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提交
4c96008a
编写于
10月 06, 2017
作者:
Y
Yi Wang
提交者:
GitHub
10月 06, 2017
浏览文件
操作
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差异文件
Merge pull request #4566 from reyoung/feature/grad_reg_mechanism_cont2
Complete register gradient for compile time
上级
f8b5d54c
803b7b62
变更
18
隐藏空白更改
内联
并排
Showing
18 changed file
with
271 addition
and
491 deletion
+271
-491
paddle/framework/CMakeLists.txt
paddle/framework/CMakeLists.txt
+1
-3
paddle/framework/backward.cc
paddle/framework/backward.cc
+31
-1
paddle/framework/backward_test.cc
paddle/framework/backward_test.cc
+23
-36
paddle/framework/framework.proto
paddle/framework/framework.proto
+0
-1
paddle/framework/grad_op_builder.cc
paddle/framework/grad_op_builder.cc
+0
-97
paddle/framework/grad_op_builder.h
paddle/framework/grad_op_builder.h
+0
-28
paddle/framework/grad_op_builder_test.cc
paddle/framework/grad_op_builder_test.cc
+0
-186
paddle/framework/op_desc.h
paddle/framework/op_desc.h
+16
-2
paddle/framework/op_info.h
paddle/framework/op_info.h
+8
-8
paddle/framework/op_proto_maker.h
paddle/framework/op_proto_maker.h
+0
-5
paddle/framework/op_registry.cc
paddle/framework/op_registry.cc
+6
-4
paddle/framework/op_registry.h
paddle/framework/op_registry.h
+47
-40
paddle/operators/mean_op.cc
paddle/operators/mean_op.cc
+18
-2
paddle/operators/minus_op.cc
paddle/operators/minus_op.cc
+32
-24
paddle/operators/pad_op.cc
paddle/operators/pad_op.cc
+20
-3
paddle/operators/scale_op.cc
paddle/operators/scale_op.cc
+15
-18
paddle/operators/softmax_with_cross_entropy_op.cc
paddle/operators/softmax_with_cross_entropy_op.cc
+32
-13
paddle/operators/sum_op.cc
paddle/operators/sum_op.cc
+22
-20
未找到文件。
paddle/framework/CMakeLists.txt
浏览文件 @
4c96008a
...
...
@@ -26,10 +26,8 @@ cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto proto_desc)
cc_library
(
operator SRCS operator.cc DEPS op_info device_context tensor scope proto_desc
)
cc_test
(
operator_test SRCS operator_test.cc DEPS operator op_registry
)
cc_library
(
grad_op_builder SRCS grad_op_builder.cc DEPS operator proto_desc
)
cc_library
(
op_registry SRCS op_registry.cc DEPS grad_op_builder op_proto_maker op_info
)
cc_library
(
op_registry SRCS op_registry.cc DEPS op_proto_maker op_info operator
)
cc_test
(
op_registry_test SRCS op_registry_test.cc DEPS op_registry
)
cc_test
(
grad_op_builder_test SRCS grad_op_builder_test.cc DEPS grad_op_builder op_registry sum_op
)
py_proto_compile
(
framework_py_proto SRCS framework.proto
)
# Generate an empty __init__.py to make framework_py_proto as a valid python module.
...
...
paddle/framework/backward.cc
浏览文件 @
4c96008a
...
...
@@ -13,6 +13,7 @@
limitations under the License. */
#include "paddle/framework/backward.h"
#include "paddle/operators/net_op.h"
#include <list>
#include <memory>
...
...
@@ -24,6 +25,35 @@
namespace
paddle
{
namespace
framework
{
static
inline
std
::
unique_ptr
<
OperatorBase
>
CreateGradOp
(
const
OperatorBase
&
op
)
{
OpDescBind
op_desc
;
op_desc
.
SetInputMap
(
op
.
Inputs
());
op_desc
.
SetOutputMap
(
op
.
Outputs
());
op_desc
.
SetType
(
op
.
Type
());
op_desc
.
SetAttrMap
(
op
.
Attrs
());
auto
&
info
=
OpInfoMap
::
Instance
().
Get
(
op
.
Type
());
auto
grad_descs
=
info
.
GradOpMaker
()(
op_desc
);
std
::
vector
<
std
::
unique_ptr
<
OperatorBase
>>
grad_ops
;
grad_ops
.
reserve
(
grad_descs
.
size
());
std
::
transform
(
grad_descs
.
begin
(),
grad_descs
.
end
(),
std
::
back_inserter
(
grad_ops
),
[](
const
std
::
unique_ptr
<
OpDescBind
>&
grad_desc
)
{
return
OpRegistry
::
CreateOp
(
*
grad_desc
);
});
PADDLE_ENFORCE
(
!
grad_ops
.
empty
());
if
(
grad_ops
.
size
()
==
1
)
{
return
std
::
move
(
grad_ops
[
0
]);
}
else
{
auto
net_op
=
new
operators
::
NetOp
();
for
(
auto
&
grad_op
:
grad_ops
)
{
net_op
->
AppendOp
(
std
::
move
(
grad_op
));
}
net_op
->
CompleteAddOp
();
return
std
::
unique_ptr
<
OperatorBase
>
(
net_op
);
}
}
template
<
typename
Map
,
typename
T
>
static
void
ForEachVarName
(
const
Map
&
names
,
T
callback
)
{
for
(
auto
&
name
:
names
)
{
...
...
@@ -171,7 +201,7 @@ static std::unique_ptr<OperatorBase> BackwardRecursive(
net
->
InsertOp
(
pos
.
first
+
1
,
std
::
move
(
pos
.
second
));
}
}
else
{
std
::
unique_ptr
<
OperatorBase
>
grad_op
(
OpRegistry
::
CreateGradOp
(
forwardOp
));
std
::
unique_ptr
<
OperatorBase
>
grad_op
(
CreateGradOp
(
forwardOp
));
ForEachVarName
(
grad_op
->
Inputs
(),
[
&
no_grad_names
,
&
net
,
&
grad_op
](
const
std
::
string
&
grad_input
)
{
...
...
paddle/framework/backward_test.cc
浏览文件 @
4c96008a
...
...
@@ -21,24 +21,34 @@
namespace
paddle
{
namespace
framework
{
using
OperatorBase
=
framework
::
OperatorBase
;
using
OpProtoAndCheckerMaker
=
framework
::
OpProtoAndCheckerMaker
;
using
OpProto
=
framework
::
OpProto
;
using
OpAttrChecker
=
framework
::
OpAttrChecker
;
using
Scope
=
framework
::
Scope
;
using
DeviceContext
=
platform
::
DeviceContext
;
class
RowWiseAddOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
RowWiseAddOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input X of Add"
)
.
NotInGradient
()
;
AddInput
(
"b"
,
"Bias of Add"
)
.
NotInGradient
()
;
AddOutput
(
"Out"
,
"Out of Add"
)
.
NotInGradient
()
;
AddInput
(
"X"
,
"Input X of Add"
);
AddInput
(
"b"
,
"Bias of Add"
);
AddOutput
(
"Out"
,
"Out of Add"
);
AddComment
(
"Add Op"
);
}
};
class
RowWiseAddGradMaker
:
public
SingleGradOpDescMaker
{
public:
using
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
OpDescBind
>
Apply
()
const
override
{
auto
grad_op
=
new
OpDescBind
();
grad_op
->
SetInput
(
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
grad_op
->
SetOutput
(
GradVarName
(
"X"
),
InputGrad
(
"X"
));
grad_op
->
SetOutput
(
GradVarName
(
"b"
),
InputGrad
(
"b"
));
grad_op
->
SetType
(
"rowwise_add_grad"
);
return
std
::
unique_ptr
<
OpDescBind
>
(
grad_op
);
}
};
class
MulOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
MulOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
...
