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c4eb5d03
编写于
12月 22, 2020
作者:
C
ceci3
提交者:
GitHub
12月 22, 2020
浏览文件
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电子邮件补丁
差异文件
fix unittest timeout (#29820)
上级
c1797c88
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
143 addition
and
78 deletion
+143
-78
python/paddle/fluid/tests/unittests/test_mul_nn_grad.py
python/paddle/fluid/tests/unittests/test_mul_nn_grad.py
+143
-0
python/paddle/fluid/tests/unittests/test_nn_grad.py
python/paddle/fluid/tests/unittests/test_nn_grad.py
+0
-78
未找到文件。
python/paddle/fluid/tests/unittests/test_mul_nn_grad.py
0 → 100644
浏览文件 @
c4eb5d03
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from
__future__
import
print_function
import
unittest
import
numpy
as
np
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.layers
as
layers
import
paddle.fluid.core
as
core
import
gradient_checker
from
decorator_helper
import
prog_scope
paddle
.
enable_static
()
class
TestMulGradCheck
(
unittest
.
TestCase
):
@
prog_scope
()
def
func
(
self
,
place
):
prog
=
fluid
.
Program
()
with
fluid
.
program_guard
(
prog
):
x
=
layers
.
create_parameter
(
dtype
=
"float64"
,
shape
=
[
2
,
8
],
name
=
'x'
)
y
=
layers
.
create_parameter
(
dtype
=
"float64"
,
shape
=
[
8
,
4
],
name
=
'y'
)
z
=
layers
.
mul
(
x
=
x
,
y
=
y
)
gradient_checker
.
grad_check
([
x
,
y
],
z
,
place
=
place
)
def
test_grad
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
fluid
.
CUDAPlace
(
0
))
for
p
in
places
:
self
.
func
(
p
)
class
TestMulDoubleGradCheck
(
unittest
.
TestCase
):
@
prog_scope
()
def
func
(
self
,
place
):
# the shape of input variable should be clearly specified, not inlcude -1.
x_shape
=
[
7
,
11
]
y_shape
=
[
11
,
9
]
eps
=
0.005
dtype
=
np
.
float64
x
=
layers
.
data
(
'x'
,
x_shape
,
False
,
dtype
)
x
.
persistable
=
True
y
=
layers
.
data
(
'y'
,
y_shape
,
False
,
dtype
)
y
.
persistable
=
True
out
=
layers
.
mul
(
x
,
y
)
x_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
x_shape
).
astype
(
dtype
)
y_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
y_shape
).
astype
(
dtype
)
gradient_checker
.
double_grad_check
(
[
x
,
y
],
out
,
x_init
=
[
x_arr
,
y_arr
],
place
=
place
,
eps
=
eps
)
def
test_grad
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
fluid
.
CUDAPlace
(
0
))
for
p
in
places
:
self
.
func
(
p
)
class
TestMatmulDoubleGradCheck
(
unittest
.
TestCase
):
def
setUp
(
self
):
self
.
init_test
()
def
init_test
(
self
):
self
.
x_shape
=
[
2
]
self
.
y_shape
=
[
2
]
self
.
transpose_x
=
False
self
.
transpose_y
=
False
@
prog_scope
()
def
func
(
self
,
place
):
eps
=
0.005
dtype
=
np
.
float64
typename
=
"float64"
x
=
layers
.
create_parameter
(
dtype
=
typename
,
shape
=
self
.
x_shape
,
name
=
'x'
)
y
=
layers
.
create_parameter
(
dtype
=
typename
,
shape
=
self
.
y_shape
,
name
=
'y'
)
out
=
layers
.
matmul
(
x
,
y
,
self
.
transpose_x
,
self
.
transpose_y
,
name
=
'out'
)
x_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
self
.
x_shape
).
astype
(
dtype
)
y_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
self
.
y_shape
).
astype
(
dtype
)
gradient_checker
.
double_grad_check
(
[
x
,
y
],
out
,
x_init
=
[
x_arr
,
y_arr
],
place
=
place
,
eps
=
eps
)
def
test_grad
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
fluid
.
CUDAPlace
(
0
))
for
p
in
places
:
self
.
func
(
p
)
def
TestMatmulDoubleGradCheckCase1
(
TestMatmulDoubleGradCheck
):
def
init_test
(
self
):
self
.
x_shape
=
[
2
,
3
]
self
.
y_shape
=
[
3
,
2
]
self
.
transpose_x
=
True
self
.
transpose_y
=
True
def
TestMatmulDoubleGradCheckCase2
(
TestMatmulDoubleGradCheck
):
def
init_test
(
self
):
self
.
x_shape
=
[
2
,
4
,
3
]
self
.
y_shape
=
[
2
,
4
,
5
]
self
.
transpose_x
=
True
self
.
transpose_y
=
False
def
TestMatmulDoubleGradCheckCase3
(
TestMatmulDoubleGradCheck
):
def
init_test
(
self
):
self
.
x_shape
=
[
2
,
3
,
4
,
5
]
self
.
y_shape
=
[
2
,
3
,
3
,
5
]
self
.
transpose_x
=
False
self
.
transpose_y
=
True
def
TestMatmulDoubleGradCheckCase4
(
TestMatmulDoubleGradCheck
):
def
init_test
(
self
):
self
.
x_shape
=
[
2
,
3
,
4
]
self
.
y_shape
=
[
4
,
3
]
self
.
transpose_x
=
False
self
.
transpose_y
=
False
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_nn_grad.py
浏览文件 @
c4eb5d03
...
