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体验新版 GitCode,发现更多精彩内容 >>
提交
0e7baabe
编写于
11月 19, 2019
作者:
D
danleifeng
提交者:
gongweibao
11月 19, 2019
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
extend elementwise broadcast function (#20957)
上级
d623e863
变更
21
展开全部
隐藏空白更改
内联
并排
Showing
21 changed file
with
1074 addition
and
503 deletion
+1074
-503
paddle/fluid/operators/elementwise/elementwise_add_op.cc
paddle/fluid/operators/elementwise/elementwise_add_op.cc
+2
-2
paddle/fluid/operators/elementwise/elementwise_add_op.h
paddle/fluid/operators/elementwise/elementwise_add_op.h
+10
-4
paddle/fluid/operators/elementwise/elementwise_div_op.cc
paddle/fluid/operators/elementwise/elementwise_div_op.cc
+1
-0
paddle/fluid/operators/elementwise/elementwise_div_op.h
paddle/fluid/operators/elementwise/elementwise_div_op.h
+12
-10
paddle/fluid/operators/elementwise/elementwise_mul_op.h
paddle/fluid/operators/elementwise/elementwise_mul_op.h
+8
-2
paddle/fluid/operators/elementwise/elementwise_op.h
paddle/fluid/operators/elementwise/elementwise_op.h
+39
-101
paddle/fluid/operators/elementwise/elementwise_op_function.cu.h
.../fluid/operators/elementwise/elementwise_op_function.cu.h
+6
-0
paddle/fluid/operators/elementwise/elementwise_op_function.h
paddle/fluid/operators/elementwise/elementwise_op_function.h
+828
-352
paddle/fluid/operators/elementwise/elementwise_sub_op.cc
paddle/fluid/operators/elementwise/elementwise_sub_op.cc
+4
-3
paddle/fluid/operators/elementwise/elementwise_sub_op.h
paddle/fluid/operators/elementwise/elementwise_sub_op.h
+10
-4
paddle/fluid/operators/elementwise/mkldnn/elementwise_add_mkldnn_op.cc
...operators/elementwise/mkldnn/elementwise_add_mkldnn_op.cc
+5
-2
paddle/fluid/operators/elementwise/mkldnn/elementwise_mul_mkldnn_op.cc
...operators/elementwise/mkldnn/elementwise_mul_mkldnn_op.cc
+6
-4
paddle/fluid/operators/layer_norm_op.h
paddle/fluid/operators/layer_norm_op.h
+1
-15
paddle/fluid/operators/op_debug_string_test.cc
paddle/fluid/operators/op_debug_string_test.cc
+5
-0
paddle/fluid/train/demo/run.sh
paddle/fluid/train/demo/run.sh
+2
-2
python/paddle/fluid/tests/unittests/test_elementwise_add_op.py
...n/paddle/fluid/tests/unittests/test_elementwise_add_op.py
+30
-0
python/paddle/fluid/tests/unittests/test_elementwise_div_op.py
...n/paddle/fluid/tests/unittests/test_elementwise_div_op.py
+33
-0
python/paddle/fluid/tests/unittests/test_elementwise_mul_op.py
...n/paddle/fluid/tests/unittests/test_elementwise_mul_op.py
+35
-0
python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py
...n/paddle/fluid/tests/unittests/test_elementwise_sub_op.py
+35
-0
python/paddle/fluid/tests/unittests/test_executor_return_tensor_not_overwriting.py
.../unittests/test_executor_return_tensor_not_overwriting.py
+1
-1
python/paddle/fluid/tests/unittests/test_fl_listen_and_serv_op.py
...addle/fluid/tests/unittests/test_fl_listen_and_serv_op.py
+1
-1
未找到文件。
paddle/fluid/operators/elementwise/elementwise_add_op.cc
浏览文件 @
0e7baabe
...
...
@@ -99,8 +99,8 @@ REGISTER_ELEMWISE_EXPLICIT_OP_WITHOUT_GRAD(elementwise_add, Add);
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
elementwise_add_grad
,
ops
::
ElementwiseOp
ExplicitGrad
,
ops
::
ElementwiseGrad
OpInplace
,
ops
::
ElementwiseGrad
NoBufVarsInference
,
elementwise_add_grad
,
ops
::
ElementwiseOp
Grad
,
ops
::
ElementwiseGradOpInplace
,
ops
::
ElementwiseGradNoBufVarsInference
,
ops
::
ElementwiseAddDoubleGradMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
ElementwiseAddDoubleGradMaker
<
paddle
::
imperative
::
OpBase
>
);
...
...
paddle/fluid/operators/elementwise/elementwise_add_op.h
浏览文件 @
0e7baabe
...
...
@@ -25,8 +25,13 @@ void default_elementwise_add(const framework::ExecutionContext &ctx,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
framework
::
Tensor
*
z
)
{
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
ElementwiseComputeEx
<
AddFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
AddFunctor
<
T
>
(),
z
);
if
(
x
->
numel
()
>=
y
->
numel
())
{
ElementwiseComputeEx
<
AddFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
AddFunctor
<
T
>
(),
z
);
}
else
{
ElementwiseComputeEx
<
InverseAddFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
InverseAddFunctor
<
T
>
(),
z
);
}
}
template
<
typename
DeviceContext
,
typename
T
,
class
Enable
=
void
>
...
