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体验新版 GitCode,发现更多精彩内容 >>
提交
80de7e5e
编写于
8月 15, 2017
作者:
Q
Qiao Longfei
提交者:
GitHub
8月 15, 2017
浏览文件
操作
浏览文件
下载
差异文件
Merge pull request #3460 from jacquesqiao/public_to_protected
change operator public to protected
上级
973618b6
219f7a46
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
63 addition
and
61 deletion
+63
-61
paddle/framework/backward.cc
paddle/framework/backward.cc
+14
-14
paddle/framework/backward_test.cc
paddle/framework/backward_test.cc
+20
-20
paddle/framework/grad_op_builder.cc
paddle/framework/grad_op_builder.cc
+7
-8
paddle/framework/grad_op_builder_test.cc
paddle/framework/grad_op_builder_test.cc
+6
-6
paddle/framework/operator.h
paddle/framework/operator.h
+5
-2
paddle/framework/pybind.cc
paddle/framework/pybind.cc
+4
-4
paddle/operators/net_op.cc
paddle/operators/net_op.cc
+2
-2
paddle/operators/net_op_test.cc
paddle/operators/net_op_test.cc
+2
-2
paddle/operators/recurrent_op.cc
paddle/operators/recurrent_op.cc
+3
-3
未找到文件。
paddle/framework/backward.cc
浏览文件 @
80de7e5e
...
...
@@ -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
;
...
...
@@ -44,7 +44,7 @@ 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
;
}
...
...
@@ -70,8 +70,8 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
std
::
unordered_set
<
std
::
string
>&
no_grad_names
,
size_t
&
uniq_id
)
{
// 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
// much time for calculation, but it is useful for simplifying logic.
if
(
AllInSet
(
forwardOp
.
inputs_
/*names*/
,
kGradVarSuffix
/*suffix*/
,
//
too
much time for calculation, but it is useful for simplifying logic.
if
(
AllInSet
(
forwardOp
.
Inputs
()
/*names*/
,
kGradVarSuffix
/*suffix*/
,
no_grad_names
/*set*/
))
{
return
NOP
();
}
...
...
@@ -79,9 +79,9 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
// 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_
/*names*/
,
kGradVarSuffix
/*suffix*/
,
if
(
AllInSet
(
forwardOp
.
Outputs
()
/*names*/
,
kGradVarSuffix
/*suffix*/
,
no_grad_names
/*set*/
))
{
ForEachVarName
(
forwardOp
.
inputs_
,
ForEachVarName
(
forwardOp
.
Inputs
()
,
[
&
no_grad_names
](
const
std
::
string
&
name
)
->
bool
{
no_grad_names
.
insert
(
GradVarName
(
name
));
return
false
;
...
...
@@ -107,7 +107,7 @@ 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
;
...
...
@@ -154,13 +154,13 @@ 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.
...
...
@@ -170,10 +170,10 @@ 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
;
});
...
...
@@ -183,7 +183,7 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
}
net
->
AddOp
(
grad_op
);
}
net
->
type_
=
"@GENERATED_BACKWARD@"
;
net
->
SetType
(
"@GENERATED_BACKWARD@"
)
;
net
->
CompleteAddOp
();
return
net
;
}
// namespace framework
...
...
paddle/framework/backward_test.cc
浏览文件 @
80de7e5e
...
...
@@ -164,8 +164,8 @@ 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"
)));
}
...
...
@@ -201,13 +201,13 @@ 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
)
{
...
...
@@ -227,10 +227,10 @@ 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
)
{
...
...
@@ -284,7 +284,7 @@ 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
)
{
...
...
@@ -325,15 +325,15 @@ 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"
)));
...
...
@@ -345,9 +345,9 @@ 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"
));
...
...
@@ -385,18 +385,18 @@ 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/grad_op_builder.cc
浏览文件 @
80de7e5e
...
...
@@ -13,7 +13,6 @@ express or implied. See the License for the specific language governing
permissions and limitations under the License. */
#include "paddle/framework/grad_op_builder.h"
#include "paddle/framework/framework.pb.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
...
...
