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体验新版 GitCode,发现更多精彩内容 >>
提交
e54f203c
编写于
4月 15, 2018
作者:
D
dzhwinter
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
"move to a new PR"
上级
494c262a
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
246 addition
and
354 deletion
+246
-354
paddle/fluid/operators/activation_op.cc
paddle/fluid/operators/activation_op.cc
+186
-330
paddle/fluid/operators/activation_op.h
paddle/fluid/operators/activation_op.h
+48
-10
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+4
-0
python/paddle/fluid/layer_helper.py
python/paddle/fluid/layer_helper.py
+5
-1
python/paddle/fluid/tests/unittests/test_activation_op.py
python/paddle/fluid/tests/unittests/test_activation_op.py
+3
-13
未找到文件。
paddle/fluid/operators/activation_op.cc
浏览文件 @
e54f203c
...
...
@@ -18,6 +18,37 @@ limitations under the License. */
namespace
paddle
{
namespace
operators
{
#define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT) \
class OP_NAME##OpMaker : public framework::OpProtoAndCheckerMaker { \
public: \
OP_NAME##OpMaker(OpProto *proto, OpAttrChecker *op_checker) \
: framework::OpProtoAndCheckerMaker(proto, op_checker) { \
AddInput("X", "Input of " #OP_NAME "operator"); \
AddOutput("Out", "Output of" #OP_NAME "operator"); \
AddAttr<bool>("use_mkldnn", \
"(bool, default false) Only used in mkldnn kernel") \
.SetDefault(false); \
AddComment(#OP_COMMENT); \
} \
}
#define REGISTER_ACTIVATION_OP_GRAD_MAKER(OP_NAME) \
class OP_NAME##GradMaker : public framework::SingleGradOpDescMaker { \
public: \
protected: \
std::unique_ptr<framework::OpDesc> Apply() const override { \
auto *op = new framework::OpDesc(); \
op->SetType(#OP_NAME "_grad"); \
op->SetInput("Out", Input("Out")); \
op->SetInput(framework::GradVarName("Out"), OutputGrad("Out")); \
\
op->SetAttrMap(Attrs()); \
\
op->SetOutput(framework::GradVarName("X"), InputGrad("X")); \
return std::unique_ptr<framework::OpDesc>(op); \
} \
}
class
ActivationOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
...
...
@@ -37,346 +68,190 @@ class ActivationOpGrad : public framework::OperatorWithKernel {
}
};
class
SigmoidOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
SigmoidOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Sigmoid operator"
);
AddOutput
(
"Out"
,
"Output of Sigmoid operator"
);
AddComment
(
R"DOC(
constexpr
char
SigmoidDoc
[]
=
R"DOC(
Sigmoid Activation Operator
$$out = \frac{1}{1 + e^{-x}}$$
)DOC"
);
}
};
)DOC"
;
class
LogSigmoidOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
LogSigmoidOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of LogSigmoid operator"
);
AddOutput
(
"Out"
,
"Output of LogSigmoid operator"
);
AddComment
(
R"DOC(
constexpr
char
LogSigmoidDoc
[]
=
R"DOC(
Logsigmoid Activation Operator
$$out = \log \frac{1}{1 + e^{-x}}$$
)DOC"
);
}
};
)DOC"
;
class
ExpOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
ExpOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Exp operator"
);
AddOutput
(
"Out"
,
"Output of Exp operator"
);
AddComment
(
R"DOC(
constexpr
char
ExpDoc
[]
=
R"DOC(
Exp Activation Operator.
$out = e^x$
)DOC"
);
}
};
)DOC"
;
class
ReluOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
ReluOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Relu operator"
);
AddOutput
(
"Out"
,
"Output of Relu operator"
);
AddAttr
<
bool
>
(
"use_mkldnn"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddComment
(
R"DOC(
constexpr
char
ReluDoc
[]
=
R"DOC(
Relu Activation Operator.
$out = \max(x, 0)$
)DOC"
);
}
};
class
LeakyReluOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
LeakyReluOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of LeakyRelu operator"
);
AddOutput
(
"Out"
,
"Output of LeakyRelu operator"
);
AddAttr
<
float
>
(
"alpha"
,
"The small negative slope"
).
