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90bd038d
编写于
3月 25, 2019
作者:
D
dengkaipeng
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix format. test=develop
上级
f45aced5
变更
11
隐藏空白更改
内联
并排
Showing
11 changed file
with
34 addition
and
28 deletion
+34
-28
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-1
paddle/fluid/operators/jit/more/mix/mix.cc
paddle/fluid/operators/jit/more/mix/mix.cc
+4
-2
paddle/fluid/operators/jit/more/mkl/mkl.cc
paddle/fluid/operators/jit/more/mkl/mkl.cc
+8
-6
paddle/fluid/operators/jit/more/mkl/mkl.h
paddle/fluid/operators/jit/more/mkl/mkl.h
+1
-1
paddle/fluid/operators/jit/refer/refer.h
paddle/fluid/operators/jit/refer/refer.h
+2
-2
paddle/fluid/operators/jit/test.cc
paddle/fluid/operators/jit/test.cc
+4
-4
paddle/fluid/operators/math/softmax.h
paddle/fluid/operators/math/softmax.h
+1
-1
paddle/fluid/operators/math/softmax_impl.h
paddle/fluid/operators/math/softmax_impl.h
+3
-2
paddle/fluid/operators/softmax_op.cc
paddle/fluid/operators/softmax_op.cc
+2
-4
paddle/fluid/operators/softmax_op.h
paddle/fluid/operators/softmax_op.h
+6
-4
paddle/fluid/operators/warpctc_cudnn_op.cu.cc
paddle/fluid/operators/warpctc_cudnn_op.cu.cc
+2
-1
未找到文件。
paddle/fluid/API.spec
浏览文件 @
90bd038d
...
...
@@ -86,7 +86,7 @@ paddle.fluid.layers.conv2d (ArgSpec(args=['input', 'num_filters', 'filter_size',
paddle.fluid.layers.conv3d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None)), ('document', '37042620f9bd3a2da6e5d3138b2f724b'))
paddle.fluid.layers.sequence_pool (ArgSpec(args=['input', 'pool_type', 'is_test'], varargs=None, keywords=None, defaults=(False,)), ('document', 'a194fb80614023f543df3949fbd0d0b8'))
paddle.fluid.layers.sequence_softmax (ArgSpec(args=['input', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', '19ef6f9cdd27feac8a1ae060f19c10b4'))
paddle.fluid.layers.softmax (ArgSpec(args=['input', 'use_cudnn', 'name', 'axis'], varargs=None, keywords=None, defaults=(False, None, -1)), ('document', '
85f9690b1b285def19077a41d9dba36c
'))
paddle.fluid.layers.softmax (ArgSpec(args=['input', 'use_cudnn', 'name', 'axis'], varargs=None, keywords=None, defaults=(False, None, -1)), ('document', '
502bad9e8bc7ef24817d0d4b20f61df3
'))
paddle.fluid.layers.pool2d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True)), ('document', 'bbd84e855e660cd1084bb71a2fd0cdaa'))
paddle.fluid.layers.pool3d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True)), ('document', '043de7333b79ee0ac55053c14ed81625'))
paddle.fluid.layers.adaptive_pool2d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'require_index', 'name'], varargs=None, keywords=None, defaults=('max', False, None)), ('document', '859b887174d06f361658f69cb7c06d95'))
...
...
paddle/fluid/operators/jit/more/mix/mix.cc
浏览文件 @
90bd038d
...
...
@@ -54,8 +54,10 @@ void Softmax(const T* x, T* y, int n, int bs, int remain) {
auto
compute_hmax
=
KernelFuncs
<
HMaxTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
auto
compute_hsum
=
KernelFuncs
<
HSumTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
auto
compute_vscal
=
KernelFuncs
<
VScalTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
auto
compute_stridesum
=
KernelFuncs
<
StrideASumTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
auto
compute_stridescal
=
KernelFuncs
<
StrideScalTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
auto
compute_stridesum
=
KernelFuncs
<
StrideASumTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
auto
compute_stridescal
=
KernelFuncs
<
StrideScalTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
auto
compute_vaddbias
=
KernelFuncs
<
VAddBiasTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
auto
compute_vexp
=
KernelFuncs
<
VExpTuple
<
T
>
,
CPUPlace
>::
Cache
().