@@ -23,9 +22,9 @@ enum class OpArgType { IN, OUT };
static
void
TransOpArg
(
const
OperatorBase
*
src_op
,
const
OpArgType
&
src_type
,
bool
is_grad
,
OperatorBase
::
VarNameMap
*
vars
)
{
const
auto
&
src_inout
=
src_type
==
OpArgType
::
IN
?
src_op
->
inputs_
:
src_op
->
outputs_
;
src_type
==
OpArgType
::
IN
?
src_op
->
Inputs
()
:
src_op
->
Outputs
()
;
auto
&
dst_inout
=
*
vars
;
const
OpProto
*
proto
=
OpRegistry
::
op_info_map
().
at
(
src_op
->
type_
).
proto_
;
const
OpProto
*
proto
=
OpRegistry
::
op_info_map
().
at
(
src_op
->
Type
()
).
proto_
;
const
auto
&
src_arg_list
=
src_type
==
OpArgType
::
IN
?
proto
->
inputs
()
:
proto
->
outputs
();
for
(
const
auto
&
arg
:
src_arg_list
)
{
...
...
@@ -41,14 +40,14 @@ static void TransOpArg(const OperatorBase* src_op, const OpArgType& src_type,
}
OperatorBase
*
BuildGradOp
(
const
OperatorBase
*
op
)
{
auto
it
=
OpRegistry
::
op_info_map
().
find
(
op
->
type_
);
auto
it
=
OpRegistry
::
op_info_map
().
find
(
op
->
Type
()
);
PADDLE_ENFORCE
(
it
!=
OpRegistry
::
op_info_map
().
end
(),
"'%s' has not been registered."
,
op
->
type_
);
"'%s' has not been registered."
,
op
->
Type
()
);
PADDLE_ENFORCE
(
it
->
second
.
proto_
!=
nullptr
,
"'%s' has no OpProto."
,
op
->
type_
);
op
->
Type
()
);
std
::
string
grad_op_type
=
it
->
second
.
grad_op_type_
;
PADDLE_ENFORCE
(
!
grad_op_type
.
empty
(),
"'%s' has no gradient operator."
,
op
->
type_
);
op
->
Type
()
);
OperatorBase
::
VarNameMap
inputs
;
OperatorBase
::
VarNameMap
outputs
;
...
...
@@ -60,7 +59,7 @@ OperatorBase* BuildGradOp(const OperatorBase* op) {
it
=
OpRegistry
::
op_info_map
().
find
(
grad_op_type
);
PADDLE_ENFORCE
(
it
!=
OpRegistry
::
op_info_map
().
end
(),
"'%s' has not been registered."
,
grad_op_type
);
return
it
->
second
.
creator_
(
grad_op_type
,
inputs
,
outputs
,
op
->
attrs_
);
return
it
->
second
.
creator_
(
grad_op_type
,
inputs
,
outputs
,
op
->
Attrs
()
);
}
}
// namespace framework
...
...
paddle/framework/grad_op_builder_test.cc
浏览文件 @
80de7e5e
...
...
@@ -44,8 +44,8 @@ TEST(GradOpBuilder, AddTwo) {
"add_two"
,
{{
"X"
,
{
"x"
}},
{
"Y"
,
{
"y"
}}},
{{
"Out"
,
{
"out"
}}},
{}));
std
::
shared_ptr
<
f
::
OperatorBase
>
grad_add_op
=
f
::
OpRegistry
::
CreateGradOp
(
*
add_op
);
EXPECT_EQ
(
grad_add_op
->
inputs_
.
size
(),
4UL
);
EXPECT_EQ
(
grad_add_op
->
outputs_
.
size
(),
2UL
);
EXPECT_EQ
(
grad_add_op
->
Inputs
()
.
size
(),
4UL
);
EXPECT_EQ
(
grad_add_op
->
Outputs
()
.
size
(),
2UL
);
EXPECT_EQ
(
grad_add_op
->
Input
(
"X"
),
"x"
);
EXPECT_EQ
(
grad_add_op
->
Input
(
"Y"
),
"y"
);
EXPECT_EQ
(
grad_add_op
->
Input
(
"Out"
),
"out"
);
...
...
@@ -66,7 +66,7 @@ TEST(GradOpBuilder, MutiInOut) {
std
::
shared_ptr
<
f
::
OperatorBase
>
grad_test_op
=
f
::
OpRegistry
::
CreateGradOp
(
*
test_op
);
ASSERT_EQ
(
grad_test_op
->
inputs_
.
size
(),
3UL
+
2UL
+
2UL
);
ASSERT_EQ
(
grad_test_op
->
Inputs
()
.
size
(),
3UL
+
2UL
+
2UL
);
EXPECT_EQ
(
grad_test_op
->
Input
(
"In1"
),
"in1"
);
EXPECT_EQ
(
grad_test_op
->
Inputs
(
"In2_mult"
),
std
::
vector
<
std
::
string
>
({
"in2_1"
,
"in2_2"
,
"in2_3"
}));
...
