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体验新版 GitCode,发现更多精彩内容 >>
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d2c2f785
编写于
8月 14, 2017
作者:
Q
qiaolongfei
浏览文件
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差异文件
change backward
上级
5d33ef61
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
34 addition
and
33 deletion
+34
-33
paddle/framework/backward.cc
paddle/framework/backward.cc
+13
-13
paddle/framework/backward_test.cc
paddle/framework/backward_test.cc
+20
-20
paddle/framework/operator.h
paddle/framework/operator.h
+1
-0
未找到文件。
paddle/framework/backward.cc
浏览文件 @
d2c2f785
...
...
@@ -22,7 +22,7 @@ namespace paddle {
namespace
framework
{
template
<
typename
Map
,
typename
T
>
static
void
ForEachVarName
(
Map
&
names
,
T
callback
)
{
static
void
ForEachVarName
(
const
Map
&
names
,
T
callback
)
{
for
(
auto
&
name
:
names
)
{
for
(
auto
&
n
:
name
.
second
)
{
if
(
callback
(
n
))
return
;
...
...
@@ -43,7 +43,7 @@ static bool AllInSet(
static
std
::
shared_ptr
<
OperatorBase
>
NOP
()
{
auto
net_op
=
std
::
make_shared
<
operators
::
NetOp
>
();
net_op
->
type_
=
"@NOP@"
;
net_op
->
SetType
(
"@NOP@"
)
;
net_op
->
CompleteAddOp
();
return
net_op
;
}
...
...
@@ -69,15 +69,15 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
// If all input gradients of forwarding operator do not need to calculate,
// just return an NOP. Not return null ptr because NOP does not take
// too much time for calculation, but it is useful for simplifying logic.
if
(
AllInSet
(
forwardOp
.
inputs_
,
kGradVarSuffix
,
no_grad_names
))
{
if
(
AllInSet
(
forwardOp
.
Inputs
()
,
kGradVarSuffix
,
no_grad_names
))
{
return
NOP
();
}
// All output gradients of forwarding operator do not need to calculate.
// Then all input gradients cannot be computed at all, and we put them into
// `no_grad_names` set. Return an NOP.
if
(
AllInSet
(
forwardOp
.
outputs_
,
kGradVarSuffix
,
no_grad_names
))
{
ForEachVarName
(
forwardOp
.
inputs_
,
if
(
AllInSet
(
forwardOp
.
Outputs
()
,
kGradVarSuffix
,
no_grad_names
))
{
ForEachVarName
(
forwardOp
.
Inputs
()
,
[
&
no_grad_names
](
const
std
::
string
&
name
)
->
bool
{
no_grad_names
.
insert
(
GradVarName
(
name
));
return
false
;
...
...
@@ -103,7 +103,7 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
auto
fwd
=
*
it
;
auto
bwd
=
BackwardRecursive
(
*
fwd
,
no_grad_names
,
uniq_id
);
net
->
AddOp
(
bwd
);
ForEachVarName
(
bwd
->
outputs_
,
ForEachVarName
(
bwd
->
Outputs
()
,
[
&
dup_output_ops
,
local_op_id
](
const
std
::
string
&
out
)
{
dup_output_ops
[
out
].
emplace_back
(
local_op_id
);
return
false
;
...
...
@@ -144,13 +144,13 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
}
else
{
std
::
shared_ptr
<
OperatorBase
>
grad_op
=
OpRegistry
::
CreateGradOp
(
forwardOp
);
ForEachVarName
(
grad_op
->
inputs_
,
[
&
no_grad_names
,
&
net
](
std
::
string
&
grad_input
)
{
ForEachVarName
(
grad_op
->
Inputs
(),
[
&
no_grad_names
,
&
net
,
grad_op
](
const
std
::
string
&
grad_input
)
{
if
(
no_grad_names
.
count
(
grad_input
))
{
// +1 for \0
std
::
string
prefix
=
grad_input
.
substr
(
0
,
grad_input
.
size
()
-
sizeof
(
kGradVarSuffix
)
/
sizeof
(
char
)
+
1
);
grad_
input
=
prefix
+
kZeroVarSuffix
;
grad_
op
->
Rename
(
grad_input
,
prefix
+
kZeroVarSuffix
)
;
// If part of input gradient of that operator is not calculated, fill
// zero variables to that input gradient.
...
...
@@ -160,10 +160,10 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
return
false
;
});
ForEachVarName
(
grad_op
->
outputs_
,
[
&
no_grad_names
](
std
::
string
&
grad_output
)
{
ForEachVarName
(
grad_op
->
Outputs
()
,
[
&
no_grad_names
,
&
grad_op
](
const
std
::
string
&
grad_output
)
{
if
(
no_grad_names
.
count
(
grad_output
))
{
grad_o
utput
=
kEmptyVarName
;
grad_o
p
->
Rename
(
grad_output
,
kEmptyVarName
)
;
}
return
false
;
});
...
...