...
@@ -137,10 +147,8 @@ class SumOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SumOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"the input tensors of sum operator."
)
.
AsDuplicable
()
.
NotInGradient
();
AddOutput
(
"Out"
,
"the output tensor of sum operator."
).
NotInGradient
();
AddInput
(
"X"
,
"the input tensors of sum operator."
).
AsDuplicable
();
AddOutput
(
"Out"
,
"the output tensor of sum operator."
);
AddComment
(
""
);
}
};
...
...
@@ -151,8 +159,9 @@ class SumOpMaker : public framework::OpProtoAndCheckerMaker {
namespace
f
=
paddle
::
framework
;
namespace
ops
=
paddle
::
operators
;
using
EnforceNotMet
=
paddle
::
platform
::
EnforceNotMet
;
REGISTER_OP
(
rowwise_add
,
f
::
NOP
,
f
::
RowWiseAddOpMaker
,
rowwise_add_grad
,
f
::
NOP
);
REGISTER_OPERATOR
(
rowwise_add
,
f
::
NOP
,
f
::
RowWiseAddOpMaker
,
f
::
RowWiseAddGradMaker
);
REGISTER_OPERATOR
(
rowwise_add_grad
,
f
::
NOP
);
REGISTER_OP
(
mul
,
f
::
NOP
,
f
::
MulOpMaker
,
mul_grad
,
f
::
NOP
);
REGISTER_OP
(
sigmoid
,
f
::
NOP
,
f
::
SigmoidOpMaker
,
sigmoid_grad
,
f
::
NOP
);
REGISTER_OP_WITHOUT_GRADIENT
(
nograd
,
f
::
NOP
,
f
::
NoGradOpMaker
);
...
...
@@ -162,17 +171,6 @@ REGISTER_OP_WITHOUT_GRADIENT(fc, f::FcOp, f::FcOpMaker);
REGISTER_OP
(
many_output_op
,
f
::
NOP
,
f
::
ManyOutputOpMaker
,
many_output_op_grad
,
f
::
NOP
);
TEST
(
Backward
,
simple_op_grad
)
{
auto
fwd
=
f
::
OpRegistry
::
CreateOp
(
"rowwise_add"
,
{{
"X"
,
{
"x"
}},
{
"b"
,
{
"b"
}}},
{{
"Out"
,
{
"out"
}}},
{});
ASSERT_NE
(
fwd
,
nullptr
);
auto
gop
=
f
::
OpRegistry
::
CreateGradOp
(
*
fwd
);
ASSERT_EQ
(
1UL
,
gop
->
Inputs
().
size
());
ASSERT_EQ
(
"rowwise_add_grad"
,
gop
->
Type
());
ASSERT_EQ
(
f
::
GradVarName
(
"x"
),
gop
->
Output
(
f
::
GradVarName
(
"X"
)));
ASSERT_EQ
(
f
::
GradVarName
(
"b"
),
gop
->
Output
(
f
::
GradVarName
(
"b"
)));
}
TEST
(
Backward
,
simple_op_not_need_grad
)
{
auto
fwd
=
f
::
OpRegistry
::
CreateOp
(
"rowwise_add"
,
{{
"X"
,
{
"x"
}},
{
"b"
,
{
"b"
}}},
{{
"Out"
,
{
"out"
}}},
{});
...
...
@@ -289,17 +287,6 @@ TEST(Backward, net_shared_weight) {
ASSERT_EQ
(
"sum"
,
bwd_net
->
ops_
[
2
]
->
Type
());
}
TEST
(
Backward
,
op_register_grad_not_for_network
)
{
auto
fwd
=
f
::
OpRegistry
::
CreateOp
(
"fc"
,
{{
"X"
,
{
"x"
}},
{
"W"
,
{
"w"
}},
{
"b"
,
{
"b"
}}},
{{
"mul_result"
,
{
"mul_out"
}},
{
"add_result"
,
{
"add_out"
}},
{
"Out"
,
{
"out1"
}}},
{{
"temporary_index"
,
std
::
vector
<
int
>
{
0
,
1
}}});
ASSERT_THROW
(
f
::
OpRegistry
::
CreateGradOp
(
*
fwd
),
EnforceNotMet
);
}
TEST
(
Backward
,
op_all_input_are_not_need
)
{
auto
fwd
=
f
::
OpRegistry
::
CreateOp
(
"rowwise_add"
,
{{
"X"
,
{
"x"
}},
{
"b"
,
{
"b"
}}},
{{
"Out"
,
{
"out"
}}},
{});
...
...
paddle/framework/framework.proto
浏览文件 @
4c96008a
...
...
@@ -66,7 +66,6 @@ message OpProto {
optional
bool
duplicable
=
3
[
default
=
false
];
optional
bool
intermediate
=
4
[
default
=
false
];
optional
bool
not_in_gradient
=
5
[
default
=
false
];
}
// AttrProto describes the C++ type Attribute.
...
...
paddle/framework/grad_op_builder.cc
已删除
100644 → 0
浏览文件 @
f8b5d54c
/* 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,
WITHOpArgType::OUT WARRANTIES OR CONDITIONS OF ANY KOpArgType::IND, either
express or implied. See the License for the specific language governing
permissions and limitations under the License. */
#include "paddle/framework/grad_op_builder.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
namespace
framework
{
enum
class
OpArgType
{
IN
,
OUT
};
static
void
TransOpArg
(
const
OperatorBase
*
src_op
,
const
OpArgType
&
src_type
,
bool
is_grad
,
VariableNameMap
*
vars
)
{
const
auto
&
src_inout
=
src_type
==
OpArgType
::
IN
?
src_op
->
Inputs
()
:
src_op
->
Outputs
();
auto
&
dst_inout
=
*
vars
;
auto
&
proto
=
OpInfoMap
::
Instance
().
Get
(
src_op
->
Type
()).
Proto
();
const
auto
&
src_arg_list
=
src_type
==
OpArgType
::
IN
?
proto
.
inputs
()
:
proto
.
outputs
();
for
(
const
auto
&
arg
:
src_arg_list
)
{
if
(
arg
.
not_in_gradient
()
&&
!
is_grad
)
continue
;
const
std
::
string
src_name
=
arg
.
name
();
std
::
string
dst_name
=
is_grad
?
GradVarName
(
src_name
)
:
src_name
;
dst_inout
[
dst_name
].
reserve
(
src_inout
.
at
(
src_name
).
size
());
for
(
auto
&
var_name
:
src_inout
.
at
(
src_name
))
{
std
::
string
s
=
is_grad
?
GradVarName
(
var_name
)
:
var_name
;
dst_inout
[
dst_name
].
emplace_back
(
s
);
}
}
}
OperatorBase
*
BuildGradOp
(
const
OperatorBase
*
op
)
{
auto
&
info
=
OpInfoMap
::
Instance
().
Get
(
op
->
Type
());
PADDLE_ENFORCE
(
info
.
