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体验新版 GitCode,发现更多精彩内容 >>
提交
2099b4ce
编写于
5月 17, 2018
作者:
E
eclipsess
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
use LOG instead of cout
上级
722d8a59
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
81 addition
and
106 deletion
+81
-106
src/io.cpp
src/io.cpp
+1
-1
test/elementwise_add_op_test.h
test/elementwise_add_op_test.h
+28
-41
test/mul_op_test.h
test/mul_op_test.h
+52
-64
未找到文件。
src/io.cpp
浏览文件 @
2099b4ce
...
...
@@ -17,7 +17,7 @@ SOFTWARE.
==============================================================================*/
#include <fstream>
#include <iostream>
//
#include <iostream>
#include "common/log.h"
#include "framework/framework.pb.h"
...
...
test/elementwise_add_op_test.h
浏览文件 @
2099b4ce
...
...
@@ -34,12 +34,12 @@ namespace paddle_mobile {
const
std
::
vector
<
std
::
shared_ptr
<
BlockDesc
>>
blocks
=
to_predict_program_
->
Blocks
();
//
std::cout << " **block size " << blocks.size() << std::endl
;
//
DLOG << " **block size " << blocks.size()
;
for
(
int
i
=
0
;
i
<
blocks
.
size
();
++
i
)
{
std
::
shared_ptr
<
BlockDesc
>
block_desc
=
blocks
[
i
];
std
::
vector
<
std
::
shared_ptr
<
OpDesc
>>
ops
=
block_desc
->
Ops
();
//
std::cout << " ops " << ops.size() << std::endl
;
//
DLOG << " ops " << ops.size()
;
for
(
int
j
=
0
;
j
<
ops
.
size
();
++
j
)
{
std
::
shared_ptr
<
OpDesc
>
op
=
ops
[
j
];
// if (op->Type() ==
...
...
@@ -47,35 +47,26 @@ namespace paddle_mobile {
// if
// (op->GetAttrMap().at("axis").Get<int>()
// != -1) {
// std::cout
// << "attr: axis = "
// <<
// op->GetAttrMap().at("axis").Get<int>()
// << std::endl;
// DLOG << "attr: axis =
// "
// <<
// op->GetAttrMap().at("axis").Get<int>();
// }
// }
//
std::cout << "op:" << op->Type() << std::endl
;
//
DLOG << "op:" << op->Type()
;
if
(
op
->
Type
()
==
"elementwise_add"
&&
op
->
Input
(
"X"
)[
0
]
==
"batch_norm_2.tmp_2"
)
{
std
::
cout
<<
" elementwise_add attr size: "
<<
op
->
GetAttrMap
().
size
()
<<
std
::
endl
;
std
::
cout
<<
" inputs size: "
<<
op
->
GetInputs
().
size
()
<<
std
::
endl
;
std
::
cout
<<
" outputs size: "
<<
op
->
GetOutputs
().
size
()
<<
std
::
endl
;
std
::
cout
<<
" Input X is : "
<<
op
->
Input
(
"X"
)[
0
]
<<
std
::
endl
;
std
::
cout
<<
" Input Y is : "
<<
op
->
Input
(
"Y"
)[
0
]
<<
std
::
endl
;
std
::
cout
<<
" Output Out is : "
<<
op
->
Output
(
"Out"
)[
0
]
<<
std
::
endl
;
DLOG
<<
" elementwise_add attr size: "
<<
op
->
GetAttrMap
().
size
();
DLOG
<<
" inputs size: "
<<
op
->
GetInputs
().
size
();
DLOG
<<
" outputs size: "
<<
op
->
GetOutputs
().
size
();
DLOG
<<
" Input X is : "
<<
op
->
Input
(
"X"
)[
0
];
DLOG
<<
" Input Y is : "
<<
op
->
Input
(
"Y"
)[
0
];
DLOG
<<
" Output Out is : "
<<
op
->
Output
(
"Out"
)[
0
];
Attribute
axis_attr
=
op
->
GetAttrMap
().
at
(
"axis"
);
int
axis
=
axis_attr
.
Get
<
int
>
();
std
::
cout
<<
" Attr axis is : "
<<
axis
<<
std
::
endl
;
DLOG
<<
" Attr axis is : "
<<
axis
;
std
::
shared_ptr
<
operators
::
ElementwiseAddOp
<
Dtype
,
float
>>
...
...