...
@@ -80,7 +80,7 @@ TEST(GradOpBuilder, MutiInOut) {
std
::
vector
<
std
::
string
>
(
{
f
::
GradVarName
(
"out2_1"
),
f
::
GradVarName
(
"out2_2"
)}));
ASSERT_EQ
(
grad_test_op
->
outputs_
.
size
(),
3UL
);
ASSERT_EQ
(
grad_test_op
->
Outputs
()
.
size
(),
3UL
);
EXPECT_EQ
(
grad_test_op
->
Output
(
f
::
GradVarName
(
"In1"
)),
f
::
GradVarName
(
"in1"
));
EXPECT_EQ
(
grad_test_op
->
Outputs
(
f
::
GradVarName
(
"In2_mult"
)),
std
::
vector
<
std
::
string
>
({
f
::
GradVarName
(
"in2_1"
),
...
...
@@ -99,7 +99,7 @@ TEST(GradOpBuilder, IOIgnoredInGradient) {
f
::
OpRegistry
::
CreateGradOp
(
*
test_op
);
// 'In2' and 'Out2' are ignored in gradient calculating
ASSERT_EQ
(
grad_test_op
->
inputs_
.
size
(),
2UL
+
1UL
+
2UL
);
ASSERT_EQ
(
grad_test_op
->
Inputs
()
.
size
(),
2UL
+
1UL
+
2UL
);
EXPECT_EQ
(
grad_test_op
->
Input
(
"In1"
),
"in1"
);
EXPECT_EQ
(
grad_test_op
->
Inputs
(
"In3_mult"
),
std
::
vector
<
std
::
string
>
({
"in3_1"
,
"in3_2"
}));
...
...
@@ -111,7 +111,7 @@ TEST(GradOpBuilder, IOIgnoredInGradient) {
EXPECT_EQ
(
grad_test_op
->
Input
(
f
::
GradVarName
(
"Out2"
)),
f
::
GradVarName
(
"out2"
));
ASSERT_EQ
(
grad_test_op
->
outputs_
.
size
(),
3UL
);
ASSERT_EQ
(
grad_test_op
->
Outputs
()
.
size
(),
3UL
);
EXPECT_EQ
(
grad_test_op
->
Output
(
f
::
GradVarName
(
"In1"
)),
f
::
GradVarName
(
"in1"
));
EXPECT_EQ
(
grad_test_op
->
Outputs
(
f
::
GradVarName
(
"In2_mult"
)),
std
::
vector
<
std
::
string
>
(
...
...
paddle/framework/operator.h
浏览文件 @
80de7e5e
...
...
@@ -97,6 +97,8 @@ class OperatorBase {
/// rename inputs outputs name
void
Rename
(
const
std
::
string
&
old_name
,
const
std
::
string
&
new_name
);
const
VarNameMap
&
Inputs
()
const
{
return
inputs_
;
}
const
VarNameMap
&
Outputs
()
const
{
return
outputs_
;
}
//! Get a input with argument's name described in `op_proto`
const
std
::
string
&
Input
(
const
std
::
string
&
name
)
const
;
//! Get a input which has multiple variables.
...
...
@@ -110,10 +112,11 @@ class OperatorBase {
virtual
std
::
vector
<
std
::
string
>
OutputVars
(
bool
has_intermediate
)
const
;
std
::
string
Type
()
const
{
return
type_
;
}
const
std
::
string
&
Type
()
const
{
return
type_
;
}
void
SetType
(
const
std
::
string
&
type
)
{
type_
=
type
;
}
const
AttributeMap
&
Attrs
()
const
{
return
attrs_
;
}
p
ublic
:
p
rotected
:
std
::
string
type_
;
// NOTE: in case of OpGrad, inputs_ contains:
// I (Inputs)
...
...
paddle/framework/pybind.cc
浏览文件 @
80de7e5e
...
...
@@ -53,15 +53,15 @@ void ExposeOperator(ClassType &m) {
.
def
(
"run"
,
&
ClassType
::
type
::
Run
)
.
def
(
"type"
,
[](
const
typename
ClassType
::
type
&
op
)
->
std
::
string
{
return
op
.
type_
;
return
op
.
Type
()
;
})
.
def
(
"outputs"
,
[](
const
typename
ClassType
::
type
&
op
)
->
std
::
map
<
std
::
string
,
std
::
vector
<
std
::
string
>>
{
return
op
.
outputs_
;
return
op
.