SetDefault
(
0.02
f
);
AddComment
(
R"DOC(
LeakyRelu Activation Operator.
$out = \max(x, \alpha * x)$
)DOC"
);
}
};
class
SoftShrinkOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
SoftShrinkOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Softshrink operator"
);
AddOutput
(
"Out"
,
"Output of Softshrink operator"
);
AddAttr
<
float
>
(
"lambda"
,
"non-negative offset"
).
SetDefault
(
0.5
f
);
AddComment
(
R"DOC(
Softshrink Activation Operator.
$$
out = \begin{cases}
x - \lambda, \text{if } x > \lambda \\
x + \lambda, \text{if } x < -\lambda \\
0, \text{otherwise}
\end{cases}
$$
)DOC"
;
)DOC"
);
}
};
class
TanhOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
TanhOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Tanh operator"
);
AddOutput
(
"Out"
,
"Output of Tanh operator"
);
AddAttr
<
bool
>
(
"use_mkldnn"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddComment
(
R"DOC(
constexpr
char
TanhDoc
[]
=
R"DOC(
Tanh Activation Operator.
$$out = \frac{e^{x} - e^{-x}}{e^{x} + e^{-x}}$$
)DOC"
);
}
};
)DOC"
;
class
TanhShrinkOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
TanhShrinkOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of TanhShrink operator"
);
AddOutput
(
"Out"
,
"Output of TanhShrink operator"
);
AddComment
(
R"DOC(
constexpr
char
TanhShrinkDoc
[]
=
R"DOC(
TanhShrink Activation Operator.
$$out = x - \frac{e^{x} - e^{-x}}{e^{x} + e^{-x}}$$
)DOC"
);
}
};
class
HardShrinkOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
HardShrinkOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of HardShrink operator"
);
AddOutput
(
"Out"
,
"Output of HardShrink operator"
);
AddAttr
<
float
>
(
"threshold"
,
"The value of threshold for HardShrink"
)
.
SetDefault
(
0.5
f
);
AddComment
(
R"DOC(
HardShrink Activation Operator.
)DOC"
;
$$
out = \begin{cases}
x, \text{if } x > \lambda \\
x, \text{if } x < -\lambda \\
0, \text{otherwise}
\end{cases}
$$
)DOC"
);
}
};
class
SqrtOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
SqrtOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Sqrt operator"
);
AddOutput
(
"Out"
,
"Output of Sqrt operator"
);
AddAttr
<
bool
>
(
"use_mkldnn"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddComment
(
R"DOC(
constexpr
char
SqrtDoc
[]
=
R"DOC(
Sqrt Activation Operator.
$out = \sqrt{x}$
)DOC"
);
}
};
)DOC"
;
class
AbsOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
AbsOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Abs operator"
);
AddOutput
(
"Out"
,
"Output of Abs operator"
);
AddAttr
<
bool
>
(
"use_mkldnn"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddComment
(
R"DOC(
constexpr
char
AbsDoc
[]
=
R"DOC(
Abs Activation Operator.
$out = |x|$
)DOC"
);
}
};
)DOC"
;
class
CeilOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
CeilOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Ceil operator"
);
AddOutput
(
"Out"
,
"Output of Ceil operator"
);
AddComment
(
R"DOC(
constexpr
char
CeilDoc
[]
=
R"DOC(
Ceil Activation Operator.
$out = ceil(x)$
)DOC"
);
}
};
)DOC"
;
class
FloorOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
FloorOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Floor operator"
);
AddOutput
(
"Out"
,
"Output of Floor operator"
);
AddComment
(
R"DOC(
constexpr
char
FloorDoc
[]
=
R"DOC(
Floor Activation Operator.
$out = floor(x)$
)DOC"
);
}
};
)DOC"
;
class
CosOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
CosOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Cosine operator"
);
AddOutput
(
"Out"
,
"Output of Cosine operator"
);
AddComment
(
R"DOC(
constexpr
char
CosDoc
[]
=
R"DOC(
Cosine Activation Operator.