@@ -104,10 +95,8 @@ namespace paddle_mobile {
Variable
*
con_output
=
scope
->
Var
(
"elementwise_add_0.tmp_0"
);
Tensor
*
output_tensor
=
con_output
->
GetMutable
<
Tensor
>
();
output_tensor
->
mutable_data
<
float
>
({
1
,
3
,
224
,
224
});
// std::cout << typeid(output_tensor).name() << std::endl;
// std::cout << "output_tensor dims: " << output_tensor->dims()
// <<
// std::endl;
// DLOG << typeid(output_tensor).name();
// DLOG << "output_tensor dims: " << output_tensor->dims();
std
::
shared_ptr
<
Tensor
>
out_tensor
=
std
::
make_shared
<
LoDTensor
>
();
...
...
@@ -131,7 +120,7 @@ namespace paddle_mobile {
for
(
int
j
=
0
;
j
<
ops_of_block_
[
*
to_predict_block
.
get
()].
size
();
++
j
)
{
auto
op
=
ops_of_block_
[
*
to_predict_block
.
get
()][
j
];
std
::
cout
<<
"op -> run()"
<<
std
::
endl
;
DLOG
<<
"op -> run()"
;
op
->
Run
();
}
}
...
...
@@ -142,8 +131,8 @@ namespace paddle_mobile {
namespace
test
{
void
testElementwiseAdd
()
{
std
::
cout
<<
"----------**********----------"
<<
std
::
endl
;
std
::
cout
<<
"begin to run ElementAddOp Test"
<<
std
::
endl
;
DLOG
<<
"----------**********----------"
;
DLOG
<<
"begin to run ElementAddOp Test"
;
paddle_mobile
::
Loader
<
paddle_mobile
::
CPU
>
loader
;
auto
program
=
loader
.
Load
(
std
::
string
(
"../../test/models/"
...
...
@@ -165,18 +154,16 @@ namespace paddle_mobile {
auto
output_add
=
testElementwiseAddOp
.
predict_add
(
inputx
,
inputy
);
float
*
output_add_ptr
=
output_add
->
data
<
float
>
();
for
(
int
j
=
0
;
j
<
output_add
->
numel
();
++
j
)
{
// std::cout << "value of output: " << output_add_ptr[j] <<
// std::endl;
}
// for (int j = 0; j < output_add->numel(); ++j) {
// DLOG << "value of output: " << output_add_ptr[j];
// }
/// output (1,3,224,224)
std
::
cout
<<
"output memory size : "
<<
output_add
->
memory_size
()
<<
std
::
endl
;
std
::
cout
<<
"output numel : "
<<
output_add
->
numel
()
<<
std
::
endl
;
DLOG
<<
"output memory size : "
<<
output_add
->
memory_size
();
DLOG
<<
"output numel : "
<<
output_add
->
numel
();
std
::
cout
<<
inputx_ptr
[
226
]
<<
" + "
<<
inputy_ptr
[
2
]
<<
" = "
<<
output_add_ptr
[
226
]
<<
std
::
endl
;
DLOG
<<
inputx_ptr
[
226
]
<<
" + "
<<
inputy_ptr
[
2
]
<<
" = "
<<
output_add_ptr
[
226
]
;
}
}
// namespace test
}
// namespace paddle_mobile
test/mul_op_test.h
浏览文件 @
2099b4ce
...
...
@@ -34,57 +34,47 @@ namespace paddle_mobile {
const
std
::
vector
<
std
::
shared_ptr
<
BlockDesc
>>
blocks
=
to_predict_program_
->
Blocks
();
//
std::cout << " **block size " << blocks.size() << std::endl
;
//
DLOG << " **block size " << blocks.size()
;
for
(
int
i
=
0
;
i
<
blocks
.
size
();
++
i
)
{
std
::
shared_ptr
<
BlockDesc
>
block_desc
=
blocks
[
i
];
std
::
vector
<
std
::
shared_ptr
<
OpDesc
>>
ops
=
block_desc
->
Ops
();
//
std::cout << " ops " << ops.size() << std::endl
;
//
DLOG << " ops " << ops.size()
;
for
(
int
j
=
0
;
j
<
ops
.
size
();
++
j
)
{
std
::
shared_ptr
<
OpDesc
>
op
=
ops
[
j
];
if
(
op
->
Type
()
==
"mul"
)
{
std
::
cout
<<
"x_num_col_dims : "
<<
op
->
GetAttrMap
()
.
at
(
"x_num_col_dims"
)
.
