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体验新版 GitCode,发现更多精彩内容 >>
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519cc7b0
编写于
6月 01, 2021
作者:
W
wangguanzhong
提交者:
GitHub
6月 01, 2021
浏览文件
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电子邮件补丁
差异文件
split conv2d_op unittest (#33231)
上级
06c63ca0
变更
4
展开全部
隐藏空白更改
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并排
Showing
4 changed file
with
741 addition
and
679 deletion
+741
-679
python/paddle/fluid/tests/unittests/CMakeLists.txt
python/paddle/fluid/tests/unittests/CMakeLists.txt
+4
-0
python/paddle/fluid/tests/unittests/test_conv2d_api.py
python/paddle/fluid/tests/unittests/test_conv2d_api.py
+360
-0
python/paddle/fluid/tests/unittests/test_conv2d_op.py
python/paddle/fluid/tests/unittests/test_conv2d_op.py
+0
-679
python/paddle/fluid/tests/unittests/test_conv2d_op_depthwise_conv.py
...le/fluid/tests/unittests/test_conv2d_op_depthwise_conv.py
+377
-0
未找到文件。
python/paddle/fluid/tests/unittests/CMakeLists.txt
浏览文件 @
519cc7b0
...
...
@@ -477,6 +477,8 @@ py_test_modules(test_imperative_static_runner_mnist MODULES test_imperative_stat
py_test_modules
(
test_imperative_static_runner_while MODULES test_imperative_static_runner_while ENVS
FLAGS_cudnn_deterministic=1
)
set_tests_properties
(
test_conv2d_op PROPERTIES LABELS
"RUN_TYPE=EXCLUSIVE"
)
set_tests_properties
(
test_conv2d_op_depthwise_conv PROPERTIES LABELS
"RUN_TYPE=EXCLUSIVE"
)
set_tests_properties
(
test_conv2d_api PROPERTIES LABELS
"RUN_TYPE=EXCLUSIVE"
)
if
(
WITH_DISTRIBUTE
)
# FIXME(typhoonzero): add these tests back
list
(
REMOVE_ITEM DIST_TEST_OPS
"test_dist_transformer"
)
...
...
@@ -838,6 +840,8 @@ set_tests_properties(test_bilinear_interp_op PROPERTIES TIMEOUT 120)
set_tests_properties
(
test_decoupled_py_reader PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_fuse_bn_act_pass PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_conv2d_op PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_conv2d_op_depthwise_conv PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_conv2d_api PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_elementwise_mul_op PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_cyclic_cifar_dataset PROPERTIES TIMEOUT 120
)
set_tests_properties
(
test_fuse_all_reduce_pass PROPERTIES TIMEOUT 120
)
...
...
python/paddle/fluid/tests/unittests/test_conv2d_api.py
0 → 100644
浏览文件 @
519cc7b0
# Copyright (c) 2021 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
paddle
.
enable_static
()
import
paddle.fluid.core
as
core
import
paddle.fluid
as
fluid
from
op_test
import
OpTest
from
paddle.fluid
import
Program
,
program_guard
class
TestConv2DAPI
(
unittest
.
TestCase
):
def
test_api
(
self
):
input_NHWC
=
fluid
.
layers
.
data
(
name
=
"input_NHWC"
,
shape
=
[
2
,
5
,
5
,
3
],
append_batch_size
=
False
,
dtype
=
"float32"
)
input_NCHW
=
fluid
.
layers
.
data
(
name
=
"input_NCHW"
,
shape
=
[
2
,
3
,
5
,
5
],
append_batch_size
=
False
,
dtype
=
"float32"
)
fluid
.
layers
.
conv2d
(
input
=
input_NHWC
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
0
,
dilation
=
[
1
,
1
],
groups
=
1
,
data_format
=
"NCHW"
)
fluid
.
layers
.
conv2d
(
input
=
input_NCHW
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
[
1
,
2
,
1
,
0
],
dilation
=
[
1
,
1
],
groups
=
1
,
data_format
=
"NCHW"
)
fluid
.
layers
.
conv2d
(
input
=
input_NCHW
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
[[
0
,
0
],
[
0
,
0
],
[
1
,
1
],
[
1
,
1
]],
dilation
=
[
1
,
1
],
groups
=
1
,
data_format
=
"NCHW"
)
fluid
.