...
@@ -128,12 +133,13 @@ class ElementwiseAddGradKernel : public ElemwiseGradKernel<T> {
using
Tensor
=
framework
::
Tensor
;
auto
*
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
auto
*
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
auto
*
dout
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
dy
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
// skip out
, x, y
// skip out
auto
*
out
=
dout
;
auto
*
x
=
dout
,
*
y
=
dout
;
if
(
dx
!=
nullptr
&&
dy
!=
nullptr
&&
(
dx
->
dims
()
==
dy
->
dims
()))
{
elementwise_add_grad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
...
...
paddle/fluid/operators/elementwise/elementwise_div_op.cc
浏览文件 @
0e7baabe
...
...
@@ -76,6 +76,7 @@ class ElementwiseDivGradOpMaker : public framework::SingleGradOpMaker<T> {
std
::
unique_ptr
<
T
>
Apply
()
const
override
{
std
::
unique_ptr
<
T
>
op
(
new
T
());
op
->
SetType
(
"elementwise_div_grad"
);
op
->
SetInput
(
"X"
,
this
->
Input
(
"X"
));
op
->
SetInput
(
"Y"
,
this
->
Input
(
"Y"
));
op
->
SetInput
(
"Out"
,
this
->
Output
(
"Out"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
this
->
OutputGrad
(
"Out"
));
...
...
paddle/fluid/operators/elementwise/elementwise_div_op.h
浏览文件 @
0e7baabe
...
...
@@ -31,8 +31,13 @@ void default_elementwise_div(const framework::ExecutionContext& ctx,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
framework
::
Tensor
*
z
)
{
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
ElementwiseComputeEx
<
DivFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
DivFunctor
<
T
>
(),
z
);
if
(
x
->
numel
()
>=
y
->
numel
())
{
ElementwiseComputeEx
<
DivFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
DivFunctor
<
T
>
(),
z
);
}
else
{
ElementwiseComputeEx
<
InverseDivFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
InverseDivFunctor
<
T
>
(),
z
);
}
}
template
<
typename
DeviceContext
,
typename
T
,
class
Enable
=
void
>
...
...
@@ -112,13 +117,13 @@ class ElementwiseDivGradKernel : public ElemwiseGradKernel<T> {
ElemwiseGradKernel
<
T
>::
Compute
(
ctx
);
using
Tensor
=
framework
::
Tensor
;
auto
*
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
auto
*
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
auto
*
out
=
ctx
.
Input
<
Tensor
>
(
"Out"
);
auto
*
dout
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
dy
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
auto
*
x
=
dout
;
// Fake x, not used
if
(
dx
!=
nullptr
&&
dy
!=
nullptr
&&
(
dx
->
dims
()
==
dy
->
dims
()))
{
elementwise_div_grad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
...
...
@@ -191,7 +196,7 @@ class ElementwiseDivDoubleGradKernel : public framework::OpKernel<T> {
// ddX_safe == null ? 0 : ddX
// ddY_safe == null ? 0 : ddY
Tensor
ddX_safe
,
ddY_safe
;
GetDoubleGradSafeTensor
<
DeviceContext
,
T
>
(
ctx
,
Out
,
ddX
,
&
ddX_safe
);
GetDoubleGradSafeTensor
<
DeviceContext
,
T
>
(
ctx
,
dX
,
ddX
,
&
ddX_safe
);
GetDoubleGradSafeTensor
<
DeviceContext
,
T
>
(
ctx
,
Y
,
ddY
,
&
ddY_safe
);
// ddOut = ddX / Y - Out * ddY / Y = (ddX - Out * ddY) / Y
...
...
@@ -209,8 +214,7 @@ class ElementwiseDivDoubleGradKernel : public framework::OpKernel<T> {
if
(
dY
)
{
// dX_div_Y = dX / Y;
Tensor
dX_div_Y
=
tmp
;
ElementwiseComputeEx
<
DivFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
dX
,
Y
,
axis
,
DivFunctor
<
T
>
(),
&
dX_div_Y
);
default_elementwise_div
<
DeviceContext
,
T
>
(
ctx
,
dX
,
Y
,
&
dX_div_Y
);
// NOTE(dengkaipeng): in the following ElemwiseGradCompute, for the
// first output tensor is nullptr, the branch to calculate first
...
...
@@ -227,10 +231,8 @@ class ElementwiseDivDoubleGradKernel : public framework::OpKernel<T> {
if
(
ddOut
)
{
// ddOut = ddX / Y - Out * ddY / Y = (ddX - Out * ddY) / Y
default_elementwise_mul
<
DeviceContext
,
T
>
(
ctx
,
Out
,
&
ddY_safe
,
&
tmp
);
ElementwiseComputeEx
<
SubFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
&
ddX_safe
,
&
tmp
,
0
,
SubFunctor
<
T
>
(),
&
tmp
);
ElementwiseComputeEx
<
DivFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
&
tmp
,
Y
,
axis
,
DivFunctor
<
T
>
(),
ddOut
);
default_elementwise_sub
<
DeviceContext
,
T
>
(
ctx
,
&
ddX_safe
,
&
tmp
,
&
tmp
);
default_elementwise_div
<
DeviceContext
,
T
>
(
ctx
,
&
tmp
,
Y
,
ddOut
);
}
if
(
dOut
)
{
...
