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16eaaf3f
编写于
9月 12, 2018
作者:
T
Tomasz Patejko
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
MKLDNN conv + elementwise_add fusion: added one more UT, found and corrected bugs in pass
上级
604bad08
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
104 addition
and
48 deletion
+104
-48
paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.cc
...uid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.cc
+16
-25
paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass_tester.cc
...mework/ir/conv_elementwise_add_mkldnn_fuse_pass_tester.cc
+88
-23
未找到文件。
paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.cc
浏览文件 @
16eaaf3f
...
...
@@ -45,17 +45,13 @@ struct Conv {
->
assert_is_op
(
"conv2d"
);
auto
input_var
=
pattern
->
new_node
(
input_name
())
->
AsInput
()
->
assert_is_op_input
(
conv_name
());
->
assert_is_op_input
(
conv_name
(),
input_name
());
auto
filter_var
=
pattern
->
new_node
(
filter_name
())
->
AsInput
()
->
assert_is_persistable_var
()
->
assert_is_op_input
(
conv_name
());
->
assert_is_op_input
(
conv_name
(),
filter_name
());
auto
output_var
=
pattern
->
new_node
(
output_name
())
->
AsOutput
()
->
assert_is_op_output
(
conv_name
());
->
assert_is_op_output
(
conv_name
(),
output_name
());
conv_op
->
LinksFrom
({
input_var
,
filter_var
});
conv_op
->
LinksTo
({
output_var
});
...
...
@@ -77,19 +73,13 @@ struct ElementwiseAdd {
->
assert_is_op
(
"elementwise_add"
);
auto
y_var
=
pattern
->
new_node
(
y_name
())
->
AsInput
()
->
assert_is_op_input
(
elementwise_add_name
());
->
assert_is_op_input
(
elementwise_add_name
(),
y_name
());
conv_output
->
assert_is_op_input
(
pattern
->
node_name
(
elementwise_add_name
()),
pattern
->
node_name
(
x_name
()));
// auto y_var = pattern->NewNode(y_name())
// ->AsInput()
// ->assert_is_op_input(elementwise_add_name());
conv_output
->
assert_is_op_input
(
elementwise_add_name
(),
x_name
());
auto
out_var
=
pattern
->
new_node
(
out_name
())
->
AsOutput
()
->
assert_is_op_output
(
pattern
->
node_name
(
elementwise_add_name
()));
->
assert_is_op_output
(
elementwise_add_name
(),
out_name
());
elementwise_add_op
->
LinksFrom
({
y_var
,
conv_output
});
elementwise_add_op
->
LinksTo
({
out_var
});
...
...
@@ -118,16 +108,16 @@ graph_ptr ConvElementwiseAddMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
GraphPatternDetector
gpd
;
auto
pattern
=
gpd
.
mutable_pattern
();
auto
pattern_ptr
=
std
::
make_shared
<
patterns
::
Pattern
>
(
pattern
,
name_scope_
);
patterns
::
Conv
conv_pattern
;
auto
conv_output
=
conv_pattern
(
pattern_ptr
)();
conv_output
->
AsIntermediate
();
patterns
::
ElementwiseAdd
elementwise_add_pattern
;
elementwise_add_pattern
(
pattern_ptr
)(
conv_output
);
conv_output
->
AsIntermediate
();
auto
link_nodes_to
=
[](
Node
*
a
,
Node
*
b
)
{
a
->
outputs
.
push_back
(
b
);
b
->
inputs
.
push_back
(
a
);
...
...
@@ -139,7 +129,7 @@ graph_ptr ConvElementwiseAddMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
op_desc
.
SetInput
(
"Input"
,
{
conv_input
->
Name
()});
op_desc
.
SetInput
(
"Filter"
,
{
conv_filter
->
Name
()});
op_desc
.
SetOutput
(
"Ouput"
,
{
y
->
Name
()});
op_desc
.
SetOutput
(
"Ou
t
put"
,
{
y
->
Name
()});
op_desc
.
SetAttr
(
"fuse_sum"
,
true
);
...
...
@@ -155,16 +145,17 @@ graph_ptr ConvElementwiseAddMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
};
auto
handler
=
[
&
](
const
GraphPatternDetector
::
subgraph_t
&
subgraph
,
Graph
*
g
)
{
auto
elementwise_add_x
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
x_name
());
auto
elementwise_add_y
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
y_name
());
auto
elementwise_add_out
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
out_name
());
auto
conv_filter
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
filter_name
());
auto
conv_op
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
conv_name
());
auto
conv_input
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
input_name
());
auto
conv_filter
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
filter_name
());
auto
conv_output
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
output_name
());
auto
elementwise_add_op
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
elementwise_add_name
());
auto
elementwise_add_y
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
y_name
());
auto
elementwise_add_out
=
node_from_subgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
out_name
());
fuse_conv
(
g
,
conv_input
,
conv_filter
,
elementwise_add_y
);
remove_unused_nodes
(
g
,
{
elementwise_add_x
,
conv_output
,
elementwise_add_out
});
remove_unused_nodes
(
g
,
{
conv_output
,
elementwise_add_out
,
conv_op
,
elementwise_add_op
});
};
gpd
(
graph
.
get
(),
handler
);
...
