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
a0363d18
P
Paddle
项目概览
PaddlePaddle
/
Paddle
11 个月 前同步成功
通知
2291
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
体验新版 GitCode,发现更多精彩内容 >>
未验证
提交
a0363d18
编写于
6月 13, 2022
作者:
C
Chenxiao Niu
提交者:
GitHub
6月 13, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[MLU] add UTs for mlu interp_v2(bilinear). (#43386)
上级
67bd5d9c
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
663 addition
and
0 deletion
+663
-0
python/paddle/fluid/tests/unittests/mlu/test_bilinear_interp_v2_op_mlu.py
...uid/tests/unittests/mlu/test_bilinear_interp_v2_op_mlu.py
+663
-0
未找到文件。
python/paddle/fluid/tests/unittests/mlu/test_bilinear_interp_v2_op_mlu.py
0 → 100644
浏览文件 @
a0363d18
# Copyright (c) 2022 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
sys
sys
.
path
.
append
(
'..'
)
from
op_test
import
OpTest
import
paddle.fluid.core
as
core
import
paddle.fluid
as
fluid
from
paddle.nn.functional
import
interpolate
import
paddle
paddle
.
enable_static
()
def
bilinear_interp_np
(
input
,
out_h
,
out_w
,
scale_w
=
0
,
scale_h
=
0
,
out_size
=
None
,
actual_shape
=
None
,
align_corners
=
True
,
align_mode
=
0
,
data_layout
=
'NCHW'
):
"""bilinear interpolation implement in shape [N, C, H, W]"""
if
data_layout
==
"NHWC"
:
input
=
np
.
transpose
(
input
,
(
0
,
3
,
1
,
2
))
# NHWC => NCHW
if
out_size
is
not
None
:
out_h
=
out_size
[
0
]
out_w
=
out_size
[
1
]
if
actual_shape
is
not
None
:
out_h
=
actual_shape
[
0
]
out_w
=
actual_shape
[
1
]
batch_size
,
channel
,
in_h
,
in_w
=
input
.
shape
ratio_h
=
ratio_w
=
0.0
if
out_h
>
1
:
if
(
align_corners
):
ratio_h
=
(
in_h
-
1.0
)
/
(
out_h
-
1.0
)
else
:
if
scale_h
>
0
:
ratio_h
=
1.0
/
scale_h
else
:
ratio_h
=
1.0
*
in_h
/
out_h
if
out_w
>
1
:
if
(
align_corners
):
ratio_w
=
(
in_w
-
1.0
)
/
(
out_w
-
1.0
)
else
:
if
scale_w
>
0
:
ratio_w
=
1.0
/
scale_w
else
:
ratio_w
=
1.0
*
in_w
/
out_w
out
=
np
.
zeros
((
batch_size
,
channel
,
out_h
,
out_w
))
for
i
in
range
(
out_h
):
if
(
align_mode
==
0
and
not
align_corners
):
h
=
int
(
ratio_h
*
(
i
+
0.5
)
-
0.5
)
else
:
h
=
int
(
ratio_h
*
i
)
h
=
max
(
0
,
h
)
hid
=
1
if
h
<
in_h
-
1
else
0
if
(
align_mode
==
0
and
not
align_corners
):
idx_src_h
=
max
(
ratio_h
*
(
i
+
0.5
)
-
0.5
,
0
)
h1lambda
=
idx_src_h
-
h
else
:
h1lambda
=
ratio_h
*
i
-
h
h2lambda
=
1.0
-
h1lambda
for
j
in
range
(
out_w
):
if
(
align_mode
==
0
and
not
align_corners
):
w
=
int
(
ratio_w
*
(
j
+
0.5
)
-
0.5
)
else
:
w
=
int
(
ratio_w
*
j
)
w
=
max
(
0
,
w
)
wid
=
1
if
w
<
in_w
-
1
else
0
if
(
align_mode
==
0
and
not
align_corners
):
idx_src_w
=
max
(
ratio_w
*
(
j
+
0.5
)
-
0.5
,
0
)
w1lambda
=
idx_src_w
-
w
else
:
w1lambda
=
ratio_w
*
j
-
w
w2lambda
=
1.0
-
w1lambda
out
[:,
:,
i
,
j
]
=
h2lambda
*
(
w2lambda
*
input
[:,
:,
h
,
w
]
+
w1lambda
*
input
[:,
:,
h
,
w
+
wid
])
+
\
h1lambda
*
(
w2lambda
*
input
[:,
:,
h
+
hid
,
w
]
+
w1lambda
*
input
[:,
:,
h
+
hid
,
w
+
wid
])
if
data_layout
==
"NHWC"
:
out
=
np
.