HasGradientOp
());
VariableNameMap
inputs
;
VariableNameMap
outputs
;
TransOpArg
(
op
,
OpArgType
::
IN
,
false
,
&
inputs
);
// I
TransOpArg
(
op
,
OpArgType
::
OUT
,
false
,
&
inputs
);
// O
TransOpArg
(
op
,
OpArgType
::
OUT
,
true
,
&
inputs
);
// OG
TransOpArg
(
op
,
OpArgType
::
IN
,
true
,
&
outputs
);
// IG
auto
&
grad_info
=
OpInfoMap
::
Instance
().
Get
(
info
.
grad_op_type_
);
return
grad_info
.
Creator
()(
info
.
grad_op_type_
,
inputs
,
outputs
,
op
->
Attrs
());
}
static
void
TransOpDescArg
(
const
OpDescBind
*
src_op
,
const
OpArgType
&
src_type
,
bool
is_grad
,
OpDescBind
*
dst_op
,
const
OpArgType
&
dst_type
)
{
PADDLE_ENFORCE
(
dst_op
!=
nullptr
,
"Protobuf desc of gradient op must be initialized first."
);
const
auto
&
proto
=
OpInfoMap
::
Instance
().
Get
(
src_op
->
Type
()).
Proto
();
const
auto
&
src_arg_list
=
src_type
==
OpArgType
::
IN
?
proto
.
inputs
()
:
proto
.
outputs
();
for
(
const
auto
&
arg
:
src_arg_list
)
{
if
(
arg
.
not_in_gradient
()
&&
!
is_grad
)
continue
;
const
std
::
string
src_name
=
arg
.
name
();
std
::
vector
<
std
::
string
>
vars
=
src_type
==
OpArgType
::
IN
?
src_op
->
Input
(
src_name
)
:
src_op
->
Output
(
src_name
);
if
(
is_grad
)
{
for
(
std
::
string
&
var
:
vars
)
{
var
=
GradVarName
(
var
);
}
}
std
::
string
dst_name
=
is_grad
?
GradVarName
(
src_name
)
:
src_name
;
dst_type
==
OpArgType
::
IN
?
dst_op
->
SetInput
(
dst_name
,
vars
)
:
dst_op
->
SetOutput
(
dst_name
,
vars
);
}
}
void
CompleteGradOpDesc
(
const
OpDescBind
*
forw_op
,
OpDescBind
*
grad_op
)
{
auto
&
info
=
OpInfoMap
::
Instance
().
Get
(
forw_op
->
Type
());
PADDLE_ENFORCE
(
info
.
HasGradientOp
());
grad_op
->
SetType
(
info
.
grad_op_type_
);
TransOpDescArg
(
forw_op
,
OpArgType
::
IN
,
false
,
grad_op
,
OpArgType
::
IN
);
TransOpDescArg
(
forw_op
,
OpArgType
::
OUT
,
false
,
grad_op
,
OpArgType
::
IN
);
TransOpDescArg
(
forw_op
,
OpArgType
::
OUT
,
true
,
grad_op
,
OpArgType
::
IN
);
TransOpDescArg
(
forw_op
,
OpArgType
::
IN
,
true
,
grad_op
,
OpArgType
::
OUT
);
grad_op
->
SetAttrMap
(
forw_op
->
GetAttrMap
());
}
}
// namespace framework
}
// namespace paddle
paddle/framework/grad_op_builder.h
已删除
100644 → 0
浏览文件 @
f8b5d54c
/* 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/op_desc.h"
#include "paddle/framework/operator.h"
namespace
paddle
{
namespace
framework
{
OperatorBase
*
BuildGradOp
(
const
OperatorBase
*
op
);
void
CompleteGradOpDesc
(
const
OpDescBind
*
forw_op
,
OpDescBind
*
grad_op
);
}
// namespace framework
}
// namespace paddle
paddle/framework/grad_op_builder_test.cc
已删除
100644 → 0
浏览文件 @
f8b5d54c
#include "paddle/framework/grad_op_builder.h"
#include <gtest/gtest.h>
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
USE_OP
(
sum
);
namespace
paddle
{
namespace
framework
{
class
MutiInOutOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
MutiInOutOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"In1"
,
"a single input"
);
AddInput
(
"In2_mult"
,
"a multiple input"
).
AsDuplicable
();
AddInput
(
"In3"
,
"another single input"
);
AddOutput
(
"Out1"
,
"a single output"
);
AddOutput
(
"Out2_mult"
,
"a multiple output"
).
AsDuplicable
();
AddComment
(
"test op with multiple inputs and outputs"
);
}
};
class
IOIgnoredOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
IOIgnoredOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"In1"
,
"a single input"
);
AddInput
(
"In2_mult"
,
"a multiple input"
).
AsDuplicable
().
NotInGradient
();
AddInput
(
"In3_mult"
,
"another multiple input"
).
AsDuplicable
();
AddOutput
(
"Out1_mult"
,
"a multiple output"
).
AsDuplicable
();
AddOutput
(
"Out2"
,
"a single output"
).
NotInGradient
();
AddComment
(
"op with inputs and outputs ignored in gradient calculating"
);
}
};
}
// namespace framework
}
// namespace paddle
namespace
f
=
paddle
::
framework
;
REGISTER_OP
(
mult_io
,
f
::
NOP
,
f
::
MutiInOutOpMaker
,
mult_io_grad
,
f
::
NOP
);
REGISTER_OP
(
io_ignored
,
f
::
NOP
,
f
::
IOIgnoredOpMaker
,
io_ignored_grad
,
f
::
NOP
);
TEST
(
GradOpBuilder
,
MutiInOut
)
{
std
::
shared_ptr
<
f
::
OperatorBase
>
test_op
(
f
::
OpRegistry
::
CreateOp
(
"mult_io"
,
{{
"In1"
,
{
"in1"
}},
{
"In2_mult"
,
{
"in2_1"
,
"in2_2"
,
"in2_3"
}},
{
"In3"
,
{
"in3"
}}},
{{
"Out1"
,
{
"out1"
}},
{
"Out2_mult"
,
{
"out2_1"
,
"out2_2"
}}},
{}));
std
::
shared_ptr
<
f
::
OperatorBase
>
grad_test_op
=
f
::
OpRegistry
::
CreateGradOp
(
*
test_op
);
ASSERT_EQ
(
grad_test_op
->
Inputs
().
size
(),
3UL
+
2UL
+
2UL
);
EXPECT_EQ
(
grad_test_op
->
Input
(
"In1"
),
"in1"
);
EXPECT_EQ
(
grad_test_op
->
Inputs
(
"In2_mult"
),
std
::
vector
<
std
::
string
>
({
"in2_1"
,
"in2_2"
,
"in2_3"
}));
EXPECT_EQ
(
grad_test_op
->
Input
(
"In3"
),
"in3"
);
EXPECT_EQ
(
grad_test_op
->
Input
(
"Out1"
),
"out1"
);
EXPECT_EQ
(
grad_test_op
->
Inputs
(
"Out2_mult"
),
std
::
vector
<
std
::
string
>
({
"out2_1"
,
"out2_2"
}));
EXPECT_EQ
(
grad_test_op
->
Input
(
f
::
GradVarName
(
"Out1"
)),
f
::
GradVarName
(
"out1"
));
EXPECT_EQ
(
grad_test_op
->
Inputs
(
f
::
GradVarName
(
"Out2_mult"
)),
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"out2_1"
),
f
::
GradVarName
(
"out2_2"
)}));
ASSERT_EQ
(
grad_test_op
->
Outputs
().
