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体验新版 GitCode,发现更多精彩内容 >>
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b587a7f6
编写于
6月 08, 2018
作者:
F
fengjiayi
提交者:
GitHub
6月 08, 2018
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差异文件
Merge pull request #11293 from JiayiFeng/update_crop_op
Update crop op
上级
259e63d4
c7bbfb33
变更
4
显示空白变更内容
内联
并排
Showing
4 changed file
with
89 addition
and
8 deletion
+89
-8
paddle/fluid/operators/crop_op.cc
paddle/fluid/operators/crop_op.cc
+34
-1
paddle/fluid/operators/crop_op.h
paddle/fluid/operators/crop_op.h
+33
-5
paddle/fluid/operators/random_crop_op.cc
paddle/fluid/operators/random_crop_op.cc
+0
-1
python/paddle/fluid/tests/unittests/test_crop_op.py
python/paddle/fluid/tests/unittests/test_crop_op.py
+22
-1
未找到文件。
paddle/fluid/operators/crop_op.cc
浏览文件 @
b587a7f6
...
...
@@ -48,6 +48,13 @@ class CropOp : public framework::OperatorWithKernel {
ctx
->
SetOutputDim
(
"Out"
,
y_dim
);
}
}
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
)
->
type
()),
ctx
.
device_context
());
}
};
class
CropOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -60,13 +67,19 @@ class CropOpMaker : public framework::OpProtoAndCheckerMaker {
"The input used as reference for cropping, "
"which is of the same dimensions as X."
)
.
AsDispensable
();
AddInput
(
"Offsets"
,
"The input used to describe offsets in runtime, which is a "
"1-D vector whose size equals to the rank of input 'X'. The "
"elements data type must be int."
)
.
AsDispensable
();
AddOutput
(
"Out"
,
"The output of crop op, "
"which is of the same dimensions as X."
);
AddAttr
<
std
::
vector
<
int
>>
(
"offsets"
,
"A list<int> describing offsets to be cropped. "
"The size of offsets list should be the same as "
"the dimension size of input X."
);
"the dimension size of input X."
)
.
SetDefault
(
std
::
vector
<
int
>
());
AddAttr
<
std
::
vector
<
int
>>
(
"shape"
,
"A list<int> describing the shape of output. "
"The size of shape list should be the same as "
...
...
@@ -77,6 +90,17 @@ Crop Operator.
Crop input into output, as specified by offsets and shape.
There are two ways to set the offsets:
1. In runtime: Using the input 'Offsets', which is a Vairbale and can be
output of other operators. This way is suitable for
dynamic offsets.
2. In network configuration: Using the attribute 'offsets', which will be
set in Python configure script. This way is
suitable for fixed offsets.
You CANNOT use these two ways at the same time. An exception will be raised
if input 'Offset' is configured and meanwhile the attribute 'offsets' is
not empty.
There are two ways to set shape:
1. reference input: crop input X into the same shape as reference input.
The dimension of reference input should
...
...
@@ -146,6 +170,15 @@ class CropOpGrad : public framework::OperatorWithKernel {
ctx
->
SetOutputDim
(
x_grad_name
,
x_dims
);
}
}
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
))
->
type
()),
ctx
.
device_context
());
}
};
}
// namespace operators
...
...
paddle/fluid/operators/crop_op.h
浏览文件 @
b587a7f6
...
...
@@ -27,6 +27,37 @@ template <typename T, size_t D, int MajorType = Eigen::RowMajor,
using
EigenTensor
=
framework
::
EigenTensor
<
T
,
D
,
MajorType
,
IndexType
>
;
using
framework
::
Tensor
;
static
std
::
vector
<
int
>
GetOffsets
(
const
framework
::
ExecutionContext
&
ctx
)
{
std
::
vector
<
int
>
res
;
int
rank
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
if
(
ctx
.
HasInput
(
"Offsets"
))
{
PADDLE_ENFORCE
(
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
).
empty
(),
"Input 'Offsets' and attribute 'offsets' should not be used "
"at the same time."
);
const
auto
*
offsets_tensor
=
ctx
.
Input
<
Tensor
>
(
"Offsets"
);
PADDLE_ENFORCE_EQ
(
offsets_tensor
->
dims
().
size
(),
1
);
PADDLE_ENFORCE_EQ
(
rank
,
offsets_tensor
->
dims
()[
0
],
"Offsets size should be equal to dimension size of input tensor."