Get
<
int
>
(
)
<<
std
::
endl
;
std
::
cout
<<
"y_num_col_dims : "
<<
op
->
GetAttrMap
()
.
at
(
"y_num_col_dims"
)
.
Get
<
int
>
(
)
<<
std
::
endl
;
std
::
cout
<<
" Input X is : "
<<
op
->
Input
(
"X"
)[
0
]
<<
std
::
endl
;
}
//
std::cout << "op:" << op->Type() << std::endl
;
//
if (op->Type() == "mul") {
// DLOG << "x_num_col_dims :
// "
// << op->GetAttrMap(
)
// .at("x_num_col_dims"
)
// .Get<int>()
;
// DLOG << "y_num_col_dims :
// "
// << op->GetAttrMap(
)
// .at("y_num_col_dims"
)
// .Get<int>()
;
// DLOG << " Input X is : "
// << op->Input("X")[0]
;
//
}
//
DLOG << "op:" << op->Type()
;
if
(
op
->
Type
()
==
"mul"
&&
op
->
Input
(
"X"
)[
0
]
==
"pool2d_0.tmp_0"
)
{
std
::
cout
<<
" mul attr size: "
<<
op
->
GetAttrMap
().
size
()
<<
std
::
endl
;
std
::
cout
<<
" inputs size: "
<<
op
->
GetInputs
().
size
()
<<
std
::
endl
;
std
::
cout
<<
" outputs size: "
<<
op
->
GetOutputs
().
size
()
<<
std
::
endl
;
std
::
cout
<<
" Input X is : "
<<
op
->
Input
(
"X"
)[
0
]
<<
std
::
endl
;
std
::
cout
<<
" Input Y is : "
<<
op
->
Input
(
"Y"
)[
0
]
<<
std
::
endl
;
std
::
cout
<<
" Output Out is : "
<<
op
->
Output
(
"Out"
)[
0
]
<<
std
::
endl
;
std
::
cout
<<
"x_num_col_dims : "
<<
op
->
GetAttrMap
()
.
at
(
"x_num_col_dims"
)
.
Get
<
int
>
()
<<
std
::
endl
;
std
::
cout
<<
"y_num_col_dims : "
<<
op
->
GetAttrMap
()
.
at
(
"y_num_col_dims"
)
.
Get
<
int
>
()
<<
std
::
endl
;
DLOG
<<
" mul attr size: "
<<
op
->
GetAttrMap
().
size
();
DLOG
<<
" inputs size: "
<<
op
->
GetInputs
().
size
();
DLOG
<<
" outputs size: "
<<
op
->
GetOutputs
().
size
();
DLOG
<<
" Input X is : "
<<
op
->
Input
(
"X"
)[
0
];
DLOG
<<
" Input Y is : "
<<
op
->
Input
(
"Y"
)[
0
];
DLOG
<<
" Output Out is : "
<<
op
->
Output
(
"Out"
)[
0
];
DLOG
<<
"x_num_col_dims : "
<<
op
->
GetAttrMap
()
.
at
(
"x_num_col_dims"
)
.
Get
<
int
>
();
DLOG
<<
"y_num_col_dims : "
<<
op
->
GetAttrMap
()
.
at
(
"y_num_col_dims"
)
.
Get
<
int
>
();
std
::
shared_ptr
<
operators
::
MulOp
<
Dtype
,
float
>>
add
=
std
::
make_shared
<
...
...
@@ -112,9 +102,8 @@ namespace paddle_mobile {
Variable
*
con_output
=
scope
->
Var
(
"fc_0.tmp_0"
);
Tensor
*
output_tensor
=
con_output
->
GetMutable
<
Tensor
>
();
output_tensor
->
mutable_data
<
float
>
({
3
,
3
});
// std::cout << typeid(output_tensor).name() << std::endl;
// std::cout << "output_tensor dims: " << output_tensor->dims()
// << std::endl;
// DLOG << typeid(output_tensor).name();
// DLOG << "output_tensor dims: " << output_tensor->dims();
std
::
shared_ptr
<
Tensor
>
out_tensor
=
std
::
make_shared
<
LoDTensor
>
();
...
...
