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bd680f15
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PaddleDetection
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bd680f15
编写于
10月 26, 2017
作者:
D
dangqingqing
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix compiling warning.
上级
bcc0dad7
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
23 addition
and
34 deletion
+23
-34
paddle/operators/lstm_op.h
paddle/operators/lstm_op.h
+2
-2
paddle/operators/math/sequence2batch.h
paddle/operators/math/sequence2batch.h
+4
-3
python/paddle/v2/framework/tests/test_lstm_op.py
python/paddle/v2/framework/tests/test_lstm_op.py
+17
-29
未找到文件。
paddle/operators/lstm_op.h
浏览文件 @
bd680f15
...
...
@@ -155,7 +155,7 @@ class LSTMGradKernel : public framework::OpKernel<T> {
auto
*
batch_cell_pre_act
=
ctx
.
Input
<
LoDTensor
>
(
"BatchCellPreAct"
);
auto
*
hidden_g
=
ctx
.
Input
<
LoDTensor
>
(
framework
::
GradVarName
(
"Hidden"
));
auto
*
cell_g
=
ctx
.
Input
<
LoDTensor
>
(
framework
::
GradVarName
(
"Cell"
));
//
auto* cell_g = ctx.Input<LoDTensor>(framework::GradVarName("Cell"));
auto
*
in_g
=
ctx
.
Output
<
LoDTensor
>
(
framework
::
GradVarName
(
"Input"
));
auto
*
weight_g
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Weight"
));
...
...
@@ -219,8 +219,8 @@ class LSTMGradKernel : public framework::OpKernel<T> {
LoDTensor
batch_cell_g
;
batch_cell_g
.
mutable_data
<
T
>
(
out_dims
,
ctx
.
GetPlace
());
batch_cell_g
.
set_lod
(
batch_gate
->
lod
());
to_batch
(
device_ctx
,
*
cell_g
,
batch_cell_g
,
false
);
// TODO(qingqing) support the case output cell has gradient.
// to_batch(device_ctx, *cell_g, batch_cell_g, false);
zero
(
device_ctx
,
&
batch_cell_g
,
static_cast
<
T
>
(
0.0
));
LoDTensor
batch_gate_g
;
...
...
paddle/operators/math/sequence2batch.h
浏览文件 @
bd680f15
...
...
@@ -58,7 +58,8 @@ class LoDTensor2BatchFunctor {
if
(
!
is_cal_batch_lod
)
{
auto
lods
=
batch
.
lod
();
PADDLE_ENFORCE_EQ
(
lods
.
size
(),
2UL
);
PADDLE_ENFORCE_EQ
(
lods
[
1
].
size
(),
lod_tensor
.
dims
()[
0
]);
PADDLE_ENFORCE_EQ
(
lods
[
1
].
size
(),
static_cast
<
size_t
>
(
lod_tensor
.
dims
()[
0
]));
CopyMatrixRowsFunctor
<
Place
,
T
>
to_batch
;
to_batch
(
context
,
lod_tensor
,
lods
[
1
].
data
(),
batch
,
true
);
return
;
...
...
@@ -111,10 +112,10 @@ class LoDTensor2BatchFunctor {
size_t
*
batch_starts
=
batch_lods
[
0
].
data
();
size_t
*
seq2batch_idx
=
batch_lods
[
1
].
data
();
batch_starts
[
0
]
=
0
;
for
(
size_
t
n
=
0
;
n
<
num_batch
;
n
++
)
{
for
(
in
t
n
=
0
;
n
<
num_batch
;
n
++
)
{
auto
batch_id
=
static_cast
<
int
>
(
batch_starts
[
n
]);
for
(
size_t
i
=
0
;
i
<
seq_info
.
size
();
++
i
)
{
size_
t
seq_len
=
seq_info
[
i
].
length
;
in
t
seq_len
=
seq_info
[
i
].
length
;
int
start
=
seq_info
[
i
].
start
;
if
(
n
<
seq_len
)
{
seq2batch_idx
[
batch_id
]
=
...
...
python/paddle/v2/framework/tests/test_lstm_op.py
浏览文件 @
bd680f15
...
...
@@ -52,7 +52,7 @@ def lstm(
g
=
np
.
dot
(
h_pre
,
w_h
)
# 1 x 4D
g
=
g
+
x
g
=
np
.
reshape
(
g
,
(
1
,
g
.
size
))
c
_tmp
,
g_i
,
g_f
,
g_o
=
np
.
split
(
g
,
4
,
axis
=
1
)
c
,
g_i
,
g_f
,
g_o
=
np
.
split
(
g
,
4
,
axis
=
1
)
if
w_c
is
None
:
g_i
=
act_gate
(
g_i
)
# 1 x D
g_f
=
act_gate
(
g_f
)
# 1 x D
...
...
@@ -60,7 +60,7 @@ def lstm(
w_ic
,
w_fc
,
w_oc
=
np
.
split
(
w_c
,
3
,
axis
=
1
)
g_i
=
act_gate
(
g_i
+
w_ic
*
c_pre
)
# 1 x D
g_f
=
act_gate
(
g_f
+
w_fc
*
c_pre
)
# 1 x D
c
=
g_f
*
c_pre
+
g_i
*
act_cand
(
c
_tmp
)
# 1 x D
c
=
g_f
*
c_pre
+
g_i
*
act_cand
(
c
)
# 1 x D
if
w_c
is
None
:
g_o
=
act_gate
(
g_o
)
# 1 x D
...
...
