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e29c50c2
编写于
11月 24, 2022
作者:
傅
傅剑寒
提交者:
GitHub
11月 24, 2022
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电子邮件补丁
差异文件
remove pad2d in nn.py (#47854)
上级
29782728
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
16 addition
and
183 deletion
+16
-183
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+0
-146
python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py
...fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py
+11
-6
python/paddle/fluid/tests/unittests/test_layers.py
python/paddle/fluid/tests/unittests/test_layers.py
+4
-12
python/paddle/fluid/tests/unittests/test_pad2d_op.py
python/paddle/fluid/tests/unittests/test_pad2d_op.py
+1
-19
未找到文件。
python/paddle/fluid/layers/nn.py
浏览文件 @
e29c50c2
...
...
@@ -116,7 +116,6 @@ __all__ = [
'crop_tensor'
,
'prelu'
,
'flatten'
,
'pad2d'
,
'unique'
,
'unique_with_counts'
,
'scale'
,
...
...
@@ -7579,151 +7578,6 @@ def crop_tensor(x, shape=None, offsets=None, name=None):
return
out
def
pad2d
(
input
,
paddings
=
[
0
,
0
,
0
,
0
],
mode
=
'constant'
,
pad_value
=
0.0
,
data_format
=
"NCHW"
,
name
=
None
,
):
"""
Pad 2-d images according to 'paddings' and 'mode'.
If mode is 'reflect', paddings[0] and paddings[1] must be no greater
than height-1. And the width dimension has the same condition.
Parameters:
input (Tensor): The input image with [N, C, H, W] format or [N, H, W, C] format, which is a 4-D Tensor with data type float32.
paddings (Tensor | List[int32]): The padding size. If padding is a List, it must
contain four integers, (padding_top, padding_bottom, padding_left, padding_right).
Otherwise, it is a 1-D Tensor with shape [4]. Data type is int32.
Default is [0, 0, 0, 0].
mode (str): Three modes: 'constant' (default), 'reflect', 'edge' .
When in 'constant' mode, this op uses a constant value to pad the input tensor.
When in 'reflect' mode, uses reflection of the input boundaries to pad the input tensor.
When in 'edge' mode, uses input boundaries to pad the input tensor.
Default is 'constant'
pad_value (float32): The value to fill the padded areas in 'constant' mode . Default is 0.0
data_format (str): An string from: "NHWC", "NCHW". Specify the data format of
the input data.
Default is "NCHW"
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, a 4-D Tensor padded according to paddings and mode and data type is same as input.
Examples:
.. code-block:: text
Input = [[[[1., 2., 3.],
[4., 5., 6.]]]]
Case 0:
paddings = [0, 1, 2, 3],
mode = 'constant'
pad_value = 0
Out = [[[[0., 0., 1., 2., 3., 0., 0., 0.],
[0., 0., 4., 5., 6., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0.]]]]
Case 1:
paddings = [0, 1, 2, 1],
mode = 'reflect'
Out = [[[[3., 2., 1., 2., 3., 2.],
[6., 5., 4., 5., 6., 5.],
[3., 2., 1., 2., 3., 2.]]]]
Case 2:
paddings = [0, 1, 2, 1],
mode = 'edge'
Out = [[[[1., 1., 1., 2., 3., 3.],
[4., 4., 4., 5., 6., 6.],
[4., 4., 4., 5., 6., 6.]]]]
Code Examples:
.. code-block:: python
import numpy as np
import paddle
import paddle.nn.functional as F
# example 1
x_shape = (1, 1, 3, 4)
x = np.arange(np.prod(x_shape), dtype=np.float32).reshape(x_shape) + 1
tensor_x = paddle.to_tensor(x)
y = paddle.fluid.layers.pad2d(tensor_x, paddings=[1, 2, 2, 1], pad_value=1, mode='constant')
print(y.numpy())
