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体验新版 GitCode,发现更多精彩内容 >>
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提交
1f24c84a
编写于
6月 24, 2020
作者:
F
FDInSky
提交者:
GitHub
6月 24, 2020
浏览文件
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电子邮件补丁
差异文件
fix conv3d_transpose_test timeout error (#25004)
* test=develop fix conv3d_transpose_test error
上级
bd0b38e6
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
231 addition
and
198 deletion
+231
-198
python/paddle/fluid/tests/unittests/test_conv3d_transpose_op.py
.../paddle/fluid/tests/unittests/test_conv3d_transpose_op.py
+16
-198
python/paddle/fluid/tests/unittests/test_conv3d_transpose_part2_op.py
...e/fluid/tests/unittests/test_conv3d_transpose_part2_op.py
+215
-0
未找到文件。
python/paddle/fluid/tests/unittests/test_conv3d_transpose_op.py
浏览文件 @
1f24c84a
...
...
@@ -111,6 +111,8 @@ class TestConv3dTransposeOp(OpTest):
def
setUp
(
self
):
# init as conv transpose
self
.
use_cudnn
=
False
self
.
check_no_input
=
False
self
.
check_no_filter
=
False
self
.
data_format
=
'NCHW'
self
.
pad
=
[
0
,
0
,
0
]
self
.
padding_algorithm
=
"EXPLICIT"
...
...
@@ -163,7 +165,7 @@ class TestConv3dTransposeOp(OpTest):
'Output'
,
max_relative_error
=
0.03
,
no_grad_set
=
set
([
'Filter'
]))
el
se
:
el
if
self
.
check_no_filter
:
self
.
check_grad
(
[
'Input'
],
'Output'
,
...
...
@@ -178,7 +180,7 @@ class TestConv3dTransposeOp(OpTest):
'Output'
,
max_relative_error
=
0.03
,
no_grad_set
=
set
([
'Input'
]))
el
se
:
el
if
self
.
check_no_input
:
self
.
check_grad
(
[
'Filter'
],
'Output'
,
...
...
@@ -200,6 +202,7 @@ class TestConv3dTransposeOp(OpTest):
class
TestWithSymmetricPad
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
check_no_input
=
True
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
...
...
@@ -242,26 +245,27 @@ class TestWithVALIDPad(TestConv3dTransposeOp):
self
.
padding_algorithm
=
'VALID'
class
TestWith
Groups
(
TestConv3dTransposeOp
):
class
TestWith
Stride
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
check_no_filter
=
True
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
stride
=
[
2
,
2
,
2
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
2
self
.
input_size
=
[
2
,
4
,
5
,
5
,
5
]
# NC
HW
self
.
groups
=
1
self
.
input_size
=
[
2
,
3
,
5
,
5
,
5
]
# NCD
HW
f_c
=
self
.
input_size
[
1
]
self
.
filter_size
=
[
f_c
,
3
,
3
,
3
,
3
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
class
TestWith
Stride
(
TestConv3dTransposeOp
):
class
TestWith
Groups
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
2
,
2
,
2
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
3
,
5
,
5
,
5
]
# NCD
HW
self
.
groups
=
2
self
.
input_size
=
[
2
,
4
,
5
,
5
,
5
]
# NC
HW
f_c
=
self
.
input_size
[
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
filter_size
=
[
f_c
,
3
,
3
,
3
,
3
]
class
TestWithDilation
(
TestConv3dTransposeOp
):
...
...
@@ -287,66 +291,6 @@ class Test_NHWC(TestConv3dTransposeOp):
self
.
data_format
=
'NHWC'
class
TestWithSymmetricPad_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
5
,
5
,
5
,
3
]
# NDHWC
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestWithAsymmetricPad_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
0
,
1
,
0
,
1
,
2
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
5
,
5
,
5
,
3
]
# NDHWC
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestWithGroups_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
2
self
.
input_size
=
[
2
,
5
,
5
,
5
,
4
]
# NDHWC
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
3
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestWithStride_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
2
,
2
,
2
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
5
,
5
,
5
,
3
]
# NCDHW
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestWithDilation_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
2
,
2
,
2
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
5
,
5
,
5
,
3
]
# NCDHW
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
# ------------ test_cudnn ------------
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
...
...
@@ -563,131 +507,5 @@ class TestCUDNNWithGroups_NHWC(TestWithGroups):
self
.
op_type
=
"conv3d_transpose"
class
TestConv3dTransposeAPI
(
unittest
.