size
(),
3UL
);
EXPECT_EQ
(
grad_test_op
->
Output
(
f
::
GradVarName
(
"In1"
)),
f
::
GradVarName
(
"in1"
));
EXPECT_EQ
(
grad_test_op
->
Outputs
(
f
::
GradVarName
(
"In2_mult"
)),
std
::
vector
<
std
::
string
>
({
f
::
GradVarName
(
"in2_1"
),
f
::
GradVarName
(
"in2_2"
),
f
::
GradVarName
(
"in2_3"
)}));
EXPECT_EQ
(
grad_test_op
->
Output
(
f
::
GradVarName
(
"In3"
)),
f
::
GradVarName
(
"in3"
));
}
TEST
(
GradOpBuilder
,
IOIgnoredInGradient
)
{
std
::
shared_ptr
<
f
::
OperatorBase
>
test_op
(
f
::
OpRegistry
::
CreateOp
(
"io_ignored"
,
{{
"In1"
,
{
"in1"
}},
{
"In2_mult"
,
{
"in2_1"
,
"in2_2"
}},
{
"In3_mult"
,
{
"in3_1"
,
"in3_2"
}}},
{{
"Out1_mult"
,
{
"out1_1"
,
"out1_2"
}},
{
"Out2"
,
{
"out2"
}}},
{}));
std
::
shared_ptr
<
f
::
OperatorBase
>
grad_test_op
=
f
::
OpRegistry
::
CreateGradOp
(
*
test_op
);
// 'In2' and 'Out2' are ignored in gradient calculating
ASSERT_EQ
(
grad_test_op
->
Inputs
().
size
(),
2UL
+
1UL
+
2UL
);
EXPECT_EQ
(
grad_test_op
->
Input
(
"In1"
),
"in1"
);
EXPECT_EQ
(
grad_test_op
->
Inputs
(
"In3_mult"
),
std
::
vector
<
std
::
string
>
({
"in3_1"
,
"in3_2"
}));
EXPECT_EQ
(
grad_test_op
->
Inputs
(
"Out1_mult"
),
std
::
vector
<
std
::
string
>
({
"out1_1"
,
"out1_2"
}));
EXPECT_EQ
(
grad_test_op
->
Inputs
(
f
::
GradVarName
(
"Out1_mult"
)),
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"out1_1"
),
f
::
GradVarName
(
"out1_2"
)}));
EXPECT_EQ
(
grad_test_op
->
Input
(
f
::
GradVarName
(
"Out2"
)),
f
::
GradVarName
(
"out2"
));
ASSERT_EQ
(
grad_test_op
->
Outputs
().
size
(),
3UL
);
EXPECT_EQ
(
grad_test_op
->
Output
(
f
::
GradVarName
(
"In1"
)),
f
::
GradVarName
(
"in1"
));
EXPECT_EQ
(
grad_test_op
->
Outputs
(
f
::
GradVarName
(
"In2_mult"
)),
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"in2_1"
),
f
::
GradVarName
(
"in2_2"
)}));
EXPECT_EQ
(
grad_test_op
->
Outputs
(
f
::
GradVarName
(
"In3_mult"
)),
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"in3_1"
),
f
::
GradVarName
(
"in3_2"
)}));
}
TEST
(
GradOpDescBuilder
,
MutiInOut
)
{
f
::
OpDescBind
*
forw_op
=
new
f
::
OpDescBind
();
forw_op
->
SetType
(
"mult_io"
);
forw_op
->
SetInput
(
"In1"
,
{
"in1"
});
forw_op
->
SetInput
(
"In2_mult"
,
{
"in2_1"
,
"in2_2"
,
"in2_3"
});
forw_op
->
SetInput
(
"In3"
,
{
"in3"
});
forw_op
->
SetOutput
(
"Out1"
,
{
"out1"
});
forw_op
->
SetOutput
(
"Out2_mult"
,
{
"out2_1"
,
"out2_2"
});
f
::
OpDescBind
*
grad_op
=
new
f
::
OpDescBind
();
f
::
CompleteGradOpDesc
(
forw_op
,
grad_op
);
EXPECT_EQ
(
grad_op
->
Type
(),
"mult_io_grad"
);
ASSERT_EQ
(
grad_op
->
InputNames
().
size
(),
3UL
+
2UL
+
2UL
);
EXPECT_EQ
(
grad_op
->
Input
(
"In1"
),
std
::
vector
<
std
::
string
>
({
"in1"
}));
EXPECT_EQ
(
grad_op
->
Input
(
"In2_mult"
),
std
::
vector
<
std
::
string
>
({
"in2_1"
,
"in2_2"
,
"in2_3"
}));
EXPECT_EQ
(
grad_op
->
Input
(
"In3"
),
std
::
vector
<
std
::
string
>
({
"in3"
}));
EXPECT_EQ
(
grad_op
->
Input
(
"Out1"
),
std
::
vector
<
std
::
string
>
({
"out1"
}));
EXPECT_EQ
(
grad_op
->
Input
(
"Out2_mult"
),
std
::
vector
<
std
::
string
>
({
"out2_1"
,
"out2_2"
}));
EXPECT_EQ
(
grad_op
->
Input
(
f
::
GradVarName
(
"Out1"
)),
std
::
vector
<
std
::
string
>
({
f
::
GradVarName
(
"out1"
)}));
EXPECT_EQ
(
grad_op
->
Input
(
f
::
GradVarName
(
"Out2_mult"
)),
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"out2_1"
),
f
::
GradVarName
(
"out2_2"
)}));
ASSERT_EQ
(
grad_op
->
OutputNames
().
size
(),
3UL
);
EXPECT_EQ
(
grad_op
->
Output
(
f
::
GradVarName
(
"In1"
)),
std
::
vector
<
std
::
string
>
({
f
::
GradVarName
(
"in1"
)}));
EXPECT_EQ
(
grad_op
->
Output
(
f
::
GradVarName
(
"In2_mult"
)),
std
::
vector
<
std
::
string
>
({
f
::
GradVarName
(
"in2_1"
),
f
::
GradVarName
(
"in2_2"
),
f
::
GradVarName
(
"in2_3"
)}));
EXPECT_EQ
(
grad_op
->
Output
(
f
::
GradVarName
(
"In3"
)),
std
::
vector
<
std
::
string
>
({
f
::
GradVarName
(
"in3"
)}));
delete
forw_op
;
delete
grad_op
;
}
TEST
(
GradOpDescBuilder
,
IOIgnoredInGradient
)
{
f
::
OpDescBind
*
forw_op
=
new
f
::
OpDescBind
();
forw_op
->
SetType
(
"io_ignored"
);
forw_op
->
SetInput
(
"In1"
,
{
"in1"
});
forw_op
->
SetInput
(
"In2_mult"
,
{
"in2_1"
,
"in2_2"
});
forw_op
->
SetInput
(
"In3_mult"
,
{
"in3_1"
,
"in3_2"
});
forw_op
->
SetOutput
(
"Out1_mult"
,
{
"out1_1"
,
"out1_2"
});
forw_op
->
SetOutput
(
"Out2"
,
{
"out2"
});
f
::
OpDescBind
*
grad_op
=
new
f
::
OpDescBind
();
f
::
CompleteGradOpDesc
(
forw_op
,
grad_op
);
EXPECT_EQ
(
grad_op
->
Type
(),
"io_ignored_grad"
);
// 'In2' and 'Out2' are ignored in gradient calculating
ASSERT_EQ
(
grad_op
->
InputNames
().