...
paddle/fluid/operators/elementwise/elementwise_mul_op.h
浏览文件 @
0e7baabe
...
...
@@ -26,9 +26,15 @@ void default_elementwise_mul(const framework::ExecutionContext& ctx,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
framework
::
Tensor
*
z
)
{
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
ElementwiseComputeEx
<
MulFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
MulFunctor
<
T
>
(),
z
);
if
(
x
->
numel
()
>=
y
->
numel
())
{
ElementwiseComputeEx
<
MulFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
MulFunctor
<
T
>
(),
z
);
}
else
{
ElementwiseComputeEx
<
InverseMulFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
InverseMulFunctor
<
T
>
(),
z
);
}
}
template
<
typename
DeviceContext
,
typename
T
,
class
Enable
=
void
>
struct
SameDimsElemwiseMul
{
void
operator
()(
const
framework
::
ExecutionContext
&
ctx
,
...
...
paddle/fluid/operators/elementwise/elementwise_op.h
浏览文件 @
0e7baabe
...
...
@@ -14,12 +14,15 @@ limitations under the License. */
#pragma once
#include <algorithm> // for max
#include <memory>
#include <string>
#include <unordered_map>
#include <vector>
#include "paddle/fluid/framework/data_layout.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
#ifdef PADDLE_WITH_MKLDNN
#include "paddle/fluid/platform/mkldnn_helper.h"
...
...
@@ -35,12 +38,12 @@ class ElementwiseOp : public framework::OperatorWithKernel {
using
Tensor
=
framework
::
Tensor
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
)
,
"Input(X) of elementwise op should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Y"
)
,
"Input(Y) of elementwise op should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
)
,
"Output(Out) of elementwise op should not be null."
);
PADDLE_ENFORCE
_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) of elementwise op should not be null."
);
PADDLE_ENFORCE
_EQ
(
ctx
->
HasInput
(
"Y"
),
true
,
"Input(Y) of elementwise op should not be null."
);
PADDLE_ENFORCE
_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
"Output(Out) of elementwise op should not be null."
);
PADDLE_ENFORCE
(
ctx
->
GetInputsVarType
(
"Y"
).
front
()
==
...
...
@@ -49,18 +52,7 @@ class ElementwiseOp : public framework::OperatorWithKernel {
ctx
->
GetInputsVarType
(
"Y"
).
front
(),
ctx
->
Inputs
(
"Y"
).
front
());
if
(
ctx
->
GetInputsVarType
(
"X"
).
front
()
==
framework
::
proto
::
VarType
::
LOD_TENSOR
)
{
auto
x_dim
=
ctx
->
GetInputDim
(
"X"
);
auto
y_dim
=
ctx
->
GetInputDim
(
"Y"
);
PADDLE_ENFORCE_GE
(
x_dim
.
size
(),
y_dim
.
size
(),
"ShapeError: the dimension of input X must greater than or equal to "
"the one of input Y. But received: the shape of input X = [%s], the "
"dimension of input X = %d, the shape of input Y = [%s], the "
"dimension of input Y = %d"
,
x_dim
,
x_dim
.
size
(),
y_dim
,
y_dim
.
size
());
}
else
if
(
ctx
->
GetInputsVarType
(
"X"
).
front
()
==
framework
::
proto
::
VarType
::
SELECTED_ROWS
)
{
framework
::
proto
::
VarType
::
SELECTED_ROWS
)
{
PADDLE_ENFORCE_EQ
(
ctx
->
GetInputDim
(
"Y"
).
size
(),
1u
,
"ShapeError: For elementwise_op, if X is Sparse(VarType.SELECTED_ROWS"
...
...
@@ -71,13 +63,31 @@ class ElementwiseOp : public framework::OperatorWithKernel {
"ShapeError: For elementwise_op, if X is Sparse(VarType.SELECTED_ROWS"
"), Y must be scalar. But reveived the first dimension of Y = %s"
,
ctx
->
GetInputDim
(
"Y"
)[
0
]);
}
else
{
}
else
if
(
ctx
->
GetInputsVarType
(
"X"
).
front
()
!=
framework
::
proto
::
VarType
::
LOD_TENSOR
)
{
PADDLE_THROW
(
"X's type[%s] is not supported by elementwise_op."
,
ctx
->
GetInputsVarType
(
"X"
).
front
());
}
ctx
->
ShareDim
(
"X"
,
/*->*/
"Out"
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
if
(
ctx
->
GetInputDim
(
"X"
)
==
ctx
->
GetInputDim
(
"Y"
))
{
ctx
->
ShareDim
(
"X"
,
/*->*/
"Out"
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
else
{
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
y_dims
=
ctx
->
GetInputDim
(
"Y"
);
int
max_dim
=
std
::
max
(
x_dims
.
size
(),
y_dims
.
size
());
int
axis
=
ctx
->
Attrs
().
