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体验新版 GitCode,发现更多精彩内容 >>
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d96ee24f
编写于
8月 15, 2018
作者:
X
Xin Pan
提交者:
GitHub
8月 15, 2018
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差异文件
Merge pull request #12697 from panyx0718/ir2
test and doc IR Graph
上级
0a641ba3
891c3c0f
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
127 addition
and
1 deletion
+127
-1
paddle/fluid/framework/ir/graph.h
paddle/fluid/framework/ir/graph.h
+32
-0
paddle/fluid/framework/ir/graph_test.cc
paddle/fluid/framework/ir/graph_test.cc
+95
-1
未找到文件。
paddle/fluid/framework/ir/graph.h
浏览文件 @
d96ee24f
...
...
@@ -28,6 +28,38 @@ namespace paddle {
namespace
framework
{
namespace
ir
{
/*
* The graph is a Directed Acyclic Single Static Assignment Graph.
*
* In more detail, the following properties must hold:
*
* The graph shouldn't contain cycle. Each node is a black-box to the graph
* so the node itself could be a loop operator.
*
* Each Variable-type node has only one input (thus single static assignment).
*
* The output/input of operator is variable and the output/input of variable
* is operator.
*
* The following data harzards in Program are addressed in the Graph:
*
* Write-After-Read
* a = op1(x)
* x = op2(b)
* A control-dependency connection is created bettwen op1 and op2 such that
* op1->op2, so as to ensure correct order.
*
* Write-After-Write
* x = op1(a)
* x = op2(b)
* A control-dependency connection is created between op1 and op2 such that
* op1->op2, so as to ensure correct order.
*
* Other properties currently hold, but is not enforced yet:
*
* Variable-type node (not control dep) with the same variable name share
* the same underlying VarDesc.
*/
class
Graph
{
public:
explicit
Graph
(
const
ProgramDesc
&
program
);
...
...
paddle/fluid/framework/ir/graph_test.cc
浏览文件 @
d96ee24f
...
...
@@ -36,7 +36,7 @@ class SumOpMaker : public OpProtoAndCheckerMaker {
public:
void
Make
()
{
AddInput
(
"X"
,
""
).
AsDuplicable
();
AddOutput
(
"Out"
,
""
);
AddOutput
(
"Out"
,
""
)
.
AsDuplicable
()
;
AddComment
(
""
);
}
};
...
...
@@ -59,11 +59,27 @@ class SumOpVarTypeInference : public VarTypeInference {
block
->
Var
(
out_var_name
)
->
SetType
(
default_var_type
);
}
};
class
DummyOpMaker
:
public
OpProtoAndCheckerMaker
{
public:
void
Make
()
{
AddInput
(
"X"
,
""
).
AsDuplicable
();
AddOutput
(
"Out"
,
""
).
AsDuplicable
();
AddComment
(
""
);
}
};
class
DummyOpVarTypeInference
:
public
VarTypeInference
{
public:
void
operator
()(
const
OpDesc
&
op_desc
,
BlockDesc
*
block
)
const
override
{}
};
}
// namespace framework
}
// namespace paddle
REGISTER_OPERATOR
(
sum
,
paddle
::
framework
::
NOP
,
paddle
::
framework
::
SumOpMaker
,
paddle
::
framework
::
SumOpVarTypeInference
);
REGISTER_OPERATOR
(
dummy
,
paddle
::
framework
::
NOP
,
paddle
::
framework
::
SumOpMaker
,
paddle
::
framework
::
SumOpVarTypeInference
);
REGISTER_OPERATOR
(
sum_without_infer_var_type
,
paddle
::
framework
::
NOP
,
paddle
::
framework
::
SumOpMaker
);
...
...
@@ -110,5 +126,83 @@ TEST(GraphTest, Basic) {
}
ASSERT_EQ
(
nodes
.
size
(),
5
);
}
TEST
(
GraphTest
,
WriteAfterRead
)
{
// void Test() {
ProgramDesc
prog
;
auto
*
op
=
prog
.