At
(
n
);
...
...
paddle/fluid/operators/jit/more/mkl/mkl.cc
浏览文件 @
90bd038d
...
...
@@ -79,18 +79,20 @@ void VScal<double>(const double* a, const double* x, double* y, int n) {
}
template
<
>
void
StrideScal
<
float
>
(
const
float
*
a
,
const
float
*
x
,
float
*
y
,
int
n
,
int
stride
)
{
void
StrideScal
<
float
>
(
const
float
*
a
,
const
float
*
x
,
float
*
y
,
int
n
,
int
stride
)
{
if
(
x
==
y
)
{
platform
::
dynload
::
cblas_sscal
(
n
/
stride
,
*
a
,
y
,
stride
);
platform
::
dynload
::
cblas_sscal
(
n
/
stride
,
*
a
,
y
,
stride
);
}
else
{
refer
::
StrideScal
<
float
>
(
a
,
x
,
y
,
n
,
stride
);
}
}
template
<
>
void
StrideScal
<
double
>
(
const
double
*
a
,
const
double
*
x
,
double
*
y
,
int
n
,
int
stride
)
{
void
StrideScal
<
double
>
(
const
double
*
a
,
const
double
*
x
,
double
*
y
,
int
n
,
int
stride
)
{
if
(
x
==
y
)
{
platform
::
dynload
::
cblas_dscal
(
n
/
stride
,
*
a
,
y
,
stride
);
platform
::
dynload
::
cblas_dscal
(
n
/
stride
,
*
a
,
y
,
stride
);
}
else
{
refer
::
StrideScal
<
double
>
(
a
,
x
,
y
,
n
,
stride
);
}
...
...
@@ -148,12 +150,12 @@ void ASum<double>(const double* x, double* res, int n) {
template
<
>
void
StrideASum
<
float
>
(
const
float
*
x
,
float
*
res
,
int
n
,
int
stride
)
{
res
[
0
]
=
platform
::
dynload
::
cblas_sasum
(
n
/
stride
,
x
,
stride
);
res
[
0
]
=
platform
::
dynload
::
cblas_sasum
(
n
/
stride
,
x
,
stride
);
}
template
<
>
void
StrideASum
<
double
>
(
const
double
*
x
,
double
*
res
,
int
n
,
int
stride
)
{
res
[
0
]
=
platform
::
dynload
::
cblas_dasum
(
n
/
stride
,
x
,
stride
);
res
[
0
]
=
platform
::
dynload
::
cblas_dasum
(
n
/
stride
,
x
,
stride
);
}
// TODO(TJ): tuning me carefully on AVX, AVX2 and AVX512
...
...
paddle/fluid/operators/jit/more/mkl/mkl.h
浏览文件 @
90bd038d
...
...
@@ -135,7 +135,7 @@ template <typename T>
void
StrideScal
(
const
T
*
a
,
const
T
*
x
,
T
*
y
,
int
n
,
int
stride
);
template
<
typename
T
>
void
Softmax
(
const
T
*
x
,
T
*
y
,
int
n
,
int
bs
,
int
remain
=
1
)
{
void
Softmax
(
const
T
*
x
,
T
*
y
,
int
n
,
int
bs
,
int
remain
=
1
)
{
std
::
vector
<
T
>
entities
(
bs
);
for
(
int
i
=
0
;
i
<
bs
;
++
i
)
{
entities
[
i
]
=
x
[
i
*
n
];
...
...
paddle/fluid/operators/jit/refer/refer.h
浏览文件 @
90bd038d
...
...