);
const
int
*
offsets_data
;
framework
::
Tensor
cpu_tmp_tensor
;
if
(
platform
::
is_cpu_place
(
offsets_tensor
->
place
()))
{
offsets_data
=
offsets_tensor
->
data
<
int
>
();
}
else
{
framework
::
TensorCopySync
(
*
offsets_tensor
,
platform
::
CPUPlace
(),
&
cpu_tmp_tensor
);
offsets_data
=
cpu_tmp_tensor
.
data
<
int
>
();
}
res
=
std
::
vector
<
int
>
(
offsets_data
,
offsets_data
+
rank
);
}
else
{
res
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
);
PADDLE_ENFORCE_EQ
(
rank
,
res
.
size
(),
"Offsets size should be equal to dimension size of input tensor."
);
}
return
res
;
}
template
<
typename
T
>
class
CropKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
...
...
@@ -37,10 +68,7 @@ class CropKernel : public framework::OpKernel<T> {
T
*
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
x_stride
=
framework
::
stride
(
x
->
dims
());
auto
out_stride
=
framework
::
stride
(
out
->
dims
());
auto
offsets
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
);
PADDLE_ENFORCE_EQ
(
x
->
dims
().
size
(),
static_cast
<
int64_t
>
(
offsets
.
size
()),
"Offsets size should be equal to dimension size of input tensor."
);
auto
offsets
=
GetOffsets
(
context
);
int64_t
offset
=
0
;
for
(
size_t
i
=
0
;
i
<
offsets
.
size
();
++
i
)
{
offset
+=
(
x_stride
[
i
]
*
offsets
[
i
]);
...
...
@@ -56,7 +84,7 @@ void CropGradFunction(const framework::ExecutionContext& context) {
if
(
d_x
!=
nullptr
)
{
auto
*
d_out
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
d_x
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
offsets
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
);
auto
offsets
=
GetOffsets
(
context
);
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
size_t
i
=
0
;
i
<
D
;
++
i
)
{
paddings
[
i
].
first
=
offsets
[
i
];
...
...
paddle/fluid/operators/random_crop_op.cc
浏览文件 @
b587a7f6
...
...
@@ -20,7 +20,6 @@ class RandomCropOp : public framework::OperatorWithKernel {
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
...
...
python/paddle/fluid/tests/unittests/test_crop_op.py
浏览文件 @
b587a7f6
...
...
@@ -42,9 +42,9 @@ class TestCropOp(OpTest):
def
setUp
(
self
):
self
.
op_type
=
"crop"
self
.
crop_by_input
=
False
self
.
offset_by_input
=
False
self
.
attrs
=
{}
self
.
initTestCase
()
self
.
attrs
[
'offsets'
]
=
self
.
offsets
if
self
.
crop_by_input
:
self
.
inputs
=
{
'X'
:
np
.
random
.
random
(
self
.
x_shape
).
astype
(
"float32"
),
...
...
@@ -55,6 +55,10 @@ class TestCropOp(OpTest):
self
.
inputs
=
{
'X'
:
np
.
random
.
random
(
self
.
x_shape
).
astype
(
"float32"
),
}
if
self
.
offset_by_input
:
self
.
inputs
[
'Offsets'
]
=
np
.
array
(
self
.
offsets
).
astype
(
'int32'
)
else
:
self
.
attrs
[
'offsets'
]
=
self
.
offsets
self
.
outputs
=
{
'Out'
:
crop
(
self
.
inputs
[
'X'
],
self
.
offsets
,
self
.
crop_shape
)
}
...
...
@@ -101,5 +105,22 @@ class TestCase4(TestCropOp):
self
.
crop_by_input
=
True
class
TestCase5
(
TestCropOp
):
def
initTestCase
(
self
):
self
.
x_shape
=
(
3
,
4
,
5
)
self
.
crop_shape
=
[
2
,
2
,
3
]
self
.
offsets
=
[
1
,
0
,
2
]
self
.
offset_by_input
=
True
class
TestCase6
(
TestCropOp
):
def
initTestCase
(
self
):
self
.
x_shape
=
(
10
,
9
,
14
)
self
.
crop_shape
=
[
3
,
3
,
5
]
self
.
offsets
=
[
3
,
5
,
4
]
self
.
crop_by_input
=
True
self
.
offset_by_input
=
True
if
__name__
==
'__main__'
:
unittest
.
main
()
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