Get
<
int
>
(
"axis"
);
axis
=
(
axis
==
-
1
?
std
::
abs
(
x_dims
.
size
()
-
y_dims
.
size
())
:
axis
);
std
::
vector
<
int
>
x_dims_array
(
max_dim
);
std
::
vector
<
int
>
y_dims_array
(
max_dim
);
std
::
vector
<
int
>
out_dims_array
(
max_dim
);
GetBroadcastDimsArrays
(
x_dims
,
y_dims
,
x_dims_array
.
data
(),
y_dims_array
.
data
(),
out_dims_array
.
data
(),
max_dim
,
axis
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
out_dims_array
));
// to do
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
}
framework
::
OpKernelType
GetExpectedKernelType
(
...
...
@@ -207,26 +217,14 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
auto
out_grad_name
=
framework
::
GradVarName
(
"Out"
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Y"
),
"Input(Y) should not be null"
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
out_grad_name
),
"Input(Out@GRAD) should not be null"
);
auto
x_dims
=
ctx
->
GetInputDim
(
out_grad_name
);
auto
y_dims
=
ctx
->
GetInputDim
(
"Y"
);
PADDLE_ENFORCE_GE
(
x_dims
.
size
(),
y_dims
.
size
(),
"ShapeError: the dimension of Out@GRAD must greater than or equal to "
"the one of input Y. But received: the shape of Out@GRAD = [%s], the "
"dimension of Out@GRAD = %d, the shape of input Y = [%s], the "
"dimension of of input Y = %d"
,
x_dims
,
x_dims
.
size
(),
y_dims
,
y_dims
.
size
());
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"Y"
),
true
,
"Input(Y) should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
out_grad_name
),
true
,
"Input(Out@GRAD) should not be null."
);
auto
x_grad_name
=
framework
::
GradVarName
(
"X"
);
auto
y_grad_name
=
framework
::
GradVarName
(
"Y"
);
if
(
ctx
->
HasOutput
(
x_grad_name
))
{
ctx
->
ShareDim
(
out_grad_name
,
/*->*/
x_grad_name
);
ctx
->
ShareLoD
(
out_grad_name
,
/*->*/
x_grad_name
);
ctx
->
ShareDim
(
"X"
,
/*->*/
x_grad_name
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
x_grad_name
);
}
if
(
ctx
->
HasOutput
(
y_grad_name
))
{
ctx
->
ShareDim
(
"Y"
,
/*->*/
y_grad_name
);
...
...
@@ -326,32 +324,6 @@ class ElementwiseOpDoubleGradWithoutDXDY
}
};
// For Add, Sub op, the X, Out is not needed.
class
ElementwiseOpExplicitGrad
:
public
ElementwiseOpGrad
{
public:
using
operators
::
ElementwiseOpGrad
::
ElementwiseOpGrad
;
using
operators
::
ElementwiseOpGrad
::
GetExpectedKernelType
;
using
Tensor
=
framework
::
Tensor
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) should not be null"
);
auto
x_grad_name
=
framework
::
GradVarName
(
"X"
);
if
(
ctx
->
HasOutput
(
x_grad_name
))
{
ctx
->
ShareDim
(
framework
::
GradVarName
(
"Out"
),
/*->*/
x_grad_name
);
ctx
->
ShareLoD
(
framework
::
GradVarName
(
"Out"
),
/*->*/
x_grad_name
);
}
auto
y_grad_name
=
framework
::
GradVarName
(
"Y"
);
if
(
ctx
->
HasOutput
(
y_grad_name
))
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Y"
),
"Input(Y) should not be null"
);
ctx
->
ShareDim
(
"Y"
,
/*->*/
y_grad_name
);
ctx
->
ShareLoD
(
"Y"
,
/*->*/
y_grad_name
);
}
}
};
template
<
typename
T
>
class
ElemwiseGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
...
...
@@ -372,13 +344,13 @@ DECLARE_INPLACE_OP_INFERER(ElementwiseGradOpInplace,
framework
::
GradVarName
(
"X"
)});
DECLARE_INPLACE_OP_INFERER
(
ElementwiseDoubleGradOpInplace
,
{
"DDX"
,
"DDOut"
});
DECLARE_NO_NEED_BUFFER_VARS_INFERENCE
(
ElementwiseGradNoBufVarsInference
,
"Y"
);
DECLARE_NO_NEED_BUFFER_VARS_INFERENCE
(
ElementwiseGradNoBufVarsInference
,
"X"
,
"Y"
);
DECLARE_NO_NEED_BUFFER_VARS_INFERENCE
(
ElementwiseDoubleGradNoBufVarsInference
,
"Y"
,
"DOut"
);
}
// namespace operators
}
// namespace paddle
#define REGISTER_ELEMWISE_GRAD_MAKER(kernel_type, op_name) \
template <typename T> \
class kernel_type##GradMaker \
...
...
@@ -390,6 +362,7 @@ DECLARE_NO_NEED_BUFFER_VARS_INFERENCE(ElementwiseDoubleGradNoBufVarsInference,
std::unique_ptr<T> Apply() const override { \
auto *op = new T(); \
op->SetType(#kernel_type "_grad"); \
op->SetInput("X", this->Input("X")); \
op->SetInput("Y", this->Input("Y")); \
op->SetInput(::paddle::framework::GradVarName("Out"), \
this->OutputGrad("Out")); \
...
...
