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体验新版 GitCode,发现更多精彩内容 >>
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d292ad85
编写于
8月 26, 2018
作者:
T
tensor-tang
提交者:
GitHub
8月 26, 2018
浏览文件
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差异文件
Merge pull request #12958 from tensor-tang/refine/op/fusion_lstm
refine fusion lstm
上级
4fcc2936
c488ee96
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
185 addition
and
33 deletion
+185
-33
paddle/fluid/operators/fusion_lstm_op.cc
paddle/fluid/operators/fusion_lstm_op.cc
+149
-7
python/paddle/fluid/tests/unittests/test_fusion_lstm_op.py
python/paddle/fluid/tests/unittests/test_fusion_lstm_op.py
+36
-26
未找到文件。
paddle/fluid/operators/fusion_lstm_op.cc
浏览文件 @
d292ad85
...
...
@@ -15,10 +15,14 @@ limitations under the License. */
#include "paddle/fluid/operators/fusion_lstm_op.h"
#include <string>
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/operators/math/cpu_vec.h"
#include "paddle/fluid/operators/math/detail/activation_functions.h"
#include "paddle/fluid/operators/math/fc_compute.h"
#include "paddle/fluid/operators/math/lstm_compute.h"
#include "paddle/fluid/operators/math/sequence2batch.h"
#include "paddle/fluid/platform/cpu_info.h"
DEFINE_bool
(
seq_mode
,
true
,
"Use sequence mode"
);
namespace
paddle
{
namespace
operators
{
...
...
@@ -98,7 +102,12 @@ void FusionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
ctx
->
ShareLoD
(
"X"
,
"Hidden"
);
ctx
->
ShareLoD
(
"X"
,
"Cell"
);
int
xx_width
=
x_dims
[
1
]
>
wx_dims
[
1
]
?
wx_dims
[
1
]
:
x_dims
[
1
];
int
xx_width
;
if
(
FLAGS_seq_mode
)
{
xx_width
=
wx_dims
[
1
];
}
else
{
xx_width
=
x_dims
[
1
]
>
wx_dims
[
1
]
?
wx_dims
[
1
]
:
x_dims
[
1
];
}
ctx
->
SetOutputDim
(
"XX"
,
{
x_dims
[
0
],
xx_width
});
ctx
->
ShareLoD
(
"X"
,
"XX"
);
}
...
...
@@ -205,10 +214,138 @@ inline void ReorderInitState(const DeviceContext& ctx,
row_shuffle
(
ctx
,
src
,
index_lod
,
dst
,
indexed_src
);
}
template
<
typename
DeviceContext
,
typename
T
>
template
<
typename
T
>
class
FuisonLSTMKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
void
SeqCompute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
using
DeviceContext
=
paddle
::
platform
::
CPUDeviceContext
;
auto
*
x
=
ctx
.
Input
<
LoDTensor
>
(
"X"
);
auto
*
h0
=
ctx
.
Input
<
Tensor
>
(
"H0"
);
auto
*
c0
=
ctx
.
Input
<
Tensor
>
(
"C0"
);
auto
*
wx
=
ctx
.
Input
<
Tensor
>
(
"WeightX"
);
auto
*
wh
=
ctx
.
Input
<
Tensor
>
(
"WeightH"
);
auto
*
bias
=
ctx
.
Input
<
Tensor
>
(
"Bias"
);
auto
*
xx
=
ctx
.
Output
<
LoDTensor
>
(
"XX"
);
auto
*
hidden_out
=
ctx
.
Output
<
LoDTensor
>
(
"Hidden"
);
auto
*
cell_out
=
ctx
.
Output
<
LoDTensor
>
(
"Cell"
);
bool
is_reverse
=
ctx
.
Attr
<
bool
>
(
"is_reverse"
);
std
::
function
<
void
(
const
int
,
const
T
*
,
T
*
)
>
act_gate
,
act_cell
,
act_cand
;
auto
&
act_gate_str
=
ctx
.
Attr
<
std
::
string
>
(
"gate_activation"
);
auto
&
act_cell_str
=
ctx
.
Attr
<
std
::
string
>
(
"cell_activation"
);
auto
&
act_cand_str
=
ctx
.
