未验证 提交 3ccee082 编写于 作者: K Kaipeng Deng 提交者: GitHub

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

* numpy -> paddle in conv. test=develop
上级 ca289201
......@@ -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
......
......@@ -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)
"""
......
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