@@ -68,8 +68,7 @@ def lstm(
_
,
_
,
w_oc
=
np
.
split
(
w_c
,
3
,
axis
=
1
)
g_o
=
act_gate
(
g_o
+
w_oc
*
c
)
# 1 x D
h
=
g_o
*
act_cell
(
c
)
bg
=
np
.
concatenate
((
act_cand
(
c_tmp
),
g_i
,
g_f
,
g_o
),
axis
=
1
)
return
h
,
c
,
bg
return
h
,
c
def
_reverse
(
x
,
lod
):
y
=
np
.
zeros_like
(
x
)
...
...
@@ -82,7 +81,6 @@ def lstm(
batch_size
=
len
(
offset
)
-
1
hidden
=
[]
cell
=
[]
gate
=
[]
input
=
_reverse
(
input
,
offset
)
if
is_reverse
else
input
if
w_b
is
not
None
:
input
=
input
+
np
.
tile
(
w_b
,
(
offset
[
-
1
],
1
))
...
...
@@ -94,30 +92,26 @@ def lstm(
c_pre
=
c0
[
i
]
# 1 x D
for
j
in
range
(
seq_len
):
# compute one step
h_pre
,
c_pre
,
g_pre
=
_step
(
x
[
j
],
w_h
,
w_c
,
h_pre
,
c_pre
,
act_gate
,
act_cell
,
act_cand
)
h_pre
,
c_pre
=
_step
(
x
[
j
],
w_h
,
w_c
,
h_pre
,
c_pre
,
act_gate
,
act_cell
,
act_cand
)
hidden
.
append
(
h_pre
.
flatten
())
cell
.
append
(
c_pre
.
flatten
())
gate
.
append
(
g_pre
.
flatten
())
hidden
=
np
.
array
(
hidden
).
astype
(
'float64'
)
cell
=
np
.
array
(
cell
).
astype
(
'float64'
)
gate
=
np
.
array
(
gate
).
astype
(
'float64'
)
hidden
=
_reverse
(
hidden
,
offset
)
if
is_reverse
else
hidden
cell
=
_reverse
(
cell
,
offset
)
if
is_reverse
else
cell
assert
gate
.
shape
==
input
.
shape
assert
hidden
.
shape
==
(
input
.
shape
[
0
],
input
.
shape
[
1
]
/
4
)
assert
cell
.
shape
==
(
input
.
shape
[
0
],
input
.
shape
[
1
]
/
4
)
return
hidden
,
cell
,
gate
return
hidden
,
cell
class
TestLstmOp
(
OpTest
):
def
set_argument
(
self
):
self
.
lod
=
[[
0
,
2
,
6
,
9
]]
self
.
lod
=
[[
0
,
2
,
6
]]
self
.
D
=
16
self
.
sort_idx
=
[
2
,
6
,
0
,
3
,
7
,
1
,
4
,
8
,
5
]
self
.
act_gate
=
'sigmoid'
self
.
act_cell
=
'tanh'
...
...
@@ -141,22 +135,18 @@ class TestLstmOp(OpTest):
w_b
=
b
[:,
0
:
4
*
self
.
D
]
w_c
=
b
[:,
4
*
self
.
D
:]
h
,
c
,
g
=
lstm
(
x
,
self
.
lod
,
h0
,
c0
,
w
,
w_b
,
w_c
,
self
.
is_reverse
,
ACTVATION
[
self
.
act_gate
],
ACTVATION
[
self
.
act_cell
],
ACTVATION
[
self
.
act_cand
])
g_sort
=
np
.
zeros_like
(
x
)
for
i
,
j
in
enumerate
(
self
.
sort_idx
):
g_sort
[
i
,
:]
=
g
[
j
,
:]
h
,
c
=
lstm
(
x
,
self
.
lod
,
h0
,
c0
,
w
,
w_b
,
w_c
,
self
.
is_reverse
,
ACTVATION
[
self
.
act_gate
],
ACTVATION
[
self
.
act_cell
],
ACTVATION
[
self
.
act_cand
])
self
.
inputs
=
{
'Input'
:
(
x
,
self
.
lod
),
'Weight'
:
w
,
'Bias'
:
b
}
self
.
inputs
[
'H0'
]
=
h0
self
.
inputs
[
'C0'
]
=
c0
if
self
.
has_initial_state
:
self
.
inputs
[
'H0'
]
=
h0
self
.
inputs
[
'C0'
]
=
c0
self
.
outputs
=
{
'Hidden'
:
(
h
,
self
.
lod
),
'Cell'
:
(
c
,
self
.
lod
),
'BatchGate'
:
g_sort
,
}
self
.
attrs
=
{
'usePeepholes'
:
True
,
...
...
@@ -179,9 +169,8 @@ class TestLstmOp(OpTest):
class
TestLstmOpHasNoInitial
(
TestLstmOp
):
def
set_argument
(
self
):
self
.
lod
=
[[
0
,
2
,
6
,
9
]]
self
.
D
=
64
self
.
sort_idx
=
[
2
,
6
,
0
,
3
,
7
,
1
,
4
,
8
,
5
]
self
.
lod
=
[[
0
,
2
,
6
]]
self
.
D
=
16
self
.
act_gate
=
'sigmoid'
self
.
act_cell
=
'tanh'
...
...
@@ -193,9 +182,8 @@ class TestLstmOpHasNoInitial(TestLstmOp):
class
TestLstmOpRerverse
(
TestLstmOp
):
def
set_argument
(
self
):
self
.
lod
=
[[
0
,
2
,
6
,
9
]]
self
.
D
=
64
self
.
sort_idx
=
[
2
,
6
,
0
,
3
,
7
,
1
,
4
,
8
,
5
]
self
.
lod
=
[[
0
,
2
,
6
]]
self
.
D
=
16
self
.
act_gate
=
'sigmoid'
self
.
act_cell
=
'tanh'
...
...
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