transpose
(
out
,
(
0
,
2
,
3
,
1
))
# NCHW => NHWC
return
out
.
astype
(
input
.
dtype
)
class
TestBilinearInterpOp
(
OpTest
):
def
setUp
(
self
):
self
.
place
=
paddle
.
device
.
MLUPlace
(
0
)
self
.
__class__
.
use_mlu
=
True
self
.
out_size
=
None
self
.
actual_shape
=
None
self
.
data_layout
=
'NCHW'
self
.
init_test_case
()
self
.
dtype
=
"float32"
self
.
op_type
=
"bilinear_interp_v2"
input_np
=
np
.
random
.
random
(
self
.
input_shape
).
astype
(
self
.
dtype
)
if
self
.
data_layout
==
"NCHW"
:
in_h
=
self
.
input_shape
[
2
]
in_w
=
self
.
input_shape
[
3
]
else
:
in_h
=
self
.
input_shape
[
1
]
in_w
=
self
.
input_shape
[
2
]
scale_h
=
0
scale_w
=
0
if
self
.
scale
:
if
isinstance
(
self
.
scale
,
float
)
or
isinstance
(
self
.
scale
,
int
):
if
self
.
scale
>
0.
:
scale_h
=
scale_w
=
float
(
self
.
scale
)
if
isinstance
(
self
.
scale
,
list
)
and
len
(
self
.
scale
)
==
1
:
scale_w
=
scale_h
=
self
.
scale
[
0
]
elif
isinstance
(
self
.
scale
,
list
)
and
len
(
self
.
scale
)
>
1
:
scale_w
=
self
.
scale
[
1
]
scale_h
=
self
.
scale
[
0
]
out_h
=
int
(
in_h
*
scale_h
)
out_w
=
int
(
in_w
*
scale_w
)
else
:
out_h
=
self
.
out_h
out_w
=
self
.
out_w
output_np
=
bilinear_interp_np
(
input_np
,
out_h
,
out_w
,
0
,
0
,
self
.
out_size
,
self
.
actual_shape
,
self
.
align_corners
,
self
.
align_mode
,
self
.
data_layout
)
self
.
inputs
=
{
'X'
:
input_np
}
if
self
.
out_size
is
not
None
:
self
.
inputs
[
'OutSize'
]
=
self
.
out_size
if
self
.
actual_shape
is
not
None
:
self
.
inputs
[
'OutSize'
]
=
self
.
actual_shape
self
.
attrs
=
{
'out_h'
:
self
.
out_h
,
'out_w'
:
self
.
out_w
,
'interp_method'
:
self
.
interp_method
,
'align_corners'
:
self
.
align_corners
,
'align_mode'
:
self
.
align_mode
,
'data_layout'
:
self
.
data_layout
}
if
self
.
scale
:
if
isinstance
(
self
.
scale
,
float
)
or
isinstance
(
self
.
scale
,
int
):
if
self
.
scale
>
0.