...
@@ -26,24 +26,6 @@ from decorator_helper import prog_scope
paddle
.
enable_static
()
class
TestMulGradCheck
(
unittest
.
TestCase
):
@
prog_scope
()
def
func
(
self
,
place
):
prog
=
fluid
.
Program
()
with
fluid
.
program_guard
(
prog
):
x
=
layers
.
create_parameter
(
dtype
=
"float64"
,
shape
=
[
2
,
8
],
name
=
'x'
)
y
=
layers
.
create_parameter
(
dtype
=
"float64"
,
shape
=
[
8
,
4
],
name
=
'y'
)
z
=
layers
.
mul
(
x
=
x
,
y
=
y
)
gradient_checker
.
grad_check
([
x
,
y
],
z
,
place
=
place
)
def
test_grad
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
fluid
.
CUDAPlace
(
0
))
for
p
in
places
:
self
.
func
(
p
)
class
TestSliceOpDoubleGradCheck
(
unittest
.
TestCase
):
def
func
(
self
,
place
):
self
.
config
()
...
...
@@ -125,66 +107,6 @@ class TestReduceSumWithDimDoubleGradCheck(unittest.TestCase):
self
.
func
(
p
)
class
TestMulDoubleGradCheck
(
unittest
.
TestCase
):
@
prog_scope
()
def
func
(
self
,
place
):
# the shape of input variable should be clearly specified, not inlcude -1.
x_shape
=
[
7
,
11
]
y_shape
=
[
11
,
9
]
eps
=
0.005
dtype
=
np
.
float64
x
=
layers
.
data
(
'x'
,
x_shape
,
False
,
dtype
)
x
.
persistable
=
True
y
=
layers
.
data
(
'y'
,
y_shape
,
False
,
dtype
)
y
.
persistable
=
True
out
=
layers
.
mul
(
x
,
y
)
x_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
x_shape
).
astype
(
dtype
)
y_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
y_shape
).
astype
(
dtype
)
gradient_checker
.
double_grad_check
(
[
x
,
y
],
out
,
x_init
=
[
x_arr
,
y_arr
],
place
=
place
,
eps
=
eps
)
def
test_grad
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
fluid
.
CUDAPlace
(
0
))
for
p
in
places
:
self
.
func
(
p
)
class
TestMatmulDoubleGradCheck
(
unittest
.
TestCase
):
@
prog_scope
()
def
func
(
self
,
place
):
eps
=
0.005
x_shapes
=
[[
2
],
[
2
,
3
],
[
2
,
4
,
3
],
[
2
,
3
,
4
,
5
],
[
2
,
3
,
4
]]
y_shapes
=
[[
2
],
[
3
,
2
],
[
2
,
4
,
5
],
[
2
,
3
,
3
,
5
],
[
4
,
3
]]
transpose_xs
=
[
False
,
True
,
True
,
False
,
False
]
transpose_ys
=
[
False
,
True
,
False
,
True
,
False
]
dtype
=
np
.
float64
typename
=
"float64"
for
i
,
(
x_shape
,
y_shape
,
transpose_x
,
transpose_y
)
\
in
enumerate
(
zip
(
x_shapes
,
y_shapes
,
transpose_xs
,
transpose_ys
)):
x
=
layers
.
create_parameter
(
dtype
=
typename
,
shape
=
x_shape
,
name
=
'x{}'
.
format
(
i
))
y
=
layers
.
create_parameter
(
dtype
=
typename
,
shape
=
y_shape
,
name
=
'y{}'
.
format
(
i
))
out
=
layers
.
matmul
(
x
,
y
,
transpose_x
,
transpose_y
,
name
=
'out{}'
.
format
(
i
))
x_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
x_shape
).
astype
(
dtype
)
y_arr
=
np
.
random
.
uniform
(
-
1
,
1
,
y_shape
).
astype
(
dtype
)
gradient_checker
.
double_grad_check
(
[
x
,
y
],
out
,
x_init
=
[
x_arr
,
y_arr
],
place
=
place
,
eps
=
eps
)
def
test_grad
(
self
):
places
=
[
fluid
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
fluid
.
CUDAPlace
(
0
))
for
p
in
places
:
self
.
func
(
p
)
class
TestReshapeDoubleGradCheck
(
unittest
.
TestCase
):
@
prog_scope
()
def
func
(
self
,
place
):
...
...
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