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
"sum"
);
op
->
SetInput
(
"X"
,
{
"a"
});
op
->
SetOutput
(
"Out"
,
{
"b"
});
op
->
SetAttr
(
"op_role"
,
1
);
op
=
prog
.
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
"dummy"
);
op
->
SetInput
(
"X"
,
{
"c"
});
op
->
SetOutput
(
"Out"
,
{
"a"
});
op
->
SetAttr
(
"op_role"
,
1
);
prog
.
MutableBlock
(
0
)
->
Var
(
"a"
)
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
prog
.
MutableBlock
(
0
)
->
Var
(
"b"
)
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
prog
.
MutableBlock
(
0
)
->
Var
(
"c"
)
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
std
::
unique_ptr
<
ir
::
Graph
>
g
(
new
ir
::
Graph
(
prog
));
ir
::
Node
*
control_dep1
=
nullptr
;
ir
::
Node
*
control_dep2
=
nullptr
;
for
(
ir
::
Node
*
n
:
g
->
Nodes
())
{
if
(
n
->
Name
()
==
"sum"
)
{
ASSERT_EQ
(
n
->
outputs
[
0
]
->
Name
(),
"b"
);
ASSERT_TRUE
(
ir
::
IsControlDepVar
(
*
n
->
outputs
[
1
]));
control_dep1
=
n
->
outputs
[
1
];
ASSERT_EQ
(
n
->
outputs
.
size
(),
2
);
}
if
(
n
->
Name
()
==
"dummy"
)
{
ASSERT_EQ
(
n
->
inputs
[
0
]
->
Name
(),
"c"
);
ASSERT_TRUE
(
ir
::
IsControlDepVar
(
*
n
->
inputs
[
1
]));
control_dep2
=
n
->
inputs
[
1
];
ASSERT_EQ
(
n
->
inputs
.
size
(),
2
);
}
}
ASSERT_EQ
(
control_dep1
,
control_dep2
);
}
TEST
(
GraphTest
,
WriteAfterWrite
)
{
// void Test() {
ProgramDesc
prog
;
auto
*
op
=
prog
.
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
"sum"
);
op
->
SetInput
(
"X"
,
{
"a"
});
op
->
SetOutput
(
"Out"
,
{
"b"
});
op
->
SetAttr
(
"op_role"
,
1
);
op
=
prog
.
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
"dummy"
);
op
->
SetInput
(
"X"
,
{
"c"
});
op
->
SetOutput
(
"Out"
,
{
"b"
});
op
->
SetAttr
(
"op_role"
,
1
);
prog
.
MutableBlock
(
0
)
->
Var
(
"a"
)
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
prog
.
MutableBlock
(
0
)
->
Var
(
"b"
)
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
prog
.
MutableBlock
(
0
)
->
Var
(
"c"
)
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
std
::
unique_ptr
<
ir
::
Graph
>
g
(
new
ir
::
Graph
(
prog
));
ir
::
Node
*
control_dep1
=
nullptr
;
ir
::
Node
*
control_dep2
=
nullptr
;
for
(
ir
::
Node
*
n
:
g
->
Nodes
())
{
if
(
n
->
Name
()
==
"sum"
)
{
ASSERT_EQ
(
n
->
outputs
[
0
]
->
Name
(),
"b"
);
ASSERT_TRUE
(
ir
::
IsControlDepVar
(
*
n
->
outputs
[
1
]));
ASSERT_EQ
(
n
->
outputs
.
size
(),
2
);
control_dep1
=
n
->
outputs
[
1
];
}
if
(
n
->
Name
()
==
"dummy"
)
{
ASSERT_EQ
(
n
->
inputs
[
0
]
->
Name
(),
"c"
);
ASSERT_TRUE
(
ir
::
IsControlDepVar
(
*
n
->
inputs
[
1
]));
control_dep2
=
n
->
inputs
[
1
];
ASSERT_EQ
(
n
->
inputs
.
size
(),
2
);
ASSERT_EQ
(
control_dep1
,
control_dep2
);
}
}
}
}
// namespace framework
}
// namespace paddle
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