Attr
<
std
::
string
>
(
"candidate_activation"
);
if
(
platform
::
jit
::
MayIUse
(
platform
::
jit
::
avx
))
{
math
::
VecActivations
<
T
,
platform
::
jit
::
avx
>
act_functor
;
act_gate
=
act_functor
(
act_gate_str
);
act_cell
=
act_functor
(
act_cell_str
);
act_cand
=
act_functor
(
act_cand_str
);
}
else
{
math
::
VecActivations
<
T
,
platform
::
jit
::
isa_any
>
act_functor
;
act_gate
=
act_functor
(
act_gate_str
);
act_cell
=
act_functor
(
act_cell_str
);
act_cand
=
act_functor
(
act_cand_str
);
}
auto
x_lod
=
x
->
lod
();
auto
x_dims
=
x
->
dims
();
// T x M
auto
wh_dims
=
wh
->
dims
();
// D x 4D
const
int
total_T
=
x_dims
[
0
];
const
int
N
=
x_lod
[
0
].
size
()
-
1
;
// batch size
const
int
M
=
x_dims
[
1
];
// x frame size
const
int
D
=
wh_dims
[
0
];
const
int
D2
=
D
*
2
;
const
int
D3
=
D
*
3
;
const
int
D4
=
wh_dims
[
1
];
const
T
*
x_data
=
x
->
data
<
T
>
();
const
T
*
h0_data
=
h0
?
h0
->
data
<
T
>
()
:
NULL
;
const
T
*
c0_data
=
c0
?
c0
->
data
<
T
>
()
:
NULL
;
const
T
*
wx_data
=
wx
->
data
<
T
>
();
const
T
*
wh_data
=
wh
->
data
<
T
>
();
T
*
xx_data
=
xx
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
T
*
hidden_out_data
=
hidden_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
T
*
cell_out_data
=
cell_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
blas
=
math
::
GetBlas
<
DeviceContext
,
T
>
(
ctx
);
math
::
FCCompute
<
DeviceContext
,
T
>
(
blas
,
total_T
,
D4
,
M
,
x_data
,
wx_data
,
xx_data
,
bias
->
data
<
T
>
());
int
xx_offset
=
D4
;
int
gate_offset
=
D
;
if
(
is_reverse
)
{
const
int
offset
=
(
total_T
-
1
)
*
D
;
xx_data
=
xx_data
+
offset
*
4
;
hidden_out_data
=
hidden_out_data
+
offset
;
cell_out_data
=
cell_out_data
+
offset
;
xx_offset
=
-
D4
;
gate_offset
=
-
D
;
}
auto
move_step
=
[
&
]()
{
xx_data
=
xx_data
+
xx_offset
;
hidden_out_data
=
hidden_out_data
+
gate_offset
;
cell_out_data
=
cell_out_data
+
gate_offset
;
};
for
(
int
i
=
0
;
i
<
N
;
++
i
)
{
int
bid
=
is_reverse
?
N
-
1
-
i
:
i
;
int
seq_len
=
x_lod
[
0
][
bid
+
1
]
-
x_lod
[
0
][
bid
];
const
T
*
prev_cell_data
=
NULL
;
const
T
*
prev_hidden_data
=
NULL
;
int
tstart
=
0
;
if
(
h0_data
)
{
prev_hidden_data
=
h0_data
+
bid
*
D
;
prev_cell_data
=
c0_data
+
bid
*
D
;
}
else
{
// W_ch, W_ih, W_fh, W_oh
act_gate
(
D3
,
xx_data
+
D
,
xx_data
+
D
);
act_cand
(
D
,
xx_data
,
xx_data
);
// cell out= input*tilde
blas
.
VMUL
(
D
,
xx_data
,
xx_data
+
D
,
cell_out_data
);
// hidden out= act_state(cellout) * outgate
act_cell
(
D
,
cell_out_data
,
xx_data
+
D2
);
blas
.
VMUL
(
D
,
xx_data
+
D2
,
xx_data
+
D3
,
hidden_out_data
);
// prev
prev_hidden_data
=
hidden_out_data
;
prev_cell_data
=
cell_out_data
;
tstart
=
1
;
move_step
();
}
for
(
int
step
=
tstart
;
step
<
seq_len
;
++
step
)
{
blas
.
GEMM
(
CblasNoTrans
,
CblasNoTrans
,
1
,
D4
,
D
,
static_cast
<
T
>
(
1
),
prev_hidden_data
,
D
,
wh_data
,
D4
,
static_cast
<
T
>
(
1
),
xx_data
,
D4
);
// W_ch, W_ih, W_fh, W_oh
act_gate
(
D3
,
xx_data
+
D
,
xx_data
+
D
);
act_cand
(
D
,
xx_data
,
xx_data
);
// a = forget * prev_cell
blas
.