:
self
.
scale
=
[
self
.
scale
]
if
isinstance
(
self
.
scale
,
list
)
and
len
(
self
.
scale
)
==
1
:
self
.
scale
=
[
self
.
scale
[
0
],
self
.
scale
[
0
]]
self
.
attrs
[
'scale'
]
=
self
.
scale
self
.
outputs
=
{
'Out'
:
output_np
}
def
test_check_output
(
self
):
self
.
check_output_with_place
(
self
.
place
)
def
test_check_grad
(
self
):
self
.
check_grad_with_place
(
self
.
place
,
[
'X'
],
'Out'
,
in_place
=
True
)
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
3
,
5
,
5
]
self
.
out_h
=
2
self
.
out_w
=
2
self
.
scale
=
0.
self
.
out_size
=
np
.
array
([
3
,
3
]).
astype
(
"int32"
)
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpCase1
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
4
,
1
,
7
,
8
]
self
.
out_h
=
1
self
.
out_w
=
1
self
.
scale
=
0.
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpCase2
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
3
,
3
,
9
,
6
]
self
.
out_h
=
12
self
.
out_w
=
12
self
.
scale
=
0.
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpCase3
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
1
,
1
,
32
,
64
]
self
.
out_h
=
64
self
.
out_w
=
32
self
.
scale
=
0.
self
.
align_corners
=
True
self
.
align_mode
=
1
def
test_check_output
(
self
):
self
.
check_output_with_place
(
self
.
place
,
atol
=
1e-5
)
class
TestBilinearInterpCase4
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
4
,
1
,
7
,
8
]
self
.
out_h
=
1
self
.
out_w
=
1
self
.
scale
=
0.
self
.
out_size
=
np
.
array
([
2
,
2
]).
astype
(
"int32"
)
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpCase5
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
3
,
3
,
9
,
6
]
self
.
out_h
=
12
self
.
out_w
=
12
self
.
scale
=
0.
self
.
out_size
=
np
.
array
([
11
,
11
]).
astype
(
"int32"
)
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpCase6
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
1
,
1
,
32
,
64
]
self
.
out_h
=
64
self
.
out_w
=
32
self
.
scale
=
0.
self
.
out_size
=
np
.
array
([
65
,
33
]).
astype
(
"int32"
)
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpCase7
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
1
,
1
,
32
,
64
]
self
.
out_h
=
64
self
.
out_w
=
32
self
.
scale
=
[
2.0
,
0.5
]
self
.
align_corners
=
False
self
.
align_mode
=
1
class
TestBilinearInterpSame
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
3
,
32
,
64
]
self
.
out_h
=
32
self
.
out_w
=
64
self
.
scale
=
0.
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpActualShape
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
3
,
2
,
32
,
16
]
self
.
out_h
=
64
self
.
out_w
=
32
self
.
scale
=
0.
self
.
out_size
=
np
.
array
([
66
,
40
]).
astype
(
"int32"
)
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpDataLayout
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
5
,
5
,
3
]
self
.
out_h
=
2
self
.
out_w
=
2
self
.
scale
=
0.
self
.
out_size
=
np
.
array
([
3
,
3
]).
astype
(
"int32"
)
self
.
align_corners
=
True
self
.
align_mode
=
1
self
.
data_layout
=
"NHWC"
class
TestBilinearInterpOtherMethod1
(
TestBilinearInterpOp
):
def
set_align_mode
(
self
):
self
.
align_corners
=
False
self
.
align_mode
=
1
class
TestBilinearInterpWithMethod2
(
TestBilinearInterpOp
):
def
set_align_mode
(
self
):
self
.
align_corners
=
False
self
.
align_mode
=
0
class
TestBilinearInterpWithMethod3
(
TestBilinearInterpOp
):
def
set_align_mode
(
self
):
self
.
align_corners
=
True
self
.
align_mode
=
0
class
TestBilinearInterpScale1
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
3
,
5
,
7
]
self
.
out_h
=
60
self
.
out_w
=
25
self
.
scale
=
2.
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpScale2
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
3
,
5
,
7
]
self
.
out_h
=
60
self
.
out_w
=
25
self
.
scale
=
1.