$out = cos(x)$
)DOC"
);
}
};
)DOC"
;
class
SinOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
SinOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Sine operator"
);
AddOutput
(
"Out"
,
"Output of Sine operator"
);
AddComment
(
R"DOC(
constexpr
char
SinDoc
[]
=
R"DOC(
Sine Activation Operator.
$out = sin(x)$
)DOC"
);
}
};
)DOC"
;
class
RoundOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
RoundOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Round operator"
);
AddOutput
(
"Out"
,
"Output of Round operator"
);
AddComment
(
R"DOC(
constexpr
char
RoundDoc
[]
=
R"DOC(
Round Activation Operator.
$out = [x]$
)DOC"
);
}
};
)DOC"
;
class
ReciprocalOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
ReciprocalOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Reciprocal operator"
);
AddOutput
(
"Out"
,
"Output of Reciprocal operator"
);
AddComment
(
R"DOC(
constexpr
char
ReciprocalDoc
[]
=
R"DOC(
Reciprocal Activation Operator.
$$out = \frac{1}{x}$$
)DOC"
);
}
};
)DOC"
;
class
LogOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
LogOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Log operator"
);
AddOutput
(
"Out"
,
"Output of Log operator"
);
AddComment
(
R"DOC(
constexpr
char
LogDoc
[]
=
R"DOC(
Log Activation Operator.
$out = \ln(x)$
Natural logarithm of x.
)DOC"
);
}
};
)DOC"
;
constexpr
char
SquareDoc
[]
=
R"DOC(
Square Activation Operator.
$out = x^2$
class
SquareOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
)DOC"
;
constexpr
char
SoftplusDoc
[]
=
R"DOC(
Softplus Activation Operator.
$out = \ln(1 + e^{x})$
)DOC"
;
constexpr
char
SoftsignDoc
[]
=
R"DOC(
Softsign Activation Operator.
$$out = \frac{x}{1 + |x|}$$
)DOC"
;
class
LeakyReluOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
Square
OpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
LeakyRelu
OpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Square operator"
);
AddOutput
(
"Out"
,
"Output of Square operator"
);
AddInput
(
"X"
,
"Input of LeakyRelu operator"
);
AddOutput
(
"Out"
,
"Output of LeakyRelu operator"
);
AddAttr
<
float
>
(
"alpha"
,
"The small negative slope"
).
SetDefault
(
0.02
f
);
AddComment
(
R"DOC(
Square
Activation Operator.
LeakyRelu
Activation Operator.
$out =
x^2
$
$out =
\max(x, \alpha * x)
$
)DOC"
);
}
};
class
Soft
plus
OpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
Soft
Shrink
OpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
Soft
plus
OpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
Soft
Shrink
OpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Softplus operator"
);
AddOutput
(
"Out"
,
"Output of Softplus operator"
);
AddInput
(
"X"
,
"Input of Softshrink operator"
);
AddOutput
(
"Out"
,
"Output of Softshrink operator"
);
AddAttr
<
float
>
(
"lambda"
,
"non-negative offset"
).
SetDefault
(
0.5
f
);
AddComment
(
R"DOC(
Soft
plus
Activation Operator.
Soft
shrink
Activation Operator.
$out = \ln(1 + e^{x})$
$$
out = \begin{cases}
x - \lambda, \text{if } x > \lambda \\
x + \lambda, \text{if } x < -\lambda \\
0, \text{otherwise}
\end{cases}
$$
)DOC"
);
}
};
class
Softsign
OpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
HardShrink
OpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
Softsign
OpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
HardShrink
OpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Softsign operator"
);
AddOutput
(
"Out"
,
"Output of Softsign operator"
);
AddInput
(
"X"
,
"Input of HardShrink operator"
);
AddOutput
(
"Out"
,
"Output of HardShrink operator"
);
AddAttr
<
float
>
(
"threshold"
,
"The value of threshold for HardShrink"
)
.
SetDefault
(
0.5
f
);
AddComment
(
R"DOC(
Softsign
Activation Operator.
HardShrink
Activation Operator.
$$out = \frac{x}{1 + |x|}$$
$$
out = \begin{cases}
x, \text{if } x > \lambda \\
x, \text{if } x < -\lambda \\
0, \text{otherwise}
\end{cases}
$$
)DOC"
);
}
...
...
