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PaddleDetection
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c9ba51ea
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PaddleDetection
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c9ba51ea
编写于
7月 11, 2018
作者:
T
tensor-tang
浏览文件
操作
浏览文件
下载
差异文件
Merge remote-tracking branch 'ups/develop' into feature/libxsmm
上级
64a8e6d2
16aca3c0
变更
10
隐藏空白更改
内联
并排
Showing
10 changed file
with
352 addition
and
167 deletion
+352
-167
paddle/fluid/operators/detection/rpn_target_assign_op.cc
paddle/fluid/operators/detection/rpn_target_assign_op.cc
+3
-2
paddle/fluid/operators/im2sequence_op.cc
paddle/fluid/operators/im2sequence_op.cc
+18
-7
paddle/fluid/operators/im2sequence_op.h
paddle/fluid/operators/im2sequence_op.h
+91
-34
paddle/fluid/operators/math/im2col.cc
paddle/fluid/operators/math/im2col.cc
+0
-26
paddle/fluid/operators/math/im2col.cu
paddle/fluid/operators/math/im2col.cu
+0
-30
python/paddle/fluid/backward.py
python/paddle/fluid/backward.py
+39
-21
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+40
-12
python/paddle/fluid/tests/unittests/test_im2sequence_op.py
python/paddle/fluid/tests/unittests/test_im2sequence_op.py
+147
-33
python/paddle/fluid/tests/unittests/test_layers.py
python/paddle/fluid/tests/unittests/test_layers.py
+6
-2
python/setup.py.in
python/setup.py.in
+8
-0
未找到文件。
paddle/fluid/operators/detection/rpn_target_assign_op.cc
浏览文件 @
c9ba51ea
...
@@ -86,8 +86,9 @@ class RpnTargetAssignKernel : public framework::OpKernel<T> {
...
@@ -86,8 +86,9 @@ class RpnTargetAssignKernel : public framework::OpKernel<T> {
std
::
minstd_rand
engine
,
std
::
minstd_rand
engine
,
std
::
vector
<
int
>*
inds
)
const
{
std
::
vector
<
int
>*
inds
)
const
{
std
::
uniform_real_distribution
<
float
>
uniform
(
0
,
1
);
std
::
uniform_real_distribution
<
float
>
uniform
(
0
,
1
);
if
(
inds
->
size
()
>
num
)
{
const
int64_t
size
=
static_cast
<
int64_t
>
(
inds
->
size
());
for
(
int
i
=
num
;
i
<
inds
->
size
();
++
i
)
{
if
(
size
>
num
)
{
for
(
int64_t
i
=
num
;
i
<
size
;
++
i
)
{
int
rng_ind
=
std
::
floor
(
uniform
(
engine
)
*
i
);
int
rng_ind
=
std
::
floor
(
uniform
(
engine
)
*
i
);
if
(
rng_ind
<
num
)
if
(
rng_ind
<
num
)
std
::
iter_swap
(
inds
->
begin
()
+
rng_ind
+
offset
,
std
::
iter_swap
(
inds
->
begin
()
+
rng_ind
+
offset
,
...
...
paddle/fluid/operators/im2sequence_op.cc
浏览文件 @
c9ba51ea
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
limitations under the License. */
#include "paddle/fluid/operators/im2sequence_op.h"
#include "paddle/fluid/operators/im2sequence_op.h"
#include <string>
#include <vector>
#include <vector>
namespace
paddle
{
namespace
paddle
{
...
@@ -28,20 +29,19 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
...
@@ -28,20 +29,19 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
"Input(X) of Im2SequenceOp should not be null."
);
"Input(X) of Im2SequenceOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of Im2SequenceOp op should not be null."
);
"Output(Out) of Im2SequenceOp op should not be null."
);
auto
in_dim
=
ctx
->
GetInputDim
(
"X"
);
auto
in_dim
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE_EQ
(
in_dim
.
size
(),
4
,
PADDLE_ENFORCE_EQ
(
in_dim
.
size
(),
4
,
"Input(X) format must be 4D tensor, eg., NCHW."
);
"Input(X) format must be 4D tensor, eg., NCHW."
);
auto
kernels
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"kernels"
);
auto
strides
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"strides"
);
auto
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
int
batch_size
=
in_dim
[
0
];
int
batch_size
=
in_dim
[
0
];
int
img_channels
=
in_dim
[
1
];
int
img_channels
=
in_dim
[
1
];
int
img_height
=
in_dim
[
2
];
int
img_height
=
in_dim
[
2
];
int
img_width
=
in_dim
[
3
];
int
img_width
=
in_dim
[
3
];
auto
kernels
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"kernels"
);
auto
strides
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"strides"
);
auto
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
int
output_height
=
Im2SeqOutputSize
(
img_height
,
kernels
[
0
],
paddings
[
0
],
int
output_height
=
Im2SeqOutputSize
(
img_height
,
kernels
[
0
],
paddings
[
0
],
paddings
[
2
],
strides
[
0
]);
paddings
[
2
],
strides
[
0
]);
int
output_width
=
Im2SeqOutputSize
(
img_width
,
kernels
[
1
],
paddings
[
1
],
int
output_width
=
Im2SeqOutputSize
(
img_width
,
kernels
[
1
],
paddings
[
1
],
...
@@ -61,6 +61,10 @@ class Im2SequenceOpMaker : public framework::OpProtoAndCheckerMaker {
...
@@ -61,6 +61,10 @@ class Im2SequenceOpMaker : public framework::OpProtoAndCheckerMaker {
"C: channels"
"C: channels"
"H: height"
"H: height"
"W: width"
);
"W: width"
);
AddInput
(
"Y"
,
"(Tensor) The input tensor of image real size(H, W)."
"2-D with shape [batchsize, 2]"
)
.