# [[[[ 1. 1. 1. 1. 1. 1. 1.]
# [ 1. 1. 1. 2. 3. 4. 1.]
# [ 1. 1. 5. 6. 7. 8. 1.]
# [ 1. 1. 9. 10. 11. 12. 1.]
# [ 1. 1. 1. 1. 1. 1. 1.]
# [ 1. 1. 1. 1. 1. 1. 1.]]]]
# example 2
x_shape = (1, 1, 2, 3)
x = np.arange(np.prod(x_shape), dtype=np.float32).reshape(x_shape) + 1
tensor_x = paddle.to_tensor(x)
y = paddle.fluid.layers.pad2d(tensor_x, paddings=[1, 1, 1, 1], mode='reflect')
print(y.numpy())
# [[[[5. 4. 5. 6. 5.]
# [2. 1. 2. 3. 2.]
# [5. 4. 5. 6. 5.]
# [2. 1. 2. 3. 2.]]]]
"""
if
_non_static_mode
():
_paddings
=
(
paddings
.
numpy
().
tolist
()
if
isinstance
(
paddings
,
Variable
)
else
paddings
)
return
_legacy_C_ops
.
pad2d
(
input
,
'mode'
,
mode
,
'pad_value'
,
pad_value
,
'data_format'
,
data_format
,
'paddings'
,
_paddings
,
)
check_variable_and_dtype
(
input
,
'input'
,
[
'float16'
,
'float32'
,
'float64'
,
'int32'
,
'int64'
],
"pad2d"
,
)
attrs
=
{
'mode'
:
mode
,
'pad_value'
:
pad_value
,
'data_format'
:
data_format
}
inputs
=
{
'X'
:
[
input
]}
if
isinstance
(
paddings
,
Variable
):
inputs
[
'Paddings'
]
=
[
paddings
]
attrs
[
'paddings'
]
=
[]
else
:
attrs
[
'paddings'
]
=
paddings
helper
=
LayerHelper
(
'pad2d'
,
**
locals
())
assert
mode
in
[
'reflect'
,
'edge'
,
'constant'
,
],
"mode should be one of constant, reflect, edge."
dtype
=
helper
.
input_dtype
(
input_param_name
=
'input'
)
out
=
helper
.
create_variable_for_type_inference
(
dtype
)
helper
.
append_op
(
type
=
'pad2d'
,
inputs
=
inputs
,
outputs
=
{
"Out"
:
out
},
attrs
=
attrs
)
return
out
@
deprecated
(
since
=
"2.0.0"
,
update_to
=
"paddle.static.nn.prelu"
)
def
prelu
(
x
,
mode
,
param_attr
=
None
,
data_format
=
"NCHW"
,
name
=
None
):
r
"""
...
...
python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py
浏览文件 @
e29c50c2
...
...
@@ -179,10 +179,12 @@ class build_resnet_block(fluid.dygraph.Layer):
self
.
dim
=
dim
def
forward
(
self
,
inputs
):
out_res
=
fluid
.
layers
.
pad2d
(
inputs
,
[
1
,
1
,
1
,
1
],
mode
=
"reflect"
)
pad1
=
paddle
.
nn
.
Pad2D
([
1
,
1
,
1
,
1
],
mode
=
"reflect"
)
out_res
=
pad1
(
inputs
)
out_res
=
self
.
conv0
(
out_res
)
out_res
=
fluid
.
layers
.
pad2d
(
out_res
,
[
1
,
1
,
1
,
1
],
mode
=
"reflect"
)
pad2
=
paddle
.
nn
.
Pad2D
([
1
,
1
,
1
,
1
],
mode
=
"reflect"
)
out_res
=
pad2
(
out_res
)
out_res
=
self
.
conv1
(
out_res
)
return
out_res
+
inputs
...
...
@@ -253,7 +255,8 @@ class build_generator_resnet_9blocks(fluid.dygraph.Layer):
)
def
forward
(
self
,
inputs
):
pad_input
=
fluid
.
layers
.
pad2d
(
inputs
,
[
3
,
3
,
3
,
3
],
mode
=
"reflect"
)
pad1
=
paddle
.
nn
.
