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
OPTHREE
Paddle
提交
55115ac6
P
Paddle
项目概览
OPTHREE
/
Paddle
与 Fork 源项目一致
Fork自
PaddlePaddle / Paddle
通知
1
Star
1
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
1
列表
看板
标记
里程碑
合并请求
0
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
Issue
1
列表
看板
标记
里程碑
合并请求
0
合并请求
0
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 >>
提交
55115ac6
编写于
7月 26, 2017
作者:
Y
Yu Yang
提交者:
GitHub
7月 26, 2017
浏览文件
操作
浏览文件
下载
差异文件
Merge pull request #3067 from reyoung/make_network_op
Make network op
上级
89512dff
e0463acf
变更
30
显示空白变更内容
内联
并排
Showing
30 changed file
with
247 addition
and
318 deletion
+247
-318
paddle/framework/CMakeLists.txt
paddle/framework/CMakeLists.txt
+1
-3
paddle/framework/net.cc
paddle/framework/net.cc
+4
-12
paddle/framework/net.h
paddle/framework/net.h
+5
-19
paddle/framework/net_op_test.cc
paddle/framework/net_op_test.cc
+15
-22
paddle/framework/net_proto.proto
paddle/framework/net_proto.proto
+0
-15
paddle/framework/operator.h
paddle/framework/operator.h
+8
-6
paddle/operators/add_op.cc
paddle/operators/add_op.cc
+12
-17
paddle/operators/add_op.cu
paddle/operators/add_op.cu
+2
-3
paddle/operators/add_op.h
paddle/operators/add_op.h
+8
-11
paddle/operators/cross_entropy_op.cc
paddle/operators/cross_entropy_op.cc
+11
-17
paddle/operators/cross_entropy_op.cu
paddle/operators/cross_entropy_op.cu
+1
-3
paddle/operators/cross_entropy_op.h
paddle/operators/cross_entropy_op.h
+6
-8
paddle/operators/fc_op.cc
paddle/operators/fc_op.cc
+17
-22
paddle/operators/mul_op.cc
paddle/operators/mul_op.cc
+12
-17
paddle/operators/mul_op.cu
paddle/operators/mul_op.cu
+1
-4
paddle/operators/mul_op.h
paddle/operators/mul_op.h
+9
-12
paddle/operators/rowwise_add_op.cc
paddle/operators/rowwise_add_op.cc
+9
-15
paddle/operators/rowwise_add_op.cu
paddle/operators/rowwise_add_op.cu
+2
-4
paddle/operators/rowwise_add_op.h
paddle/operators/rowwise_add_op.h
+9
-11
paddle/operators/sgd_op.cc
paddle/operators/sgd_op.cc
+8
-13
paddle/operators/sgd_op.cu
paddle/operators/sgd_op.cu
+1
-3
paddle/operators/sgd_op.h
paddle/operators/sgd_op.h
+8
-12
paddle/operators/sigmoid_op.cc
paddle/operators/sigmoid_op.cc
+12
-20
paddle/operators/sigmoid_op.cu
paddle/operators/sigmoid_op.cu
+1
-3
paddle/operators/sigmoid_op.h
paddle/operators/sigmoid_op.h
+7
-9
paddle/operators/softmax_op.cc
paddle/operators/softmax_op.cc
+10
-17
paddle/operators/softmax_op.cu
paddle/operators/softmax_op.cu
+1
-2
paddle/operators/softmax_op.h
paddle/operators/softmax_op.h
+7
-9
paddle/operators/type_alias.h
paddle/operators/type_alias.h
+51
-0
paddle/pybind/pybind.cc
paddle/pybind/pybind.cc
+9
-9
未找到文件。
paddle/framework/CMakeLists.txt
浏览文件 @
55115ac6
...
...
@@ -29,7 +29,5 @@ py_proto_compile(framework_py_proto SRCS attr_type.proto op_proto.proto op_desc.
add_custom_target
(
framework_py_proto_init ALL COMMAND
${
CMAKE_COMMAND
}
-E touch __init__.py
)
add_dependencies
(
framework_py_proto framework_py_proto_init
)
proto_library
(
net_proto SRCS net_proto.proto DEPS op_proto
)
# cc_library(net SRCS net.cc DEPS operator net_proto op_registry fc_op)
cc_library
(
net SRCS net.cc DEPS operator net_proto op_registry
)
cc_library
(
net SRCS net.cc DEPS op_registry
)
cc_test
(
net_op_test SRCS net_op_test.cc DEPS net add_op mul_op sigmoid_op softmax_op fc_op
)
paddle/framework/net.cc
浏览文件 @
55115ac6
...
...
@@ -20,17 +20,7 @@
namespace
paddle
{
namespace
framework
{
std
::
shared_ptr
<
PlainNet
>
AddBackwardOp
(
std
::
shared_ptr
<
PlainNet
>
ForwardOps
)
{
auto
grad_ops
=
std
::
make_shared
<
PlainNet
>
();
for
(
auto
&
op
:
ForwardOps
->
ops_
)
{
auto
op_grad
=
OpRegistry
::
CreateGradOp
(
op
);
grad_ops
->
AddOp
(
op_grad
);
}
grad_ops
->
CompleteAddOp
();
return
grad_ops
;
}
void
PlainNet
::
CompleteAddOp
(
bool
calc
)
{
void
NetOp
::
CompleteAddOp
(
bool
calc
)
{
add_op_done_
=
true
;
if
(
!
calc
)
return
;
std
::
unordered_set
<
std
::
string
>
input_set
;
...
...
@@ -70,7 +60,7 @@ void PlainNet::CompleteAddOp(bool calc) {
attrs_
[
"temporary_index"
]
=
tmp_index
;
}
std
::
string
PlainNet
::
DebugString
()
const
{
std
::
string
NetOp
::
DebugString
()
const
{
std
::
ostringstream
os
;
os
<<
OperatorBase
::
DebugString
()
<<
std
::
endl
;
for
(
auto
&
op
:
ops_
)
{
...