@@ -414,13 +414,13 @@ void HSum(const T* x, T* res, int n) {
template
<
typename
T
>
void
StrideASum
(
const
T
*
x
,
T
*
res
,
int
n
,
int
stride
)
{
res
[
0
]
=
x
[
0
];
for
(
int
i
=
stride
;
i
<
n
;
i
+=
stride
)
{
for
(
int
i
=
stride
;
i
<
n
;
i
+=
stride
)
{
res
[
0
]
+=
std
::
abs
(
x
[
i
]);
}
}
template
<
typename
T
>
void
StrideScal
(
const
T
*
a
,
const
T
*
x
,
T
*
y
,
int
n
,
int
stride
)
{
void
StrideScal
(
const
T
*
a
,
const
T
*
x
,
T
*
y
,
int
n
,
int
stride
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
if
(
i
%
stride
==
0
)
{
y
[
i
]
=
x
[
i
]
*
a
[
0
];
...
...
paddle/fluid/operators/jit/test.cc
浏览文件 @
90bd038d
...
...
@@ -723,7 +723,7 @@ void TestKernelSoftmax() {
VLOG
(
10
)
<<
"Test JITKernel: "
<<
jit
::
to_string
(
KernelTuple
::
kernel_type
);
for
(
int
bs
:
{
1
,
2
,
10
})
{
for
(
int
n
:
TestSizes
())
{
for
(
int
m
:
{
1
,
2
,
3
})
{
// remain
for
(
int
m
:
{
1
,
2
,
3
})
{
// remain
if
(
m
>
n
||
n
%
m
!=
0
)
{
continue
;
}
...
...
@@ -770,7 +770,7 @@ void TestKernelStrideASum() {
using
T
=
typename
KernelTuple
::
data_type
;
VLOG
(
10
)
<<
"Test JITKernel: "
<<
jit
::
to_string
(
KernelTuple
::
kernel_type
);
for
(
int
d
:
TestSizes
())
{
for
(
int
m
:
{
1
,
2
,
3
})
{
// stride
for
(
int
m
:
{
1
,
2
,
3
})
{
// stride
if
(
m
>
d
||
d
%
m
!=
0
)
{
continue
;
}
...
...
@@ -782,7 +782,7 @@ void TestKernelStrideASum() {
ref
(
x
.
data
(),
&
ref_res
,
d
,
m
);
auto
verifier
=
[](
const
typename
KernelTuple
::
func_type
tgt
,
const
std
::
vector
<
T
>&
x
,
const
T
ref_res
,
const
std
::
vector
<
T
>&
x
,
const
T
ref_res
,
const
int
m
)
{
EXPECT_TRUE
(
tgt
!=
nullptr
);
T
tgt_res
;
...
...
@@ -801,7 +801,7 @@ void TestKernelStrideScal() {
// for (int d : TestSizes()) {
// for (int m : {1, 2, 3}) { // stride
for
(
int
d
:
{
4
})
{
for
(
int
m
:
{
2
})
{
// stride
for
(
int
m
:
{
2
})
{
// stride
if
(
m
>
d
||
d
%
m
!=
0
)
{
continue
;
}
...
...
paddle/fluid/operators/math/softmax.h
浏览文件 @
90bd038d
...
...
@@ -31,7 +31,7 @@ template <typename DeviceContext, typename T>
class
SoftmaxGradFunctor
{
public:
void
operator
()(
const
DeviceContext
&
context
,
const
int
axis_dim
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
y_grad
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
y_grad
,
framework
::
Tensor
*
x_grad
);
};
...
...
paddle/fluid/operators/math/softmax_impl.h
浏览文件 @
90bd038d
...
...
@@ -94,8 +94,9 @@ class SoftmaxFunctor<DeviceContext, float, true, enable_if_CPU<DeviceContext>> {
template
<
typename
DeviceContext
,
typename
T
>
void
SoftmaxGradFunctor
<
DeviceContext
,
T
>::
operator
()(
const
DeviceContext
&
context
,
const
int
axis_dim
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
y_grad
,
framework
::
Tensor
*
x_grad
)
{
const
DeviceContext
&
context
,
const
int
axis_dim
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
y_grad
,
framework
::
Tensor
*
x_grad
)
{
auto
softmax
=
EigenMatrix
<
T
>::
From
(
*
y
);
auto
softmax_grad
=
EigenMatrix
<
T
>::
From
(
*
y_grad
);
auto
logits_grad
=
EigenMatrix
<
T
>::
From
(
*
x_grad
);
...