@@ -402,41 +375,6 @@ DECLARE_NO_NEED_BUFFER_VARS_INFERENCE(ElementwiseDoubleGradNoBufVarsInference,
} \
}
#define REGISTER_ELEMWISE_OP(op_type, op_name, equation) \
class __ElemwiseOp##op_type##Maker__ \
: public ::paddle::operators::ElementwiseOpMaker { \
protected: \
virtual std::string GetName() const { return op_name; } \
virtual std::string GetEquation() const { return equation; } \
}; \
REGISTER_OPERATOR( \
op_type, ::paddle::operators::ElementwiseOp, \
__ElemwiseOp##op_type##Maker__, \
::paddle::operators::ElementwiseOpInferVarType, \
::paddle::framework::DefaultGradOpMaker<::paddle::framework::OpDesc, \
true>, \
::paddle::framework::DefaultGradOpMaker<::paddle::imperative::OpBase, \
true>); \
REGISTER_OPERATOR(op_type##_grad, ::paddle::operators::ElementwiseOpGrad)
#define REGISTER_ELEMWISE_EXPLICIT_OP(op_type, op_name, equation) \
class __ElemwiseOp##op_type##Maker__ \
: public ::paddle::operators::ElementwiseOpMaker { \
protected: \
virtual std::string GetName() const { return op_name; } \
virtual std::string GetEquation() const { return equation; } \
}; \
REGISTER_OPERATOR(op_type, ::paddle::operators::ElementwiseOp, \
__ElemwiseOp##op_type##Maker__, \
::paddle::operators::ElementwiseOpInferVarType, \
op_type##GradMaker<::paddle::framework::OpDesc>, \
op_type##GradMaker<::paddle::imperative::OpBase>, \
::paddle::operators::ElementwiseOpInplace); \
REGISTER_OPERATOR(op_type##_grad, \
::paddle::operators::ElementwiseOpExplicitGrad, \
::paddle::operators::ElementwiseGradOpInplace, \
::paddle::operators::ElementwiseGradNoBufVarsInference)
#define REGISTER_ELEMWISE_EXPLICIT_OP_WITHOUT_GRAD(op_type, op_name) \
REGISTER_OPERATOR(op_type, ::paddle::operators::ElementwiseOp, \
::paddle::operators::Elementwise##op_name##OpMaker, \
...
...
paddle/fluid/operators/elementwise/elementwise_op_function.cu.h
浏览文件 @
0e7baabe
...
...
@@ -44,6 +44,12 @@ namespace operators {
inline HOSTDEVICE T operator()(const T& a, const T& b) const { \
return a expr b; \
} \
}; \
template <typename T, class Enable = void> \
struct Inverse##Func##Functor { \
inline HOSTDEVICE T operator()(const T& a, const T& b) const { \
return b expr a; \
} \
};
DEFINE_SIMPLE_BINARY_FUNCTOR
(
Add
,
+
)
...
...
paddle/fluid/operators/elementwise/elementwise_op_function.h
浏览文件 @
0e7baabe
此差异已折叠。
点击以展开。
paddle/fluid/operators/elementwise/elementwise_sub_op.cc
浏览文件 @
0e7baabe
...
...
@@ -93,13 +93,14 @@ class ElementwiseSubDoubleGradMaker : public framework::SingleGradOpMaker<T> {
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_ELEMWISE_GRAD_MAKER
(
elementwise_sub
,
Sub
);
REGISTER_ELEMWISE_EXPLICIT_OP_WITHOUT_GRAD
(
elementwise_sub
,
Sub
);
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
elementwise_sub_grad
,
ops
::
ElementwiseOp
ExplicitGrad
,
ops
::
ElementwiseGrad
OpInplace
,
ops
::
ElementwiseGrad
NoBufVarsInference
,
elementwise_sub_grad
,
ops
::
ElementwiseOp
Grad
,
ops
::
ElementwiseGradOpInplace
,
ops
::
ElementwiseGradNoBufVarsInference
,
ops
::
ElementwiseSubDoubleGradMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
ElementwiseSubDoubleGradMaker
<
paddle
::
imperative
::
OpBase
>
);
REGISTER_OPERATOR
(
elementwise_sub_grad_grad
,
...
...
paddle/fluid/operators/elementwise/elementwise_sub_op.h
浏览文件 @
0e7baabe
...
...
@@ -26,8 +26,13 @@ void default_elementwise_sub(const framework::ExecutionContext& ctx,
const
framework
::
Tensor
*
x
,
const
framework
::
Tensor
*
y
,
framework
::
Tensor
*
z
)
{
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
ElementwiseComputeEx
<
SubFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
SubFunctor
<
T
>
(),
z
);
if
(
x
->
numel
()
>=
y
->
numel
())
{
ElementwiseComputeEx
<
SubFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
SubFunctor
<
T
>
(),
z
);
}
else
{
ElementwiseComputeEx
<
InverseSubFunctor
<
T
>
,
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
axis
,
InverseSubFunctor
<
T
>
(),
z
);
}
}
template
<
typename
DeviceContext
,
typename
T
,
class
Enable
=
void
>
...
...
@@ -98,13 +103,14 @@ class ElementwiseSubGradKernel : public ElemwiseGradKernel<T> {
ElemwiseGradKernel
<
T
>::
Compute
(
ctx
);
using
Tensor
=
framework
::
Tensor
;
auto
*
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
auto
*
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
auto
*
dout
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
dy
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
// skip out
, x, y
// skip out
auto
*
out
=
dout
;
auto
*
x
=
dout
,
*
y
=
dout
;
if
(
dx
!=
nullptr
&&
dy
!=
nullptr
&&
(
dx
->
dims
()
==
dy
->
dims
()))
{
elementwise_sub_grad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
}
else
{
...