@@ -553,100 +428,80 @@ $$out = \frac{x}{1 + e^{- \beta x}}$$
}
};
REGISTER_ACTIVATION_OP_MAKER
(
Sigmoid
,
SigmoidDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
LogSigmoid
,
LogSigmoidDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Exp
,
ExpDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Relu
,
ReluDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Tanh
,
TanhDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
TanhShrink
,
TanhShrinkDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Sqrt
,
SqrtDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Abs
,
AbsDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Ceil
,
CeilDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Floor
,
FloorDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Cos
,
CosDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Sin
,
SinDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Round
,
RoundDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Reciprocal
,
ReciprocalDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Log
,
LogDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Square
,
SquareDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Softplus
,
SoftplusDoc
);
REGISTER_ACTIVATION_OP_MAKER
(
Softsign
,
SoftsignDoc
);
// NOTE(*) only gradient can be inplaced need to register its gradient maker,
// To tell the executor which input variable is used. By default, every Input
// variable
// is used in gradient operator.
// The operator name written in lowercase intentionally.
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
sigmoid
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
exp
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
relu
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
tanh
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
sqrt
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
ceil
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
floor
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
reciprocal
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
relu6
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
soft_relu
);
REGISTER_ACTIVATION_OP_GRAD_MAKER
(
hard_sigmoid
);
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
sigmoid
,
ops
::
ActivationOp
,
ops
::
SigmoidOpMaker
,
sigmoid_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
logsigmoid
,
ops
::
ActivationOp
,
ops
::
LogSigmoidOpMaker
,
logsigmoid_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
exp
,
ops
::
ActivationOp
,
ops
::
ExpOpMaker
,
exp_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
relu
,
ops
::
ActivationWithMKLDNNOp
,
ops
::
ReluOpMaker
,
relu_grad
,
ops
::
ActivationWithMKLDNNOpGrad
);
REGISTER_OP
(
tanh
,
ops
::
ActivationWithMKLDNNOp
,
ops
::
TanhOpMaker
,
tanh_grad
,
ops
::
ActivationWithMKLDNNOpGrad
);
REGISTER_OP
(
tanh_shrink
,
ops
::
ActivationOp
,
ops
::
TanhShrinkOpMaker
,
tanh_shrink_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
softshrink
,
ops
::
ActivationOp
,
ops
::
SoftShrinkOpMaker
,
softshrink_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
sqrt
,
ops
::
ActivationWithMKLDNNOp
,
ops
::
SqrtOpMaker
,
sqrt_grad
,
ops
::
ActivationWithMKLDNNOpGrad
);
REGISTER_OP
(
abs
,
ops
::
ActivationWithMKLDNNOp
,
ops
::
AbsOpMaker
,
abs_grad
,
ops
::
ActivationWithMKLDNNOpGrad
);
REGISTER_OP
(
ceil
,
ops
::
ActivationOp
,
ops
::
CeilOpMaker
,
ceil_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
floor
,
ops
::
ActivationOp
,
ops
::
FloorOpMaker
,
floor_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
cos
,
ops
::
ActivationOp
,
ops
::
CosOpMaker
,
cos_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
sin
,
ops
::
ActivationOp
,
ops
::
SinOpMaker
,
sin_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
round
,
ops
::
ActivationOp
,
ops
::
RoundOpMaker
,
round_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
reciprocal
,
ops
::
ActivationOp
,
ops
::
ReciprocalOpMaker
,
reciprocal_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
log
,
ops
::