layers
.
conv2d
(
input
=
input_NHWC
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
[[
0
,
0
],
[
1
,
1
],
[
1
,
1
],
[
0
,
0
]],
dilation
=
[
1
,
1
],
groups
=
1
,
data_format
=
"NHWC"
)
fluid
.
layers
.
conv2d
(
input
=
input_NCHW
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
"SAME"
,
dilation
=
[
1
,
1
],
groups
=
1
,
data_format
=
"NCHW"
)
fluid
.
layers
.
conv2d
(
input
=
input_NCHW
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
"VALID"
,
dilation
=
[
1
,
1
],
groups
=
1
,
data_format
=
"NCHW"
)
def
test_depthwise_conv2d
(
self
):
x_var
=
paddle
.
uniform
((
2
,
8
,
8
,
4
),
dtype
=
'float32'
,
min
=-
1.
,
max
=
1.
)
conv
=
paddle
.
nn
.
Conv2D
(
in_channels
=
4
,
out_channels
=
4
,
kernel_size
=
(
3
,
3
),
groups
=
4
,
data_format
=
'NHWC'
)
y_var
=
conv
(
x_var
)
class
TestConv2DAPI_Error
(
unittest
.
TestCase
):
def
test_api
(
self
):
input
=
fluid
.
layers
.
data
(
name
=
"input"
,
shape
=
[
2
,
5
,
5
,
5
],
append_batch_size
=
False
,
dtype
=
"float32"
)
# ValueError: cudnn
def
run_1
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
0
,
dilation
=
[
1
,
1
],
groups
=
1
,
use_cudnn
=
[
0
],
data_format
=
"NCHW"
)
self
.
assertRaises
(
ValueError
,
run_1
)
# ValueError: data_format
def
run_2
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
0
,
dilation
=
[
1
,
1
],
groups
=
1
,
use_cudnn
=
False
,
data_format
=
"NCHWC"
)
self
.
assertRaises
(
ValueError
,
run_2
)
# ValueError: padding
def
run_3
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
"SAMEE"
,
dilation
=
[
1
,
1
],
groups
=
1
,
use_cudnn
=
False
,
data_format
=
"NCHW"
)
self
.
assertRaises
(
ValueError
,
run_3
)
def
run_4
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
[[
0
,
1
],
[
0
,
1
],
[
0
,
1
],
[
0
,
1
]],
dilation
=
[
1
,
1
],
groups
=
1
,
use_cudnn
=
False
,
data_format
=
"NCHW"
)
self
.
assertRaises
(
ValueError
,
run_4
)
def
run_5
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
[[
0
,
1
],
[
0
,
1
],
[
0
,
1
],
[
0
,
1
]],
dilation
=
[
1
,
1
],
groups
=
1
,
use_cudnn
=
False
,
data_format
=
"NHWC"
)
self
.
assertRaises
(
ValueError
,
run_5
)
# ValueError: channel dimmention
x
=
fluid
.
layers
.
data
(
name
=
"x"
,
shape
=
[
2
,
5
,
5
,
-
1
],
append_batch_size
=
False
,
dtype
=
"float32"
)
def
run_6
():
fluid
.
layers
.
conv2d
(
input
=
x
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
0
,
dilation
=
[
1
,
1
],
groups
=
1
,
use_cudnn
=
False
,
data_format
=
"NHWC"
)
self
.
assertRaises
(
ValueError
,
run_6
)
# ValueError: groups
def
run_7
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
3
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
0
,
dilation
=
[
1
,
1
],
groups
=
3
,
use_cudnn
=
False
,
data_format
=
"NHWC"
)
self
.
assertRaises
(
ValueError
,
run_7
)
# ValueError: filter num
def
run_8
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
0
,
filter_size
=
0
,
stride
=
0
,
padding
=
0
,
dilation
=
0
,
groups
=
1
,
use_cudnn
=
False
,
data_format
=
"NCHW"
)
self
.
assertRaises
(
ValueError
,
run_8
)
# ValueError: groups
def
run_9
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
0
,
filter_size
=
0
,
stride
=
0
,
padding
=
0
,
dilation
=
0
,
groups
=
0
,
use_cudnn
=
False
,
data_format
=
"NCHW"
)
self
.
