data of the same shape to x

python/paddle/tensor/linalg.py

@@ -96,7 +96,6 @@ def matmul(x, y, transpose_x=False, transpose_y=False, name=None):
         import paddle
         import numpy as np
 
-        paddle.disable_static()
         # vector * vector
         x_data = np.random.random([10]).astype(np.float32)
         y_data = np.random.random([10]).astype(np.float32)
@@ -563,7 +562,7 @@ def dot(x, y, name=None):
         name(str, optional): Name of the output. Default is None. It's used to print debug info for developers. Details: :ref:`api_guide_Name`
 
     Returns:
-        Variable: the calculated result Tensor.
+        Tensor: the calculated result Tensor.
 
     Examples:
 
@@ -572,13 +571,12 @@ def dot(x, y, name=None):
         import paddle
         import numpy as np
 
-        paddle.disable_static()
         x_data = np.random.uniform(0.1, 1, [10]).astype(np.float32)
         y_data = np.random.uniform(1, 3, [10]).astype(np.float32)
         x = paddle.to_tensor(x_data)
         y = paddle.to_tensor(y_data)
         z = paddle.dot(x, y)
-        print(z.numpy())
+        print(z)
 
     """
     op_type = 'dot'
@@ -750,7 +748,7 @@ def cholesky(x, upper=False, name=None):
     :math:`L` is lower-triangular.
 
     Args:
-        x (Variable): The input tensor. Its shape should be `[*, M, M]`,
+        x (Tensor): The input tensor. Its shape should be `[*, M, M]`,
             where * is zero or more batch dimensions, and matrices on the
             inner-most 2 dimensions all should be symmetric positive-definite.
             Its data type should be float32 or float64.
@@ -758,7 +756,7 @@ def cholesky(x, upper=False, name=None):
             triangular matrices. Default: False.
 
     Returns:
-        Variable: A Tensor with same shape and data type as `x`. It represents \
+        Tensor: A Tensor with same shape and data type as `x`. It represents \
             triangular matrices generated by Cholesky decomposition.
         
     Examples:
@@ -767,13 +765,12 @@ def cholesky(x, upper=False, name=None):
             import paddle
             import numpy as np
 
-            paddle.disable_static()
             a = np.random.rand(3, 3)
             a_t = np.transpose(a, [1, 0])
             x_data = np.matmul(a, a_t) + 1e-03
             x = paddle.to_tensor(x_data)
             out = paddle.cholesky(x, upper=False)
-            print(out.numpy())
+            print(out)
             # [[1.190523   0.         0.        ]
             #  [0.9906703  0.27676893 0.        ]
             #  [1.25450498 0.05600871 0.06400121]]

python/paddle/tensor/manipulation.py

@@ -862,6 +862,7 @@ def scatter(x, index, updates, overwrite=True, name=None):
     Output is obtained by updating the input on selected indices based on updates.
     
     .. code-block:: python
+    
         import numpy as np
         #input:
         x = np.array([[1, 1], [2, 2], [3, 3]])
@@ -902,7 +903,6 @@ def scatter(x, index, updates, overwrite=True, name=None):
         .. code-block:: python
             
             import paddle
-            paddle.disable_static()
 
             x = paddle.to_tensor([[1, 1], [2, 2], [3, 3]], dtype='float32')
             index = paddle.to_tensor([2, 1, 0, 1], dtype='int64')

python/paddle/tensor/math.py

@@ -312,12 +312,10 @@ def divide(x, y, name=None):
 
             import paddle
 
-            paddle.disable_static()
-
             x = paddle.to_tensor([2, 3, 4], dtype='float64')
             y = paddle.to_tensor([1, 5, 2], dtype='float64')
             z = paddle.divide(x, y)
-            print(z.numpy())  # [2., 0.6, 2.]
+            print(z)  # [2., 0.6, 2.]
 
     """
     op_type = 'elementwise_div'
@@ -354,12 +352,10 @@ def floor_divide(x, y, name=None):
 
             import paddle
 
-            paddle.disable_static()
-
             x = paddle.to_tensor([2, 3, 8, 7])
             y = paddle.to_tensor([1, 5, 3, 3])
             z = paddle.floor_divide(x, y)
-            print(z.numpy())  # [2, 0, 2, 2]
+            print(z)  # [2, 0, 2, 2]
 
     """
     op_type = 'elementwise_floordiv'
@@ -376,10 +372,11 @@ def remainder(x, y, name=None):
     Mod two tensors element-wise. The equation is:
 
     .. math::
+
         out = x \% y
 
     **Note**:
-    ``paddle.mod`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
+    ``paddle.remainder`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
         x (Tensor): the input tensor, it's data type should be float32, float64, int32, int64.
@@ -397,7 +394,7 @@ def remainder(x, y, name=None):
 
             x = paddle.to_tensor([2, 3, 8, 7])
             y = paddle.to_tensor([1, 5, 3, 3])
-            z = paddle.mod(x, y)
+            z = paddle.remainder(x, y)
             print(z)  # [0, 3, 2, 1]
 
     """
@@ -1037,7 +1034,7 @@ def inverse(x, name=None):
     (2-D Tensor) or batches of square matrices.
 
     Args:
-        x (Variable): The input tensor. The last two
+        x (Tensor): The input tensor. The last two
             dimensions should be equal. When the number of dimensions is
             greater than 2, it is treated as batches of square matrix. The data
             type can be float32 and float64.
@@ -1046,14 +1043,13 @@ def inverse(x, name=None):
             please refer to :ref:`api_guide_Name`
 
     Returns:
-        Variable: A Tensor holds the inverse of x. The shape and data type
+        Tensor: A Tensor holds the inverse of x. The shape and data type
                         is the same as x.
 
     Examples:
         .. code-block:: python
 
             import paddle
-            paddle.disable_static()
 
             mat = paddle.to_tensor([[2, 0], [0, 2]], dtype='float32')
             inv = paddle.inverse(mat)
@@ -1915,7 +1911,6 @@ def sign(x, name=None):
 
           import paddle
 
-          paddle.disable_static()
           x = paddle.to_tensor([3.0, 0.0, -2.0, 1.7], dtype='float32')
           out = paddle.sign(x=x)
           print(out)  # [1.0, 0.0, -1.0, 1.0]