ActivationOp
,
ops
::
LogOpMaker
,
log_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
square
,
ops
::
ActivationOp
,
ops
::
SquareOpMaker
,
square_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
softplus
,
ops
::
ActivationOp
,
ops
::
SoftplusOpMaker
,
softplus_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
softsign
,
ops
::
ActivationOp
,
ops
::
SoftsignOpMaker
,
softsign_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
brelu
,
ops
::
ActivationOp
,
ops
::
BReluOpMaker
,
brelu_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
leaky_relu
,
ops
::
ActivationOp
,
ops
::
LeakyReluOpMaker
,
leaky_relu_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
soft_relu
,
ops
::
ActivationOp
,
ops
::
SoftReluOpMaker
,
soft_relu_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
elu
,
ops
::
ActivationOp
,
ops
::
ELUOpMaker
,
elu_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
relu6
,
ops
::
ActivationOp
,
ops
::
Relu6OpMaker
,
relu6_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
pow
,
ops
::
ActivationOp
,
ops
::
PowOpMaker
,
pow_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
stanh
,
ops
::
ActivationOp
,
ops
::
STanhOpMaker
,
stanh_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
hard_shrink
,
ops
::
ActivationOp
,
ops
::
HardShrinkOpMaker
,
hard_shrink_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
thresholded_relu
,
ops
::
ActivationOp
,
ops
::
ThresholdedReluOpMaker
,
thresholded_relu_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
hard_sigmoid
,
ops
::
ActivationOp
,
ops
::
HardSigmoidOpMaker
,
hard_sigmoid_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
swish
,
ops
::
ActivationOp
,
ops
::
SwishOpMaker
,
swish_grad
,
ops
::
ActivationOpGrad
);
#define REGISTER_ACTIVATION_OP(act_type, op_name) \
REGISTER_OP(act_type, ops::ActivationOp, ops::op_name##OpMaker, \
act_type##_grad, ops::ActivationOpGrad);
#define FOR_EACH_OP_FUNCTOR(__macro) \
__macro(sigmoid, Sigmoid); \
__macro(logsigmoid, LogSigmoid); \
__macro(exp, Exp); \
__macro(tanh, Tanh); \
__macro(softshrink, SoftShrink); \
__macro(sqrt, Sqrt); \
__macro(abs, Abs); \
__macro(ceil, Ceil); \
__macro(floor, Floor); \
__macro(cos, Cos); \
__macro(sin, Sin); \
__macro(round, Round); \
__macro(reciprocal, Reciprocal); \
__macro(log, Log); \
__macro(square, Square); \
__macro(brelu, BRelu); \
__macro(soft_relu, SoftRelu); \
__macro(pow, Pow); \
__macro(stanh, STanh); \
__macro(softplus, Softplus); \
__macro(softsign, Softsign); \
__macro(relu6, Relu6); \
__macro(leaky_relu, LeakyRelu); \
__macro(tanh_shrink, TanhShrink); \
__macro(elu, ELU); \
__macro(hard_shrink, HardShrink); \
__macro(hard_sigmoid, HardSigmoid); \
__macro(swish, Swish); \
__macro(thresholded_relu, ThresholdedRelu);
#define REGISTER_ACTIVATION_CPU_KERNEL(act_type, functor, grad_functor) \
REGISTER_OP_CPU_KERNEL( \
...
...
@@ -661,4 +516,5 @@ REGISTER_OP(swish, ops::ActivationOp, ops::SwishOpMaker, swish_grad,
ops::ActivationGradKernel<paddle::platform::CPUDeviceContext, \
ops::grad_functor<double>>);
FOR_EACH_OP_FUNCTOR
(
REGISTER_ACTIVATION_OP
);
FOR_EACH_KERNEL_FUNCTOR
(
REGISTER_ACTIVATION_CPU_KERNEL
);
paddle/fluid/operators/activation_op.h
浏览文件 @
e54f203c
...
...
@@ -10,6 +10,9 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <glog/logging.h>
#include <string>
#include <unordered_set>
#include <utility>
#include <vector>
...
...
@@ -25,6 +28,16 @@ limitations under the License. */
namespace
paddle
{
namespace
operators
{
/* Use ugly global variable, for the using in python layer side
Please refer to the layer_helper.py and get the details.
*/
static
std
::
unordered_set
<
std
::
string
>
InplaceOpSet
=
{
"sigmoid"
,
"exp"
,
"relu"
,
"tanh"
,
"sqrt"
,
"ceil"
,
"floor"
,
"reciprocal"
,
"relu6"
,
"soft_relu"
,
"hard_sigmoid"
,
};
static
bool
IsInplace
(
std
::
string
op
)
{
return
InplaceOpSet
.
count
(
op
);
}
template
<
typename
DeviceContext
,
typename
Functor
>
class
ActivationKernel
:
public
framework
::
OpKernel
<
typename
Functor
::
ELEMENT_TYPE
>
{
...