size
(),
2UL
+
1UL
+
2UL
);
EXPECT_EQ
(
grad_op
->
Input
(
"In1"
),
std
::
vector
<
std
::
string
>
({
"in1"
}));
EXPECT_EQ
(
grad_op
->
Input
(
"In3_mult"
),
std
::
vector
<
std
::
string
>
({
"in3_1"
,
"in3_2"
}));
EXPECT_EQ
(
grad_op
->
Input
(
"Out1_mult"
),
std
::
vector
<
std
::
string
>
({
"out1_1"
,
"out1_2"
}));
EXPECT_EQ
(
grad_op
->
Input
(
f
::
GradVarName
(
"Out1_mult"
)),
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"out1_1"
),
f
::
GradVarName
(
"out1_2"
)}));
EXPECT_EQ
(
grad_op
->
Input
(
f
::
GradVarName
(
"Out2"
)),
std
::
vector
<
std
::
string
>
({
f
::
GradVarName
(
"out2"
)}));
ASSERT_EQ
(
grad_op
->
OutputNames
().
size
(),
3UL
);
EXPECT_EQ
(
grad_op
->
Output
(
f
::
GradVarName
(
"In1"
)),
std
::
vector
<
std
::
string
>
({
f
::
GradVarName
(
"in1"
)}));
EXPECT_EQ
(
grad_op
->
Output
(
f
::
GradVarName
(
"In2_mult"
)),
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"in2_1"
),
f
::
GradVarName
(
"in2_2"
)}));
EXPECT_EQ
(
grad_op
->
Output
(
f
::
GradVarName
(
"In3_mult"
)),
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"in3_1"
),
f
::
GradVarName
(
"in3_2"
)}));
delete
forw_op
;
delete
grad_op
;
}
paddle/framework/op_desc.h
浏览文件 @
4c96008a
...
...
@@ -70,6 +70,22 @@ class OpDescBind {
std
::
vector
<
std
::
string
>
InputNames
()
const
{
return
MapKeys
(
inputs_
);
}
std
::
vector
<
std
::
string
>
OutputNames
()
const
{
return
MapKeys
(
outputs_
);
}
void
SetInputMap
(
const
VariableNameMap
&
input
)
{
this
->
inputs_
=
input
;
this
->
need_update_
=
true
;
}
void
SetOutputMap
(
const
VariableNameMap
&
output
)
{
this
->
outputs_
=
output
;
this
->
need_update_
=
true
;
}
void
Sync
();
const
VariableNameMap
&
Inputs
()
const
{
return
inputs_
;
}
const
VariableNameMap
&
Outputs
()
const
{
return
outputs_
;
}
private:
template
<
typename
MapType
>
static
std
::
vector
<
typename
MapType
::
key_type
>
MapKeys
(
const
MapType
&
map
)
{
...
...
@@ -81,8 +97,6 @@ class OpDescBind {
return
ret_val
;
}
void
Sync
();
OpDesc
op_desc_
;
VariableNameMap
inputs_
;
VariableNameMap
outputs_
;
...
...
paddle/framework/op_info.h
浏览文件 @
4c96008a
...
...
@@ -17,6 +17,7 @@
#include <map>
#include <string>
#include <unordered_map>
#include "paddle/framework/attribute.h"
#include "paddle/framework/op_desc.h"
#include "paddle/framework/type_defs.h"
...
...
@@ -27,7 +28,6 @@ namespace framework {
struct
OpInfo
{
OpCreator
creator_
;
std
::
string
grad_op_type_
;
GradOpMakerFN
grad_op_maker_
;
OpProto
*
proto_
{
nullptr
};
OpAttrChecker
*
checker_
{
nullptr
};
...
...
@@ -43,19 +43,19 @@ struct OpInfo {
return
*
proto_
;
}
const
OpAttrChecker
&
Checker
()
const
{
PADDLE_ENFORCE_NOT_NULL
(
checker_
,
"Operator Checker has not been registered"
);
return
*
checker_
;
}
const
OpCreator
&
Creator
()
const
{
PADDLE_ENFORCE_NOT_NULL
(
creator_
,
"Operator Creator has not been registered"
);
return
creator_
;
}
bool
HasGradientOp
()
const
{
return
!
grad_op_type_
.
empty
();
}
const
GradOpMakerFN
&
GradOpMaker
()
const
{
PADDLE_ENFORCE_NOT_NULL
(
grad_op_maker_
,
"Operator GradOpMaker has not been registered."
);
return
grad_op_maker_
;
}
const
OpAttrChecker
*
Checker
()
const
{
return
checker_
;
}
};
class
OpInfoMap
{
...
...
paddle/framework/op_proto_maker.h
浏览文件 @
4c96008a
...
...
@@ -44,11 +44,6 @@ class OpProtoAndCheckerMaker {
var_
->
set_intermediate
(
true
);
return
*
this
;
}
VariableBuilder
&
NotInGradient
()
{
var_
->
set_not_in_gradient
(
true
);
return
*
this
;
}
};
VariableBuilder
AddInput
(
const
std
::
string
&
name
,
const
std
::
string
&
comment
);
...
...
paddle/framework/op_registry.cc
浏览文件 @
4c96008a
...
...
@@ -23,7 +23,9 @@ std::unique_ptr<OperatorBase> OpRegistry::CreateOp(
const
std
::
string
&
type
,
const
VariableNameMap
&
inputs
,
const
VariableNameMap
&
outputs
,
AttributeMap
attrs
)
{
auto
&
info
=
OpInfoMap
::
Instance
().
Get
(
type
);
info
.
Checker
().
Check
(
attrs
);
if
(
info
.
Checker
()
!=
nullptr
)
{
info
.
Checker
()
->
Check
(
attrs
);
}
auto
op
=
info
.
Creator
()(
type
,
inputs
,
outputs
,
attrs
);
return
std
::
unique_ptr
<
OperatorBase
>
(
op
);
}
...
...
@@ -52,9 +54,9 @@ std::unique_ptr<OperatorBase> OpRegistry::CreateOp(const OpDesc& op_desc) {
return
CreateOp
(
op_desc
.
type
(),
inputs
,
outputs
,
attrs
);
}
std
::
unique_ptr
<
OperatorBase
>
OpRegistry
::
Create
GradOp
(
const
OperatorBase
&
op
)
{
PADDLE_ENFORCE
(
!
op
.
IsNetOp
(),
"Use framework::Backward to get backward ops"
);
return
std
::
unique_ptr
<
OperatorBase
>
(
BuildGradOp
(
&
op
));
std
::
unique_ptr
<
OperatorBase
>
OpRegistry
::
Create
Op
(
const
OpDescBind
&
op_desc
)
{
return
CreateOp
(
op_desc
.
Type
(),
op_desc
.
Inputs
(),
op_desc
.
Outputs
(),
op_desc
.
GetAttrMap
(
));
}
}
// namespace framework
...
...
paddle/framework/op_registry.h
浏览文件 @
4c96008a
...
...