...
paddle/fluid/operators/elementwise/mkldnn/elementwise_add_mkldnn_op.cc
浏览文件 @
0e7baabe
...
...
@@ -108,8 +108,9 @@ class EltwiseAddMKLDNNKernel : public framework::OpKernel<T> {
auto
y_dims
=
trim_trailing_singular_dims
(
y_dims_untrimed
);
axis
=
(
y_dims
.
size
()
==
0
)
?
x_dims
.
size
()
:
axis
;
int
pre
,
n
,
post
;
get_mid_dims
(
x_dims
,
y_dims
,
axis
,
&
pre
,
&
n
,
&
post
);
int
pre
,
n
,
post
,
is_run_common_broadcast
;
get_mid_dims
(
x_dims
,
y_dims
,
axis
,
&
pre
,
&
n
,
&
post
,
&
is_run_common_broadcast
);
if
(
post
==
1
)
{
functor
.
RunRowWise
(
n
,
pre
);
...
...
@@ -212,6 +213,8 @@ class EltwiseAddMKLDNNGradKernel : public ElemwiseGradKernel<T> {
}
}
else
{
// Execute default kernel when broadcast is needed
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
ElemwiseExplicitGradCompute
<
paddle
::
platform
::
CPUDeviceContext
,
T
,
IdentityGrad
<
T
>
,
IdentityGrad
<
T
>>
(
ctx
,
*
x
,
*
y
,
*
out
,
*
dout
,
axis
,
dx
,
dy
,
IdentityGrad
<
T
>
(),
...
...
paddle/fluid/operators/elementwise/mkldnn/elementwise_mul_mkldnn_op.cc
浏览文件 @
0e7baabe
...
...
@@ -91,8 +91,9 @@ class ElementwiseMulMKLDNNKernel : public framework::OpKernel<T> {
const
bool
is_y_format_correct
=
y
->
format
()
==
MKLDNNMemoryFormat
::
nc
;
if
(
is_x_format_correct
&&
is_y_format_correct
&&
are_dims_divisable
&&
is_avx512_enabled
)
{
int
pre
,
n
,
post
;
get_mid_dims
(
x_dims
,
y_dims_untrimmed
,
axis
,
&
pre
,
&
n
,
&
post
);
int
pre
,
n
,
post
,
is_run_common_broadcast
;
get_mid_dims
(
x_dims
,
y_dims_untrimmed
,
axis
,
&
pre
,
&
n
,
&
post
,
&
is_run_common_broadcast
);
if
(
post
==
1
)
{
PADDLE_THROW
(
"Not implemented when post is 1"
);
...
...
@@ -168,8 +169,9 @@ class ElementwiseMulMKLDNNKernel : public framework::OpKernel<T> {
auto
y_dims
=
trim_trailing_singular_dims
(
y_dims_untrimmed
);
axis
=
(
y_dims
.
size
()
==
0
)
?
x_dims
.
size
()
:
axis
;
int
pre
,
n
,
post
;
get_mid_dims
(
x_dims
,
y_dims
,
axis
,
&
pre
,
&
n
,
&
post
);
int
pre
,
n
,
post
,
is_run_common_broadcast
;
get_mid_dims
(
x_dims
,
y_dims
,
axis
,
&
pre
,
&
n
,
&
post
,
&
is_run_common_broadcast
);
if
(
post
==
1
)
{
functor
.
RunRowWise
(
n
,
pre
);
...
...
paddle/fluid/operators/layer_norm_op.h
浏览文件 @
0e7baabe
...
...
@@ -15,6 +15,7 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/elementwise/elementwise_op_function.cu.h"
#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
#include "paddle/fluid/operators/math/blas.h"
#if !defined(PADDLE_WITH_CUDA) && !defined(_WIN32) && !defined(__APPLE__) && \
...
...
@@ -139,21 +140,6 @@ struct DivAndSqrtFunctor {
T
epsilon_
;
};
template
<
typename
T
>
struct
MulFunctor
{
inline
HOSTDEVICE
T
operator
()(
T
a
,
T
b
)
const
{
return
a
*
b
;
}
};
template
<
typename
T
>
struct
AddFunctor
{
inline
HOSTDEVICE
T
operator
()(
T
a
,
T
b
)
const
{
return
a
+
b
;
}
};
template
<
typename
T
>
struct
SubFunctor
{
inline
HOSTDEVICE
T
operator
()(
T
a
,
T
b
)
const
{
return
a
-
b
;
}
};
template
<
typename
T
>
struct
MulInvVarFunctor
{
inline
HOSTDEVICE
T
operator
()(
T
a
,
T
b
)
const
{
...
...
paddle/fluid/operators/op_debug_string_test.cc
浏览文件 @
0e7baabe
...
...
@@ -32,6 +32,7 @@ TEST(op_debug_str, test_unknown_dtype) {
framework
::
Scope
scope
;
desc
.
SetType
(
"elementwise_add_grad"
);
desc
.