AsDispensable
();
AddOutput
(
"Out"
,
"(LodTensor) The output data of im2sequence op,"
);
AddOutput
(
"Out"
,
"(LodTensor) The output data of im2sequence op,"
);
AddAttr
<
std
::
vector
<
int
>>
(
"kernels"
,
AddAttr
<
std
::
vector
<
int
>>
(
"kernels"
,
"(vector<int>), the "
"(vector<int>), the "
...
@@ -73,6 +77,13 @@ class Im2SequenceOpMaker : public framework::OpProtoAndCheckerMaker {
...
@@ -73,6 +77,13 @@ class Im2SequenceOpMaker : public framework::OpProtoAndCheckerMaker {
"(vector<int> default:{0, 0, 0, 0}), the "
"(vector<int> default:{0, 0, 0, 0}), the "
"paddings(up_pad, left_pad, down_pad, right_pad)"
)
"paddings(up_pad, left_pad, down_pad, right_pad)"
)
.
SetDefault
({
0
,
0
,
0
,
0
});
.
SetDefault
({
0
,
0
,
0
,
0
});
AddAttr
<
std
::
vector
<
int
>>
(
"out_stride"
,
"the attribute is valid only when input(Y)"
"is not NULL.this attribute represents the"
"scaling of the pic through the CNN"
"(vector<int> dedault:{1,1}),the out_stride"
" (out_stride_height, out_stride_width)"
)
.
SetDefault
({
1
,
1
});
AddComment
(
R"DOC(
AddComment
(
R"DOC(
This op uses kernels to scan images and converts these images to sequences.
This op uses kernels to scan images and converts these images to sequences.
After expanding, The number of time steps are output_height * output_width
After expanding, The number of time steps are output_height * output_width
...
@@ -123,7 +134,7 @@ output.data = [[ 6. 2. 8. 3. 2. 4. 6. 3.]
...
@@ -123,7 +134,7 @@ output.data = [[ 6. 2. 8. 3. 2. 4. 6. 3.]
[ 7. 1. 7. 9. 2. 1. 3. 5.]
[ 7. 1. 7. 9. 2. 1. 3. 5.]
[ 5. 7. 2. 4. 1. 3. 9. 0.]
[ 5. 7. 2. 4. 1. 3. 9. 0.]
[ 7. 9. 4. 8. 3. 5. 0. 8.]]
[ 7. 9. 4. 8. 3. 5. 0. 8.]]
output.dims = {8,
9
}
output.dims = {8,
8
}
output.lod = [[0, 4, 8]]
output.lod = [[0, 4, 8]]
)DOC"
);
)DOC"
);
...
...
paddle/fluid/operators/im2sequence_op.h
浏览文件 @
c9ba51ea
...
@@ -13,6 +13,7 @@
...
@@ -13,6 +13,7 @@
limitations under the License. */
limitations under the License. */
#pragma once
#pragma once
#include <string>
#include <vector>
#include <vector>
#include "paddle/fluid/framework/data_layout.h"
#include "paddle/fluid/framework/data_layout.h"
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/eigen.h"
...
@@ -39,50 +40,106 @@ class Im2SequenceKernel : public framework::OpKernel<T> {
...
@@ -39,50 +40,106 @@ class Im2SequenceKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
const
Tensor
*
in
=
ctx
.
Input
<
Tensor
>
(
"X"
);
const
Tensor
*
in
=
ctx
.
Input
<
Tensor
>
(
"X"
);
LoDTensor
*
out
=
ctx
.
Output
<
LoDTensor
>
(
"Out"
);
LoDTensor
*
out
=
ctx
.
Output
<
LoDTensor
>
(
"Out"
);
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
// TODO(wanghaoshuang): Add layout checker after 'set_layout'
// being available for python API
// PADDLE_ENFORCE_EQ(in->layout(), framework::DataLayout::kNCHW,
// "Input(X) layout must be NCHW");
auto
in_dim
=
in
->
dims
();
auto
in_dim
=
in
->
dims
();
int
batch_size
=
in_dim
[
0
];
int
batch_size
=
in_dim
[
0
];
int
img_channels
=
in_dim
[
1
];
int
img_channels
=
in_dim
[
1
];
int
img_height
=
in_dim
[
2
];
int
img_height
=
in_dim
[
2
];
int
img_width
=
in_dim
[
3
];
int
img_width
=
in_dim
[
3
];
auto
kernels
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"kernels"
);
auto
kernels
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"kernels"
);
auto
strides
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
auto
strides
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
auto
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
auto
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
int
output_height
=
Im2SeqOutputSize
(
img_height
,
kernels
[
0
],
paddings
[
0
],
if
(
ctx
.
HasInput
(
"Y"
)
&&
batch_size
>
1
)
{
paddings
[
2
],
strides
[
0
]);
const
Tensor
*
imgrealsize
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
int
output_width
=
Im2SeqOutputSize
(
img_width
,
kernels
[
1
],
paddings
[
1
],
auto
out_stride
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"out_stride"
);
paddings
[
3
],
strides
[
1
]);
Tensor
cpu_shape_tensor
;
TensorCopySync
(
*
imgrealsize
,
platform
::
CPUPlace
(),
&
cpu_shape_tensor
);
const
std
::
vector
<
int
>
dilations
({
1
,
1
});
std
::
vector
<
int
>
imgreal_h
;
std
::
vector
<
int
>
imgreal_w
;
auto
out_dims
=
out
->
dims
();
std
::
vector
<
int
>
output_height
;
out
->
Resize
({
batch_size
,
out
->
numel
()
/
batch_size
});
std
::
vector
<
int
>
output_width
;
for
(
int
i
=
0
;
i
<
batch_size
;
i
++
)
{
int
result
=
0
;
const
Tensor
src
=
for
(
int
i
=
0
;
i
<
batch_size
;
i
++
)
{
in
->
Slice
(
i
,
i
+
1
).
Resize
({
img_channels
,
img_height
,
img_width
});
int
tmp_real_h
=
static_cast
<
int
>
((
cpu_shape_tensor
.
data
<
T
>
())[
2
*
i
]);
Tensor
dst
=
out
->
Slice
(
i
,
i
+
1
).