...
@@ -82,5 +72,7 @@ std::string PlainNet::DebugString() const {
return
os
.
str
();
}
bool
NetOp
::
IsNetOp
()
const
{
return
true
;
}
}
// namespace framework
}
// namespace paddle
paddle/framework/net.h
浏览文件 @
55115ac6
...
...
@@ -37,21 +37,7 @@ namespace framework {
* This is the base class of network, all the networks should implement the APIs
* it defines.
*/
class
Net
:
public
OperatorBase
{
public:
virtual
void
AddOp
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
)
=
0
;
virtual
void
CompleteAddOp
(
bool
calc
)
=
0
;
};
using
NetPtr
=
std
::
shared_ptr
<
Net
>
;
/**
* @brief a basic implementation of Net.
*
* PlainNet is a very simple Net, it create a list of operators, and run them
* sequentially following the order they added.
*/
class
PlainNet
:
public
Net
{
class
NetOp
:
public
OperatorBase
{
public:
/**
* Infer all the operators' input and output variables' shapes, will be called
...
...
@@ -80,15 +66,17 @@ class PlainNet : public Net {
/**
* @brief Add an operator by ptr
*/
void
AddOp
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
)
override
{
void
AddOp
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
)
{
PADDLE_ENFORCE
(
!
add_op_done_
,
"Cannot AddOp when this network is sealed"
);
ops_
.
push_back
(
op
);
}
void
CompleteAddOp
(
bool
calculate
=
true
)
override
;
void
CompleteAddOp
(
bool
calculate
=
true
);
std
::
string
DebugString
()
const
override
;
bool
IsNetOp
()
const
override
;
std
::
vector
<
std
::
shared_ptr
<
OperatorBase
>>
ops_
;
private:
...
...
@@ -100,7 +88,5 @@ class PlainNet : public Net {
}
};
std
::
shared_ptr
<
PlainNet
>
AddBackwardOp
(
std
::
shared_ptr
<
PlainNet
>
ForwardOps
);
}
// namespace framework
}
// namespace paddle
paddle/framework/net_op_test.cc
浏览文件 @
55115ac6
...
...
@@ -40,7 +40,7 @@ void AssertSameVectorWithoutOrder(const std::vector<T>& expected,
}
TEST
(
OpKernel
,
all
)
{
auto
net
=
std
::
make_shared
<
PlainNet
>
();
auto
net
=
std
::
make_shared
<
NetOp
>
();
ASSERT_NE
(
net
,
nullptr
);
auto
op1
=
std
::
make_shared
<
TestOp
>
();
...
...
@@ -71,28 +71,21 @@ TEST(OpKernel, all) {
ASSERT_EQ
(
2
,
run_cnt
);
ASSERT_THROW
(
net
->
AddOp
(
op2
),
paddle
::
platform
::
EnforceNotMet
);
}
TEST
(
AddBackwardOp
,
TestGradOp
)
{
auto
net
=
std
::
make_shared
<
PlainNet
>
();
ASSERT_NE
(
net
,
nullptr
);
net
->
AddOp
(
framework
::
OpRegistry
::
CreateOp
(
"mul"
,
{
"X"
,
"Y"
},
{
"Out"
},
{}));
net
->
AddOp
(
framework
::
OpRegistry
::
CreateOp
(
"add_two"
,
{
"X"
,
"Y"
},
{
"Out"
},
{}));
net
->
AddOp
(
framework
::
OpRegistry
::
CreateOp
(
"add_two"
,
{
"X"
,
"Y"
},
{
""
},
{}));
auto
grad_ops
=
AddBackwardOp
(
net
);
for
(
auto
&
op
:
grad_ops
->
ops_
)
{
op
->
DebugString
();
}
}
//
TODO(zhihong): add fc grad without registering
.
// TEST(AddBackwardOp, Test
No
GradOp) {
//
auto net = std::make_shared<PlainNet
>();
//
! TODO(yuyang18): Refine Backward Op
.
// TEST(AddBackwardOp, TestGradOp) {
//
auto net = std::make_shared<NetOp
>();
// ASSERT_NE(net, nullptr);
// net->AddOp(framework::OpRegistry::CreateOp("fc", {"X", "W", "b"}, {"Y"},
// {})); auto grad_ops = AddBackwardOp(net); for (auto& op : grad_ops->ops_) {
// net->AddOp(framework::OpRegistry::CreateOp("mul", {"X", "Y"}, {"Out"}, {}));
// net->AddOp(
// framework::OpRegistry::CreateOp("add_two", {"X", "Y"}, {"Out"}, {}));
// net->AddOp(framework::OpRegistry::CreateOp("add_two", {"X", "Y"}, {""},
// {}));
// auto grad_ops = AddBackwardOp(net);
// for (auto& op : grad_ops->ops_) {
// op->DebugString();
// }
//
}
//}
}
// namespace framework
}
// namespace paddle
paddle/framework/net_proto.proto
已删除
100644 → 0
浏览文件 @
89512dff
syntax
=
"proto2"
;
package
paddle
.
framework
;
import
"op_proto.proto"
;
message
NetDesc
{
// network identification
optional
string
name
=
1
;
// operator contains in network
repeated
OpProto
operators
=
2
;
// network type to run with. e.g "plainNet", "DAG"
optional
string
net_type
=
3
;
// num worker always
optional
int32
num_workers
=
4
;
}
paddle/framework/operator.h
浏览文件 @
55115ac6
...
...
@@ -90,15 +90,17 @@ class OperatorBase {
virtual
void
Run
(
const
std
::
shared_ptr
<
Scope
>&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
=
0
;
// Get a input with argument's name described in `op_proto`
virtual
bool
IsNetOp
()
const
{
return
false
;
}
//! Get a input with argument's name described in `op_proto`
const
std
::
string
&
Input
(
const
std
::
string
&
name
)
const
;
// Get a input which has multiple variables.
// TODO add a vector_view to prevent memory copy.
