refine the doc for API2.0 (#28386)

python/paddle/device.py

@@ -82,7 +82,7 @@ def get_cudnn_version():
             
             import paddle
 
-            cudnn_version = get_cudnn_version()
+            cudnn_version = paddle.get_cudnn_version()
 
 
 
@@ -117,7 +117,7 @@ def set_device(device):
      .. code-block:: python
             
         import paddle
-        paddle.disable_static()
+
         paddle.set_device("cpu")
         x1 = paddle.ones(name='x1', shape=[1, 2], dtype='int32')
         x2 = paddle.zeros(name='x2', shape=[1, 2], dtype='int32')
@@ -179,7 +179,6 @@ def get_device():
      .. code-block:: python
             
         import paddle
-        paddle.disable_static()
         device = paddle.get_device()
 
     """

python/paddle/tensor/creation.py

@@ -224,7 +224,6 @@ def full_like(x, fill_value, dtype=None, name=None):
           import paddle
           import numpy as np
           
-          paddle.disable_static()  # Now we are in imperative mode 
           input = paddle.full(shape=[2, 3], fill_value=0.0, dtype='float32', name='input')
           output = paddle.full_like(input, 2.0)
           # [[2. 2. 2.]
@@ -277,7 +276,6 @@ def ones(shape, dtype=None, name=None):
         .. code-block:: python
 
           import paddle 
-          paddle.disable_static()
           
           # default dtype for ones OP
           data1 = paddle.ones(shape=[3, 2]) 
@@ -361,7 +359,6 @@ def zeros(shape, dtype=None, name=None):
 
           import paddle
           
-          paddle.disable_static()  # Now we are in imperative mode
           data = paddle.zeros(shape=[3, 2], dtype='float32') 
           # [[0. 0.]
           #  [0. 0.]
@@ -446,7 +443,6 @@ def eye(num_rows, num_columns=None, dtype=None, name=None):
           
           import paddle
 
-          paddle.disable_static()  # Now we are in imperative mode
           data = paddle.eye(3, dtype='int32')
           # [[1 0 0]
           #  [0 1 0]
@@ -493,7 +489,6 @@ def full(shape, fill_value, dtype=None, name=None):
 
           import paddle
 
-          paddle.disable_static()  # Now we are in imperative mode
           data1 = paddle.full(shape=[2,1], fill_value=0, dtype='int64') 
           #[[0]
           # [0]]

python/paddle/tensor/manipulation.py

@@ -67,8 +67,6 @@ __all__ = [
 
 def concat(x, axis=0, name=None):
     """
-	:alias_main: paddle.concat
-	:alias: paddle.tensor.concat, paddle.tensor.manipulation.concat
 
     This OP concatenates the input along the axis.
 
@@ -91,7 +89,6 @@ def concat(x, axis=0, name=None):
             
             import paddle
             
-            paddle.disable_static()  # Now we are in imperative mode
             x1 = paddle.to_tensor([[1, 2, 3],
                                    [4, 5, 6]])
             x2 = paddle.to_tensor([[11, 12, 13],
@@ -465,7 +462,6 @@ def split(x, num_or_sections, axis=0, name=None):
             import numpy as np
             import paddle
             
-            paddle.disable_static()
             # x is a Tensor which shape is [3, 9, 5]
             x_np = np.random.random([3, 9, 5]).astype("int32")
             x = paddle.to_tensor(x_np)
@@ -608,7 +604,6 @@ def unique(x,
 
             import paddle
 
-            paddle.disable_static()
             x = paddle.to_tensor([2, 3, 3, 1, 5, 3])
             unique = paddle.unique(x)
             np_unique = unique.numpy() # [1 2 3 5]
@@ -744,9 +739,6 @@ def unsqueeze(x, axis, name=None):
 
 def gather(x, index, axis=None, name=None):
     """
-
-    **Gather Layer**
-
     Output is obtained by gathering entries of ``axis``
     of ``x`` indexed by ``index`` and concatenate them together.
 