Resize
(
int
tmp_real_w
=
{
output_height
,
output_width
,
img_channels
,
kernels
[
0
],
kernels
[
1
]});
static_cast
<
int
>
((
cpu_shape_tensor
.
data
<
T
>
())[
2
*
i
+
1
]);
if
(
tmp_real_h
%
out_stride
[
0
]
==
0
)
{
math
::
Im2ColFunctor
<
math
::
ColFormat
::
kOCF
,
DeviceContext
,
T
>
f
;
tmp_real_h
=
tmp_real_h
/
out_stride
[
0
];
auto
&
dev_ctx
=
ctx
.
template
device_context
<
DeviceContext
>();
}
else
{
f
(
dev_ctx
,
src
,
dilations
,
strides
,
paddings
,
&
dst
);
tmp_real_h
=
tmp_real_h
/
out_stride
[
0
]
+
1
;
}
}
out
->
Resize
(
out_dims
);
if
(
tmp_real_w
%
out_stride
[
1
]
==
0
)
{
tmp_real_w
=
tmp_real_w
/
out_stride
[
1
];
// set lod information
}
else
{
// TODO(wanghaoshuang): Move this to InferShape
tmp_real_w
=
tmp_real_w
/
out_stride
[
1
]
+
1
;
framework
::
LoD
lod
(
1
);
}
lod
[
0
].
reserve
(
batch_size
+
1
);
imgreal_h
.
push_back
(
tmp_real_h
);
for
(
int
i
=
0
,
offset
=
0
;
i
<
batch_size
+
1
;
++
i
)
{
imgreal_w
.
push_back
(
tmp_real_w
);
output_height
.
push_back
(
Im2SeqOutputSize
(
imgreal_h
[
i
],
kernels
[
0
],
paddings
[
0
],
paddings
[
2
],
strides
[
0
]));
output_width
.
push_back
(
Im2SeqOutputSize
(
imgreal_w
[
i
],
kernels
[
1
],
paddings
[
1
],
paddings
[
3
],
strides
[
1
]));
result
+=
output_height
[
i
]
*
output_width
[
i
];
}
out
->
mutable_data
<
T
>
({
result
,
img_channels
*
kernels
[
0
]
*
kernels
[
1
]},
ctx
.
GetPlace
());
const
std
::
vector
<
int
>
dilations
({
1
,
1
});
int
offset_out
=
0
;
for
(
int
i
=
0
;
i
<
batch_size
;
i
++
)
{
const
Tensor
src
=
in
->
Slice
(
i
,
i
+
1
).
Resize
({
img_channels
,
img_height
,
img_width
});
Tensor
dst
=
out
->
Slice
(
offset_out
,
offset_out
+
output_height
[
i
]
*
output_width
[
i
])
.
Resize
({
output_height
[
i
],
output_width
[
i
],
img_channels
,
kernels
[
0
],
kernels
[
1
]});
offset_out
+=
output_height
[
i
]
*
output_width
[
i
];
math
::
Im2ColFunctor
<
math
::
ColFormat
::
kOCF
,
DeviceContext
,
T
>
f
;
auto
&
dev_ctx
=
ctx
.
template
device_context
<
DeviceContext
>();
f
(
dev_ctx
,
src
,
dilations
,
strides
,
paddings
,
&
dst
);
}
framework
::
LoD
lod
(
1
);
lod
[
0
].
reserve
(
batch_size
+
1
);
int
offset
=
0
;
lod
[
0
].
push_back
(
offset
);
for
(
int
i
=
0
;
i
<
batch_size
;
++
i
)
{
offset
+=
output_height
[
i
]
*
output_width
[
i
];
lod
[
0
].
push_back
(
offset
);
}
out
->
set_lod
(
lod
);
}
else
{
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
int
output_height
=
Im2SeqOutputSize
(
img_height
,
kernels
[
0
],
paddings
[
0
],
paddings
[
2
],
strides
[
0
]);
int
output_width
=
Im2SeqOutputSize
(
img_width
,
kernels
[
1
],
paddings
[
1
],
paddings
[
3
],
strides
[
1
]);
const
std
::
vector
<
int
>
dilations
({
1
,
1
});
auto
out_dims
=
out
->
dims
();
out
->
Resize
({
batch_size
,
out
->
numel
()
/
batch_size
});
for
(
int
i
=
0
;
i
<
batch_size
;
i
++
)
{
const
Tensor
src
=
in
->
Slice
(
i
,
i
+
1
).
Resize
({
img_channels
,
img_height
,
img_width
});
Tensor
dst
=
out
->
Slice
(
i
,
i
+
1
).
Resize
({
output_height
,
output_width
,
img_channels
,
kernels
[
0
],
kernels
[
1
]});
math
::
Im2ColFunctor
<
math
::
ColFormat
::
kOCF
,
DeviceContext
,
T
>
f
;
auto
&
dev_ctx
=
ctx
.
template
device_context
<
DeviceContext
>();
f
(
dev_ctx
,
src
,
dilations
,
strides
,
paddings
,
&
dst
);
}
out
->
Resize
(
out_dims
);
framework
::
LoD
lod
(
1
);
lod
[
0
].
reserve
(
batch_size
+
1
);
int
offset
=
0
;
lod
[
0
].
push_back
(
offset
);
lod
[
0
].
push_back
(
offset
);
offset
+=
output_height
*
output_width
;
for
(
int
i
=
0
;
i
<
batch_size
;
++
i
)
{
offset
+=
output_height
*
output_width
;
lod
[
0
].
push_back
(
offset
);
}
out
->
set_lod
(
lod
);
}
}
out
->
set_lod
(
lod
);
}
}
};
};
...
...
paddle/fluid/operators/math/im2col.cc
浏览文件 @
c9ba51ea
...
@@ -43,21 +43,6 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
...