//
!
Get a input which has multiple variables.
//
!
TODO add a vector_view to prevent memory copy.
std
::
vector
<
std
::
string
>
Inputs
(
const
std
::
string
&
name
)
const
;
// Get a output with argument's name described in `op_proto`
//
!
Get a output with argument's name described in `op_proto`
const
std
::
string
&
Output
(
const
std
::
string
&
name
)
const
;
// Get an output which has multiple variables.
// TODO add a vector_view to prevent memory copy.
//
!
Get an output which has multiple variables.
//
!
TODO add a vector_view to prevent memory copy.
std
::
vector
<
std
::
string
>
Outputs
(
const
std
::
string
&
name
)
const
;
public:
...
...
paddle/operators/add_op.cc
浏览文件 @
55115ac6
...
...
@@ -13,17 +13,14 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/add_op.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/tensor.h"
namespace
paddle
{
namespace
operators
{
class
AddOp
:
public
framework
::
OperatorWithKernel
{
class
AddOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{
PADDLE_ENFORCE
(
inputs
.
size
()
==
2
,
"Input size of AddOp must be two"
);
PADDLE_ENFORCE
(
outputs
.
size
()
==
1
,
"Output size of AddOp must be one"
);
PADDLE_ENFORCE
(
...
...
@@ -35,10 +32,10 @@ protected:
}
};
class
AddOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
AddOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
AddOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The first input of add op"
);
AddInput
(
"Y"
,
"The second input of add op"
);
AddOutput
(
"Out"
,
"The output of add op"
);
...
...
@@ -50,11 +47,10 @@ The equation is: Out = X + Y
}
};
class
AddOpGrad
:
public
framework
::
OperatorWithKernel
{
class
AddOpGrad
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{}
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{}
std
::
string
DebugString
()
const
override
{
LOG
(
INFO
)
<<
"AddOpGrad"
;
return
""
;
...
...
@@ -64,7 +60,6 @@ protected:
}
// namespace operators
}
// namespace paddle
REGISTER_OP
(
add_two
,
paddle
::
operators
::
AddOp
,
paddle
::
operators
::
AddOpMaker
);
REGISTER_GRADIENT_OP
(
add_two
,
add_two_grad
,
paddle
::
operators
::
AddOpGrad
);
REGISTER_OP_CPU_KERNEL
(
add_two
,
paddle
::
operators
::
AddKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP
(
add_two
,
ops
::
AddOp
,
ops
::
AddOpMaker
);
REGISTER_GRADIENT_OP
(
add_two
,
add_two_grad
,
ops
::
AddOpGrad
);
REGISTER_OP_CPU_KERNEL
(
add_two
,
ops
::
AddKernel
<
ops
::
CPUPlace
,
float
>
);
paddle/operators/add_op.cu
浏览文件 @
55115ac6
#include "paddle/operators/add_op.h"
#include "paddle/framework/op_registry.h"
#include "paddle/operators/add_op.h"
REGISTER_OP_GPU_KERNEL
(
add_two
,
paddle
::
operators
::
AddKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
\ No newline at end of file
REGISTER_OP_GPU_KERNEL
(
add_two
,
ops
::
AddKernel
<
ops
::
GPUPlace
,
float
>
);
paddle/operators/add_op.h
浏览文件 @
55115ac6
...
...
@@ -13,27 +13,24 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/operators/type_alias.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
Place
,
typename
T
>
class
AddKernel
:
public
framework
::
OpKernel
{
class
AddKernel
:
public
OpKernel
{
public:
void
Compute
(
const
framework
::
KernelContext
&
context
)
const
override
{
auto
input0
=
context
.
Input
(
0
)
->
Get
<
framework
::
Tensor
>
();
auto
input1
=
context
.
Input
(
1
)
->
Get
<
framework
::
Tensor
>
();
auto
*
output
=
context
.
Output
(
0
)
->
GetMutable
<
framework
::
Tensor
>
();
void
Compute
(
const
KernelContext
&
context
)
const
override
{
auto
input0
=
context
.
Input
(
0
)
->
Get
<
Tensor
>
();
auto
input1
=
context
.
Input
(
1
)
->
Get
<
Tensor
>
();
auto
output
=
context
.
Output
(
0
)
->
GetMutable
<
Tensor
>
();
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
framework
::
EigenVector
<
T
>::
Flatten
(
*
output
).
device
(
EigenVector
<
T
>::
Flatten
(
*
output
).
device
(
*
(
context
.
GetEigenDevice
<
Place
>
()))
=
framework
::
EigenVector
<
T
>::
Flatten
(
input0
)
+
framework
::
EigenVector
<
T
>::
Flatten
(
input1
);
EigenVector
<
T
>::
Flatten
(
input0
)
+
EigenVector
<
T
>::
Flatten
(
input1
);
}
};
...
...
paddle/operators/cross_entropy_op.cc
浏览文件 @
55115ac6
...
...
@@ -13,17 +13,14 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/cross_entropy_op.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/tensor.h"
namespace
paddle
{
namespace
operators
{
class
OnehotCrossEntropyOp
:
public
framework
::
OperatorWithKernel
{
class
OnehotCrossEntropyOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{
PADDLE_ENFORCE
(
inputs
.
size
()
==
2
,
"Input size of OnehotCrossEntropyOp must be two"
);
PADDLE_ENFORCE
(
outputs
.
size
()
==
1
,
...
...
@@ -35,15 +32,14 @@ protected:
PADDLE_ENFORCE
(
inputs
[
0
]
->
dims
().
size
()
==
2
,
"X's dimension must be 2."
);
PADDLE_ENFORCE
(
outputs
[
0
]
->
dims
().
size
()
==
1
,
"label's dimension must be 1."
