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体验新版 GitCode,发现更多精彩内容 >>
提交
d6b6a337
编写于
7月 19, 2019
作者:
A
Adam
提交者:
Tao Luo
7月 19, 2019
浏览文件
操作
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差异文件
Add LeakyRelu MKLDNN support (#18656)
test=develop
上级
0b9acb49
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
68 addition
and
14 deletion
+68
-14
paddle/fluid/operators/activation_op.cc
paddle/fluid/operators/activation_op.cc
+9
-0
paddle/fluid/operators/activation_op.h
paddle/fluid/operators/activation_op.h
+1
-1
paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc
paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc
+17
-12
python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py
...fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py
+22
-1
python/paddle/fluid/tests/unittests/test_activation_op.py
python/paddle/fluid/tests/unittests/test_activation_op.py
+19
-0
未找到文件。
paddle/fluid/operators/activation_op.cc
浏览文件 @
d6b6a337
...
...
@@ -363,6 +363,13 @@ class LeakyReluOpMaker : public framework::OpProtoAndCheckerMaker {
AddInput
(
"X"
,
"Input of LeakyRelu operator"
);
AddOutput
(
"Out"
,
"Output of LeakyRelu operator"
);
AddAttr
<
float
>
(
"alpha"
,
"The small negative slope"
).
SetDefault
(
0.02
f
);
AddAttr
<
bool
>
(
"use_mkldnn"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddAttr
<
bool
>
(
"is_test"
,
"(bool, default false) Set to true for inference only, false "
"for training. Some layers may run faster when this is true."
)
.
SetDefault
(
false
);
AddComment
(
R"DOC(
LeakyRelu Activation Operator.
...
...
@@ -695,6 +702,8 @@ class LeakyReluDoubleGradMaker
op
->
SetType
(
"leaky_relu_grad_grad"
);
// input1: X
op
->
SetInput
(
"X"
,
Input
(
"X"
));
// input2: Out
op
->
SetInput
(
"Out"
,
Input
(
"Out"
));
// X@GRAD@GRAD: ddx
op
->
SetInput
(
"DDX"
,
OutputGrad
(
framework
::
GradVarName
(
"X"
)));
op
->
SetAttrMap
(
Attrs
());
...
...
paddle/fluid/operators/activation_op.h
浏览文件 @
d6b6a337
...
...
@@ -1001,7 +1001,7 @@ struct LeakyReluGradFunctor : public BaseActivationFunctor<T> {
dx
.
device
(
d
)
=
dout
*
(
temp1
+
temp2
).
template
cast
<
T
>();
}
static
constexpr
ActBwdOpFwdDeps
FwdDeps
()
{
return
kDepX
;
}
static
constexpr
ActBwdOpFwdDeps
FwdDeps
()
{
return
kDepX
Out
;
}
};
template
<
typename
T
>
...
...
paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc
浏览文件 @
d6b6a337
...
...
@@ -77,8 +77,7 @@ class MKLDNNActivationGradKernel
template
<
typename
T
>
void
eltwise_forward
(
const
framework
::
ExecutionContext
&
ctx
,
mkldnn
::
algorithm
algorithm
,
const
T
alpha
=
0
,
const
T
beta
=
0
)
{
mkldnn
::
algorithm
algorithm
)
{
PADDLE_ENFORCE
(
paddle
::
platform
::
is_cpu_place
(
ctx
.
GetPlace
()),
"It must use CPUPlace."
);
auto
&
dev_ctx
=
ctx
.
template
device_context
<
MKLDNNDeviceContext
>();
...
...
@@ -90,6 +89,9 @@ void eltwise_forward(const framework::ExecutionContext &ctx,
const
T
*
x_data
=
x
->
data
<
T
>
();
T
*
y_data
=
y
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
const
T
alpha
=
ctx
.
op
().
HasAttr
(
"alpha"
)
?
ctx
.
Attr
<
T
>
(
"alpha"
)
:
0
;
const
T
beta
=
ctx
.
op
().