@@ -23,25 +23,37 @@ limitations under the License. */
#include "paddle/framework/attribute.h"
#include "paddle/framework/details/op_registry.h"
#include "paddle/framework/framework.pb.h"
#include "paddle/framework/grad_op_builder.h"
#include "paddle/framework/grad_op_desc_maker.h"
#include "paddle/framework/op_desc.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/scope.h"
namespace
paddle
{
namespace
framework
{
class
Registrar
{
public:
// In our design, various kinds of classes, e.g., operators and kernels,
// have their corresponding registry and registrar. The action of
// registration is in the constructor of a global registrar variable, which,
// however, are not used in the code that calls package framework, and would
// be removed from the generated binary file by the linker. To avoid such
// removal, we add Touch to all registrar classes and make USE_OP macros to
// call this method. So, as long as the callee code calls USE_OP, the global
// registrar variable won't be removed by the linker.
void
Touch
()
{}
};
template
<
typename
...
ARGS
>
struct
OperatorRegistrar
{
struct
OperatorRegistrar
:
public
Registrar
{
explicit
OperatorRegistrar
(
const
char
*
op_type
)
:
op_type
(
op_type
)
{
PADDLE_ENFORCE
(
!
OpInfoMap
::
Instance
().
Has
(
op_type
),
"'%s' is registered more than once."
,
op_type
);
static_assert
(
sizeof
...(
ARGS
)
!=
0
,
"OperatorRegistrar should be invoked at least by OpClass"
);
details
::
OperatorRegistrarRecursive
<
0
,
false
,
ARGS
...
>
(
op_type
,
&
info
);
OpInfoMap
::
Instance
().
Insert
(
op_type
,
info
);
}
~
OperatorRegistrar
()
{
OpInfoMap
::
Instance
().
Insert
(
op_type
,
info
);
}
const
char
*
op_type
;
OpInfo
info
;
...
...
@@ -67,20 +79,7 @@ class OpRegistry {
static
std
::
unique_ptr
<
OperatorBase
>
CreateOp
(
const
OpDesc
&
op_desc
);
static
std
::
unique_ptr
<
OperatorBase
>
CreateGradOp
(
const
OperatorBase
&
op
);
};
class
Registrar
{
public:
// In our design, various kinds of classes, e.g., operators and kernels,
// have their corresponding registry and registrar. The action of
// registration is in the constructor of a global registrar variable, which,
// however, are not used in the code that calls package framework, and would
// be removed from the generated binary file by the linker. To avoid such
// removal, we add Touch to all registrar classes and make USE_OP macros to
// call this method. So, as long as the callee code calls USE_OP, the global
// registrar variable won't be removed by the linker.
void
Touch
()
{}
static
std
::
unique_ptr
<
OperatorBase
>
CreateOp
(
const
OpDescBind
&
op_desc
);
};
template
<
typename
OpType
,
typename
ProtoMakerType
,
typename
GradOpType
>
...
...
@@ -138,33 +137,41 @@ class OpKernelRegistrar : public Registrar {
__test_global_namespace_##uniq_name##__>::value, \
msg)
#define REGISTER_OPERATOR(op_type, op_class, ...) \
STATIC_ASSERT_GLOBAL_NAMESPACE( \
__reg_op__##op_type, \
"REGISTER_OPERATOR must be called in global namespace"); \
class _OpClass_##op_type##_ : public op_class { \
public: \
DEFINE_OP_CLONE_METHOD(_OpClass_##op_type##_); \
DEFINE_OP_CONSTRUCTOR(_OpClass_##op_type##_, op_class); \
}; \
static ::paddle::framework::OperatorRegistrar<_OpClass_##op_type##_, \
##__VA_ARGS__> \
__op_registrar_##op_type##__(#op_type); \
int TouchOpRegistrar_##op_type() { \
__op_registrar_##op_type##__.Touch(); \
return 0; \
}
/**
* Macro to register Operator.
*/
#define REGISTER_OP(op_type, op_class, op_maker_class, grad_op_type, \
grad_op_class) \
STATIC_ASSERT_GLOBAL_NAMESPACE( \
__reg_op__##op_type, "REGISTER_OP must be called in global namespace"); \
class _OpClass_##op_type##_ : public op_class { \
public: \
DEFINE_OP_CLONE_METHOD(_OpClass_##op_type##_); \
DEFINE_OP_CONSTRUCTOR(_OpClass_##op_type##_, op_class); \
}; \
class _OpGradClass_##op_type##_ : public grad_op_class { \
public: \
DEFINE_OP_CLONE_METHOD(_OpGradClass_##op_type##_); \
DEFINE_OP_CONSTRUCTOR(_OpGradClass_##op_type##_, grad_op_class); \
}; \
static ::paddle::framework::OpRegistrar< \
_OpClass_##op_type##_, op_maker_class, _OpGradClass_##op_type##_> \
__op_registrar_##op_type##__(#op_type, #grad_op_type); \
int TouchOpRegistrar_##op_type() { \
__op_registrar_##op_type##__.Touch(); \
return 0; \
}
#define REGISTER_OP(op_type, op_class, op_maker_class, grad_op_type, \
grad_op_class) \
REGISTER_OPERATOR(grad_op_type, grad_op_class); \
class _GradOpDescMaker_##grad_op_type##_ \
: public ::paddle::framework::DefaultGradOpDescMaker { \
using ::paddle::framework::DefaultGradOpDescMaker::DefaultGradOpDescMaker; \
\
protected: \
virtual std::string GradOpType() const { return #grad_op_type; } \
}; \
REGISTER_OPERATOR(op_type, op_class, _GradOpDescMaker_##grad_op_type##_, \
op_maker_class);
#define REGISTER_OP_WITHOUT_GRADIENT(op_type, op_class, op_maker_class) \
REGISTER_OP
(op_type, op_class, op_maker_class, , ::paddle::framework::NOP
)
REGISTER_OP
ERATOR(op_type, op_class, op_maker_class
)
/**
* Macro to register OperatorKernel.
...
...
paddle/operators/mean_op.cc
浏览文件 @
4c96008a
...
...
@@ -36,7 +36,7 @@ class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
MeanOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The input of mean op"
);
AddOutput
(
"Out"
,
"The output of mean op"
)
.
NotInGradient
()
;
AddOutput
(
"Out"
,
"The output of mean op"
);
AddComment
(
R"DOC( Mean Operator
)DOC"
);
}
...
...
@@ -52,11 +52,27 @@ class MeanGradOp : public framework::OperatorWithKernel {
}
};
class
MeanGradMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDescBind
>
Apply
()
const
override
{
auto
*
grad_op
=
new
framework
::
OpDescBind
();
grad_op
->
SetType
(
"mean_grad"
);
grad_op
->
SetInput
(
"X"
,
Input
(
"X"
));
grad_op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
grad_op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
return
std
::
unique_ptr
<
framework
::
OpDescBind
>
(
grad_op
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
mean
,
ops
::
MeanOp
,
ops
::
MeanOpMaker
,
mean_grad
,
ops
::
MeanGradOp
);
REGISTER_OPERATOR
(
mean
,
ops
::
MeanOp
,
ops
::
MeanOpMaker
,
ops
::
MeanGradMaker
);
REGISTER_OPERATOR
(
mean_grad
,
ops
::
MeanGradOp
);
REGISTER_OP_CPU_KERNEL
(
mean
,
ops
::
MeanKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
mean_grad
,
...
...
paddle/operators/minus_op.cc
浏览文件 @
4c96008a
...
...
@@ -49,9 +49,9 @@ class MinusOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MinusOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The left tensor of minus operator."