@@ -43,21 +43,6 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
int
col_height
=
col
->
dims
()[
3
];
int
col_height
=
col
->
dims
()[
3
];
int
col_width
=
col
->
dims
()[
4
];
int
col_width
=
col
->
dims
()[
4
];
PADDLE_ENFORCE_EQ
((
im_height
+
padding
[
0
]
+
padding
[
2
]
-
((
dilation
[
0
]
*
(
filter_height
-
1
)
+
1
)))
/
stride
[
0
]
+
1
,
col_height
,
"Output_height and padding(padding_up, padding_down) are "
"inconsistent."
);
PADDLE_ENFORCE_EQ
((
im_width
+
padding
[
1
]
+
padding
[
3
]
-
((
dilation
[
1
]
*
(
filter_width
-
1
)
+
1
)))
/
stride
[
1
]
+
1
,
col_width
,
"Output_height and padding(padding_up, padding_down) are "
"inconsistent."
);
int
channels_col
=
im_channels
*
filter_height
*
filter_width
;
int
channels_col
=
im_channels
*
filter_height
*
filter_width
;
const
T
*
im_data
=
im
.
data
<
T
>
();
const
T
*
im_data
=
im
.
data
<
T
>
();
...
@@ -178,17 +163,6 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
...
@@ -178,17 +163,6 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
int
col_height
=
col
->
dims
()[
0
];
int
col_height
=
col
->
dims
()[
0
];
int
col_width
=
col
->
dims
()[
1
];
int
col_width
=
col
->
dims
()[
1
];
PADDLE_ENFORCE_EQ
(
(
im_height
+
padding
[
0
]
+
padding
[
2
]
-
filter_height
)
/
stride
[
0
]
+
1
,
col_height
,
"Output_height and padding(padding_up, padding_down) are "
"inconsistent."
);
PADDLE_ENFORCE_EQ
(
(
im_width
+
padding
[
1
]
+
padding
[
3
]
-
filter_width
)
/
stride
[
1
]
+
1
,
col_width
,
"col_width and padding(padding_left, padding_right) are "
"inconsistent."
);
const
T
*
im_data
=
im
.
data
<
T
>
();
const
T
*
im_data
=
im
.
data
<
T
>
();
T
*
col_data
=
col
->
data
<
T
>
();
T
*
col_data
=
col
->
data
<
T
>
();
...
...
paddle/fluid/operators/math/im2col.cu
浏览文件 @
c9ba51ea
...
@@ -77,21 +77,6 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
...
@@ -77,21 +77,6 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
int
col_height
=
col
->
dims
()[
3
];
int
col_height
=
col
->
dims
()[
3
];
int
col_width
=
col
->
dims
()[
4
];
int
col_width
=
col
->
dims
()[
4
];
PADDLE_ENFORCE_EQ
((
im_height
+
padding
[
0
]
+
padding
[
2
]
-
(
dilation
[
0
]
*
(
filter_height
-
1
)
+
1
))
/
stride
[
0
]
+
1
,
col_height
,
"Output_height and padding(padding_up, padding_down) are "
"inconsistent."
);
PADDLE_ENFORCE_EQ
((
im_width
+
padding
[
1
]
+
padding
[
3
]
-
(
dilation
[
1
]
*
(
filter_width
-
1
)
+
1
))
/
stride
[
1
]
+
1
,
col_width
,
"col_width and padding(padding_left, padding_right) are "
"inconsistent."
);
int
num_outputs
=
im_channels
*
col_height
*
col_width
;
int
num_outputs
=
im_channels
*
col_height
*
col_width
;
int
blocks
=
(
num_outputs
+
1024
-
1
)
/
1024
;
int
blocks
=
(
num_outputs
+
1024
-
1
)
/
1024
;
int
block_x
=
512
;
int
block_x
=
512
;
...
@@ -274,21 +259,6 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
...
@@ -274,21 +259,6 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
int
col_height
=
col
->
dims
()[
0
];
int
col_height
=
col
->
dims
()[
0
];
int
col_width
=
col
->
dims
()[
1
];
int
col_width
=
col
->
dims
()[
1
];
PADDLE_ENFORCE_EQ
((
im_height
+
padding
[
0
]
+
padding
[
2
]
-
(
dilation
[
0
]
*
(
filter_height
-
1
)
+
1
))
/
stride
[
0
]
+
1
,
col_height
,
"Output_height and padding(padding_up, padding_down) are "
"inconsistent."
);
PADDLE_ENFORCE_EQ
((
im_width
+
padding
[
1
]
+
padding
[
3
]
-
(
dilation
[
1
]
*
(
filter_width
-
1
)
+
1
))
/
stride
[
1
]
+
1
,
col_width
,
"col_width and padding(padding_left, padding_right) are "
"inconsistent."
);
int
block_dim_x
=
0
;
int
block_dim_x
=
0
;
int
block_dim_y
=
0
;
int
block_dim_y
=
0
;
if
(
filter_height
<=
4
&&
filter_width
<=
4
)
{
if
(
filter_height
<=
4
&&
filter_width
<=
4
)
{
...
...
python/paddle/fluid/backward.py
浏览文件 @
c9ba51ea
...
@@ -123,7 +123,8 @@ def _append_grad_suffix_(name):
...
@@ -123,7 +123,8 @@ def _append_grad_suffix_(name):
def
_addup_repetitive_outputs_
(
op_descs
):
def
_addup_repetitive_outputs_
(
op_descs
):
"""
"""
In backward part, an variable may be the output of more than one ops.
In backward part, an variable may be the output of more than one ops.
In this case, the variable should be the accumulation of all the outputs.
And one op may yield its multiple outputs to the same variable.
In these cases, the variable should be the accumulation of all the outputs.
`sum_op`s are added to implement the accumulate.
`sum_op`s are added to implement the accumulate.
"""
"""
pending_sum_ops
=
[]
pending_sum_ops
=
[]
...
@@ -136,29 +137,46 @@ def _addup_repetitive_outputs_(op_descs):
...