HasAttr
(
"beta"
)
?
ctx
.
Attr
<
T
>
(
"beta"
)
:
0
;
PADDLE_ENFORCE
(
x
->
dims
().
size
()
==
2
||
x
->
dims
().
size
()
==
3
||
x
->
dims
().
size
()
==
4
,
"Input dim must be with 2, 3 or 4"
);
...
...
@@ -101,10 +103,9 @@ void eltwise_forward(const framework::ExecutionContext &ctx,
bool
is_test
=
ctx
.
Attr
<
bool
>
(
"is_test"
);
// TODO(jczaja): When adding leaky-relu , swish , elu make sure to extend key
// with alpha, beta
std
::
string
key
=
platform
::
MKLDNNHandler
::
GetHash
(
src_tz
,
std
::
to_string
(
algorithm
)
+
ctx
.
op
().
Output
(
"Out"
));
src_tz
,
std
::
to_string
(
algorithm
)
+
std
::
to_string
(
alpha
)
+
std
::
to_string
(
beta
)
+
ctx
.
op
().
Output
(
"Out"
));
// TODO(jczaja): Make it Thread safe
// save input data and layout to be referred in backward path
...
...
@@ -153,8 +154,7 @@ void eltwise_forward(const framework::ExecutionContext &ctx,
template
<
typename
T
>
void
eltwise_grad
(
const
framework
::
ExecutionContext
&
ctx
,
mkldnn
::
algorithm
algorithm
,
const
T
alpha
=
0
,
const
T
beta
=
0
)
{
mkldnn
::
algorithm
algorithm
)
{
auto
&
dev_ctx
=
ctx
.
template
device_context
<
MKLDNNDeviceContext
>();
const
auto
&
mkldnn_engine
=
dev_ctx
.
GetEngine
();
...
...
@@ -164,6 +164,9 @@ void eltwise_grad(const framework::ExecutionContext &ctx,
const
T
*
diff_y_data
=
diff_y
->
data
<
T
>
();
T
*
diff_x_data
=
diff_x
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
const
T
alpha
=
ctx
.
op
().
HasAttr
(
"alpha"
)
?
ctx
.
Attr
<
T
>
(
"alpha"
)
:
0
;
const
T
beta
=
ctx
.
op
().
HasAttr
(
"beta"
)
?
ctx
.
Attr
<
T
>
(
"beta"
)
:
0
;
std
::
vector
<
int
>
diff_dst_tz
=
framework
::
vectorize2int
(
diff_y
->
dims
());
auto
diff_y_format
=
...
...
@@ -173,7 +176,8 @@ void eltwise_grad(const framework::ExecutionContext &ctx,
diff_dst_tz
,
platform
::
MKLDNNGetDataType
<
T
>
(),
diff_y_format
);
std
::
string
key
=
platform
::
MKLDNNHandler
::
GetHash
(
diff_dst_tz
,
std
::
to_string
(
algorithm
)
+
ctx
.
op
().
Input
(
"Out"
));
diff_dst_tz
,
std
::
to_string
(
algorithm
)
+
std
::
to_string
(
alpha
)
+
std
::
to_string
(
beta
)
+
ctx
.
op
().
Input
(
"Out"
));
const
std
::
string
key_src_data
=
key
+
"@eltwise_fwd_src_data"
;
const
std
::
string
key_src_layout
=
key
+
"@eltwise_fwd_src_layout"
;
...
...