)
.
NotInGradient
()
;
AddInput
(
"Y"
,
"The right tensor of minus operator."
)
.
NotInGradient
()
;
AddOutput
(
"Out"
,
"The output tensor of minus operator."
)
.
NotInGradient
()
;
AddInput
(
"X"
,
"The left tensor of minus operator."
);
AddInput
(
"Y"
,
"The right tensor of minus operator."
);
AddOutput
(
"Out"
,
"The output tensor of minus operator."
);
AddComment
(
R"DOC(Minus Operator
...
...
@@ -64,26 +64,35 @@ or not. But the output only shares the LoD with input `X`.
)DOC"
);
}
};
template
<
typename
AttrType
>
class
MinusGrad
Op
:
public
NetOp
{
class
MinusGrad
Maker
:
public
framework
::
GradOpDescMakerBase
{
public:
MinusGradOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
NetOp
(
type
,
inputs
,
outputs
,
attrs
)
{
auto
out_grad
=
Input
(
framework
::
GradVarName
(
"Out"
));
auto
x_grad
=
Output
(
framework
::
GradVarName
(
"X"
));
auto
y_grad
=
Output
(
framework
::
GradVarName
(
"Y"
));
// x_grad = out_grad
AppendOp
(
framework
::
OpRegistry
::
CreateOp
(
"identity"
,
{{
"X"
,
{
out_grad
}}},
{{
"Y"
,
{
x_grad
}}},
{}));
framework
::
AttributeMap
scale_attr
;
scale_attr
[
"scale"
]
=
static_cast
<
AttrType
>
(
-
1
);
AppendOp
(
framework
::
OpRegistry
::
CreateOp
(
"scale"
,
{{
"X"
,
{
out_grad
}}},
{{
"Out"
,
{
y_grad
}}},
scale_attr
));
CompleteAddOp
(
false
);
using
framework
::
GradOpDescMakerBase
::
GradOpDescMakerBase
;
std
::
vector
<
std
::
unique_ptr
<
framework
::
OpDescBind
>>
operator
()()
const
override
{
std
::
vector
<
std
::
unique_ptr
<
framework
::
OpDescBind
>>
ops
;
auto
x_g
=
InputGrad
(
"X"
);
if
(
!
x_g
.
empty
())
{
auto
*
x_g_op
=
new
framework
::
OpDescBind
();
x_g_op
->
SetType
(
"scale"
);
x_g_op
->
SetInput
(
"X"
,
OutputGrad
(
"Out"
));
x_g_op
->
SetOutput
(
"Out"
,
x_g
);
x_g_op
->
SetAttr
(
"scale"
,
1.0
f
);
ops
.
emplace_back
(
x_g_op
);
}
auto
y_g
=
InputGrad
(
"Y"
);
if
(
!
y_g
.
empty
())
{
auto
*
y_g_op
=
new
framework
::
OpDescBind
();
y_g_op
->
SetType
(
"scale"
);
y_g_op
->
SetInput
(
"X"
,
OutputGrad
(
"Out"
));
y_g_op
->
SetOutput
(
"Out"
,
y_g
);
y_g_op
->
SetAttr
(
"scale"
,
-
1.0
f
);
ops
.
emplace_back
(
y_g_op
);
}
return
ops
;
}
};
...
...
@@ -91,7 +100,6 @@ class MinusGradOp : public NetOp {
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
minus
,
ops
::
MinusOp
,
ops
::
MinusOpMaker
,
minus_grad
,
ops
::
MinusGradOp
<
float
>
);
REGISTER_OPERATOR
(
minus
,
ops
::
MinusOp
,
ops
::
MinusOpMaker
,
ops
::
MinusGradMaker
);
REGISTER_OP_CPU_KERNEL
(
minus
,
ops
::
MinusKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
paddle/operators/pad_op.cc
浏览文件 @
4c96008a
...
...
@@ -56,8 +56,7 @@ class PadOpMaker : public framework::OpProtoAndCheckerMaker {
"The input should be a k-D tensor(k > 0 and k < 7)"
);
AddOutput
(
"Out"
,
"The output of pad op."
"A tensor with the same shape as X."
)
.
NotInGradient
();
"A tensor with the same shape as X."
);
AddComment
(
R"DOC(
Pad input into output, as specified by paddings and pad_value. The input should be a k-D tensor(k > 0 and k < 7). As an example:
...
...
@@ -111,11 +110,29 @@ class PadOpGrad : public framework::OperatorWithKernel {
}
};
class
PadOpGradMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDescBind
>
Apply
()
const
override
{
auto
*
bind
=
new
framework
::
OpDescBind
();
bind
->
SetInput
(
"X"
,
Input
(
"X"
));
bind
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
bind
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
bind
->
SetAttrMap
(
Attrs
());
bind
->
SetType
(
"pad_grad"
);
return
std
::
unique_ptr
<
framework
::
OpDescBind
>
(
bind
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
pad
,
ops
::
PadOp
,
ops
::
PadOpMaker
,
pad_grad
,
ops
::
PadOpGrad
);
REGISTER_OPERATOR
(
pad
,
ops
::
PadOp
,
ops
::
PadOpMaker
,
ops
::
PadOpGradMaker
);
REGISTER_OPERATOR
(
pad_grad
,
ops
::
PadOpGrad
);
REGISTER_OP_CPU_KERNEL
(
pad
,
ops
::
PadKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
pad_grad
,
ops
::
PadGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
paddle/operators/scale_op.cc
浏览文件 @
4c96008a
...
...
@@ -41,8 +41,8 @@ class ScaleOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ScaleOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The input tensor of scale operator."
)
.
NotInGradient
()
;
AddOutput
(
"Out"
,
"The output tensor of scale operator."
)
.
NotInGradient
()
;
AddInput
(
"X"
,
"The input tensor of scale operator."
);
AddOutput
(
"Out"
,
"The output tensor of scale operator."
);
AddComment
(
R"DOC(Scale operator
The equation is: Out = scale*X
...
...
@@ -52,21 +52,18 @@ The equation is: Out = scale*X
}
};
// The operator to calculate gradients of a scale operator is just the scale
// operator itself.
// Grad(Out=scale(X)) => Grad(X) = scale(Grad(Out))
template
<
typename
AttrType
>
class
ScaleGradOp
:
public
NetOp
{
class
ScaleGradMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
ScaleGradOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
NetOp
(
type
,
inputs
,
outputs
,
attrs
)
{
AppendOp
(
framework
::
OpRegistry
::
CreateOp
(
"scale"
,
{{
"X"
,
{
Input
(
framework
::
GradVarName
(
"Out"
))}}},
{{
"Out"
,
{
Output
(
framework
::
GradVarName
(
"X"
))}}},
{{
"scale"
,
Attr
<
AttrType
>
(
"scale"
)}}));
CompleteAddOp
(
false
);
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDescBind
>
Apply
()
const
override
{
auto
*
grad_op
=
new
framework
::
OpDescBind
();
grad_op
->
SetType
(
"scale"
);
grad_op
->
SetInput
(
"X"
,
OutputGrad
(
"Out"
));
grad_op
->
SetOutput
(
"Out"
,
InputGrad
(
"X"
));
grad_op
->
SetAttr
(
"scale"
,
GetAttr
(
"scale"
));
return
std
::
unique_ptr
<
framework
::
OpDescBind
>
(
grad_op
);
}
};
...