);
outputs
[
0
]
->
Resize
(
framework
::
make_ddim
({
inputs
[
0
]
->
dims
()[
0
]})
);
outputs
[
0
]
->
Resize
(
{
inputs
[
0
]
->
dims
()[
0
]}
);
}
};
class
OnehotCrossEntropyOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
OnehotCrossEntropyOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
OnehotCrossEntropyOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
OnehotCrossEntropyOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The first input of OnehotCrossEntropyOp"
);
AddInput
(
"label"
,
"The second input of OnehotCrossEntropyOp"
);
AddOutput
(
"Y"
,
"The output of OnehotCrossEntropyOp"
);
...
...
@@ -59,9 +55,7 @@ OnehotCrossEntropy Operator.
}
// namespace paddle
REGISTER_OP
(
onehot_cross_entropy
,
paddle
::
operators
::
OnehotCrossEntropyOp
,
paddle
::
operators
::
OnehotCrossEntropyOpMaker
);
REGISTER_OP_CPU_KERNEL
(
onehot_cross_entropy
,
paddle
::
operators
::
OnehotCrossEntropyOpKernel
<::
paddle
::
platform
::
CPUPlace
,
float
>
);
ops
::
OnehotCrossEntropyOp
,
ops
::
OnehotCrossEntropyOpMaker
);
REGISTER_OP_CPU_KERNEL
(
onehot_cross_entropy
,
ops
::
OnehotCrossEntropyOpKernel
<
ops
::
CPUPlace
,
float
>
);
paddle/operators/cross_entropy_op.cu
浏览文件 @
55115ac6
#include "paddle/operators/cross_entropy_op.h"
#include "paddle/framework/op_registry.h"
REGISTER_OP_GPU_KERNEL
(
onehot_cross_entropy
,
paddle
::
operators
::
OnehotCrossEntropyOpKernel
<
::
paddle
::
platform
::
GPUPlace
,
float
>
);
\ No newline at end of file
ops
::
OnehotCrossEntropyOpKernel
<
ops
::
GPUPlace
,
float
>
);
\ No newline at end of file
paddle/operators/cross_entropy_op.h
浏览文件 @
55115ac6
...
...
@@ -13,23 +13,21 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "glog/logging.h"
#include "paddle/framework/operator.h"
#include "paddle/operators/type_alias.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
Place
,
typename
T
>
class
OnehotCrossEntropyOpKernel
:
public
framework
::
OpKernel
{
class
OnehotCrossEntropyOpKernel
:
public
OpKernel
{
public:
constexpr
T
LOG_THRESHOLD
()
const
{
return
static_cast
<
T
>
(
1e-20
);
}
void
Compute
(
const
framework
::
KernelContext
&
context
)
const
override
{
auto
X
=
context
.
Input
(
0
)
->
Get
<
framework
::
Tensor
>
();
void
Compute
(
const
KernelContext
&
context
)
const
override
{
auto
X
=
context
.
Input
(
0
)
->
Get
<
Tensor
>
();
const
T
*
X_data
=
X
.
data
<
T
>
();
const
int
*
label_data
=
context
.
Input
(
1
)
->
Get
<
framework
::
Tensor
>
().
data
<
int
>
();
auto
*
Y
=
context
.
Output
(
0
)
->
GetMutable
<
framework
::
Tensor
>
();
const
int
*
label_data
=
context
.
Input
(
1
)
->
Get
<
Tensor
>
().
data
<
int
>
();
auto
*
Y
=
context
.
Output
(
0
)
->
GetMutable
<
Tensor
>
();
Y
->
mutable_data
<
T
>
(
context
.
GetPlace
());
...
...
paddle/operators/fc_op.cc
浏览文件 @
55115ac6
...
...
@@ -12,41 +12,38 @@
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/framework/net.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
#include "type_alias.h"
namespace
paddle
{
namespace
operators
{
class
FullyConnectedOp
:
public
framework
::
PlainNet
{
class
FullyConnectedOp
:
public
NetOp
{
public:
void
Init
()
override
{
AddOp
(
framework
::
OpRegistry
::
CreateOp
(
"mul"
,
AddOp
(
OpRegistry
::
CreateOp
(
"mul"
,
{
Input
(
"X"
),
Input
(
"W"
),
},
{
Output
(
"before_act"
)},
{}));
auto
b
=
Input
(
"b"
);
if
(
b
!=
framework
::
OperatorBase
::
EMPTY_VAR_NAME
())
{
AddOp
(
framework
::
OpRegistry
::
CreateOp
(
"rowwise_add"
,
if
(
b
!=
EMPTY_VAR_NAME
())
{
AddOp
(
OpRegistry
::
CreateOp
(
"rowwise_add"
,
{
Output
(
"before_act"
),
Input
(
"b"
)},
{
Output
(
"before_act"
)},
{}));
}
auto
activation
=
GetAttr
<
std
::
string
>
(
"activation"
);
AddOp
(
framework
::
OpRegistry
::
CreateOp
(
AddOp
(
OpRegistry
::
CreateOp
(
activation
,
{
Output
(
"before_act"
)},
{
Output
(
"Y"
)},
{}));
CompleteAddOp
(
false
);
}
};
class
FullyConnectedOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
FullyConnectedOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
FullyConnectedOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
FullyConnectedOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"the input of fc operator"
);
AddInput
(
"W"
,
"the weight of fc operator"
);
...
...
@@ -71,6 +68,4 @@ USE_OP(rowwise_add);
USE_OP
(
sigmoid
);
USE_OP
(
softmax
);
REGISTER_OP
(
fc
,
paddle
::
operators
::
FullyConnectedOp
,
paddle
::
operators
::
FullyConnectedOpMaker
);
REGISTER_OP
(
fc
,
ops
::
FullyConnectedOp
,
ops
::
FullyConnectedOpMaker
);
paddle/operators/mul_op.cc
浏览文件 @
55115ac6
...
...
@@ -13,17 +13,14 @@
limitations under the License. */
#include "paddle/operators/mul_op.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/tensor.h"
namespace
paddle
{
namespace
operators
{
class
MulOp
:
public
framework
::
OperatorWithKernel
{
class
MulOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{
PADDLE_ENFORCE
(
inputs
.
size
()
==
2
,
"The mul op must take two inputs"
);
auto
dim0
=
inputs
[
0
]
->
dims
();
auto
dim1
=
inputs
[
1
]
->
dims
();
...