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpScale3
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
3
,
5
,
7
]
self
.
out_h
=
60
self
.
out_w
=
25
self
.
scale
=
1.5
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpScale4
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
3
,
5
,
7
]
self
.
out_h
=
60
self
.
out_w
=
25
self
.
scale
=
[
1.5
,
0.5
]
self
.
align_corners
=
True
self
.
align_mode
=
1
class
TestBilinearInterpZero
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
3
,
5
,
7
]
self
.
out_h
=
60
self
.
out_w
=
25
self
.
scale
=
0.2
self
.
align_corners
=
False
self
.
align_mode
=
0
class
TestBilinearInterpOp_attr_tensor
(
OpTest
):
def
setUp
(
self
):
self
.
place
=
paddle
.
device
.
MLUPlace
(
0
)
self
.
__class__
.
use_mlu
=
True
self
.
out_size
=
None
self
.
actual_shape
=
None
self
.
init_test_case
()
self
.
op_type
=
"bilinear_interp_v2"
self
.
shape_by_1Dtensor
=
False
self
.
scale_by_1Dtensor
=
False
self
.
attrs
=
{
'interp_method'
:
self
.
interp_method
,
'align_corners'
:
self
.
align_corners
,
}
input_np
=
np
.
random
.
random
(
self
.
input_shape
).
astype
(
"float32"
)
self
.
inputs
=
{
'X'
:
input_np
}
if
self
.
scale_by_1Dtensor
:
self
.
inputs
[
'Scale'
]
=
np
.
array
([
self
.
scale
]).
astype
(
"float32"
)
elif
self
.
scale
:
if
isinstance
(
self
.
scale
,
float
)
or
isinstance
(
self
.
scale
,
int
):
if
self
.
scale
>
0
:
scale_h
=
scale_w
=
float
(
self
.
scale
)
if
isinstance
(
self
.
scale
,
list
)
and
len
(
self
.
scale
)
==
1
:
scale_w
=
scale_h
=
self
.
scale
[
0
]
elif
isinstance
(
self
.
scale
,
list
)
and
len
(
self
.
scale
)
>
1
:
scale_w
=
self
.
scale
[
1
]
scale_h
=
self
.
scale
[
0
]
out_h
=
int
(
self
.
input_shape
[
2
]
*
scale_h
)
out_w
=
int
(
self
.
input_shape
[
3
]
*
scale_w
)
else
:
out_h
=
self
.
out_h
out_w
=
self
.
out_w
if
self
.
shape_by_1Dtensor
:
self
.
inputs
[
'OutSize'
]
=
self
.
out_size
elif
self
.
out_size
is
not
None
:
size_tensor
=
[]
for
index
,
ele
in
enumerate
(
self
.
out_size
):
size_tensor
.
append
((
"x"
+
str
(
index
),
np
.
ones
(
(
1
)).
astype
(
'int32'
)
*
ele
))
self
.
inputs
[
'SizeTensor'
]
=
size_tensor
self
.
attrs
[
'out_h'
]
=
self
.
out_h
self
.
attrs
[
'out_w'
]
=
self
.
out_w
if
self
.
scale
:
if
isinstance
(
self
.
scale
,
float
)
or
isinstance
(
self
.
scale
,
int
):
if
self
.
scale
>
0
:
self
.
scale
=
[
self
.
scale
]
if
isinstance
(
self
.
scale
,
list
)
and
len
(
self
.
scale
)
==
1
:
self
.
scale
=
[
self
.
scale
[
0
],
self
.
scale
[
0
]]
self
.
attrs
[
'scale'
]
=
self
.
scale
output_np
=
bilinear_interp_np
(
input_np
,
out_h
,
out_w
,
0
,
0
,
self
.
out_size
,
self
.
actual_shape
,
self
.
align_corners
)
self
.
outputs
=
{
'Out'
:
output_np
}
def
test_check_output
(
self
):
self
.
check_output_with_place
(
self
.
place
)
def
test_check_grad
(
self
):
self
.
check_grad_with_place
(
self
.
place
,
[
'X'
],
'Out'
,
in_place
=
True
)
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
2
,
3
,
5
,
5
]
self
.