...
@@ -60,7 +73,6 @@ class ActivationGradKernel
public:
using
T
=
typename
Functor
::
ELEMENT_TYPE
;
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
X
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
*
Out
=
context
.
Input
<
framework
::
Tensor
>
(
"Out"
);
auto
*
dOut
=
context
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
...
...
@@ -68,7 +80,6 @@ class ActivationGradKernel
dX
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dout
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dOut
);
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
X
);
auto
out
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
Out
);
auto
dx
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dX
);
auto
*
place
=
...
...
@@ -78,7 +89,16 @@ class ActivationGradKernel
for
(
auto
&
attr
:
attrs
)
{
*
attr
.
second
=
context
.
Attr
<
float
>
(
attr
.
first
);
}
functor
(
*
place
,
x
,
out
,
dout
,
dx
);
bool
inplace
=
functor
.
Inplace
();
if
(
!
inplace
)
{
auto
*
X
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
X
);
functor
(
*
place
,
x
,
out
,
dout
,
dx
);
}
else
{
VLOG
(
10
)
<<
" Inplace activation "
;
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dX
);
functor
(
*
place
,
x
,
out
,
dout
,
dx
);
}
}
};
...
...
@@ -89,6 +109,14 @@ struct BaseActivationFunctor {
using
AttrPair
=
std
::
vector
<
std
::
pair
<
const
char
*
,
float
*>>
;
AttrPair
GetAttrs
()
{
return
AttrPair
();
}
/* NOTE(*): Output reuse X memory if X is not dependented by its Gradient.
For example, sigmoid op's gradient didn't involve x, so its output can
reuse
input memory. But abs op's gradient use x, it can not be inplaced.
gradient did use x.
*/
bool
Inplace
()
const
{
return
false
;
}
};
// sigmoid(x) = 1 / (1 + exp(-x))
...
...
@@ -102,6 +130,7 @@ struct SigmoidFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
SigmoidGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"sigmoid"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -156,6 +185,7 @@ struct ExpFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
ExpGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"exp"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -174,10 +204,11 @@ struct ReluFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
ReluGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"relu"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
dx
.
device
(
d
)
=
dout
*
(
x
>
static_cast
<
T
>
(
0
)).
template
cast
<
T
>();
dx
.
device
(
d
)
=
dout
*
(
out
>
static_cast
<
T
>
(
0
)).
template
cast
<
T
>();
}
};
...
...
@@ -192,6 +223,7 @@ struct TanhFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
TanhGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"tanh"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -297,6 +329,7 @@ struct SqrtFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
SqrtGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"sqrt"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -316,10 +349,11 @@ struct CeilFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
ZeroGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"ceil"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
dx
.
device
(
d
)
=
static_cast
<
T
>
(
0
)
/
x
;
dx
.
device
(
d
)
=
static_cast
<
T
>
(
0
)
/
out
;
}
};
...
...
@@ -432,6 +466,7 @@ struct ReciprocalFunctor : public BaseActivationFunctor<T> {
template
<
typename
T
>
struct
ReciprocalGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
bool
Inplace
()
const
{
return
IsInplace
(
"reciprocal"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
@@ -531,12 +566,14 @@ struct Relu6GradFunctor : public BaseActivationFunctor<T> {
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"threshold"
,
&
threshold
}};
}
bool
Inplace
()
const
{
return
IsInplace
(
"relu6"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
dx
.
device
(
d
)
=
dout
*
((
x
>
static_cast
<
T
>
(
0
))
*
(
x
<
static_cast
<
T
>
(
threshold
)))
.
template
cast
<
T
>();
dx
.
device
(
d
)
=
dout
*
((
out
>
static_cast
<
T
>
(
0
))
*
(
out
<
static_cast
<
T
>
(
threshold
)))
.
template
cast
<
T
>();
}
};
...
...