@@ -273,10 +277,11 @@ namespace ops = paddle::operators;
act_type##_grad, MKLDNN, ::paddle::platform::CPUPlace, \
ops::MKLDNNActivationGradKernel<ops::grad_functor<float>>);
#define FOR_EACH_MKLDNN_KERNEL_FUNCTOR(__macro) \
__macro(relu, ReluMKLDNNFunctor, ReluMKLDNNGradFunctor); \
__macro(tanh, TanhMKLDNNFunctor, TanhMKLDNNGradFunctor); \
__macro(sqrt, SqrtMKLDNNFunctor, SqrtMKLDNNGradFunctor); \
#define FOR_EACH_MKLDNN_KERNEL_FUNCTOR(__macro) \
__macro(relu, ReluMKLDNNFunctor, ReluMKLDNNGradFunctor); \
__macro(leaky_relu, ReluMKLDNNFunctor, ReluMKLDNNGradFunctor); \
__macro(tanh, TanhMKLDNNFunctor, TanhMKLDNNGradFunctor); \
__macro(sqrt, SqrtMKLDNNFunctor, SqrtMKLDNNGradFunctor); \
__macro(abs, AbsMKLDNNFunctor, AbsMKLDNNGradFunctor);
FOR_EACH_MKLDNN_KERNEL_FUNCTOR
(
REGISTER_ACTIVATION_MKLDNN_KERNEL
);
python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py
浏览文件 @
d6b6a337
...
...
@@ -18,7 +18,7 @@ import unittest
import
numpy
as
np
import
paddle.fluid.core
as
core
from
paddle.fluid.tests.unittests.op_test
import
OpTest
from
paddle.fluid.tests.unittests.test_activation_op
import
TestRelu
,
TestTanh
,
TestSqrt
,
TestAbs
from
paddle.fluid.tests.unittests.test_activation_op
import
TestRelu
,
TestTanh
,
TestSqrt
,
TestAbs
,
TestLeakyRelu
from
mkldnn_op_test
import
check_if_mkldnn_primitives_exist_in_bwd
...
...
@@ -29,6 +29,13 @@ class TestMKLDNNReluDim2(TestRelu):
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNLeakyReluDim2
(
TestLeakyRelu
):
def
setUp
(
self
):
super
(
TestMKLDNNLeakyReluDim2
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNTanhDim2
(
TestTanh
):
def
setUp
(
self
):
super
(
TestMKLDNNTanhDim2
,
self
).
setUp
()
...
...
@@ -63,6 +70,20 @@ class TestMKLDNNReluDim4(TestRelu):
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNLeakyReluDim4
(
TestLeakyRelu
):
def
setUp
(
self
):
super
(
TestMKLDNNLeakyReluDim4
,
self
).
setUp
()
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
# The same reason with TestAbs
x
[
np
.
abs
(
x
)
<
0.005
]
=
0.02
out
=
np
.
maximum
(
x
,
0.02
*
x
)
self
.
inputs
=
{
'X'
:
OpTest
.
np_dtype_to_fluid_dtype
(
x
)}
self
.
outputs
=
{
'Out'
:
out
}
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNTanhDim4
(
TestTanh
):
def
setUp
(
self
):
super
(
TestMKLDNNTanhDim4
,
self
).
setUp
()
...
...
python/paddle/fluid/tests/unittests/test_activation_op.py
浏览文件 @
d6b6a337
...
...
@@ -367,6 +367,25 @@ class TestRelu(TestActivation):
self
.
check_grad
([
'X'
],
'Out'
,
max_relative_error
=
0.007
)
class
TestLeakyRelu
(
TestActivation
):
def
setUp
(
self
):
self
.
op_type
=
"leaky_relu"
self
.
init_dtype
()
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
11
,
17
]).
astype
(
self
.
dtype
)
# The same reason with TestAbs
x
[
np
.
abs
(
x
)
<
0.005
]
=
0.02
out
=
np
.
maximum
(
x
,
0.02
*
x
)
self
.
inputs
=
{
'X'
:
OpTest
.
np_dtype_to_fluid_dtype
(
x
)}
self
.
outputs
=
{
'Out'
:
out
}
def
test_check_grad
(
self
):
if
self
.
dtype
==
np
.
float16
:
return
self
.
check_grad
([
'X'
],
'Out'
,
max_relative_error
=
0.007
)
class
TestGelu
(
TestActivation
):
def
setUp
(
self
):
self
.
op_type
=
"gelu"
...
...
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