SetInput
(
"X"
,
{
"X"
});
desc
.
SetInput
(
"Y"
,
{
"Y"
});
desc
.
SetInput
(
framework
::
GradVarName
(
"Out"
),
{
framework
::
GradVarName
(
"Out"
)});
desc
.
SetOutput
(
framework
::
GradVarName
(
"X"
),
{
framework
::
GradVarName
(
"X"
)});
...
...
@@ -41,6 +42,10 @@ TEST(op_debug_str, test_unknown_dtype) {
desc
.
SetAttr
(
"x_data_format"
,
""
);
desc
.
SetAttr
(
"y_data_format"
,
""
);
auto
x_tensor
=
scope
.
Var
(
"X"
)
->
GetMutable
<
framework
::
LoDTensor
>
();
x_tensor
->
Resize
(
dim
);
x_tensor
->
mutable_data
<
float
>
(
place
);
auto
y_tensor
=
scope
.
Var
(
"Y"
)
->
GetMutable
<
framework
::
LoDTensor
>
();
y_tensor
->
Resize
(
dim
);
y_tensor
->
mutable_data
<
float
>
(
place
);
...
...
paddle/fluid/train/demo/run.sh
浏览文件 @
0e7baabe
...
...
@@ -7,8 +7,8 @@ TURN_ON_MKL=$2 # use MKL or Openblas
# download models
function
download
()
{
wget
-q
http://paddle-tar.bj.bcebos.com/train_demo/LR/main_program
wget
-q
http://paddle-tar.bj.bcebos.com/train_demo/LR/startup_program
wget
-q
http://paddle-tar.bj.bcebos.com/train_demo/LR
-1-7
/main_program
wget
-q
http://paddle-tar.bj.bcebos.com/train_demo/LR
-1-7
/startup_program
}
download
...
...
python/paddle/fluid/tests/unittests/test_elementwise_add_op.py
浏览文件 @
0e7baabe
...
...
@@ -308,6 +308,36 @@ class TestFP16ElementwiseAddOp_channelwise_add(TestFP16ElementwiseAddOp):
self
.
axis
=
-
1
class
TestElementwiseAddOp_commonuse_add1
(
TestElementwiseAddOp
):
def
init_input_output
(
self
):
self
.
x
=
np
.
random
.
rand
(
2
,
3
,
4
).
astype
(
self
.
dtype
)
self
.
y
=
np
.
random
.
rand
(
1
,
1
,
4
).
astype
(
self
.
dtype
)
self
.
out
=
self
.
x
+
self
.
y
def
init_axis
(
self
):
self
.
axis
=
-
1
class
TestElementwiseAddOp_commonuse_add2
(
TestElementwiseAddOp
):
def
init_input_output
(
self
):
self
.
x
=
np
.
random
.
rand
(
2
,
3
,
1
,
5
).
astype
(
self
.
dtype
)
self
.
y
=
np
.
random
.
rand
(
2
,
1
,
4
,
1
).
astype
(
self
.
dtype
)
self
.
out
=
self
.
x
+
self
.
y
def
init_axis
(
self
):
self
.
axis
=
-
1
class
TestElementwiseAddOp_xsize_lessthan_ysize_add
(
TestElementwiseAddOp
):
def
init_input_output
(
self
):
self
.
x
=
np
.
random
.
rand
(
4
,
5
).
astype
(
self
.
dtype
)
self
.
y
=
np
.
random
.
rand
(
2
,
3
,
4
,
5
).
astype
(
self
.
dtype
)
self
.
out
=
self
.
x
+
self
.
y
def
init_axis
(
self
):
self
.
axis
=
2
class
TestElementwiseAddOpError
(
OpTest
):
def
test_errors
(
self
):
with
program_guard
(
Program
(),
Program
()):
...
...
python/paddle/fluid/tests/unittests/test_elementwise_div_op.py
浏览文件 @
0e7baabe
...
...
@@ -151,6 +151,39 @@ class TestElementwiseDivOp_broadcast_5(ElementwiseDivOp):
self
.
outputs
=
{
'Out'
:
np
.
divide
(
self
.
inputs
[
'X'
],
self
.
inputs
[
'Y'
])}
class
TestElementwiseDivOp_commonuse_1
(
ElementwiseDivOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_div"
self
.
inputs
=
{
'X'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
3
,
4
]).
astype
(
"float32"
),
'Y'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
1
,
1
,
4
]).
astype
(
"float32"
),
}
self
.
outputs
=
{
'Out'
:
np
.
divide
(
self
.
inputs
[
'X'
],
self
.
inputs
[
'Y'
])}
class
TestElementwiseDivOp_commonuse_2
(
ElementwiseDivOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_div"
self
.
inputs
=
{
'X'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
3
,
1
,
5
]).
astype
(
"float32"
),
'Y'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
1
,
4
,
1
]).
astype
(
"float32"
),
}
self
.
outputs
=
{
'Out'
:
np
.
divide
(
self
.
inputs
[
'X'
],
self
.
inputs
[
'Y'
])}
class
TestElementwiseDivOp_xsize_lessthan_ysize
(
ElementwiseDivOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_div"
self
.
inputs
=
{
'X'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
4
,
5
]).
astype
(
"float32"
),
'Y'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
3
,
4
,
5
]).
astype
(
"float32"
),
}
self
.
attrs
=
{
'axis'
:
2
}
self
.
outputs
=
{
'Out'
:
np
.
divide
(
self
.
inputs
[
'X'
],
self
.
inputs
[
'Y'
])}
class
TestElementwiseDivOp_INT
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_div"
...
