Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
Paddle
提交
e5c167dc
P
Paddle
项目概览
PaddlePaddle
/
Paddle
大约 1 年 前同步成功
通知
2299
Star
20931
Fork
5422
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
1423
列表
看板
标记
里程碑
合并请求
543
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
1,423
Issue
1,423
列表
看板
标记
里程碑
合并请求
543
合并请求
543
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
提交
e5c167dc
编写于
10月 27, 2017
作者:
C
chengduoZH
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix unit test
上级
0ab012cf
变更
2
显示空白变更内容
内联
并排
Showing
2 changed file
with
140 addition
and
161 deletion
+140
-161
python/paddle/v2/framework/tests/test_pool2d_cudnn_op.py
python/paddle/v2/framework/tests/test_pool2d_cudnn_op.py
+0
-144
python/paddle/v2/framework/tests/test_pool2d_op.py
python/paddle/v2/framework/tests/test_pool2d_op.py
+140
-17
未找到文件。
python/paddle/v2/framework/tests/test_pool2d_cudnn_op.py
已删除
100644 → 0
浏览文件 @
0ab012cf
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
def
max_pool2D_forward_naive
(
x
,
ksize
,
strides
,
paddings
=
[
0
,
0
],
global_pool
=
0
):
N
,
C
,
H
,
W
=
x
.
shape
if
global_pool
==
1
:
ksize
=
[
H
,
W
]
H_out
=
(
H
-
ksize
[
0
]
+
2
*
paddings
[
0
])
/
strides
[
0
]
+
1
W_out
=
(
W
-
ksize
[
1
]
+
2
*
paddings
[
1
])
/
strides
[
1
]
+
1
out
=
np
.
zeros
((
N
,
C
,
H_out
,
W_out
))
for
i
in
xrange
(
H_out
):
for
j
in
xrange
(
W_out
):
r_start
=
np
.
max
((
i
*
strides
[
0
]
-
paddings
[
0
],
0
))
r_end
=
np
.
min
((
i
*
strides
[
0
]
+
ksize
[
0
]
-
paddings
[
0
],
H
))
c_start
=
np
.
max
((
j
*
strides
[
1
]
-
paddings
[
1
],
0
))
c_end
=
np
.
min
((
j
*
strides
[
1
]
+
ksize
[
1
]
-
paddings
[
1
],
W
))
x_masked
=
x
[:,
:,
r_start
:
r_end
,
c_start
:
c_end
]
out
[:,
:,
i
,
j
]
=
np
.
max
(
x_masked
,
axis
=
(
2
,
3
))
return
out
def
avg_pool2D_forward_naive
(
x
,
ksize
,
strides
,
paddings
=
[
0
,
0
],
global_pool
=
0
):
N
,
C
,
H
,
W
=
x
.
shape
if
global_pool
==
1
:
ksize
=
[
H
,
W
]
H_out
=
(
H
-
ksize
[
0
]
+
2
*
paddings
[
0
])
/
strides
[
0
]
+
1
W_out
=
(
W
-
ksize
[
1
]
+
2
*
paddings
[
1
])
/
strides
[
1
]
+
1
out
=
np
.
zeros
((
N
,
C
,
H_out
,
W_out
))
for
i
in
xrange
(
H_out
):
for
j
in
xrange
(
W_out
):
r_start
=
np
.
max
((
i
*
strides
[
0
]
-
paddings
[
0
],
0
))
r_end
=
np
.
min
((
i
*
strides
[
0
]
+
ksize
[
0
]
-
paddings
[
0
],
H
))
c_start
=
np
.
max
((
j
*
strides
[
1
]
-
paddings
[
1
],
0
))
c_end
=
np
.
min
((
j
*
strides
[
1
]
+
ksize
[
1
]
-
paddings
[
1
],
W
))
x_masked
=
x
[:,
:,
r_start
:
r_end
,
c_start
:
c_end
]
out
[:,
:,
i
,
j
]
=
np
.
sum
(
x_masked
,
axis
=
(
2
,
3
))
/
(
(
r_end
-
r_start
)
*
(
c_end
-
c_start
))
return
out
class
TestPool2d_cudnn_Op
(
OpTest
):
def
setUp
(
self
):
self
.
initTestCase
()
input
=
np
.
random
.
random
(
self
.
shape
).
astype
(
"float32"
)
output
=
self
.
pool2D_forward_naive
(
input
,
self
.
ksize
,
self
.
strides
,
self
.
paddings
,
self
.
global_pool
)
self
.
inputs
=
{
'X'
:
input
}
self
.
attrs
=
{
'strides'
:
self
.
strides
,
'paddings'
:
self
.
paddings
,
'ksize'
:
self
.
ksize
,
'poolingType'
:
self
.
pool_type
,
'globalPooling'
:
self
.
global_pool
,
}
self
.
outputs
=
{
'Out'
:
output
}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
if
self
.
pool_type
!=
"max"
:
self
.
check_grad
(
set
([
'X'
]),
'Out'
,
max_relative_error
=
0.07
)
def
initTestCase
(
self
):
self
.
global_pool
=
True
self
.
op_type
=
"pool2d_cudnn"
self
.
pool_type
=
"avg"
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
5
,
5
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
class
TestCase1
(
TestPool2d_cudnn_Op
):
def
initTestCase
(
self
):
self
.
global_pool
=
False
self
.
op_type
=
"pool2d_cudnn"
self
.
pool_type
=
"avg"
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
class
TestCase2
(
TestPool2d_cudnn_Op
):
def
initTestCase
(
self
):
self
.
global_pool
=
False
self
.
op_type
=
"pool2d_cudnn"
self
.
pool_type
=
"avg"
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
1
,
1
]
class
TestCase3
(
TestPool2d_cudnn_Op
):
def
initTestCase
(
self
):
self
.
global_pool
=
True
self
.
op_type
=
"pool2d_cudnn"
self
.
pool_type
=
"max"
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
5
,
5
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
class
TestCase4
(
TestPool2d_cudnn_Op
):
def
initTestCase
(
self
):
self
.
global_pool
=
False
self
.
op_type
=
"pool2d_cudnn"
self
.
pool_type
=
"max"
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
class
TestCase5
(
TestPool2d_cudnn_Op
):
def
initTestCase
(
self
):
self
.
global_pool
=
False
self
.
op_type
=
"pool2d_cudnn"
self
.
pool_type
=
"max"
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
1
,
1
]
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/v2/framework/tests/test_pool2d_op.py
浏览文件 @
e5c167dc
...