assertRaises
(
ValueError
,
run_9
)
# ValueError: stride
def
run_10
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
1
,
filter_size
=
1
,
stride
=
0
,
padding
=
0
,
dilation
=
0
,
groups
=
1
,
use_cudnn
=
False
,
data_format
=
"NCHW"
)
self
.
assertRaises
(
ValueError
,
run_10
)
def
test_api_with_error_input
(
self
):
input
=
fluid
.
layers
.
data
(
name
=
"error_input"
,
shape
=
[
1
],
append_batch_size
=
False
,
dtype
=
"float32"
)
# ValueError: cudnn
def
run_1
():
fluid
.
layers
.
conv2d
(
input
=
input
,
num_filters
=
0
,
filter_size
=
0
,
stride
=
0
,
padding
=
0
,
dilation
=
0
,
groups
=
0
,
use_cudnn
=
False
,
data_format
=
"NCHW"
)
self
.
assertRaises
(
ValueError
,
run_1
)
# --------- test environment variable ------
@
unittest
.
skipIf
(
not
(
core
.
is_compiled_with_cuda
()
or
core
.
is_compiled_with_rocm
()),
"core is not compiled with CUDA or ROCM"
)
class
TestConv2DEnviron
(
unittest
.
TestCase
):
def
run1
(
self
,
place
):
with
fluid
.
program_guard
(
fluid
.
Program
(),
fluid
.
Program
()):
inputs
=
fluid
.
layers
.
data
(
shape
=
[
2
,
3
,
5
,
5
],
append_batch_size
=
False
,
name
=
"inputs"
,
dtype
=
"float32"
)
result
=
fluid
.
layers
.
conv2d
(
input
=
inputs
,
num_filters
=
4
,
filter_size
=
[
3
,
3
],
stride
=
[
1
,
1
],
padding
=
0
,
dilation
=
[
1
,
1
],
groups
=
1
,
data_format
=
"NCHW"
)
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
())
fetches
=
exe
.
run
(
fluid
.
default_main_program
(),
feed
=
{
"inputs"
:
self
.
input_np
},
fetch_list
=
[
result
])
def
run2
(
self
,
place
):
with
fluid
.
dygraph
.
guard
(
place
):
inputs
=
fluid
.
dygraph
.
to_variable
(
self
.
input_np
)
conv
=
paddle
.
nn
.
Conv2D
(
in_channels
=
3
,
out_channels
=
4
,
kernel_size
=
(
3
,
3
),
data_format
=
"NCHW"
)
result
=
conv
(
inputs
)
def
run3
(
self
,
place
):
with
fluid
.
dygraph
.
guard
(
place
):
inputs
=
fluid
.
dygraph
.
to_variable
(
self
.
input_np
)
conv
=
paddle
.
fluid
.
dygraph
.
nn
.
Conv2D
(
num_channels
=
3
,
num_filters
=
4
,
filter_size
=
(
3
,
3
),
)
result
=
conv
(
inputs
)
def
run_all
(
self
,
place
):
self
.
run1
(
place
)
self
.
run2
(
place
)
self
.
run3
(
place
)
def
test_environ
(
self
):
self
.
input_np
=
np
.
random
.
random
([
2
,
3
,
5
,
5
]).
astype
(
"float32"
)
for
place
in
[
paddle
.
CPUPlace
(),
paddle
.
CUDAPlace
(
0
)]:
fluid
.
set_flags
({
'FLAGS_conv2d_disable_cudnn'
:
False
})
self
.
run_all
(
place
)
fluid
.
set_flags
({
'FLAGS_conv2d_disable_cudnn'
:
True
})
self
.
run_all
(
place
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_conv2d_op.py
浏览文件 @
519cc7b0
此差异已折叠。
点击以展开。
python/paddle/fluid/tests/unittests/test_conv2d_op_depthwise_conv.py
0 → 100644
浏览文件 @
519cc7b0
# Copyright (c) 2021 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
paddle
.
enable_static
()
import
paddle.fluid.core
as
core
import
paddle.fluid
as
fluid
from
op_test
import
OpTest
from
paddle.fluid
import
Program
,
program_guard
from
test_conv2d_op
import
TestConv2DOp
,
TestConv2DOp_v2
,
create_test_padding_SAME_class
,
create_test_padding_VALID_class
,
create_test_channel_last_class
,
create_test_cudnn_padding_SAME_class
,
create_test_cudnn_channel_last_class
#----------------TestDepthwiseConv -----
class
TestDepthwiseConv
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
12
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConv2
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
12
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConv3
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConvWithDilation
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
self
.