Pad2D
([
3
,
3
,
3
,
3
],
mode
=
"reflect"
)
pad_input
=
pad1
(
inputs
)
y
=
self
.
conv0
(
pad_input
)
y
=
self
.
conv1
(
y
)
y
=
self
.
conv2
(
y
)
...
...
@@ -261,7 +264,8 @@ class build_generator_resnet_9blocks(fluid.dygraph.Layer):
y
=
build_resnet_block_i
(
y
)
y
=
self
.
deconv0
(
y
)
y
=
self
.
deconv1
(
y
)
y
=
fluid
.
layers
.
pad2d
(
y
,
[
3
,
3
,
3
,
3
],
mode
=
"reflect"
)
pad2
=
paddle
.
nn
.
Pad2D
([
3
,
3
,
3
,
3
],
mode
=
"reflect"
)
y
=
pad2
(
y
)
y
=
self
.
conv3
(
y
)
y
=
paddle
.
tanh
(
y
)
return
y
...
...
@@ -461,9 +465,10 @@ class DeConv2D(fluid.dygraph.Layer):
def
forward
(
self
,
inputs
):
conv
=
self
.
_deconv
(
inputs
)
conv
=
fluid
.
layers
.
pad2d
(
conv
,
paddings
=
self
.
outpadding
,
mode
=
'constant'
,
pad_
value
=
0.0
tmp_pad
=
paddle
.
nn
.
Pad2D
(
padding
=
self
.
outpadding
,
mode
=
'constant'
,
value
=
0.0
)
conv
=
tmp_pad
(
conv
)
if
self
.
norm
:
conv
=
self
.
bn
(
conv
)
...
...
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @
e29c50c2
...
...
@@ -3502,23 +3502,15 @@ class TestBook(LayerTest):
input
=
self
.
_get_data
(
name
=
"input"
,
shape
=
[
3
,
100
,
100
],
dtype
=
"float32"
)
paddings
=
layers
.
fill_constant
(
shape
=
[
4
],
dtype
=
'int32'
,
value
=
1
)
out
=
layers
.
pad2d
(
input
,
paddings
=
[
1
,
2
,
3
,
4
],
mode
=
'reflect'
,
data_format
=
'NCHW'
,
name
=
"shape"
,
)
out_1
=
layers
.
pad2d
(
input
,
paddings
=
paddings
,
tmp_pad
=
paddle
.
nn
.
Pad2D
(
padding
=
[
1
,
2
,
3
,
4
],
mode
=
'reflect'
,
data_format
=
'NCHW'
,
name
=
"shape"
,
)
out
=
tmp_pad
(
input
)
return
out
return
out_1
def
make_prelu
(
self
):
with
program_guard
(
...
...
python/paddle/fluid/tests/unittests/test_pad2d_op.py
浏览文件 @
e29c50c2
...
...
@@ -12,11 +12,9 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
import
paddle.fluid
as
fluid
from
paddle.fluid
import
Program
,
program_guard
import
unittest
class
TestPad2dOp
(
OpTest
):
...
...
@@ -138,21 +136,5 @@ class TestCase7(TestPad2dOp):
self
.
variable_paddings
=
True
class
TestPad2dOpError
(
unittest
.
TestCase
):
def
test_errors
(
self
):
with
program_guard
(
Program
(),
Program
()):
input_data
=
np
.
random
.
random
((
2
,
2
,
2
,
2
)).
astype
(
"float32"
)
def
test_Variable
():
fluid
.
layers
.
pad2d
(
input
=
input_data
,
paddings
=
[
1
,
1
,
1
,
1
])
self
.
assertRaises
(
TypeError
,
test_Variable
)
data
=
fluid
.
data
(
name
=
'data'
,
shape
=
[
None
,
3
,
20
,
20
],
dtype
=
'float16'
)
fluid
.
layers
.
pad2d
(
input
=
data
,
paddings
=
[
1
,
1
,
1
,
1
])
if
__name__
==
'__main__'
:
unittest
.
main
()
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