@@ -173,7 +173,7 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
}
net
->
AddOp
(
grad_op
);
}
net
->
type_
=
"@GENERATED_BACKWARD@"
;
net
->
SetType
(
"@GENERATED_BACKWARD@"
)
;
net
->
CompleteAddOp
();
return
net
;
}
...
...
paddle/framework/backward_test.cc
浏览文件 @
d2c2f785
...
...
@@ -173,8 +173,8 @@ TEST(Backward, simple_op_grad) {
"rowwise_add"
,
{{
"X"
,
{
"x"
}},
{
"b"
,
{
"b"
}}},
{{
"Out"
,
{
"out"
}}},
{});
ASSERT_NE
(
fwd
,
nullptr
);
auto
gop
=
f
::
OpRegistry
::
CreateGradOp
(
*
fwd
);
ASSERT_EQ
(
1UL
,
gop
->
inputs_
.
size
());
ASSERT_EQ
(
"rowwise_add_grad"
,
gop
->
type_
);
ASSERT_EQ
(
1UL
,
gop
->
Inputs
()
.
size
());
ASSERT_EQ
(
"rowwise_add_grad"
,
gop
->
Type
()
);
ASSERT_EQ
(
f
::
GradVarName
(
"x"
),
gop
->
Output
(
f
::
GradVarName
(
"X"
)));
ASSERT_EQ
(
f
::
GradVarName
(
"b"
),
gop
->
Output
(
f
::
GradVarName
(
"b"
)));
}
...
...
@@ -210,13 +210,13 @@ TEST(Backward, net_fc_backward_normal) {
ASSERT_EQ
(
3UL
,
net
->
ops_
.
size
());
f
::
OperatorBase
&
d_sigmoid
=
*
net
->
ops_
[
0
];
ASSERT_EQ
(
"sigmoid_grad"
,
d_sigmoid
.
type_
);
ASSERT_EQ
(
"sigmoid_grad"
,
d_sigmoid
.
Type
()
);
f
::
OperatorBase
&
d_add
=
*
net
->
ops_
[
1
];
ASSERT_EQ
(
"rowwise_add_grad"
,
d_add
.
type_
);
ASSERT_EQ
(
"rowwise_add_grad"
,
d_add
.
Type
()
);
f
::
OperatorBase
&
d_mul
=
*
net
->
ops_
[
2
];
ASSERT_EQ
(
"mul_grad"
,
d_mul
.
type_
);
ASSERT_EQ
(
"mul_grad"
,
d_mul
.
Type
()
);
}
TEST
(
Backward
,
net_fc_backward_not_have_b
)
{
...
...
@@ -236,10 +236,10 @@ TEST(Backward, net_fc_backward_not_have_b) {
ASSERT_EQ
(
2UL
,
net
->
ops_
.
size
());
f
::
OperatorBase
&
d_sigmoid
=
*
net
->
ops_
[
0
];
ASSERT_EQ
(
"sigmoid_grad"
,
d_sigmoid
.
type_
);
ASSERT_EQ
(
"sigmoid_grad"
,
d_sigmoid
.
Type
()
);
f
::
OperatorBase
&
d_mul
=
*
net
->
ops_
[
1
];
ASSERT_EQ
(
"mul_grad"
,
d_mul
.
type_
);
ASSERT_EQ
(
"mul_grad"
,
d_mul
.
Type
()
);
}
TEST
(
Backward
,
net_input_of_network_not_need_grad
)
{
...
...
@@ -293,7 +293,7 @@ TEST(Backward, net_shared_weight) {
ASSERT_TRUE
(
bwd
->
IsNetOp
());
auto
bwd_net
=
static_cast
<
ops
::
NetOp
*>
(
bwd
.
get
());
ASSERT_EQ
(
3UL
,
bwd_net
->
ops_
.
size
());
ASSERT_EQ
(
"add"
,
bwd_net
->
ops_
[
2
]
->
type_
);
ASSERT_EQ
(
"add"
,
bwd_net
->
ops_
[
2
]
->
Type
()
);
}
TEST
(
Backward
,
op_register_grad_not_for_network
)
{
...
...
@@ -334,15 +334,15 @@ TEST(Backward, op_part_of_output_are_not_need) {
ASSERT_EQ
(
net
->
ops_
.
size
(),
2UL
);
auto
&
fill_zero
=
*
net
->
ops_
[
0
];
ASSERT_EQ
(
"fill_zeros_like"
,
fill_zero
.
type_
);
ASSERT_EQ
(
"fill_zeros_like"
,
fill_zero
.
Type
()
);
ASSERT_EQ
(
1UL
,
fill_zero
.
Inputs
(
"Src"
).
size
());
ASSERT_EQ
(
"Z"
,
fill_zero
.
Input
(
"Src"
));
ASSERT_EQ
(
1UL
,
fill_zero
.
Outputs
(
"Dst"
).
size
());
ASSERT_EQ
(
std
::
string
(
"Z"
)
+
f
::
kZeroVarSuffix
,
fill_zero
.