@@ -136,29 +137,46 @@ def _addup_repetitive_outputs_(op_descs):
"sum"
,
{
"X"
:
renamed_vars
[
var_name
]},
{
"Out"
:
[
var_name
]},
"sum"
,
{
"X"
:
renamed_vars
[
var_name
]},
{
"Out"
:
[
var_name
]},
{
"use_mkldnn"
:
False
}),
idx
))
{
"use_mkldnn"
:
False
}),
idx
))
renamed_vars
[
var_name
]
=
[
var_name
]
renamed_vars
[
var_name
]
=
[
var_name
]
for
var_name
in
op_desc
.
output_arg_names
():
for
param_idx
,
param_name
in
enumerate
(
op_desc
.
output_names
()):
if
var_name
==
core
.
empty_var_name
(
arg_names
=
op_desc
.
output
(
param_name
)
)
or
var_name
in
op_desc
.
input_arg_names
():
for
arg_idx
,
var_name
in
enumerate
(
arg_names
):
# empty variable or inplace op
if
var_name
==
core
.
empty_var_name
(
continue
)
or
var_name
in
op_desc
.
input_arg_names
():
if
len
(
renamed_vars
[
var_name
])
==
0
:
# empty variable or inplace op
# it's the first time we get the variable
continue
renamed_vars
[
var_name
]
=
[
var_name
]
if
len
(
renamed_vars
[
var_name
])
==
0
:
else
:
# it's the first time we get the variable
if
len
(
renamed_vars
[
var_name
])
==
1
:
renamed_vars
[
var_name
]
=
[
var_name
]
else
:
if
len
(
renamed_vars
[
var_name
])
==
1
:
new_name
=
var_name
+
"@RENAME@"
+
\
str
(
var_rename_count
[
var_name
])
var_rename_count
[
var_name
]
+=
1
# rename original var_name
renamed_vars
[
var_name
][
0
]
=
new_name
_rename_arg_
(
op_descs
,
var_name
,
new_name
,
0
,
idx
)
_rename_arg_
(
pending_sum_ops
,
var_name
,
new_name
)
for
p
in
op_desc
.
output_names
()[:
param_idx
]:
p_arg_names
=
op_desc
.
output
(
p
)
if
var_name
in
p_arg_names
:
op_desc
.
set_output
(
p
,
[
new_name
if
x
==
var_name
else
x
for
x
in
p_arg_names
])
arg_names
=
[
new_name
if
x
==
var_name
else
x
for
x
in
arg_names
[:
arg_idx
]
]
+
arg_names
[
arg_idx
:]
new_name
=
var_name
+
"@RENAME@"
+
\
new_name
=
var_name
+
"@RENAME@"
+
\
str
(
var_rename_count
[
var_name
])
str
(
var_rename_count
[
var_name
])
var_rename_count
[
var_name
]
+=
1
var_rename_count
[
var_name
]
+=
1
# rename original var_name
arg_names
[
arg_idx
]
=
new_name
renamed_vars
[
var_name
][
0
]
=
new_name
op_desc
.
set_output
(
param_name
,
arg_names
)
_rename_arg_
(
op_descs
,
var_name
,
new_name
,
0
,
idx
)
renamed_vars
[
var_name
].
append
(
new_name
)
_rename_arg_
(
pending_sum_ops
,
var_name
,
new_name
)
new_name
=
var_name
+
"@RENAME@"
+
\
str
(
var_rename_count
[
var_name
])
var_rename_count
[
var_name
]
+=
1
op_desc
.
rename_output
(
var_name
,
new_name
)
renamed_vars
[
var_name
].
append
(
new_name
)
for
var_name
,
inputs
in
renamed_vars
.
iteritems
():
for
var_name
,
inputs
in
renamed_vars
.
iteritems
():
if
len
(
inputs
)
>
1
:
if
len
(
inputs
)
>
1
:
pending_sum_ops
.
append
(
pending_sum_ops
.
append
(
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
c9ba51ea
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
# 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.
# Copyright (c ) 2018 PaddlePaddle Authors. All Rights Reserved.
#
#
# Licensed under the Apache License, Version 2.0 (the "License");
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# you may not use this file except in compliance with the License.
...
@@ -3900,7 +3914,13 @@ def transpose(x, perm, name=None):
...
@@ -3900,7 +3914,13 @@ def transpose(x, perm, name=None):
return
out
return
out
def
im2sequence
(
input
,
filter_size
=
1
,
stride
=
1
,
padding
=
0
,
name
=
None
):
def
im2sequence
(
input
,
filter_size
=
1
,
stride
=
1
,
padding
=
0
,
input_image_size
=
None
,
out_stride
=
1
,
name
=
None
):
"""
"""
Extracts image patches from the input tensor to form a tensor of shape
Extracts image patches from the input tensor to form a tensor of shape
{input.batch_size * output_height * output_width, filter_size_H *
{input.batch_size * output_height * output_width, filter_size_H *
...
@@ -3937,6 +3957,15 @@ def im2sequence(input, filter_size=1, stride=1, padding=0, name=None):
...
@@ -3937,6 +3957,15 @@ def im2sequence(input, filter_size=1, stride=1, padding=0, name=None):
padding_up = padding_down = padding_left = padding_right = padding
padding_up = padding_down = padding_left = padding_right = padding
Default: padding = 0.
Default: padding = 0.
input_image_size(Variable): the input contains image real size.It's dim
is [batchsize, 2]. It is dispensable.It is just for batch inference.
out_stride(int|tuple): The scaling of image through CNN. It is
dispensable. It is valid only when input_image_size is not null.
If out_stride is tuple, it must contain two intergers,
(out_stride_H, out_stride_W). Otherwise,
the out_stride_H = out_stride_W = out_stride.
name (int): The name of this layer. It is optional.
name (int): The name of this layer. It is optional.
Returns:
Returns:
...
@@ -3987,7 +4016,7 @@ def im2sequence(input, filter_size=1, stride=1, padding=0, name=None):
...
@@ -3987,7 +4016,7 @@ def im2sequence(input, filter_size=1, stride=1, padding=0, name=None):
[ 5. 7. 2. 4. 1. 3. 9. 0.]
