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dc06eaa0
编写于
7月 28, 2017
作者:
F
fengjiayi
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差异文件
Merge branch 'feature/backward' of
https://github.com/reyoung/Paddle
into feature/backward
上级
1de465b5
302046aa
变更
1
隐藏空白更改
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并排
Showing
1 changed file
with
17 addition
and
8 deletion
+17
-8
paddle/framework/backward_test.cc
paddle/framework/backward_test.cc
+17
-8
未找到文件。
paddle/framework/backward_test.cc
浏览文件 @
dc06eaa0
...
...
@@ -60,6 +60,16 @@ class SigmoidOpMaker : public OpProtoAndCheckerMaker {
}
};
class
NoGradOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
NoGradOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"X input"
);
AddOutput
(
"Y"
,
"Y output"
);
AddComment
(
"NoGradOp, same input output. no Grad"
);
}
};
class
FcOp
:
public
NetOp
{
public:
void
Init
()
override
{
...
...
@@ -139,6 +149,7 @@ REGISTER_OP(mul, f::EmptyOp, f::MulOpMaker);
REGISTER_GRADIENT_OP
(
mul
,
mul_grad
,
f
::
EmptyOp
);
REGISTER_OP
(
sigmoid
,
f
::
EmptyOp
,
f
::
SigmoidOpMaker
);
REGISTER_GRADIENT_OP
(
sigmoid
,
sigmoid_grad
,
f
::
EmptyOp
);
REGISTER_OP
(
nograd
,
f
::
EmptyOp
,
f
::
NoGradOpMaker
);
REGISTER_OP
(
fill_zeros_like
,
f
::
EmptyOp
,
f
::
FillZeroOpMaker
);
REGISTER_OP
(
add
,
f
::
EmptyOp
,
f
::
AddOpMaker
);
REGISTER_GRADIENT_OP
(
add
,
add_grad
,
f
::
EmptyOp
);
...
...
@@ -266,9 +277,11 @@ TEST(Backward, net_shared_weight) {
}
TEST
(
Backward
,
op_register_grad_not_for_network
)
{
auto
fwd
=
f
::
OpRegistry
::
CreateOp
(
"fc"
,
{
"X"
,
"W"
,
"b"
},
{
"Out"
,
"tmp_out"
},
{{
"temporary_index"
,
std
::
vector
<
int
>
{
1
}}});
// auto fwd =
// f::OpRegistry::CreateOp("fc", {"X", "W", "b"}, {"Out", "tmp_out"},
// {{"temporary_index", std::vector<int>{1}}});
auto
fwd
=
f
::
OpRegistry
::
CreateOp
(
"nograd"
,
{
"x"
},
{
"x"
},
{});
ASSERT_THROW
(
f
::
OpRegistry
::
CreateGradOp
(
*
fwd
),
EnforceNotMet
);
}
...
...
@@ -317,11 +330,7 @@ TEST(Backward, op_part_of_output_are_not_need) {
TEST(Backward, op_part_of_input_are_not_need) {
auto fwd = f::OpRegistry::CreateOp("mul", {"a", "b"}, {"out"}, {});
auto backward = f::Backward(*fwd, {"a"});
ASSERT_FALSE(backward->IsNetOp());
auto net = static_cast<f::NetOp *>(backward.get());
ASSERT_EQ(net->ops_.size(), 1UL);
auto &grad_mul = *net->ops_[0];
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);
...
...
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