TestCase
):
def
test_case1
(
self
):
data1
=
fluid
.
layers
.
data
(
name
=
'data1'
,
shape
=
[
3
,
5
,
5
,
5
],
dtype
=
'float32'
)
data2
=
fluid
.
layers
.
data
(
name
=
'data2'
,
shape
=
[
5
,
5
,
5
,
3
],
dtype
=
'float32'
)
out1
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data1
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
data_format
=
'NCDHW'
)
out2
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
data_format
=
'NDHWC'
)
out3
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data1
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
[[
0
,
0
],
[
0
,
0
],
[
1
,
1
],
[
0
,
0
],
[
1
,
1
]],
data_format
=
'NCDHW'
)
out4
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
3
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
[[
0
,
0
],
[
0
,
0
],
[
1
,
1
],
[
1
,
2
],
[
0
,
0
]],
data_format
=
'NDHWC'
)
out5
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
'SAME'
,
data_format
=
'NCDHW'
)
out6
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
'VALID'
,
data_format
=
'NDHWC'
)
out7
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
1
,
num_filters
=
6
,
output_size
=
[
7
,
7
,
7
],
padding
=
[
0
,
0
,
0
],
data_format
=
'NDHWC'
)
data1_np
=
np
.
random
.
random
((
2
,
3
,
5
,
5
,
5
)).
astype
(
"float32"
)
data2_np
=
np
.
random
.
random
((
2
,
5
,
5
,
5
,
3
)).
astype
(
"float32"
)
if
core
.
is_compiled_with_cuda
():
place
=
core
.
CUDAPlace
(
0
)
else
:
place
=
core
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
())
results
=
exe
.
run
(
fluid
.
default_main_program
(),
feed
=
{
"data1"
:
data1_np
,
"data2"
:
data2_np
},
fetch_list
=
[
out1
,
out2
,
out3
,
out4
,
out5
,
out6
,
out7
],
return_numpy
=
True
)
self
.
assertIsNotNone
(
results
[
0
])
self
.
assertIsNotNone
(
results
[
1
])
self
.
assertIsNotNone
(
results
[
2
])
self
.
assertIsNotNone
(
results
[
3
])
self
.
assertIsNotNone
(
results
[
4
])
self
.
assertIsNotNone
(
results
[
5
])
self
.
assertIsNotNone
(
results
[
6
])
class
TestConv3dTransposeOpException
(
unittest
.
TestCase
):
def
test_exception
(
self
):
data
=
fluid
.
layers
.
data
(
name
=
'data'
,
shape
=
[
3
,
5
,
5
,
5
],
dtype
=
"float32"
)
def
attr_data_format
():
out
=
fluid
.
layers
.
conv2d_transpose
(
input
=
data
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
data_format
=
"NCDW"
)
self
.
assertRaises
(
ValueError
,
attr_data_format
)
def
attr_padding_str
():
out
=
fluid
.
layers
.
conv2d_transpose
(
input
=
data
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
'Vald'
)
self
.
assertRaises
(
ValueError
,
attr_padding_str
)
def
attr_padding_list
():
out
=
fluid
.
layers
.
conv2d_transpose
(
input
=
data
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
[[
1
,
1
],
[
1
,
1
],
[
0
,
0
],
[
0
,
0
],
[
1
,
1
]])
self
.
assertRaises
(
ValueError
,
attr_padding_list
)
def
attr_padding_with_data_format
():
out
=
fluid
.
layers
.
conv2d_transpose
(
input
=
data
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
[[
1
,
1
],
[
0
,
0
],
[
0
,
0
],
[
1
,
0
],
[
1
,
1
]],
data_format
=
'NDHWC'
)
self
.
assertRaises
(
ValueError
,
attr_padding_with_data_format
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_conv3d_transpose_part2_op.py
0 → 100644
浏览文件 @
1f24c84a
# Copyright (c) 2018 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.fluid.core
as
core
import
paddle.fluid
as
fluid
from
op_test
import
OpTest
from
test_conv3d_transpose_op
import
conv3dtranspose_forward_naive
,
TestConv3dTransposeOp
class
TestWithSymmetricPad_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
5
,
5
,
5
,
3
]
# NDHWC
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestWithAsymmetricPad_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
0
,
1
,
0
,
1
,
2
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
5
,
5
,
5
,
3
]
# NDHWC
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestWithGroups_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
check_no_filter
=
True
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
2
self
.
input_size
=
[
2
,
5
,
5
,
5
,
4
]
# NDHWC
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
3
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestWithStride_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
2
,
2
,
2
]
self
.
dilations
=
[
1
,
1
,
1
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
5
,
5
,
5
,
3
]
# NCDHW
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestWithDilation_NHWC
(
TestConv3dTransposeOp
):
def
init_test_case
(
self
):
self
.
check_no_input
=
True
self
.
pad
=
[
1
,
1
,
1
]
self
.
stride
=
[
1
,
1
,
1
]
self
.
dilations
=
[
2
,
2
,
2
]
self
.
groups
=
1
self
.
input_size
=
[
2
,
5
,
5
,
5
,
3
]
# NCDHW
f_c
=
self
.
input_size
[
-
1
]
self
.
filter_size
=
[
f_c
,
6
,
3
,
3
,
3
]
self
.
data_format
=
'NHWC'
class
TestConv3dTransposeAPI
(
unittest
.