[ 5. 7. 2. 4. 1. 3. 9. 0.]
[ 7. 9. 4. 8. 3. 5. 0. 8.]]
[ 7. 9. 4. 8. 3. 5. 0. 8.]]
output.dims = {8,
9
}
output.dims = {8,
8
}
output.lod = [[4, 4]]
output.lod = [[4, 4]]
...
@@ -4009,18 +4038,17 @@ def im2sequence(input, filter_size=1, stride=1, padding=0, name=None):
...
@@ -4009,18 +4038,17 @@ def im2sequence(input, filter_size=1, stride=1, padding=0, name=None):
if
len
(
padding
)
==
2
:
if
len
(
padding
)
==
2
:
padding
.
append
(
padding
[
0
])
padding
.
append
(
padding
[
0
])
padding
.
append
(
padding
[
1
])
padding
.
append
(
padding
[
1
])
inputs
=
{
"X"
:
input
}
attrs
=
{
"kernels"
:
filter_size
,
"strides"
:
stride
,
"padding"
:
padding
}
if
input_image_size
:
if
isinstance
(
out_stride
,
int
):
out_stride
=
[
out_stride
,
out_stride
]
inputs
[
"Y"
]
=
input_image_size
attrs
[
"out_stride"
]
=
out_stride
helper
=
LayerHelper
(
'im2sequence'
,
**
locals
())
helper
=
LayerHelper
(
'im2sequence'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
helper
.
append_op
(
helper
.
append_op
(
type
=
'im2sequence'
,
type
=
'im2sequence'
,
inputs
=
inputs
,
outputs
=
{
'Out'
:
out
},
attrs
=
attrs
)
inputs
=
{
'X'
:
input
},
outputs
=
{
'Out'
:
out
},
attrs
=
{
'kernels'
:
filter_size
,
'strides'
:
stride
,
'paddings'
:
padding
,
})
return
out
return
out
...
...
python/paddle/fluid/tests/unittests/test_im2sequence_op.py
浏览文件 @
c9ba51ea
...
@@ -16,23 +16,48 @@ import numpy as np
...
@@ -16,23 +16,48 @@ import numpy as np
from
op_test
import
OpTest
from
op_test
import
OpTest
def
get_output_shape
(
attrs
,
in_shape
):
def
get_output_shape
(
attrs
,
in_shape
,
img_real_size
):
batchsize
=
in_shape
[
0
]
img_height
=
in_shape
[
2
]
img_height
=
in_shape
[
2
]
img_width
=
in_shape
[
3
]
img_width
=
in_shape
[
3
]
paddings
=
np
.
array
(
attrs
[
'paddings'
]).
astype
(
"int32"
)
kernels
=
np
.
array
(
attrs
[
'kernels'
]).
astype
(
"int32"
)
strides
=
np
.
array
(
attrs
[
'strides'
]).
astype
(
"int32"
)
output_height
=
np
.
zeros
((
1
,
batchsize
)).
astype
(
"int32"
)
output_width
=
np
.
zeros
((
1
,
batchsize
)).
astype
(
"int32"
)
if
len
(
img_real_size
):
out_stride
=
np
.
array
(
attrs
[
'out_stride'
]).
astype
(
"int32"
)
imgreal_h
=
0
imgreal_w
=
0
for
index
in
range
(
batchsize
):
if
img_real_size
[
index
,
0
]
%
out_stride
[
0
]
==
0
:
imgreal_h
=
img_real_size
[
index
,
0
]
/
out_stride
[
0
]
else
:
imgreal_h
=
img_real_size
[
index
,
0
]
/
out_stride
[
0
]
+
1
if
img_real_size
[
index
,
0
]
%
out_stride
[
1
]
==
0
:
imgreal_w
=
img_real_size
[
index
,
1
]
/
out_stride
[
1
]
else
:
imgreal_w
=
img_real_size
[
index
,
0
]
/
out_stride
[
1
]
+
1
output_height
[
0
,
index
]
=
\
1
+
\
(
imgreal_h
+
paddings
[
0
]
+
paddings
[
2
]
-
kernels
[
0
]
+
strides
[
0
]
-
1
)
/
\
strides
[
0
]
paddings
=
attrs
[
'paddings'
]
output_width
[
0
,
index
]
=
\
kernels
=
attrs
[
'kernels'
]
1
+
\
strides
=
attrs
[
'strides'
]
(
imgreal_w
+
paddings
[
1
]
+
paddings
[
3
]
-
kernels
[
1
]
+
strides
[
1
]
-
1
)
/
\
strides
[
1
]
else
:
for
index
in
range
(
batchsize
):
output_height
[
0
,
index
]
=
\
1
+
\
(
img_height
+
paddings
[
0
]
+
paddings
[
2
]
-
kernels
[
0
]
+
strides
[
0
]
-
1
)
/
\
strides
[
0
]
output_height
=
\
output_width
[
0
,
index
]
=
\
1
+
\
1
+
\
(
img_height
+
paddings
[
0
]
+
paddings
[
2
]
-
kernels
[
0
]
+
strides
[
0
]
-
1
)
/
\
(
img_width
+
paddings
[
1
]
+
paddings
[
3
]
-
kernels
[
1
]
+
strides
[
1
]
-
1
)
/
\
strides
[
0
]
strides
[
1
]
output_width
=
\
1
+
\
(
img_width
+
paddings
[
1
]
+
paddings
[
3
]
-
kernels
[
1
]
+
strides
[
1
]
-
1
)
/
\
strides
[
1
]
return
output_height
,
output_width
return
output_height
,
output_width
...
@@ -75,22 +100,25 @@ def im2col(attrs, im, col):
...
