numpy -> paddle in conv & conv_transpose (#27669)

* numpy -> paddle in conv. test=develop

python/paddle/nn/functional/conv.py

@@ -438,20 +438,14 @@ def conv2d(x,
 
           import paddle
           import paddle.nn.functional as F
-          import numpy as np
-
-          x = np.random.randn(2, 3, 8, 8).astype(np.float32)
-          w = np.random.randn(6, 3, 3, 3).astype(np.float32)
 
-          paddle.disable_static()
+          x_var = paddle.randn((2, 3, 8, 8), dtype='float32')
+          w_var = paddle.randn((6, 3, 3, 3), dtype='float32')
 
-          x_var = paddle.to_tensor(x)
-          w_var = paddle.to_tensor(w)
           y_var = F.conv2d(x_var, w_var)
           y_np = y_var.numpy()
 
           print(y_np.shape)
-
           # (2, 6, 6, 6)
     """
     # entry checks
@@ -946,20 +940,16 @@ def conv_transpose2d(x,
     Examples:
         .. code-block:: python
 
-          import numpy as np
           import paddle
           import paddle.nn.functional as F
 
-          x = np.random.randn(2, 3, 8, 8).astype(np.float32)
-          w = np.random.randn(3, 6, 3, 3).astype(np.float32)
+          x_var = paddle.randn((2, 3, 8, 8), dtype='float32')
+          w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
 
-          paddle.disable_static()
-          x_var = paddle.to_tensor(x)
-          w_var = paddle.to_tensor(w)
           y_var = F.conv_transpose2d(x_var, w_var)
           y_np = y_var.numpy()
-          print(y_np.shape)
 
+          print(y_np.shape)
           # (2, 6, 10, 10)
     """
 
@@ -1166,20 +1156,16 @@ def conv3d(x,
     Examples:
         .. code-block:: python
 
-            import numpy as np
             import paddle
             import paddle.nn.functional as F
 
-            x = np.random.randn(2, 3, 8, 8, 8).astype(np.float32)
-            w = np.random.randn(6, 3, 3, 3, 3).astype(np.float32)
+            x_var = paddle.randn((2, 3, 8, 8, 8), dtype='float32')
+            w_var = paddle.randn((6, 3, 3, 3, 3), dtype='float32')
 
-            paddle.disable_static()
-            x_var = paddle.to_tensor(x)
-            w_var = paddle.to_tensor(w)
             y_var = F.conv3d(x_var, w_var)
             y_np = y_var.numpy()
-            print(y_np.shape)
 
+            print(y_np.shape)
             # (2, 6, 6, 6, 6)
     """
     # entry check
@@ -1399,22 +1385,16 @@ def conv_transpose3d(x,
     Examples:
        .. code-block:: python
           
-          import numpy as np
-
           import paddle
           import paddle.nn.functional as F
 
-          x = np.random.randn(2, 3, 8, 8, 8).astype(np.float32)
-          w = np.random.randn(3, 6, 3, 3, 3).astype(np.float32)
+          x_var = paddle.randn((2, 3, 8, 8, 8), dtype='float32')
+          w_var = paddle.randn((3, 6, 3, 3, 3), dtype='float32')
 
-          paddle.disable_static()
-
-          x_var = paddle.to_tensor(x)
-          w_var = paddle.to_tensor(w)
           y_var = F.conv_transpose3d(x_var, w_var)
           y_np = y_var.numpy()
-          print(y_np.shape)
 
+          print(y_np.shape)
           # (2, 6, 10, 10, 10)
     """
     # entry checks

python/paddle/nn/layer/conv.py

@@ -534,18 +534,15 @@ class Conv2d(_ConvNd):
 
         .. code-block:: python
 
-          import numpy as np
           import paddle
           import paddle.nn as nn
-          x = np.random.uniform(-1, 1, (2, 4, 8, 8)).astype('float32')
 
-          paddle.disable_static()
-          x_var = paddle.to_tensor(x)
+          x_var = paddle.uniform((2, 4, 8, 8), dtype='float32', min=-1., max=1.)
+          
           conv = nn.Conv2d(4, 6, (3, 3))
           y_var = conv(x_var)
           y_np = y_var.numpy()
           print(y_np.shape)
-          
           # (2, 6, 6, 6)
     """
 
@@ -702,17 +699,15 @@ class ConvTranspose2d(_ConvNd):
 
        .. code-block:: python
 
-          import numpy as np
           import paddle
           import paddle.nn as nn
-          x = np.random.uniform(-1, 1, (2, 4, 8, 8)).astype('float32')
-          paddle.disable_static()
-          x_var = paddle.to_tensor(x)
+
+          x_var = paddle.uniform((2, 4, 8, 8), dtype='float32', min=-1., max=1.)
+
           conv = nn.ConvTranspose2d(4, 6, (3, 3))
           y_var = conv(x_var)
           y_np = y_var.numpy()
           print(y_np.shape)
-          
           # (2, 6, 10, 10)
     """
 
@@ -856,19 +851,15 @@ class Conv3d(_ConvNd):
 
         .. code-block:: python
 
-          import numpy as np
-          
           import paddle
           import paddle.nn as nn
-          x = np.random.uniform(-1, 1, (2, 4, 8, 8, 8)).astype('float32')
 
-          paddle.disable_static()
-          x_var = dg.to_variable(x)
+          x_var = paddle.uniform((2, 4, 8, 8, 8), dtype='float32', min=-1., max=1.)
+          
           conv = nn.Conv3d(4, 6, (3, 3, 3))
           y_var = conv(x_var)
           y_np = y_var.numpy()
           print(y_np.shape)
-          
           # (2, 6, 6, 6, 6)
     """
 
@@ -1042,18 +1033,15 @@ class ConvTranspose3d(_ConvNd):
 
        .. code-block:: python
 
-          import numpy as np
           import paddle
           import paddle.nn as nn
-          x = np.random.uniform(-1, 1, (2, 4, 8, 8, 8)).astype('float32')
 
-          paddle.disable_static()
-          x_var = paddle.to_tensor(x)
+          x_var = paddle.uniform((2, 4, 8, 8, 8), dtype='float32', min=-1., max=1.)
+          
           conv = nn.ConvTranspose3d(4, 6, (3, 3, 3))
           y_var = conv(x_var)
           y_np = y_var.numpy()
           print(y_np.shape)
-          
           # (2, 6, 10, 10, 10)
     """