VMUL
(
D
,
xx_data
+
D2
,
prev_cell_data
,
xx_data
+
D2
);
// b = input * tilde
blas
.
VMUL
(
D
,
xx_data
,
xx_data
+
D
,
xx_data
+
D
);
// cell out= a+b
blas
.
VADD
(
D
,
xx_data
+
D
,
xx_data
+
D2
,
cell_out_data
);
// hidden out= act_state(cellout) * outgate
act_cell
(
D
,
cell_out_data
,
xx_data
+
D2
);
blas
.
VMUL
(
D
,
xx_data
+
D2
,
xx_data
+
D3
,
hidden_out_data
);
// prev
prev_hidden_data
=
hidden_out_data
;
prev_cell_data
=
cell_out_data
;
move_step
();
}
}
}
void
BatchCompute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
using
DeviceContext
=
platform
::
CPUDeviceContext
;
auto
*
x
=
ctx
.
Input
<
LoDTensor
>
(
"X"
);
auto
*
wx
=
ctx
.
Input
<
Tensor
>
(
"WeightX"
);
auto
*
wh
=
ctx
.
Input
<
Tensor
>
(
"WeightH"
);
...
...
@@ -339,6 +476,13 @@ class FuisonLSTMKernel : public framework::OpKernel<T> {
// restore the output cell state in LoDTensor from the batch cell
to_seq
(
dev_ctx
,
batch_cell
,
cell_out
);
}
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
if
(
FLAGS_seq_mode
)
{
SeqCompute
(
ctx
);
}
else
{
BatchCompute
(
ctx
);
}
}
};
}
// namespace operators
...
...
@@ -348,7 +492,5 @@ namespace ops = paddle::operators;
REGISTER_OPERATOR
(
fusion_lstm
,
ops
::
FusionLSTMOp
,
ops
::
FusionLSTMOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OP_CPU_KERNEL
(
fusion_lstm
,
ops
::
FuisonLSTMKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
FuisonLSTMKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
fusion_lstm
,
ops
::
FuisonLSTMKernel
<
float
>
,
ops
::
FuisonLSTMKernel
<
double
>
);
python/paddle/fluid/tests/unittests/test_fusion_lstm_op.py
浏览文件 @
d292ad85
...
...
@@ -43,13 +43,13 @@ def fusion_lstm(
act_cell
,
act_cand
)
class
Test
Lstm
Op
(
OpTest
):
def
set_
argument
(
self
):
self
.
lod
=
[[
2
,
3
,
2
]]
class
Test
FusionLSTM
Op
(
OpTest
):
def
set_
conf
(
self
):
pass
def
setUp
(
self
):
self
.
op_type
=
'fusion_lstm'
self
.
lod
=
[[
2
,
3
,
2
]]
self
.
lod
=
[[
2
,
3
,
5
,
4
]]
self
.
M
=
8
self
.
D
=
16
self
.
has_initial_state
=
False
...
...
@@ -58,33 +58,33 @@ class TestLstmOp(OpTest):
self
.
act_cell
=
'tanh'
self
.
act_cand
=
'tanh'
self
.
use_peepholes
=
False
self
.
set_
argument
()
self
.
set_
conf
()
T
=
sum
(
self
.
lod
[
0
])
bs
=
len
(
self
.
lod
[
0
])
x
=
np
.
random
.
normal
(
size
=
(
T
,
self
.
M
)).
astype
(
'float
64
'
)
x
=
np
.
random
.
normal
(
size
=
(
T
,
self
.
M
)).
astype
(
'float
32
'
)
if
self
.
has_initial_state
:
h0
=
np
.
random
.
normal
(
size
=
(
bs
,
self
.
D
)).
astype
(
'float
64
'
)
c0
=
np
.
random
.
normal
(
size
=
(
bs
,
self
.
D
)).
astype
(
'float
64
'
)
h0
=
np
.
random
.
normal
(
size
=
(
bs
,
self
.
D
)).
astype
(
'float
32
'
)
c0
=
np
.
random
.
normal
(
size
=
(
bs
,
self
.
D
)).
astype
(
'float
32
'
)
else
:
h0
=
np
.
zeros
((
bs
,
self
.