...
@@ -46,7 +46,9 @@ def avg_pool2D_forward_naive(x, ksize, strides, paddings=[0, 0], global_pool=0):
class
TestPool2d_Op
(
OpTest
):
def
setUp
(
self
):
self
.
initTestCase
()
self
.
init_test_case
()
self
.
init_op_type
()
self
.
init_pool_type
()
input
=
np
.
random
.
random
(
self
.
shape
).
astype
(
"float32"
)
output
=
self
.
pool2D_forward_naive
(
input
,
self
.
ksize
,
self
.
strides
,
self
.
paddings
,
self
.
global_pool
)
...
...
@@ -69,76 +71,197 @@ class TestPool2d_Op(OpTest):
if
self
.
pool_type
!=
"max"
:
self
.
check_grad
(
set
([
'X'
]),
'Out'
,
max_relative_error
=
0.07
)
def
init
TestC
ase
(
self
):
def
init
_test_c
ase
(
self
):
self
.
global_pool
=
True
self
.
op_type
=
"pool2d"
self
.
pool_type
=
"avg"
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
5
,
5
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d"
def
init_pool_type
(
self
):
self
.
pool_type
=
"avg"
class
TestCase1
(
TestPool2d_Op
):
def
init
TestC
ase
(
self
):
def
init
_test_c
ase
(
self
):
self
.
global_pool
=
False
self
.
op_type
=
"pool2d"
self
.
pool_type
=
"avg"
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d"
def
init_pool_type
(
self
):
self
.
pool_type
=
"avg"
class
TestCase2
(
TestPool2d_Op
):
def
init
TestC
ase
(
self
):
def
init
_test_c
ase
(
self
):
self
.
global_pool
=
False
self
.
op_type
=
"pool2d"
self
.
pool_type
=
"avg"
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
1
,
1
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d"
def
init_pool_type
(
self
):
self
.
pool_type
=
"avg"
class
TestCase3
(
TestPool2d_Op
):
def
init
TestC
ase
(
self
):
def
init
_test_c
ase
(
self
):
self
.
global_pool
=
True
self
.
op_type
=
"pool2d"
self
.
pool_type
=
"max"
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
5
,
5
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d"
def
init_pool_type
(
self
):
self
.
pool_type
=
"max"
class
TestCase4
(
TestPool2d_Op
):
def
init
TestC
ase
(
self
):
def
init
_test_c
ase
(
self
):
self
.
global_pool
=
False
self
.
op_type
=
"pool2d"
self
.
pool_type
=
"max"
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d"
def
init_pool_type
(
self
):
self
.
pool_type
=
"max"
class
TestCase5
(
TestPool2d_Op
):
def
init
TestC
ase
(
self
):
def
init
_test_c
ase
(
self
):
self
.
global_pool
=
False
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
1
,
1
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d"
def
init_pool_type
(
self
):
self
.
pool_type
=
"max"
#--------------------test pool2d_cudnn--------------------
class
TestCaseCudnn1
(
TestPool2d_Op
):
def
init_test_case
(
self
):
self
.
global_pool
=
True
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
5
,
5
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d_cudnn"
def
init_pool_type
(
self
):
self
.
pool_type
=
"avg"
class
TestCaseCudnn2
(
TestPool2d_Op
):
def
init_test_case
(
self
):
self
.
global_pool
=
False
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d_cudnn"
def
init_pool_type
(
self
):
self
.
pool_type
=
"avg"
class
TestCaseCudnn3
(
TestPool2d_Op
):
def
init_test_case
(
self
):
self
.
global_pool
=
False
self
.
pool2D_forward_naive
=
avg_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
1
,
1
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d_cudnn"
def
init_pool_type
(
self
):
self
.
pool_type
=
"avg"
class
TestCaseCudnn4
(
TestPool2d_Op
):
def
init_test_case
(
self
):
self
.
global_pool
=
True
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
5
,
5
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d_cudnn"
def
init_pool_type
(
self
):
self
.
pool_type
=
"max"
class
TestCaseCudnn5
(
TestPool2d_Op
):
def
init_test_case
(
self
):
self
.
global_pool
=
False
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
0
,
0
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d_cudnn"
def
init_pool_type
(
self
):
self
.
pool_type
=
"max"
class
TestCaseCudnn6
(
TestPool2d_Op
):
def
init_test_case
(
self
):
self
.
global_pool
=
False
self
.
pool2D_forward_naive
=
max_pool2D_forward_naive
self
.
shape
=
[
2
,
3
,
7
,
7
]
self
.
ksize
=
[
3
,
3
]
self
.
strides
=
[
1
,
1
]
self
.
paddings
=
[
1
,
1
]
def
init_op_type
(
self
):
self
.
op_type
=
"pool2d_cudnn"
def
init_pool_type
(
self
):
self
.
pool_type
=
"max"
if
__name__
==
'__main__'
:
unittest
.
main
()
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录