dilations
=
[
2
,
2
]
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConvWithDilation2
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
self
.
dilations
=
[
2
,
2
]
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConvandFuse
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
12
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConv2andFuse
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
12
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConv3andFuse
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConvWithDilationandFuse
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
self
.
dilations
=
[
2
,
2
]
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConvWithDilation2andFuse
(
TestConv2DOp
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
self
.
dilations
=
[
2
,
2
]
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
class
TestDepthwiseConv_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
12
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
1
,
1
,
0
,
1
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConv2_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
12
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
0
,
1
,
0
,
2
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConv3_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
1
,
1
,
0
,
0
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConvWithDilation_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
self
.
dilations
=
[
2
,
2
]
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
1
,
1
,
2
,
1
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConvWithDilation2_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
self
.
dilations
=
[
2
,
2
]
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
0
,
1
,
1
,
0
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConvandFuse_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
12
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
2
,
1
,
2
,
3
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConv2andFuse_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
12
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
1
,
1
,
1
,
2
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConv3andFuse_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
1
,
2
,
0
,
2
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConvWithDilationandFuse_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
2
,
2
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
self
.
dilations
=
[
2
,
2
]
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
2
,
1
,
1
,
0
]
self
.
padding_algorithm
=
"EXPLICIT"
class
TestDepthwiseConvWithDilation2andFuse_AsyPadding
(
TestConv2DOp_v2
):
def
init_test_case
(
self
):
self
.
fuse_relu_before_depthwise_conv
=
True
self
.
use_cuda
=
True
self
.
pad
=
[
1
,
1
]
self
.
stride
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
self
.
groups
=
3
self
.
dilations
=
[
2
,
2
]
assert
np
.
mod
(
self
.
input_size
[
1
],
self
.
groups
)
==
0
f_c
=
self
.
input_size
[
1
]
//
self
.
groups
self
.
filter_size
=
[
24
,
f_c
,
3
,
3
]
self
.
op_type
=
"depthwise_conv2d"
def
init_paddings
(
self
):
self
.
pad
=
[
1
,
3
,
1
,
3
]
self
.
padding_algorithm
=
"EXPLICIT"
# depthwise conv2d
create_test_padding_SAME_class
(
TestDepthwiseConv_AsyPadding
)
create_test_padding_SAME_class
(
TestDepthwiseConvWithDilation_AsyPadding
)
create_test_padding_SAME_class
(
TestDepthwiseConvandFuse_AsyPadding
)
create_test_padding_SAME_class
(
TestDepthwiseConvWithDilationandFuse_AsyPadding
)
create_test_padding_VALID_class
(
TestDepthwiseConv_AsyPadding
)
create_test_padding_VALID_class
(
TestDepthwiseConvWithDilation_AsyPadding
)
create_test_padding_VALID_class
(
TestDepthwiseConvandFuse_AsyPadding
)
create_test_padding_VALID_class
(
TestDepthwiseConvWithDilationandFuse_AsyPadding
)
# channel last
create_test_channel_last_class
(
TestDepthwiseConv_AsyPadding
)
create_test_channel_last_class
(
TestDepthwiseConvWithDilation2_AsyPadding
)
create_test_channel_last_class
(
TestDepthwiseConvandFuse_AsyPadding
)
create_test_channel_last_class
(
TestDepthwiseConvWithDilationandFuse_AsyPadding
)
# ------------ depthwise conv2d in MIOPEN ---------
if
core
.
is_compiled_with_rocm
():
create_test_cudnn_padding_SAME_class
(
TestDepthwiseConv_AsyPadding
)
create_test_cudnn_padding_SAME_class
(
TestDepthwiseConvWithDilation_AsyPadding
)
create_test_padding_VALID_class
(
TestDepthwiseConv_AsyPadding
)
create_test_padding_VALID_class
(
TestDepthwiseConvWithDilation_AsyPadding
)
create_test_cudnn_channel_last_class
(
TestDepthwiseConv_AsyPadding
)
create_test_cudnn_channel_last_class
(
TestDepthwiseConvWithDilation2_AsyPadding
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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