out_h
=
3
self
.
out_w
=
3
self
.
scale
=
0.
self
.
out_size
=
[
3
,
3
]
self
.
align_corners
=
True
# out_size is a 1-D tensor
class
TestBilinearInterp_attr_tensor_Case1
(
TestBilinearInterpOp_attr_tensor
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
3
,
3
,
9
,
6
]
self
.
out_h
=
12
self
.
out_w
=
12
self
.
scale
=
0.
self
.
out_size
=
[
8
,
12
]
self
.
align_corners
=
True
# scale is a 1-D tensor
class
TestBilinearInterp_attr_tensor_Case2
(
TestBilinearInterpOp_attr_tensor
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
3
,
2
,
32
,
16
]
self
.
out_h
=
64
self
.
out_w
=
32
self
.
scale
=
0.
self
.
out_size
=
np
.
array
([
66
,
40
]).
astype
(
"int32"
)
self
.
align_corners
=
True
self
.
shape_by_1Dtensor
=
True
# scale is a 1-D tensor
class
TestBilinearInterp_attr_tensor_Case3
(
TestBilinearInterpOp_attr_tensor
):
def
init_test_case
(
self
):
self
.
interp_method
=
'bilinear'
self
.
input_shape
=
[
3
,
2
,
32
,
16
]
self
.
out_h
=
64
self
.
out_w
=
32
self
.
scale
=
2.0
self
.
out_size
=
None
self
.
align_corners
=
True
self
.
scale_by_1Dtensor
=
True
#TODO: comment this test for now until bilinear_interp_op added.
# class TestBilinearInterpOpAPI(unittest.TestCase):
# def test_case(self):
# x = fluid.data(name="x", shape=[2, 3, 6, 6], dtype="float32")
# dim = fluid.data(name="dim", shape=[1], dtype="int32")
# shape_tensor = fluid.data(name="shape_tensor", shape=[2], dtype="int32")
# actual_size = fluid.data(name="actual_size", shape=[2], dtype="int32")
# scale_tensor = fluid.data(
# name="scale_tensor", shape=[1], dtype="float32")
# out1 = fluid.layers.resize_bilinear(x, out_shape=[12, 12])
# out2 = fluid.layers.resize_bilinear(x, out_shape=[12, dim])
# out3 = fluid.layers.resize_bilinear(x, out_shape=shape_tensor)
# out4 = fluid.layers.resize_bilinear(
# x, out_shape=[4, 4], actual_shape=actual_size)
# out5 = fluid.layers.resize_bilinear(x, scale=scale_tensor)
# x_data = np.random.random((2, 3, 6, 6)).astype("float32")
# dim_data = np.array([12]).astype("int32")
# shape_data = np.array([12, 12]).astype("int32")
# actual_size_data = np.array([12, 12]).astype("int32")
# scale_data = np.array([2.0]).astype("float32")
# if core.is_compiled_with_mlu():
# place = paddle.device.MLUPlace(0)
# else:
# place = core.CPUPlace()
# exe = fluid.Executor(place)
# exe.run(fluid.default_startup_program())
# results = exe.run(fluid.default_main_program(),
# feed={
# "x": x_data,
# "dim": dim_data,
# "shape_tensor": shape_data,
# "actual_size": actual_size_data,
# "scale_tensor": scale_data
# },
# fetch_list=[out1, out2, out3, out4, out5],
# return_numpy=True)
# expect_res = bilinear_interp_np(
# x_data, out_h=12, out_w=12, align_corners=True)
# for res in results:
# self.assertTrue(np.allclose(res, expect_res))
class
TestBilinearInterpOpAPI_dy
(
unittest
.
TestCase
):
def
test_case
(
self
):
import
paddle
if
core
.
is_compiled_with_mlu
():
place
=
paddle
.
device
.
MLUPlace
(
0
)
else
:
place
=
core
.