Output
(
"Dst"
));
auto
&
d_many_out
=
*
net
->
ops_
[
1
];
ASSERT_EQ
(
"many_output_op_grad"
,
d_many_out
.
type_
);
ASSERT_EQ
(
1UL
+
2UL
+
2UL
,
d_many_out
.
inputs_
.
size
());
// I/O/OG
ASSERT_EQ
(
"many_output_op_grad"
,
d_many_out
.
Type
()
);
ASSERT_EQ
(
1UL
+
2UL
+
2UL
,
d_many_out
.
Inputs
()
.
size
());
// I/O/OG
ASSERT_EQ
(
std
::
string
(
"Z"
)
+
f
::
kZeroVarSuffix
,
d_many_out
.
Input
(
f
::
GradVarName
(
"z"
)));
ASSERT_EQ
(
f
::
GradVarName
(
"Y"
),
d_many_out
.
Input
(
f
::
GradVarName
(
"y"
)));
...
...
@@ -354,9 +354,9 @@ TEST(Backward, op_part_of_input_are_not_need) {
{{
"Out"
,
{
"out"
}}},
{});
auto
backward
=
f
::
Backward
(
*
fwd
,
{
"a"
});
auto
&
grad_mul
=
*
backward
;
ASSERT_EQ
(
grad_mul
.
type_
,
"mul_grad"
);
ASSERT_EQ
(
grad_mul
.
inputs_
.
size
(),
2UL
+
1UL
+
1UL
);
ASSERT_EQ
(
grad_mul
.
outputs_
.
size
(),
2UL
);
ASSERT_EQ
(
grad_mul
.
Type
()
,
"mul_grad"
);
ASSERT_EQ
(
grad_mul
.
Inputs
()
.
size
(),
2UL
+
1UL
+
1UL
);
ASSERT_EQ
(
grad_mul
.
Outputs
()
.
size
(),
2UL
);
ASSERT_EQ
(
grad_mul
.
Output
(
f
::
GradVarName
(
"X"
)),
f
::
kEmptyVarName
);
ASSERT_EQ
(
grad_mul
.
Output
(
f
::
GradVarName
(
"Y"
)),
f
::
GradVarName
(
"b"
));
ASSERT_EQ
(
grad_mul
.
Input
(
f
::
GradVarName
(
"Out"
)),
f
::
GradVarName
(
"out"
));
...
...
@@ -394,18 +394,18 @@ TEST(Backward, linear_net_intermediate_variable_has_no_grad) {
auto
&
grad_fc
=
*
bwd_net
->
ops_
[
0
];
const
char
*
all
=
paddle
::
operators
::
NetOp
::
kAll
;
EXPECT_EQ
(
grad_fc
.
inputs_
[
all
]
.
size
(),
EXPECT_EQ
(
grad_fc
.
Inputs
(
all
)
.
size
(),
2UL
/* external input number */
+
1UL
/* external output number*/
+
1UL
/* number of gradient of external output*/
+
2U
/* internal variable number*/
);
EXPECT_EQ
(
grad_fc
.
outputs_
[
all
]
.
size
(),
EXPECT_EQ
(
grad_fc
.
Outputs
(
all
)
.
size
(),
2UL
/* input number of mul*/
+
2UL
/* input number of rowwise_add
*/
+
1UL
/* input number of sigmod */
);
EXPECT_EQ
(
bwd_net
->
ops_
[
1
]
->
inputs_
[
all
]
.
size
(),
0UL
);
EXPECT_EQ
(
bwd_net
->
ops_
[
1
]
->
outputs_
[
all
]
.
size
(),
0UL
);
EXPECT_EQ
(
bwd_net
->
ops_
[
2
]
->
inputs_
[
all
]
.
size
(),
0UL
);
EXPECT_EQ
(
bwd_net
->
ops_
[
2
]
->
outputs_
[
all
]
.
size
(),
0UL
);
EXPECT_EQ
(
bwd_net
->
ops_
[
1
]
->
Inputs
(
all
)
.
size
(),
0UL
);
EXPECT_EQ
(
bwd_net
->
ops_
[
1
]
->
Outputs
(
all
)
.
size
(),
0UL
);
EXPECT_EQ
(
bwd_net
->
ops_
[
2
]
->
Inputs
(
all
)
.
size
(),
0UL
);
EXPECT_EQ
(
bwd_net
->
ops_
[
2
]
->
Outputs
(
all
)
.
size
(),
0UL
);
}
paddle/framework/operator.h
浏览文件 @
d2c2f785
...
...
@@ -121,6 +121,7 @@ class OperatorBase {
virtual
std
::
vector
<
std
::
string
>
OutputVars
(
bool
has_intermediate
)
const
;
const
std
::
string
&
Type
()
const
{
return
type_
;
}
void
SetType
(
const
std
::
string
&
type
)
{
type_
=
type
;
}
const
AttributeMap
&
Attrs
()
const
{
return
attrs_
;
}
protected:
...
...
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