...
@@ -37,10 +34,10 @@ protected:
}
};
class
MulOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
MulOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
MulOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
MulOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The first input of mul op"
);
AddInput
(
"Y"
,
"The second input of mul op"
);
AddOutput
(
"Out"
,
"The output of mul op"
);
...
...
@@ -52,11 +49,10 @@ The equation is: Out = X * Y
}
};
class
MulOpGrad
:
public
framework
::
OperatorWithKernel
{
class
MulOpGrad
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{}
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{}
std
::
string
DebugString
()
const
override
{
LOG
(
INFO
)
<<
"MulGrad"
;
return
""
;
...
...
@@ -66,8 +62,7 @@ protected:
}
// namespace operators
}
// namespace paddle
REGISTER_OP
(
mul
,
paddle
::
operators
::
MulOp
,
paddle
::
operator
s
::
MulOpMaker
);
REGISTER_GRADIENT_OP
(
mul
,
mul_grad
,
paddle
::
operator
s
::
MulOpGrad
);
REGISTER_OP
(
mul
,
ops
::
MulOp
,
op
s
::
MulOpMaker
);
REGISTER_GRADIENT_OP
(
mul
,
mul_grad
,
op
s
::
MulOpGrad
);
REGISTER_OP_CPU_KERNEL
(
mul
,
paddle
::
operators
::
MulKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
mul
,
ops
::
MulKernel
<
ops
::
CPUPlace
,
float
>
);
paddle/operators/mul_op.cu
浏览文件 @
55115ac6
...
...
@@ -13,8 +13,5 @@
limitations under the License. */
#include "paddle/operators/mul_op.h"
#include "paddle/framework/op_registry.h"
REGISTER_OP_GPU_KERNEL
(
mul
,
paddle
::
operators
::
MulKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
\ No newline at end of file
REGISTER_OP_GPU_KERNEL
(
mul
,
ops
::
MulKernel
<
ops
::
GPUPlace
,
float
>
);
\ No newline at end of file
paddle/operators/mul_op.h
浏览文件 @
55115ac6
...
...
@@ -14,30 +14,27 @@
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/operators/type_alias.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
Place
,
typename
T
>
class
MulKernel
:
public
framework
::
OpKernel
{
class
MulKernel
:
public
OpKernel
{
public:
void
Compute
(
const
framework
::
KernelContext
&
context
)
const
override
{
void
Compute
(
const
KernelContext
&
context
)
const
override
{
Eigen
::
array
<
Eigen
::
IndexPair
<
Eigen
::
DenseIndex
>
,
1
>
dim_pair
=
{
{
Eigen
::
IndexPair
<
Eigen
::
DenseIndex
>
(
1
,
0
)}};
auto
input0
=
context
.
Input
(
0
)
->
Get
<
framework
::
Tensor
>
();
auto
input1
=
context
.
Input
(
1
)
->
Get
<
framework
::
Tensor
>
();
auto
*
output
=
context
.
Output
(
0
)
->
GetMutable
<
framework
::
Tensor
>
();
auto
input0
=
context
.
Input
(
0
)
->
Get
<
Tensor
>
();
auto
input1
=
context
.
Input
(
1
)
->
Get
<
Tensor
>
();
auto
*
output
=
context
.
Output
(
0
)
->
GetMutable
<
Tensor
>
();
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
framework
::
EigenMatrix
<
T
>::
From
(
*
output
).
device
(
*
(
context
.
GetEigenDevice
<
Place
>
()))
=
framework
::
EigenMatrix
<
T
>::
From
(
input0
).
contract
(
framework
::
EigenMatrix
<
T
>::
From
(
input1
),
dim_pair
);
EigenMatrix
<
T
>::
From
(
*
output
).
device
(
*
(
context
.
GetEigenDevice
<
Place
>
()))
=
EigenMatrix
<
T
>::
From
(
input0
).
contract
(
EigenMatrix
<
T
>::
From
(
input1
),
dim_pair
);
}
};
}
// namespace operators
...
...
paddle/operators/rowwise_add_op.cc
浏览文件 @
55115ac6
...
...
@@ -13,15 +13,13 @@
limitations under the License. */
#include "paddle/operators/rowwise_add_op.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
class
RowWiseAddOp
:
public
framework
::
OperatorWithKernel
{
class
RowWiseAddOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{
PADDLE_ENFORCE
(
inputs
.
size
()
==
2UL
,
"Two inputs is needed by rowwise add"
);
auto
dim0
=
inputs
[
0
]
->
dims
();
auto
dim1
=
inputs
[
1
]
->
dims
();
...
...
@@ -34,11 +32,10 @@ protected:
}
};
class
RowWiseAddOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
RowWiseAddOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
RowWiseAddOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
RowWiseAddOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The left input of row-wise add op, must be matrix"
);
AddInput
(
"b"
,
"The right input of row-wise add op, must be vector"
);
AddOutput
(
"Out"
,
"The output of row-wise add op"
);
...
...
@@ -53,9 +50,6 @@ for i in xrange(X.shape[0]):
}
// namespace operators
}
// namespace paddle
REGISTER_OP
(
rowwise_add
,
paddle
::
operators
::
RowWiseAddOp
,
paddle
::
operators
::
RowWiseAddOpMaker
);
REGISTER_OP_CPU_KERNEL
(
rowwise_add
,
paddle
::
operators
::
RowWiseAddKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP
(
rowwise_add
,
ops
::
RowWiseAddOp
,
ops
::
RowWiseAddOpMaker
);
REGISTER_OP_CPU_KERNEL
(
rowwise_add
,
ops
::
RowWiseAddKernel
<
ops
::
CPUPlace
,
float
>
);
paddle/operators/rowwise_add_op.cu
浏览文件 @
55115ac6
#include "paddle/framework/op_registry.h"
#include "paddle/operators/rowwise_add_op.h"
REGISTER_OP_GPU_KERNEL
(
rowwise_add
,
paddle
::
operators
::
RowWiseAddKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
rowwise_add
,
ops
::
RowWiseAddKernel
<
ops
::
GPUPlace
,
float
>
);
paddle/operators/rowwise_add_op.h
浏览文件 @
55115ac6
...