@@ -138,7 +127,7 @@ namespace paddle_mobile {
for
(
int
j
=
0
;
j
<
ops_of_block_
[
*
to_predict_block
.
get
()].
size
();
++
j
)
{
auto
op
=
ops_of_block_
[
*
to_predict_block
.
get
()][
j
];
std
::
cout
<<
"op -> run()"
<<
std
::
endl
;
DLOG
<<
"op -> run()"
;
op
->
Run
();
}
}
...
...
@@ -149,8 +138,8 @@ namespace paddle_mobile {
namespace
test
{
void
testMul
()
{
std
::
cout
<<
"----------**********----------"
<<
std
::
endl
;
std
::
cout
<<
"begin to run MulOp Test"
<<
std
::
endl
;
DLOG
<<
"----------**********----------"
;
DLOG
<<
"begin to run MulOp Test"
;
paddle_mobile
::
Loader
<
paddle_mobile
::
CPU
>
loader
;
auto
program
=
loader
.
Load
(
std
::
string
(
"../../test/models/"
...
...
@@ -175,40 +164,39 @@ namespace paddle_mobile {
float
*
output_mul_ptr
=
output_mul
->
data
<
float
>
();
auto
dimx_1
=
inputx
.
numel
()
/
inputx
.
dims
()[
0
];
std
::
cout
<<
"inputx : "
<<
std
::
endl
;
DLOG
<<
" inputx : "
;
for
(
int
i
=
0
;
i
<
inputx
.
dims
()[
0
];
++
i
)
{
for
(
int
j
=
0
;
j
<
dimx_1
;
++
j
)
{
std
::
cout
<<
inputx_ptr
[
i
*
dimx_1
+
j
]
<<
" "
;
DLOGF
(
"%f "
,
inputx_ptr
[
i
*
dimx_1
+
j
])
;
}
std
::
cout
<<
std
::
endl
;
DLOGF
(
"
\n
"
)
;
}
auto
dimy_1
=
inputy
.
numel
()
/
inputy
.
dims
()[
0
];
std
::
cout
<<
"inputy : "
<<
std
::
endl
;
DLOG
<<
" inputy : "
;
for
(
int
i
=
0
;
i
<
inputy
.
dims
()[
0
];
++
i
)
{
for
(
int
j
=
0
;
j
<
dimy_1
;
++
j
)
{
std
::
cout
<<
inputy_ptr
[
i
*
dimy_1
+
j
]
<<
" "
;
DLOGF
(
"%f "
,
inputy_ptr
[
i
*
dimx_1
+
j
])
;
}
std
::
cout
<<
std
::
endl
;
DLOGF
(
"
\n
"
)
;
}
auto
dim_output_1
=
output_mul
->
numel
()
/
output_mul
->
dims
()[
0
];
std
::
cout
<<
"output : "
<<
std
::
endl
;
DLOG
<<
" output : "
;
for
(
int
i
=
0
;
i
<
output_mul
->
dims
()[
0
];
++
i
)
{
for
(
int
j
=
0
;
j
<
dim_output_1
;
++
j
)
{
std
::
cout
<<
output_mul_ptr
[
i
*
dimy_1
+
j
]
<<
" "
;
DLOGF
(
"%f "
,
output_mul_ptr
[
i
*
dimy_1
+
j
])
;
}
std
::
cout
<<
std
::
endl
;
DLOGF
(
"
\n
"
)
;
}
/// output (3,3)
std
::
cout
<<
"output memory size : "
<<
output_mul
->
memory_size
()
<<
std
::
endl
;
std
::
cout
<<
"output numel : "
<<
output_mul
->
numel
()
<<
std
::
endl
;
DLOG
<<
"output memory size : "
<<
output_mul
->
memory_size
();
DLOG
<<
"output numel : "
<<
output_mul
->
numel
();
std
::
cout
<<
inputx_ptr
[
0
]
<<
" x "
<<
inputy_ptr
[
0
]
<<
" + "
<<
inputx_ptr
[
1
]
<<
" x "
<<
inputy_ptr
[
0
+
3
]
<<
" = "
<<
output_mul_ptr
[
0
]
<<
std
::
endl
;
DLOG
<<
inputx_ptr
[
0
]
<<
" x "
<<
inputy_ptr
[
0
]
<<
" + "
<<
inputx_ptr
[
1
]
<<
" x "
<<
inputy_ptr
[
0
+
3
]
<<
" = "
<<
output_mul_ptr
[
0
]
;
}
}
// namespace test
}
// namespace paddle_mobile
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