TestCase
):
def
test_case1
(
self
):
data1
=
fluid
.
layers
.
data
(
name
=
'data1'
,
shape
=
[
3
,
5
,
5
,
5
],
dtype
=
'float32'
)
data2
=
fluid
.
layers
.
data
(
name
=
'data2'
,
shape
=
[
5
,
5
,
5
,
3
],
dtype
=
'float32'
)
out1
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data1
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
data_format
=
'NCDHW'
)
out2
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
data_format
=
'NDHWC'
)
out3
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data1
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
[[
0
,
0
],
[
0
,
0
],
[
1
,
1
],
[
0
,
0
],
[
1
,
1
]],
data_format
=
'NCDHW'
)
out4
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
3
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
[[
0
,
0
],
[
0
,
0
],
[
1
,
1
],
[
1
,
2
],
[
0
,
0
]],
data_format
=
'NDHWC'
)
out5
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
'SAME'
,
data_format
=
'NCDHW'
)
out6
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
'VALID'
,
data_format
=
'NDHWC'
)
out7
=
fluid
.
layers
.
conv3d_transpose
(
input
=
data2
,
groups
=
1
,
num_filters
=
6
,
output_size
=
[
7
,
7
,
7
],
padding
=
[
0
,
0
,
0
],
data_format
=
'NDHWC'
)
data1_np
=
np
.
random
.
random
((
2
,
3
,
5
,
5
,
5
)).
astype
(
"float32"
)
data2_np
=
np
.
random
.
random
((
2
,
5
,
5
,
5
,
3
)).
astype
(
"float32"
)
if
core
.
is_compiled_with_cuda
():
place
=
core
.
CUDAPlace
(
0
)
else
:
place
=
core
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
())
results
=
exe
.
run
(
fluid
.
default_main_program
(),
feed
=
{
"data1"
:
data1_np
,
"data2"
:
data2_np
},
fetch_list
=
[
out1
,
out2
,
out3
,
out4
,
out5
,
out6
,
out7
],
return_numpy
=
True
)
self
.
assertIsNotNone
(
results
[
0
])
self
.
assertIsNotNone
(
results
[
1
])
self
.
assertIsNotNone
(
results
[
2
])
self
.
assertIsNotNone
(
results
[
3
])
self
.
assertIsNotNone
(
results
[
4
])
self
.
assertIsNotNone
(
results
[
5
])
self
.
assertIsNotNone
(
results
[
6
])
class
TestConv3dTransposeOpException
(
unittest
.
TestCase
):
def
test_exception
(
self
):
data
=
fluid
.
layers
.
data
(
name
=
'data'
,
shape
=
[
3
,
5
,
5
,
5
],
dtype
=
"float32"
)
def
attr_data_format
():
out
=
fluid
.
layers
.
conv2d_transpose
(
input
=
data
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
data_format
=
"NCDW"
)
self
.
assertRaises
(
ValueError
,
attr_data_format
)
def
attr_padding_str
():
out
=
fluid
.
layers
.
conv2d_transpose
(
input
=
data
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
'Vald'
)
self
.
assertRaises
(
ValueError
,
attr_padding_str
)
def
attr_padding_list
():
out
=
fluid
.
layers
.
conv2d_transpose
(
input
=
data
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
[[
1
,
1
],
[
1
,
1
],
[
0
,
0
],
[
0
,
0
],
[
1
,
1
]])
self
.
assertRaises
(
ValueError
,
attr_padding_list
)
def
attr_padding_with_data_format
():
out
=
fluid
.
layers
.
conv2d_transpose
(
input
=
data
,
groups
=
1
,
num_filters
=
6
,
filter_size
=
3
,
padding
=
[[
1
,
1
],
[
0
,
0
],
[
0
,
0
],
[
1
,
0
],
[
1
,
1
]],
data_format
=
'NDHWC'
)
self
.
assertRaises
(
ValueError
,
attr_padding_with_data_format
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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