...
@@ -13,25 +13,23 @@
limitations under the License. */
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/operators/type_alias.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
Place
,
typename
T
>
class
RowWiseAddKernel
:
public
framework
::
OpKernel
{
class
RowWiseAddKernel
:
public
OpKernel
{
public:
void
Compute
(
const
framework
::
KernelContext
&
context
)
const
override
{
auto
in0
=
context
.
Input
(
0
)
->
Get
<
framework
::
Tensor
>
();
auto
in1
=
context
.
Input
(
1
)
->
Get
<
framework
::
Tensor
>
();
auto
*
out
=
context
.
Output
(
0
)
->
GetMutable
<
framework
::
Tensor
>
();
void
Compute
(
const
KernelContext
&
context
)
const
override
{
auto
in0
=
context
.
Input
(
0
)
->
Get
<
Tensor
>
();
auto
in1
=
context
.
Input
(
1
)
->
Get
<
Tensor
>
();
auto
*
out
=
context
.
Output
(
0
)
->
GetMutable
<
Tensor
>
();
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
input
=
framework
::
EigenMatrix
<
T
>::
From
(
in0
);
auto
bias
=
framework
::
EigenVector
<
T
>::
From
(
in1
);
auto
output
=
framework
::
EigenMatrix
<
T
>::
From
(
*
out
);
auto
input
=
EigenMatrix
<
T
>::
From
(
in0
);
auto
bias
=
EigenVector
<
T
>::
From
(
in1
);
auto
output
=
EigenMatrix
<
T
>::
From
(
*
out
);
const
int
bias_size
=
bias
.
dimension
(
0
);
const
int
rest_size
=
input
.
size
()
/
bias_size
;
...
...
paddle/operators/sgd_op.cc
浏览文件 @
55115ac6
...
...
@@ -13,17 +13,14 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/sgd_op.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/tensor.h"
namespace
paddle
{
namespace
operators
{
class
SGDOp
:
public
framework
::
OperatorWithKernel
{
class
SGDOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{
PADDLE_ENFORCE
(
inputs
.
size
()
==
2
,
"Input size of SGDOp must be two"
);
PADDLE_ENFORCE
(
outputs
.
size
()
==
1
,
"Output size of SGDOp must be one"
);
PADDLE_ENFORCE
(
inputs
[
0
]
!=
nullptr
,
"inputs[0] mast be set"
);
...
...
@@ -35,10 +32,10 @@ protected:
}
};
class
SGDOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
SGDOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
SGDOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
SGDOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"param"
,
"input parameter"
);
AddInput
(
"grad"
,
"input gradient"
);
AddOutput
(
"param_out"
,
"output parameter"
);
...
...
@@ -55,7 +52,5 @@ param_out = param - learning_rate * grad;
}
// namespace operators
}
// namespace paddle
REGISTER_OP
(
sgd
,
paddle
::
operators
::
SGDOp
,
paddle
::
operators
::
SGDOpMaker
);
typedef
paddle
::
operators
::
SGDOpKernel
<::
paddle
::
platform
::
CPUPlace
,
float
>
SGDOpKernel_CPU_float
;
REGISTER_OP_CPU_KERNEL
(
sgd
,
SGDOpKernel_CPU_float
);
REGISTER_OP
(
sgd
,
ops
::
SGDOp
,
ops
::
SGDOpMaker
);
REGISTER_OP_CPU_KERNEL
(
sgd
,
ops
::
SGDOpKernel
<
ops
::
CPUPlace
,
float
>
);
paddle/operators/sgd_op.cu
浏览文件 @
55115ac6
#include "paddle/operators/sgd_op.h"
#include "paddle/framework/op_registry.h"
typedef
paddle
::
operators
::
SGDOpKernel
<::
paddle
::
platform
::
GPUPlace
,
float
>
SGDOpKernel_GPU_float
;
REGISTER_OP_GPU_KERNEL
(
sgd
,
SGDOpKernel_GPU_float
);
\ No newline at end of file
REGISTER_OP_GPU_KERNEL
(
sgd
,
ops
::
SGDOpKernel
<
ops
::
GPUPlace
,
float
>
);
\ No newline at end of file
paddle/operators/sgd_op.h
浏览文件 @
55115ac6
...
...
@@ -13,28 +13,24 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/operators/type_alias.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
Place
,
typename
T
>
class
SGDOpKernel
:
public
framework
::
OpKernel
{
class
SGDOpKernel
:
public
OpKernel
{
public:
void
Compute
(
const
framework
::
KernelContext
&
ctx
)
const
override
{
auto
param
=
ctx
.
Input
(
"param"
)
->
Get
<
framework
::
Tensor
>
();
auto
grad
=
ctx
.
Input
(
"grad"
)
->
Get
<
framework
::
Tensor
>
();
auto
*
param_out
=
ctx
.
Output
(
0
)
->
GetMutable
<
framework
::
Tensor
>
();
void
Compute
(
const
KernelContext
&
ctx
)
const
override
{
auto
param
=
ctx
.
Input
(
"param"
)
->
Get
<
Tensor
>
();
auto
grad
=
ctx
.
Input
(
"grad"
)
->
Get
<
Tensor
>
();
auto
*
param_out
=
ctx
.
Output
(
0
)
->
GetMutable
<
Tensor
>
();
float
lr
=
ctx
.
op_
.
GetAttr
<
float
>
(
"learning_rate"
);
param_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
framework
::
EigenVector
<
T
>::
Flatten
(
*
param_out
)
.
device
(
*
(
ctx
.