...
paddle/fluid/operators/softmax_op.cc
浏览文件 @
90bd038d
...
...
@@ -49,10 +49,8 @@ class SoftmaxOp : public framework::OperatorWithKernel {
auto
use_cudnn
=
ctx
->
Attrs
().
Get
<
bool
>
(
"use_cudnn"
);
auto
use_mkldnn
=
ctx
->
Attrs
().
Get
<
bool
>
(
"use_mkldnn"
);
if
(
axis
!=
rank_x
-
1
&&
axis
!=
-
1
)
{
PADDLE_ENFORCE
(
!
use_cudnn
,
"CUDNN kernel only support axis as -1."
);
PADDLE_ENFORCE
(
!
use_mkldnn
,
"MKLDNN kernel only support axis as -1."
);
PADDLE_ENFORCE
(
!
use_cudnn
,
"CUDNN kernel only support axis as -1."
);
PADDLE_ENFORCE
(
!
use_mkldnn
,
"MKLDNN kernel only support axis as -1."
);
}
ctx
->
SetOutputDim
(
"Out"
,
ctx
->
GetInputDim
(
"X"
));
...
...
paddle/fluid/operators/softmax_op.h
浏览文件 @
90bd038d
...
...
@@ -66,10 +66,12 @@ class SoftmaxKernel : public framework::OpKernel<T> {
#ifdef PADDLE_ON_INFERENCE
math
::
SoftmaxFunctor
<
DeviceContext
,
T
,
true
>
()(
context
.
template
device_context
<
DeviceContext
>(),
axis_dim
,
&
X_2d
,
&
Out_2d
);
context
.
template
device_context
<
DeviceContext
>(),
axis_dim
,
&
X_2d
,
&
Out_2d
);
#else
math
::
SoftmaxFunctor
<
DeviceContext
,
T
,
false
>
()(
context
.
template
device_context
<
DeviceContext
>(),
axis_dim
,
&
X_2d
,
&
Out_2d
);
context
.
template
device_context
<
DeviceContext
>(),
axis_dim
,
&
X_2d
,
&
Out_2d
);
#endif
}
};
...
...
@@ -96,8 +98,8 @@ class SoftmaxGradKernel : public framework::OpKernel<T> {
dOut_2d
.
ShareDataWith
(
*
dOut
).
Resize
({
n
,
d
});
math
::
SoftmaxGradFunctor
<
DeviceContext
,
T
>
()(
context
.
template
device_context
<
DeviceContext
>(),
axis_dim
,
&
Out_2d
,
&
dOut_2d
,
&
dX_2d
);
context
.
template
device_context
<
DeviceContext
>(),
axis_dim
,
&
Out_2d
,
&
d
Out_2d
,
&
d
X_2d
);
}
};
...
...
paddle/fluid/operators/warpctc_cudnn_op.cu.cc
浏览文件 @
90bd038d
...
...
@@ -69,7 +69,8 @@ class CudnnCTCKernel : public framework::OpKernel<T> {
int
rank
=
logits
->
dims
().
size
();
Tensor
in_2d
=
framework
::
ReshapeToMatrix
(
*
logits
,
rank
-
1
);
Tensor
out_2d
=
framework
::
ReshapeToMatrix
(
softmax_logits
,
rank
-
1
);
math
::
SoftmaxFunctor
<
DeviceContext
,
T
,
false
>
()(
dev_ctx
,
-
1
,
&
in_2d
,
&
out_2d
);
math
::
SoftmaxFunctor
<
DeviceContext
,
T
,
false
>
()(
dev_ctx
,
-
1
,
&
in_2d
,
&
out_2d
);
// ctc needs sequences data stored in transposed padding format
// logits and grad using padding data of layout 'TNC'
...
...
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