@@ -75,22 +100,25 @@ def im2col(attrs, im, col):
im_row_offset
][
im_col_offset
]
im_row_offset
][
im_col_offset
]
def
Im2Sequence
(
inputs
,
attrs
):
def
Im2Sequence
(
inputs
,
img_real_size
,
attrs
):
output_height
,
output_width
=
get_output_shape
(
attrs
,
inputs
.
shape
)
output_height
,
output_width
=
get_output_shape
(
attrs
,
inputs
.
shape
,
img_real_size
)
img_channels
=
inputs
.
shape
[
1
]
img_channels
=
inputs
.
shape
[
1
]
batch_size
=
inputs
.
shape
[
0
]
batch_size
=
inputs
.
shape
[
0
]
out
=
np
.
zeros
([
out
=
[]
batch_size
,
output_height
,
output_width
,
img_channels
,
for
index
in
range
(
batch_size
):
attrs
[
'kernels'
][
0
],
attrs
[
'kernels'
][
1
]
tmp
=
np
.
zeros
([
]).
astype
(
"float32"
)
output_height
[
0
,
index
],
output_width
[
0
,
index
],
img_channels
,
attrs
[
'kernels'
][
0
],
attrs
[
'kernels'
][
1
]
for
i
in
range
(
len
(
inputs
)):
]).
astype
(
"float32"
)
im2col
(
attrs
,
inputs
[
i
],
out
[
i
])
out
.
append
(
tmp
)
for
index
in
range
(
len
(
inputs
)):
out
=
out
.
reshape
([
im2col
(
attrs
,
inputs
[
index
],
out
[
index
])
batch_size
*
output_height
*
output_width
,
out
[
index
]
=
out
[
index
].
reshape
([
img_channels
*
attrs
[
'kernels'
][
0
]
*
attrs
[
'kernels'
][
1
]
output_height
[
0
,
index
]
*
output_width
[
0
,
index
],
])
img_channels
*
attrs
[
'kernels'
][
0
]
*
attrs
[
'kernels'
][
1
]
])
out
=
np
.
concatenate
(
out
,
axis
=
0
)
return
out
return
out
...
@@ -103,7 +131,7 @@ class TestBlockExpandOp(OpTest):
...
@@ -103,7 +131,7 @@ class TestBlockExpandOp(OpTest):
self
.
attrs
=
{
self
.
attrs
=
{
'kernels'
:
[
2
,
2
],
'kernels'
:
[
2
,
2
],
'strides'
:
[
1
,
1
],
'strides'
:
[
1
,
1
],
'paddings'
:
[
1
,
1
,
1
,
1
]
'paddings'
:
[
1
,
1
,
1
,
1
]
,
}
}
def
setUp
(
self
):
def
setUp
(
self
):
...
@@ -113,7 +141,8 @@ class TestBlockExpandOp(OpTest):
...
@@ -113,7 +141,8 @@ class TestBlockExpandOp(OpTest):
self
.
batch_size
,
self
.
img_channels
,
self
.
img_height
,
self
.
img_width
self
.
batch_size
,
self
.
img_channels
,
self
.
img_height
,
self
.
img_width
]).
astype
(
"float32"
)
]).
astype
(
"float32"
)
out
=
Im2Sequence
(
x
,
self
.
attrs
)
real_size
=
np
.
array
([]).
astype
(
"float32"
)
out
=
Im2Sequence
(
x
,
real_size
,
self
.
attrs
)
self
.
inputs
=
{
'X'
:
x
}
self
.
inputs
=
{
'X'
:
x
}
self
.
outputs
=
{
'Out'
:
out
}
self
.
outputs
=
{
'Out'
:
out
}
...
@@ -133,20 +162,20 @@ class TestBlockExpandOpCase2(TestBlockExpandOp):
...
@@ -133,20 +162,20 @@ class TestBlockExpandOpCase2(TestBlockExpandOp):
self
.
attrs
=
{
self
.
attrs
=
{
'kernels'
:
[
2
,
1
],
'kernels'
:
[
2
,
1
],
'strides'
:
[
2
,
1
],
'strides'
:
[
2
,
1
],
'paddings'
:
[
2
,
1
,
2
,
1
]
'paddings'
:
[
2
,
1
,
2
,
1
]
,
}
}
class
TestBlockExpandOpCase3
(
TestBlockExpandOp
):
class
TestBlockExpandOpCase3
(
TestBlockExpandOp
):
def
config
(
self
):
def
config
(
self
):
self
.
batch_size
=
3
self
.
batch_size
=
2
self
.
img_channels
=
1
self
.
img_channels
=
1
self
.
img_height
=
4
self
.
img_height
=
4
self
.
img_width
=
5
self
.
img_width
=
5
self
.
attrs
=
{
self
.
attrs
=
{
'kernels'
:
[
2
,
1
],
'kernels'
:
[
2
,
1
],
'strides'
:
[
2
,
1
],
'strides'
:
[
2
,
1
],
'paddings'
:
[
2
,
0
,
2
,
0
]
'paddings'
:
[
2
,
0
,
2
,
0
]
,
}
}
...
@@ -159,9 +188,94 @@ class TestBlockExpandOpCase4(TestBlockExpandOp):
...
@@ -159,9 +188,94 @@ class TestBlockExpandOpCase4(TestBlockExpandOp):
self
.
attrs
=
{
self
.
attrs
=
{
'kernels'
:
[
2
,
2
],
'kernels'
:
[
2
,
2
],
'strides'
:
[
1
,
1
],
'strides'
:
[
1
,
1
],
'paddings'
:
[
0
,
0
,
0
,
0
]
'paddings'
:
[
0
,
0
,
0
,
0
],
}
class
TestBlockExpandOpCase5
(
OpTest
):
def
config
(
self
):
self
.
batch_size
=
1
self
.
img_channels
=
3
self
.
img_height
=
4
self
.
img_width
=
5
self
.
attrs
=
{
'kernels'
:
[
2
,
1
],
'strides'
:
[
2
,
1
],
'paddings'
:
[
2
,
1
,
2
,
1
],
'out_stride'
:
[
2
,
2
],
}
def
setUp
(
self
):
self
.
config
()
self
.
op_type
=
"im2sequence"
x
=
np
.