D
)).
astype
(
'float
64
'
)
c0
=
np
.
zeros
((
bs
,
self
.
D
)).
astype
(
'float
64
'
)
h0
=
np
.
zeros
((
bs
,
self
.
D
)).
astype
(
'float
32
'
)
c0
=
np
.
zeros
((
bs
,
self
.
D
)).
astype
(
'float
32
'
)
wh
=
np
.
random
.
normal
(
size
=
(
self
.
D
,
4
*
self
.
D
)).
astype
(
'float
64
'
)
wh
=
np
.
random
.
normal
(
size
=
(
self
.
D
,
4
*
self
.
D
)).
astype
(
'float
32
'
)
if
self
.
use_peepholes
:
b
=
np
.
random
.
normal
(
size
=
(
1
,
7
*
self
.
D
)).
astype
(
'float
64
'
)
b
=
np
.
random
.
normal
(
size
=
(
1
,
7
*
self
.
D
)).
astype
(
'float
32
'
)
else
:
b
=
np
.
random
.
normal
(
size
=
(
1
,
4
*
self
.
D
)).
astype
(
'float
64
'
)
b
=
np
.
random
.
normal
(
size
=
(
1
,
4
*
self
.
D
)).
astype
(
'float
32
'
)
w_b
=
np
.
copy
(
b
[:,
0
:
4
*
self
.
D
])
w_c
=
b
[:,
4
*
self
.
D
:]
if
self
.
use_peepholes
else
None
# this is the weight of fc
wx
=
np
.
random
.
normal
(
size
=
(
self
.
M
,
4
*
self
.
D
)).
astype
(
'float
64
'
)
wx
=
np
.
random
.
normal
(
size
=
(
self
.
M
,
4
*
self
.
D
)).
astype
(
'float
32
'
)
# this is the bias of fc
# and it should be manually added into the bias of this fusion LSTM
bx
=
np
.
random
.
normal
(
size
=
(
1
,
4
*
self
.
D
)).
astype
(
'float
64
'
)
bx
=
np
.
random
.
normal
(
size
=
(
1
,
4
*
self
.
D
)).
astype
(
'float
32
'
)
b
[
0
,
0
:
4
*
self
.
D
]
+=
bx
[
0
,
:]
h
,
c
=
fusion_lstm
(
x
,
self
.
lod
,
wx
,
bx
,
h0
,
c0
,
wh
,
w_b
,
w_c
,
self
.
is_reverse
,
ACTIVATION
[
self
.
act_gate
],
...
...
@@ -114,35 +114,45 @@ class TestLstmOp(OpTest):
}
def
test_check_output
(
self
):
self
.
check_output
(
atol
=
1e-8
)
self
.
check_output
()
class
TestLstmOpInitReverse
(
TestLstmOp
):
def
set_argument
(
self
):
class
TestFusionLSTMOpInit
(
TestFusionLSTMOp
):
def
set_conf
(
self
):
self
.
has_initial_state
=
True
class
TestFusionLSTMOpReverse
(
TestFusionLSTMOp
):
def
set_conf
(
self
):
self
.
is_reverse
=
True
class
TestFusionLSTMOpInitReverse
(
TestFusionLSTMOp
):
def
set_conf
(
self
):
self
.
has_initial_state
=
True
self
.
is_reverse
=
True
class
Test
LstmOpMD1
(
TestLstm
Op
):
def
set_
argument
(
self
):
class
Test
FusionLSTMOpMD1
(
TestFusionLSTM
Op
):
def
set_
conf
(
self
):
self
.
M
=
36
self
.
D
=
8
class
Test
LstmOpMD2
(
TestLstm
Op
):
def
set_
argument
(
self
):
class
Test
FusionLSTMOpMD2
(
TestFusionLSTM
Op
):
def
set_
conf
(
self
):
self
.
M
=
8
self
.
D
=
8
class
Test
LstmOpMD3
(
TestLstm
Op
):
def
set_
argument
(
self
):
class
Test
FusionLSTMOpMD3
(
TestFusionLSTM
Op
):
def
set_
conf
(
self
):
self
.
M
=
15
self
.
D
=
3
class
Test
LstmOpBS1
(
TestLstm
Op
):
def
set_
argument
(
self
):
class
Test
FusionLSTMOpBS1
(
TestFusionLSTM
Op
):
def
set_
conf
(
self
):
self
.
lod
=
[[
3
]]
self
.
D
=
16
...
...
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