Outputs
()
;
})
.
def
(
"inputs"
,
[](
const
typename
ClassType
::
type
&
op
)
{
return
op
.
inputs_
;
})
[](
const
typename
ClassType
::
type
&
op
)
{
return
op
.
Inputs
()
;
})
.
def
(
"__str__"
,
&
ClassType
::
type
::
DebugString
)
.
def
(
"no_intermediate_outputs"
,
[](
const
typename
ClassType
::
type
&
op
)
{
...
...
@@ -232,7 +232,7 @@ All parameter, weight, gradient are variables in Paddle.
net
.
def_static
(
"create"
,
[]()
->
std
::
shared_ptr
<
operators
::
NetOp
>
{
auto
retv
=
std
::
make_shared
<
operators
::
NetOp
>
();
retv
->
type_
=
"plain_net"
;
retv
->
SetType
(
"plain_net"
)
;
return
retv
;
})
.
def
(
"add_op"
,
&
operators
::
NetOp
::
AddOp
)
...
...
paddle/operators/net_op.cc
浏览文件 @
80de7e5e
...
...
@@ -29,7 +29,7 @@ void NetOp::CompleteAddOp(bool calc) {
std
::
set
<
std
::
string
>
input_set
;
std
::
set
<
std
::
string
>
output_set
;
for
(
auto
&
op
:
ops_
)
{
for
(
auto
&
ipt
:
op
->
inputs_
)
{
for
(
auto
&
ipt
:
op
->
Inputs
()
)
{
for
(
auto
&
var_name
:
ipt
.
second
)
{
if
(
!
Contains
(
output_set
,
var_name
))
{
// Not other op's output
input_set
.
insert
(
var_name
);
...
...
@@ -39,7 +39,7 @@ void NetOp::CompleteAddOp(bool calc) {
}
}
for
(
auto
&
opt
:
op
->
outputs_
)
{
for
(
auto
&
opt
:
op
->
Outputs
()
)
{
for
(
auto
&
var_name
:
opt
.
second
)
{
output_set
.
insert
(
var_name
);
}
...
...
paddle/operators/net_op_test.cc
浏览文件 @
80de7e5e
...
...
@@ -49,8 +49,8 @@ TEST(OpKernel, all) {
net
->
CompleteAddOp
();
AssertSameVectorWithoutOrder
({
"x"
,
"w1"
,
"b1"
,
"w2"
,
"b2"
},
net
->
inputs_
.
at
(
NetOp
::
kAll
));
AssertSameVectorWithoutOrder
({
"y"
,
"z"
},
net
->
outputs_
.
at
(
NetOp
::
kAll
));
net
->
Inputs
(
NetOp
::
kAll
));
AssertSameVectorWithoutOrder
({
"y"
,
"z"
},
net
->
Outputs
(
NetOp
::
kAll
));
auto
final_outs
=
net
->
OutputVars
(
false
);
...
...
paddle/operators/recurrent_op.cc
浏览文件 @
80de7e5e
...
...
@@ -82,14 +82,14 @@ void RecurrentAlgorithm::CreateScopes(const Scope& scope) const {
PADDLE_ENFORCE
(
net_var
!=
nullptr
,
"no stepnet called %s in scope"
,
arg_
->
step_net
);
auto
net_op
=
net_var
->
GetMutable
<
NetOp
>
();
PADDLE_ENFORCE
(
!
net_op
->
outputs_
.
empty
(),
"net_op has no outputs"
);
PADDLE_ENFORCE
(
!
net_op
->
Outputs
()
.
empty
(),
"net_op has no outputs"
);
if
(
seq_len_
>
step_scopes
->
size
())
{
for
(
size_t
i
=
step_scopes
->
size
();
i
<
seq_len_
;
++
i
)
{
auto
&
step_scope
=
scope
.
NewScope
();
// create step net's temp inputs
for
(
auto
&
input
:
net_op
->
inputs_
)
{
for
(
auto
&
input
:
net_op
->
Inputs
()
)
{
// the weight are located in parent scope
for
(
auto
&
var_name
:
input
.
second
)
{
if
(
!
step_scope
.
FindVar
(
var_name
))
{
...
...
@@ -98,7 +98,7 @@ void RecurrentAlgorithm::CreateScopes(const Scope& scope) const {
}
}
// create stepnet's outputs
for
(
const
auto
&
output
:
net_op
->
outputs_
)
{
for
(
const
auto
&
output
:
net_op
->
Outputs
()
)
{
for
(
auto
&
var_name
:
output
.
second
)
{
step_scope
.
NewVar
(
var_name
);
}
...
...
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