@@ -765,7 +757,8 @@ def gather(x, index, axis=None, name=None):
                 Then:
 
                 out = [[3, 4],
-                       [5, 6]]
+                       [5, 6]] 
+
     Args:
         x (Tensor): The source input tensor with rank>=1. Supported data type is
             int32, int64, float32, float64 and uint8 (only for CPU),
@@ -784,7 +777,6 @@ def gather(x, index, axis=None, name=None):
 
             import paddle
 
-            paddle.disable_static()
             input = paddle.to_tensor([[1,2],[3,4],[5,6]])
             index = paddle.to_tensor([0,1])
             output = paddle.gather(input, index, axis=0)
@@ -1059,7 +1051,6 @@ def chunk(x, chunks, axis=0, name=None):
             import numpy as np
             import paddle
             
-            paddle.disable_static()
             # x is a Tensor which shape is [3, 9, 5]
             x_np = np.random.random([3, 9, 5]).astype("int32")
             x = paddle.to_tensor(x_np)
@@ -1452,7 +1443,6 @@ def gather_nd(x, index, name=None):
             
             import paddle
             
-            paddle.disable_static()
             x = paddle.to_tensor([[[1, 2], [3, 4], [5, 6]],
                                   [[7, 8], [9, 10], [11, 12]]])
             index = paddle.to_tensor([[0, 1]])

python/paddle/tensor/math.py

@@ -1780,44 +1780,31 @@ def prod(x, axis=None, keepdim=False, dtype=None, name=None):
 
             import paddle
 
-            paddle.disable_static()
-
             # the axis is a int element
             x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9],
                                   [0.1, 0.2, 0.6, 0.7]])
             out1 = paddle.prod(x)
-            print(out1.numpy())
             # [0.0002268]
 
             out2 = paddle.prod(x, -1)
-            print(out2.numpy())
             # [0.027  0.0084]
 
             out3 = paddle.prod(x, 0)
-            print(out3.numpy())
             # [0.02 0.06 0.3  0.63]
-            print(out3.numpy().dtype)
-            # float32
 
             out4 = paddle.prod(x, 0, keepdim=True)
-            print(out4.numpy())
             # [[0.02 0.06 0.3  0.63]]
 
             out5 = paddle.prod(x, 0, dtype='int64')
-            print(out5.numpy())
             # [0 0 0 0]
-            print(out5.numpy().dtype)
-            # int64
 
             # the axis is list
             y = paddle.to_tensor([[[1.0, 2.0], [3.0, 4.0]],
                                   [[5.0, 6.0], [7.0, 8.0]]])
             out6 = paddle.prod(y, [0, 1])
-            print(out6.numpy())
             # [105. 384.]
 
             out7 = paddle.prod(y, (1, 2))
-            print(out7.numpy())
             # [  24. 1680.]
 
     """

python/paddle/tensor/search.py

@@ -280,8 +280,6 @@ def argmin(x, axis=None, keepdim=False, dtype="int64", name=None):
 
 def index_select(x, index, axis=0, name=None):
     """
-	:alias_main: paddle.index_select
-	:alias: paddle.tensor.index_select, paddle.tensor.search.index_select
 
     Returns a new tensor which indexes the ``input`` tensor along dimension ``axis`` using 
     the entries in ``index`` which is a Tensor. The returned tensor has the same number 
@@ -304,7 +302,6 @@ def index_select(x, index, axis=0, name=None):
             
             import paddle
 
-            paddle.disable_static()  # Now we are in imperative mode
             x = paddle.to_tensor([[1.0, 2.0, 3.0, 4.0],
                                   [5.0, 6.0, 7.0, 8.0],
                                   [9.0, 10.0, 11.0, 12.0]])
@@ -680,7 +677,6 @@ def masked_select(x, mask, name=None):
 
             import paddle
 
-            paddle.disable_static()
 
             x = paddle.to_tensor([[1.0, 2.0, 3.0, 4.0],
                                   [5.0, 6.0, 7.0, 8.0],

python/paddle/tensor/stat.py

@@ -242,7 +242,6 @@ def numel(x, name=None):
 
             import paddle
             
-            paddle.disable_static()
             x = paddle.full(shape=[4, 5, 7], fill_value=0, dtype='int32')
             numel = paddle.numel(x) # 140