GetEigenDevice
<
Place
>
()))
=
framework
::
EigenVector
<
T
>::
Flatten
(
param
)
-
lr
*
framework
::
EigenVector
<
T
>::
Flatten
(
grad
);
EigenVector
<
T
>::
Flatten
(
*
param_out
).
device
(
*
(
ctx
.
GetEigenDevice
<
Place
>
()))
=
EigenVector
<
T
>::
Flatten
(
param
)
-
lr
*
EigenVector
<
T
>::
Flatten
(
grad
);
}
};
...
...
paddle/operators/sigmoid_op.cc
浏览文件 @
55115ac6
...
...
@@ -13,37 +13,33 @@
limitations under the License. */
#include "paddle/operators/sigmoid_op.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
class
SigmoidOp
:
public
framework
::
OperatorWithKernel
{
class
SigmoidOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{
PADDLE_ENFORCE
(
inputs
.
size
()
==
1
,
"Sigmoid Op only have one input"
);
PADDLE_ENFORCE
(
outputs
.
size
()
==
1
,
"Sigmoid Op only have one output"
);
outputs
[
0
]
->
Resize
(
inputs
[
0
]
->
dims
());
}
};
class
SigmoidOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
SigmoidOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
SigmoidOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
SigmoidOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"sigmoid input"
);
AddOutput
(
"Y"
,
"sigmoid output"
);
AddComment
(
"Sigmoid function"
);
}
};
class
SigmoidOpGrad
:
public
framework
::
OperatorWithKernel
{
class
SigmoidOpGrad
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{}
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{}
std
::
string
DebugString
()
const
override
{
LOG
(
INFO
)
<<
"SigmoidGrad"
;
return
""
;
...
...
@@ -53,11 +49,7 @@ protected:
}
// namespace operators
}
// namespace paddle
REGISTER_OP
(
sigmoid
,
paddle
::
operators
::
SigmoidOp
,
paddle
::
operators
::
SigmoidOpMaker
);
REGISTER_GRADIENT_OP
(
sigmoid
,
sigmoid_grad
,
paddle
::
operators
::
SigmoidOpGrad
);
REGISTER_OP
(
sigmoid
,
ops
::
SigmoidOp
,
ops
::
SigmoidOpMaker
);
REGISTER_GRADIENT_OP
(
sigmoid
,
sigmoid_grad
,
ops
::
SigmoidOpGrad
);
REGISTER_OP_CPU_KERNEL
(
sigmoid
,
paddle
::
operators
::
SigmoidKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
sigmoid
,
ops
::
SigmoidKernel
<
ops
::
CPUPlace
,
float
>
);
paddle/operators/sigmoid_op.cu
浏览文件 @
55115ac6
#include "paddle/operators/sigmoid_op.h"
#include "paddle/framework/op_registry.h"
REGISTER_OP_GPU_KERNEL
(
sigmoid
,
paddle
::
operators
::
SigmoidKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
sigmoid
,
ops
::
SigmoidKernel
<
ops
::
GPUPlace
,
float
>
);
paddle/operators/sigmoid_op.h
浏览文件 @
55115ac6
...
...
@@ -14,25 +14,23 @@
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/operators/type_alias.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
Place
,
typename
T
>
class
SigmoidKernel
:
public
framework
::
OpKernel
{
class
SigmoidKernel
:
public
OpKernel
{
public:
void
Compute
(
const
framework
::
KernelContext
&
context
)
const
override
{
auto
input
=
context
.
Input
(
0
)
->
Get
<
framework
::
Tensor
>
();
auto
*
output
=
context
.
Output
(
0
)
->
GetMutable
<
framework
::
Tensor
>
();
void
Compute
(
const
KernelContext
&
context
)
const
override
{
auto
input
=
context
.
Input
(
0
)
->
Get
<
Tensor
>
();
auto
*
output
=
context
.
Output
(
0
)
->
GetMutable
<
Tensor
>
();
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
framework
::
EigenVector
<
T
>::
Flatten
(
*
output
).
device
(
EigenVector
<
T
>::
Flatten
(
*
output
).
device
(
*
(
context
.
GetEigenDevice
<
Place
>
()))
=
1.0
/
(
1.0
+
(
-
1.0
*
framework
::
EigenVector
<
T
>::
Flatten
(
input
)).
exp
());
1.0
/
(
1.0
+
(
-
1.0
*
EigenVector
<
T
>::
Flatten
(
input
)).
exp
());
}
};
}
// namespace operators
...
...
paddle/operators/softmax_op.cc
浏览文件 @
55115ac6
...
...
@@ -12,16 +12,14 @@
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/softmax_op.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
class
SoftmaxOp
:
public
framework
::
OperatorWithKernel
{
class
SoftmaxOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{
PADDLE_ENFORCE
(
inputs
.
size
()
==
1
,
"Only one input is need for softmax"
);
PADDLE_ENFORCE
(
inputs
[
0
]
->
dims
().
size
()
==
2
,
"The input of softmax op must be matrix"
);
...
...
@@ -31,10 +29,9 @@ protected:
}
};
class
SoftmaxOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
SoftmaxOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
SoftmaxOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
SoftmaxOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"input of softmax"
);
AddOutput
(
"Y"
,
"output of softmax"
);
...
...
@@ -42,11 +39,10 @@ public:
}
};
class
SoftmaxOpGrad
:
public
framework
::
OperatorWithKernel
{
class
SoftmaxOpGrad
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
std
::
vector
<
const
framework
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
framework
::
Tensor
*>
&
outputs
)
const
override
{}
void
InferShape
(
const
std
::
vector
<
const
Tensor
*>
&
inputs
,
const
std
::
vector
<
Tensor
*>
&
outputs
)
const
override
{}
std
::
string
DebugString
()
const
override
{
LOG
(
INFO
)
<<
"SoftmaxOpGrad"
;
return
""
;
...
...