CPUPlace
()
with
fluid
.
dygraph
.
guard
(
place
):
input_data
=
np
.
random
.
random
((
2
,
3
,
6
,
6
)).
astype
(
"float32"
)
input_data
=
np
.
load
(
'input.npy'
).
astype
(
"float32"
)
# print(input_data)
input_x
=
paddle
.
to_tensor
(
input_data
)
expect_res
=
bilinear_interp_np
(
input_data
,
out_h
=
12
,
out_w
=
12
,
align_corners
=
False
)
out
=
interpolate
(
x
=
input_x
,
size
=
[
12
,
12
],
mode
=
"bilinear"
,
align_corners
=
False
)
self
.
assertTrue
(
np
.
allclose
(
out
.
numpy
(),
expect_res
))
class
TestBilinearInterpOpAPI_dy2
(
unittest
.
TestCase
):
def
test_case
(
self
):
import
paddle
if
core
.
is_compiled_with_mlu
():
place
=
paddle
.
device
.
MLUPlace
(
0
)
else
:
place
=
core
.
CPUPlace
()
with
fluid
.
dygraph
.
guard
(
place
):
input_data
=
np
.
random
.
random
((
2
,
3
,
6
,
6
)).
astype
(
"float32"
)
size_np
=
np
.
array
([
12
,
12
]).
astype
(
"int64"
)
input_x
=
paddle
.
to_tensor
(
input_data
)
size
=
paddle
.
to_tensor
(
size_np
)
expect_res
=
bilinear_interp_np
(
input_data
,
out_h
=
12
,
out_w
=
12
,
align_corners
=
False
)
out
=
interpolate
(
x
=
input_x
,
size
=
size
,
mode
=
"bilinear"
,
align_corners
=
False
)
self
.
assertTrue
(
np
.
allclose
(
out
.
numpy
(),
expect_res
))
class
TestBilinearInterpOpAPI_dy3
(
unittest
.
TestCase
):
def
test_case
(
self
):
import
paddle
if
core
.
is_compiled_with_mlu
():
place
=
paddle
.
device
.
MLUPlace
(
0
)
else
:
place
=
core
.
CPUPlace
()
with
fluid
.
dygraph
.
guard
(
place
):
input_data
=
np
.
random
.
random
((
2
,
3
,
6
,
6
)).
astype
(
"float32"
)
size_1
=
np
.
array
([
12
]).
astype
(
"int64"
)
input_x
=
paddle
.
to_tensor
(
input_data
)
size
=
paddle
.
to_tensor
(
size_1
)
expect_res
=
bilinear_interp_np
(
input_data
,
out_h
=
12
,
out_w
=
12
,
align_corners
=
False
)
out
=
interpolate
(
x
=
input_x
,
size
=
[
size
,
size
],
mode
=
"bilinear"
,
align_corners
=
False
)
self
.
assertTrue
(
np
.
allclose
(
out
.
numpy
(),
expect_res
))
class
TestBilinearInterpOpAPI_dy4
(
unittest
.
TestCase
):
def
test_case
(
self
):
import
paddle
if
core
.
is_compiled_with_mlu
():
place
=
paddle
.
device
.
MLUPlace
(
0
)
else
:
place
=
core
.
CPUPlace
()
with
fluid
.
dygraph
.
guard
(
place
):
input_data
=
np
.
random
.
random
((
2
,
3
,
6
,
6
)).
astype
(
"float32"
)
scale_np
=
np
.
array
([
2
,
2
]).
astype
(
"int64"
)
input_x
=
paddle
.
to_tensor
(
input_data
)
scale
=
paddle
.
to_tensor
(
scale_np
)
expect_res
=
bilinear_interp_np
(
input_data
,
out_h
=
12
,
out_w
=
12
,
align_corners
=
False
)
out
=
interpolate
(
x
=
input_x
,
scale_factor
=
scale
,
mode
=
"bilinear"
,
align_corners
=
False
)
self
.
assertTrue
(
np
.
allclose
(
out
.
numpy
(),
expect_res
))
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