...
@@ -75,7 +72,7 @@ class ScaleGradOp : public NetOp {
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
scale
,
ops
::
ScaleOp
,
ops
::
ScaleOpMaker
<
float
>
,
scale_grad
,
ops
::
ScaleGradOp
<
float
>
);
REGISTER_OP
ERATOR
(
scale
,
ops
::
ScaleOp
,
ops
::
ScaleOpMaker
<
float
>
,
ops
::
ScaleGradMaker
);
REGISTER_OP_CPU_KERNEL
(
scale
,
ops
::
ScaleKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
paddle/operators/softmax_with_cross_entropy_op.cc
浏览文件 @
4c96008a
...
...
@@ -14,6 +14,7 @@
#include "paddle/operators/softmax_with_cross_entropy_op.h"
#include <paddle/function/TensorType.h>
#include <iostream>
namespace
paddle
{
namespace
operators
{
...
...
@@ -27,15 +28,14 @@ class SoftmaxWithCrossEntropyOpMaker
AddInput
(
"Logits"
,
"(Tensor, default: Tensor<float>), The unscaled log probabilities "
"which is a 2-D tensor with shape [N x K]. N is the batch_size, "
"and K is the class number."
)
.
NotInGradient
();
AddInput
(
"Label"
,
"(Tensor, default: Tensor<int>), The ground truth which is a 2-D "
"tensor. "
"If softLable is set to 0, Label is a Tensor<int> with shape [N x 1]. "
"If softLable is set to 1, Label is a Tensor<float/double> "
"with shape [N x K]."
);
"and K is the class number."
);
AddInput
(
"Label"
,
"(Tensor, default: Tensor<int>), The ground truth which is a 2-D "
"tensor. "
"If softLable is set to 0, Label is a Tensor<int> with shape [N x "
"1]. "
"If softLable is set to 1, Label is a Tensor<float/double> "
"with shape [N x K]."
);
AddOutput
(
"Softmax"
,
"(Tensor, default: Tensor<float>), A 2-D tensor with shape [N x K]. "
...
...
@@ -163,15 +163,34 @@ class SoftmaxWithCrossEntropyOpGrad : public framework::OperatorWithKernel {
}
};
class
SoftmaxGradMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDescBind
>
Apply
()
const
override
{
auto
*
grad_op
=
new
framework
::
OpDescBind
();
grad_op
->
SetType
(
"softmax_with_cross_entropy_grad"
);
grad_op
->
SetInput
(
"Label"
,
Input
(
"Label"
));
grad_op
->
SetInput
(
"Softmax"
,
Output
(
"Softmax"
));
grad_op
->
SetInput
(
"Loss"
,
Output
(
"Loss"
));
grad_op
->
SetInput
(
framework
::
GradVarName
(
"Softmax"
),
OutputGrad
(
"Softmax"
));
grad_op
->
SetInput
(
framework
::
GradVarName
(
"Loss"
),
OutputGrad
(
"Loss"
));
grad_op
->
SetOutput
(
framework
::
GradVarName
(
"Logits"
),
InputGrad
(
"Logits"
));
grad_op
->
SetAttrMap
(
Attrs
());
return
std
::
unique_ptr
<
framework
::
OpDescBind
>
(
grad_op
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
softmax_with_cross_entropy
,
ops
::
SoftmaxWithCrossEntropyOp
,
ops
::
SoftmaxWithCrossEntropyOpMaker
,
softmax_with_cross_entropy_grad
,
ops
::
SoftmaxWithCrossEntropyOpGrad
);
REGISTER_OP
ERATOR
(
softmax_with_cross_entropy
,
ops
::
SoftmaxWithCrossEntropyOp
,
ops
::
SoftmaxWithCrossEntropyOpMaker
,
ops
::
SoftmaxGradMaker
);
REGISTER_OPERATOR
(
softmax_with_cross_entropy_grad
,
ops
::
SoftmaxWithCrossEntropyOpGrad
);
REGISTER_OP_CPU_KERNEL
(
softmax_with_cross_entropy
,
ops
::
SoftmaxWithCrossEntropyKernel
<
float
>
);
REGISTER_OP_CPU_KERNEL
(
softmax_with_cross_entropy_grad
,
...
...
paddle/operators/sum_op.cc
浏览文件 @
4c96008a
...
...
@@ -45,10 +45,8 @@ class SumOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SumOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"the input tensors of sum operator."
)
.
AsDuplicable
()
.
NotInGradient
();
AddOutput
(
"Out"
,
"the output tensor of sum operator."
).
NotInGradient
();
AddInput
(
"X"
,
"the input tensors of sum operator."
).
AsDuplicable
();
AddOutput
(
"Out"
,
"the output tensor of sum operator."
);
AddComment
(
R"DOC(
Sum the input tensors.
...
...
@@ -58,23 +56,26 @@ or not. But the output only shares the LoD with the first input.
}
};
class
SumGrad
Op
:
public
NetOp
{
class
SumGrad
Maker
:
public
framework
::
GradOpDescMakerBase
{
public:
SumGradOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
NetOp
(
type
,
inputs
,
outputs
,
attrs
)
{
auto
&
x_grad_names
=
Outputs
(
framework
::
GradVarName
(
"X"
));
auto
out_grad_name
=
this
->
Input
(
framework
::
GradVarName
(
"Out"
));
using
framework
::
GradOpDescMakerBase
::
GradOpDescMakerBase
;
framework
::
AttributeMap
grad_attrs
;
grad_attrs
[
"scale"
]
=
1.0
f
;
for
(
auto
&
x_grad_name
:
x_grad_names
)
{
AppendOp
(
framework
::
OpRegistry
::
CreateOp
(
"scale"
,
{{
"X"
,
{
out_grad_name
}}},
{{
"Out"
,
{
x_grad_name
}}},
grad_attrs
));
}
CompleteAddOp
(
false
);
std
::
vector
<
std
::
unique_ptr
<
framework
::
OpDescBind
>>
operator
()()
const
override
{
auto
x_grads
=
InputGrad
(
"X"
);
std
::
vector
<
std
::
unique_ptr
<
framework
::
OpDescBind
>>
grad_ops
;
grad_ops
.
reserve
(
x_grads
.
size
());
auto
og
=
OutputGrad
(
"Out"
);
std
::
transform
(
x_grads
.
begin
(),
x_grads
.
end
(),
std
::
back_inserter
(
grad_ops
),
[
&
og
](
const
std
::
string
&
x_grad
)
{
auto
*
grad_op
=
new
framework
::
OpDescBind
();
grad_op
->
SetType
(
"scale"
);
grad_op
->
SetInput
(
"X"
,
og
);
grad_op
->
SetOutput
(
"Out"
,
{
x_grad
});
grad_op
->
SetAttr
(
"scale"
,
1.0
f
);
return
std
::
unique_ptr
<
framework
::
OpDescBind
>
(
grad_op
);
});
return
grad_ops
;
}
};
...
...
@@ -82,5 +83,6 @@ class SumGradOp : public NetOp {
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
sum
,
ops
::
SumOp
,
ops
::
SumOpMaker
,
sum_grad
,
ops
::
SumGradOp
);
REGISTER_OPERATOR
(
sum
,
ops
::
SumOp
,
ops
::
SumOpMaker
,
ops
::
SumGradMaker
);
REGISTER_OP_CPU_KERNEL
(
sum
,
ops
::
SumKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
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