@@ -56,9 +52,6 @@ protected:
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
softmax
,
ops
::
SoftmaxOp
,
ops
::
SoftmaxOpMaker
);
REGISTER_GRADIENT_OP
(
softmax
,
softmax_grad
,
paddle
::
operators
::
SoftmaxOpGrad
);
REGISTER_OP_CPU_KERNEL
(
softmax
,
ops
::
SoftmaxKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_GRADIENT_OP
(
softmax
,
softmax_grad
,
ops
::
SoftmaxOpGrad
);
REGISTER_OP_CPU_KERNEL
(
softmax
,
ops
::
SoftmaxKernel
<
ops
::
CPUPlace
,
float
>
);
paddle/operators/softmax_op.cu
浏览文件 @
55115ac6
#include "paddle/framework/op_registry.h"
#include "paddle/operators/softmax_op.h"
REGISTER_OP_GPU_KERNEL
(
softmax
,
paddle
::
operators
::
SoftmaxKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
softmax
,
ops
::
SoftmaxKernel
<
ops
::
GPUPlace
,
float
>
);
paddle/operators/softmax_op.h
浏览文件 @
55115ac6
...
...
@@ -14,23 +14,21 @@
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/operators/type_alias.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
Place
,
typename
T
>
class
SoftmaxKernel
:
public
framework
::
OpKernel
{
class
SoftmaxKernel
:
public
OpKernel
{
public:
void
Compute
(
const
framework
::
KernelContext
&
context
)
const
override
{
auto
input
=
context
.
Input
(
0
)
->
Get
<
framework
::
Tensor
>
();
auto
*
output
=
context
.
Output
(
0
)
->
GetMutable
<
framework
::
Tensor
>
();
void
Compute
(
const
KernelContext
&
context
)
const
override
{
auto
input
=
context
.
Input
(
0
)
->
Get
<
Tensor
>
();
auto
*
output
=
context
.
Output
(
0
)
->
GetMutable
<
Tensor
>
();
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
logits
=
framework
::
EigenMatrix
<
T
>::
From
(
input
);
auto
softmax
=
framework
::
EigenMatrix
<
T
>::
From
(
*
output
);
auto
logits
=
EigenMatrix
<
T
>::
From
(
input
);
auto
softmax
=
EigenMatrix
<
T
>::
From
(
*
output
);
const
int
kBatchDim
=
0
;
const
int
kClassDim
=
1
;
...
...
paddle/operators/type_alias.h
0 → 100644
浏览文件 @
55115ac6
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#pragma once
#include "paddle/framework/eigen.h"
#include "paddle/framework/net.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
using
OpKernel
=
framework
::
OpKernel
;
using
KernelContext
=
framework
::
KernelContext
;
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenVector
=
framework
::
EigenVector
<
T
,
MajorType
,
IndexType
>
;
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenMatrix
=
framework
::
EigenMatrix
<
T
,
MajorType
,
IndexType
>
;
template
<
typename
T
,
size_t
D
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenTensor
=
framework
::
EigenTensor
<
T
,
D
,
MajorType
,
IndexType
>
;
using
Tensor
=
framework
::
Tensor
;
using
OperatorWithKernel
=
framework
::
OperatorWithKernel
;
using
OpProtoAndCheckerMaker
=
framework
::
OpProtoAndCheckerMaker
;
using
OpProto
=
framework
::
OpProto
;
using
OpAttrChecker
=
framework
::
OpAttrChecker
;
using
CPUPlace
=
platform
::
CPUPlace
;
using
GPUPlace
=
platform
::
GPUPlace
;
using
NetOp
=
framework
::
NetOp
;
using
OpRegistry
=
framework
::
OpRegistry
;
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
paddle/pybind/pybind.cc
浏览文件 @
55115ac6
...
...
@@ -146,22 +146,22 @@ All parameter, weight, gradient are variables in Paddle.
});
ExposeOperator
(
operator_base
);
using
PlainNetPtr
=
std
::
shared_ptr
<
pd
::
PlainNet
>
;
py
::
class_
<
pd
::
PlainNet
,
PlainNetPtr
>
net
(
m
,
"Net"
);
py
::
class_
<
pd
::
NetOp
,
std
::
shared_ptr
<
pd
::
NetOp
>>
net
(
m
,
"Net"
);
net
.
def_static
(
"create"
,
[]()
->
std
::
shared_ptr
<
pd
::
PlainNet
>
{
auto
retv
=
std
::
make_shared
<
pd
::
PlainNet
>
();
[]()
->
std
::
shared_ptr
<
pd
::
NetOp
>
{
auto
retv
=
std
::
make_shared
<
pd
::
NetOp
>
();
retv
->
type_
=
"plain_net"
;
return
retv
;
})
.
def
(
"add_op"
,
&
pd
::
PlainNet
::
AddOp
)
.
def
(
"add_op"
,
&
pd
::
NetOp
::
AddOp
)
.
def
(
"add_op"
,
[](
PlainNetPtr
&
self
,
const
PlainNetPtr
&
net
)
->
void
{
self
->
AddOp
(
std
::
static_pointer_cast
<
pd
::
OperatorBase
>
(
net
));
[](
pd
::
NetOp
&
self
,
const
std
::
shared_ptr
<
pd
::
NetOp
>
&
net
)
->
void
{
self
.
AddOp
(
std
::
static_pointer_cast
<
pd
::
OperatorBase
>
(
net
));
})
.
def
(
"complete_add_op"
,
&
pd
::
PlainNet
::
CompleteAddOp
)
.
def
(
"complete_add_op"
,
[](
PlainNetPtr
&
self
)
{
self
->
CompleteAddOp
();
});
.
def
(
"complete_add_op"
,
&
pd
::
NetOp
::
CompleteAddOp
)
.
def
(
"complete_add_op"
,
[](
std
::
shared_ptr
<
pd
::
NetOp
>&
self
)
{
self
->
CompleteAddOp
();
});
ExposeOperator
(
net
);
m
.
def
(
"unique_integer"
,
UniqueIntegerGenerator
);
...
...
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