...
python/paddle/fluid/tests/unittests/test_elementwise_mul_op.py
浏览文件 @
0e7baabe
...
...
@@ -162,6 +162,41 @@ class TestElementwiseMulOpFp16(ElementwiseMulOp):
self
.
dtype
=
np
.
float16
class
TestElementwiseMulOp_commonuse_1
(
ElementwiseMulOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_mul"
self
.
inputs
=
{
'X'
:
np
.
random
.
rand
(
2
,
3
,
4
).
astype
(
np
.
float64
),
'Y'
:
np
.
random
.
rand
(
1
,
1
,
4
).
astype
(
np
.
float64
)
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
]
*
self
.
inputs
[
'Y'
]}
class
TestElementwiseMulOp_commonuse_2
(
ElementwiseMulOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_mul"
self
.
inputs
=
{
'X'
:
np
.
random
.
rand
(
2
,
3
,
1
,
5
).
astype
(
np
.
float64
),
'Y'
:
np
.
random
.
rand
(
2
,
1
,
4
,
1
).
astype
(
np
.
float64
)
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
]
*
self
.
inputs
[
'Y'
]}
class
TestElementwiseMulOp_xsize_lessthan_ysize
(
ElementwiseMulOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_mul"
self
.
inputs
=
{
'X'
:
np
.
random
.
rand
(
4
,
5
).
astype
(
np
.
float64
),
'Y'
:
np
.
random
.
rand
(
2
,
3
,
4
,
5
).
astype
(
np
.
float64
)
}
self
.
attrs
=
{
'axis'
:
2
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
reshape
(
1
,
1
,
4
,
5
)
*
self
.
inputs
[
'Y'
]
}
class
TestElementwiseMulOpError
(
OpTest
):
def
test_errors
(
self
):
with
program_guard
(
Program
(),
Program
()):
...
...
python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py
浏览文件 @
0e7baabe
...
...
@@ -127,5 +127,40 @@ class TestElementwiseSubOp_broadcast_4(TestElementwiseOp):
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
]
-
self
.
inputs
[
'Y'
]}
class
TestElementwiseSubOp_commonuse_1
(
TestElementwiseOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_sub"
self
.
inputs
=
{
'X'
:
np
.
random
.
rand
(
2
,
3
,
4
).
astype
(
np
.
float32
),
'Y'
:
np
.
random
.
rand
(
1
,
1
,
4
).
astype
(
np
.
float32
)
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
]
-
self
.
inputs
[
'Y'
]}
class
TestElementwiseSubOp_commonuse_2
(
TestElementwiseOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_sub"
self
.
inputs
=
{
'X'
:
np
.
random
.
rand
(
2
,
3
,
1
,
5
).
astype
(
np
.
float32
),
'Y'
:
np
.
random
.
rand
(
2
,
1
,
4
,
1
).
astype
(
np
.
float32
)
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
]
-
self
.
inputs
[
'Y'
]}
class
TestElementwiseSubOp_xsize_lessthan_ysize
(
TestElementwiseOp
):
def
setUp
(
self
):
self
.
op_type
=
"elementwise_sub"
self
.
inputs
=
{
'X'
:
np
.
random
.
rand
(
4
,
5
).
astype
(
np
.
float32
),
'Y'
:
np
.
random
.
rand
(
2
,
3
,
4
,
5
).
astype
(
np
.
float32
)
}
self
.
attrs
=
{
'axis'
:
2
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
reshape
(
1
,
1
,
4
,
5
)
-
self
.
inputs
[
'Y'
]
}
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_executor_return_tensor_not_overwriting.py
浏览文件 @
0e7baabe
...
...
@@ -47,7 +47,7 @@ class TestExecutorReturnTensorNotOverwritingWithOptest(OpTest):
'Y'
:
OpTest
.
np_dtype_to_fluid_dtype
(
self
.
y
)
}
self
.
outputs
=
{
'Out'
:
self
.
out
}
self
.
op_type
=
"
elementwise_
mul"
self
.
op_type
=
"mul"
self
.
dtype
=
np
.
float32
outs
,
fetch_list
=
self
.
_calc_output
(
place
,
parallel
=
parallel
)
return
outs
...
...
python/paddle/fluid/tests/unittests/test_fl_listen_and_serv_op.py
浏览文件 @
0e7baabe
...
...
@@ -57,7 +57,7 @@ def run_trainer(use_cuda, sync_mode, ip, port, trainers, trainer_id):
exe
.
run
(
trainer_startup_program
)
for
i
in
range
(
5
):
exe
.
run
(
recv_program
)
exe
.
run
(
main_program
,
exe
.
run
(
fluid
.
default_main_program
()
,
feed
=
{
"x"
:
numpy
.
array
([
1
,
2
]).
astype
(
'float32'
).
reshape
(
2
,
1
),
"y"
:
numpy
.
array
([
2
,
3
]).
astype
(
'float32'
).
reshape
(
2
,
1
)
...
...
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