@@ -611,11 +648,12 @@ struct SoftReluGradFunctor : public BaseActivationFunctor<T> {
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"threshold"
,
&
threshold
}};
}
bool
Inplace
()
const
{
return
IsInplace
(
"softrelu"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
auto
tmp
=
static_cast
<
T
>
(
threshold
);
auto
temp
=
((
x
>
-
tmp
)
*
(
x
<
tmp
)).
template
cast
<
T
>().
eval
();
auto
temp
=
((
out
>
-
tmp
)
*
(
out
<
tmp
)).
template
cast
<
T
>().
eval
();
dx
.
device
(
d
)
=
dout
*
(
static_cast
<
T
>
(
1
)
-
(
-
out
).
exp
())
*
temp
;
}
};
...
...
@@ -791,7 +829,7 @@ struct HardSigmoidGradFunctor : public BaseActivationFunctor<T> {
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"slope"
,
&
slope
},
{
"offset"
,
&
offset
}};
}
bool
Inplace
()
{
return
IsInplace
(
"hard_sigmoid"
);
}
template
<
typename
Device
,
typename
X
,
typename
Out
,
typename
dOut
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Out
out
,
dOut
dout
,
dX
dx
)
const
{
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
e54f203c
...
...
@@ -33,6 +33,7 @@ limitations under the License. */
#include "paddle/fluid/framework/prune.h"
#include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/operators/activation_op.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/profiler.h"
...
...
@@ -461,6 +462,9 @@ All parameter, weight, gradient are variables in Paddle.
self
.
back
().
set_lod
(
t
.
lod
());
});
m
.
def
(
"IsInplace"
,
[](
std
::
string
op
)
->
bool
{
return
operators
::
IsInplace
(
op
);
});
m
.
def
(
"op_support_gpu"
,
OpSupportGPU
);
#ifdef PADDLE_WITH_CUDA
m
.
def
(
"get_cuda_device_count"
,
platform
::
GetCUDADeviceCount
);
...
...
python/paddle/fluid/layer_helper.py
浏览文件 @
e54f203c
...
...
@@ -19,6 +19,7 @@ from framework import Variable, Parameter, default_main_program, default_startup
import
unique_name
from
paddle.fluid.initializer
import
Constant
,
Xavier
from
param_attr
import
ParamAttr
,
WeightNormParamAttr
import
core
class
LayerHelper
(
object
):
...
...
@@ -398,13 +399,16 @@ class LayerHelper(object):
return
input_var
if
isinstance
(
act
,
basestring
):
act
=
{
'type'
:
act
}
tmp
=
self
.
create_tmp_variable
(
dtype
=
input_var
.
dtype
)
if
'use_mkldnn'
in
self
.
kwargs
:
act
[
'use_mkldnn'
]
=
self
.
kwargs
.
get
(
'use_mkldnn'
)
act_type
=
act
.
pop
(
'type'
)
if
'use_mkldnn'
in
self
.
kwargs
:
act
[
'use_mkldnn'
]
=
self
.
kwargs
.
get
(
'use_mkldnn'
)
tmp
=
input_var
# NOTE(dzhwinter): some activation support inplace compution.
if
not
core
.
IsInplace
(
act_type
):
tmp
=
self
.
create_tmp_variable
(
dtype
=
input_var
.
dtype
)
self
.
append_op
(
type
=
act_type
,
inputs
=
{
"X"
:
[
input_var
]},
...
...
python/paddle/fluid/tests/unittests/test_activation_op.py
浏览文件 @
e54f203c
...
...
@@ -361,10 +361,7 @@ class TestCeil(OpTest):
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
if
self
.
dtype
==
np
.
float16
:
return
self
.
check_grad
([
'X'
],
'Out'
,
max_relative_error
=
0.007
)
# The same reason with TestFloor
def
init_dtype
(
self
):
pass
...
...
@@ -396,10 +393,8 @@ class TestFloor(OpTest):
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
if
self
.
dtype
==
np
.
float16
:
return
self
.
check_grad
([
'X'
],
'Out'
,
max_relative_error
=
0.007
)
# the gradient on floor, ceil, round is undefined.
# we return zero as gradient, but the numpy return nan
def
init_dtype
(
self
):
pass
...
...
@@ -501,11 +496,6 @@ class TestRound(OpTest):
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
if
self
.
dtype
==
np
.
float16
:
return
self
.
check_grad
([
'X'
],
'Out'
,
max_relative_error
=
0.007
)
def
init_dtype
(
self
):
pass
...
...
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