random
.
uniform
(
0.1
,
1
,
[
self
.
batch_size
,
self
.
img_channels
,
self
.
img_height
,
self
.
img_width
]).
astype
(
"float32"
)
real_size
=
np
.
array
([[
8
,
10
],
[
5
,
8
]]).
astype
(
"float32"
)
out
=
np
.
array
(
Im2Sequence
(
x
,
real_size
,
self
.
attrs
))
self
.
inputs
=
{
'X'
:
x
,
'Y'
:
real_size
}
#l ??
self
.
outputs
=
{
'Out'
:
out
}
def
test_check_output
(
self
):
self
.
check_output
()
class
TestBlockExpandOpCase6
(
OpTest
):
def
config
(
self
):
self
.
batch_size
=
3
self
.
img_channels
=
1
self
.
img_height
=
4
self
.
img_width
=
5
self
.
attrs
=
{
'kernels'
:
[
2
,
1
],
'strides'
:
[
1
,
1
],
'paddings'
:
[
0
,
0
,
0
,
0
],
'out_stride'
:
[
1
,
1
],
}
def
setUp
(
self
):
self
.
config
()
self
.
op_type
=
"im2sequence"
x
=
np
.
random
.
uniform
(
0.1
,
1
,
[
self
.
batch_size
,
self
.
img_channels
,
self
.
img_height
,
self
.
img_width
]).
astype
(
"float32"
)
real_size
=
np
.
array
([[
8
,
10
],
[
5
,
8
],
[
5
,
8
]]).
astype
(
"float32"
)
out
=
np
.
array
(
Im2Sequence
(
x
,
real_size
,
self
.
attrs
))
self
.
inputs
=
{
'X'
:
x
,
'Y'
:
real_size
}
#l ??
self
.
outputs
=
{
'Out'
:
out
}
def
test_check_output
(
self
):
self
.
check_output
()
class
TestBlockExpandOpCase7
(
OpTest
):
def
config
(
self
):
self
.
batch_size
=
2
self
.
img_channels
=
2
self
.
img_height
=
3
self
.
img_width
=
3
self
.
attrs
=
{
'kernels'
:
[
2
,
2
],
'strides'
:
[
1
,
1
],
'paddings'
:
[
1
,
0
,
1
,
0
],
'out_stride'
:
[
2
,
2
],
}
}
def
setUp
(
self
):
self
.
config
()
self
.
op_type
=
"im2sequence"
x
=
np
.
random
.
uniform
(
0.1
,
1
,
[
self
.
batch_size
,
self
.
img_channels
,
self
.
img_height
,
self
.
img_width
]).
astype
(
"float32"
)
real_size
=
np
.
array
([[
6
,
6
],
[
4
,
4
]]).
astype
(
"float32"
)
out
=
np
.
array
(
Im2Sequence
(
x
,
real_size
,
self
.
attrs
))
self
.
inputs
=
{
'X'
:
x
,
'Y'
:
real_size
}
self
.
outputs
=
{
'Out'
:
out
}
def
test_check_output
(
self
):
self
.
check_output
()
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
unittest
.
main
()
unittest
.
main
()
#set shiftwidth=4 set expandtab set tabstop=4
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @
c9ba51ea
...
@@ -251,12 +251,16 @@ class TestBook(unittest.TestCase):
...
@@ -251,12 +251,16 @@ class TestBook(unittest.TestCase):
print
(
str
(
program
))
print
(
str
(
program
))
def
test_im2sequence
(
self
):
def
test_im2sequence
(
self
):
print
(
"test_im2sequence"
)
program
=
Program
()
program
=
Program
()
with
program_guard
(
program
):
with
program_guard
(
program
):
x
=
layers
.
data
(
name
=
'x'
,
shape
=
[
3
,
128
,
128
],
dtype
=
'float32'
)
x
=
layers
.
data
(
name
=
'x'
,
shape
=
[
3
,
128
,
128
],
dtype
=
'float32'
)
y
=
layers
.
data
(
name
=
'y'
,
shape
=
[],
dtype
=
'float32'
)
output
=
layers
.
im2sequence
(
output
=
layers
.
im2sequence
(
input
=
x
,
stride
=
[
1
,
1
],
filter_size
=
[
2
,
2
])
input
=
x
,
input_image_size
=
y
,
stride
=
[
1
,
1
],
filter_size
=
[
2
,
2
],
out_stride
=
[
1
,
1
])
self
.
assertIsNotNone
(
output
)
self
.
assertIsNotNone
(
output
)
print
(
str
(
program
))
print
(
str
(
program
))
...
...
python/setup.py.in
浏览文件 @
c9ba51ea
...
@@ -181,6 +181,14 @@ else:
...
@@ -181,6 +181,14 @@ else:
command = "patchelf --set-rpath '$ORIGIN/../libs/' ${PADDLE_BINARY_DIR}/python/paddle/fluid/core.so"
command = "patchelf --set-rpath '$ORIGIN/../libs/' ${PADDLE_BINARY_DIR}/python/paddle/fluid/core.so"
if os.system(command) != 0:
if os.system(command) != 0:
raise Exception("patch core.so failed, command: %s" % command)
raise Exception("patch core.so failed, command: %s" % command)
if '${WITH_FLUID_ONLY}'== 'OFF':
# change rpath of _swig_paddle.so.
if "@APPLE@" == "1":
command = "install_name_tool -id \"@loader_path/../paddle/libs/\" ${PADDLE_BINARY_DIR}/python/py_paddle/_swig_paddle.so"
else:
command = "patchelf --set-rpath '$ORIGIN/../paddle/libs/' ${PADDLE_BINARY_DIR}/python/py_paddle/_swig_paddle.so"
if os.system(command) != 0:
raise Exception("patch _swig_paddle.so failed, command: %s" % command)
setup(name='${PACKAGE_NAME}',
setup(name='${PACKAGE_NAME}',
version='${PADDLE_VERSION}',
version='${PADDLE_VERSION}',
...
...
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