...
paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass_tester.cc
浏览文件 @
16eaaf3f
...
...
@@ -16,7 +16,7 @@ void SetOp(ProgramDesc* prog, const std::string& type,
op
->
SetAttr
(
"use_mkldnn"
,
true
);
op
->
SetInput
(
"Input"
,
{
inputs
[
0
]});
op
->
SetInput
(
"Filter"
,
{
inputs
[
1
]});
op
->
Set
Input
(
"Output"
,
{
outputs
}
);
op
->
Set
Output
(
"Output"
,
outputs
);
}
else
if
(
type
==
"elementwise_add"
)
{
op
->
SetInput
(
"X"
,
{
inputs
[
0
]});
op
->
SetInput
(
"Y"
,
{
inputs
[
1
]});
...
...
@@ -24,54 +24,119 @@ void SetOp(ProgramDesc* prog, const std::string& type,
}
}
ProgramDesc
BuildProgramDesc
()
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"c"
,
"d"
,
"weights"
,
"f"
,
"g"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
if
(
v
==
"weights"
||
v
==
"bias"
)
{
var
->
SetPersistable
(
true
);
TEST
(
ConvElementwiseAddMKLDNNFusePass
,
ConvolutionWithElementwiseAddWithOps
)
{
auto
build_program_desc
=
[
&
]()
->
ProgramDesc
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"weights"
,
"c"
,
"d"
,
"e"
,
"f"
,
"g"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
if
(
v
==
"weights"
||
v
==
"bias"
)
{
var
->
SetPersistable
(
true
);
}
}
}
SetOp
(
&
prog
,
"OP0"
,
{
"a"
},
{
"b"
});
SetOp
(
&
prog
,
"OP1"
,
{
"c"
},
{
"d"
});
SetOp
(
&
prog
,
"conv2d"
,
{
"d"
,
"weights"
},
{
"f"
});
SetOp
(
&
prog
,
"elemenwise_add"
,
{
"d"
,
"f"
},
{
"g"
});
SetOp
(
&
prog
,
"OP0"
,
{
"a"
},
{
"b"
});
SetOp
(
&
prog
,
"OP1"
,
{
"c"
},
{
"d"
});
SetOp
(
&
prog
,
"conv2d"
,
{
"b"
,
"weights"
},
{
"e"
});
SetOp
(
&
prog
,
"elementwise_add"
,
{
"e"
,
"d"
},
{
"f"
});
SetOp
(
&
prog
,
"OP3"
,
{
"f"
},
{
"g"
});
return
prog
;
};
return
prog
;
auto
prog
=
build_program_desc
();
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
prog
));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_elementwise_add_mkldnn_fuse_pass"
);
int
original_nodes_num
=
graph
->
Nodes
().
size
();
graph
=
pass
->
Apply
(
std
::
move
(
graph
));
int
current_nodes_num
=
graph
->
Nodes
().
size
();
EXPECT_EQ
(
original_nodes_num
-
4
+
1
,
current_nodes_num
);
// Assert conv_relu op in newly generated graph
int
conv_count
=
0
;
int
elementwise_add_count
=
0
;
for
(
auto
*
node
:
graph
->
Nodes
())
{
if
(
node
->
IsOp
()
&&
node
->
Op
()
->
Type
()
==
"conv2d"
)
{
++
conv_count
;
}
if
(
node
->
IsOp
()
&&
node
->
Op
()
->
Type
()
==
"elementwise_add"
)
{
++
elementwise_add_count
;
}
/*
if (node->Op()->HasAttr("use_mkldnn")) {
bool use_mkldnn = boost::get<bool>(node->Op()->GetAttr("use_mkldnn"));
if (use_mkldnn) {
if (node->Op()->HasAttr("fuse_sum")) {
// bool fuse_sum = boost::get<bool>(node->Op()->GetAttr("fuse_sum"));
if (fuse_sum) {
++conv_elementwise_add_count;
}
}
}
}
}
*/
}
EXPECT_EQ
(
conv_count
,
1
);
EXPECT_EQ
(
elementwise_add_count
,
0
);
}
TEST
(
ConvElementwiseAddMKLDNNFusePass
,
basic
)
{
auto
prog
=
BuildProgramDesc
();
TEST
(
ConvElementwiseAddMKLDNNFusePass
,
OnlyConvolutionElementwiseAdd
)
{
auto
build_program_desc
=
[
&
]()
->
ProgramDesc
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"weights"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
if
(
v
==
"weights"
||
v
==
"bias"
)
{
var
->
SetPersistable
(
true
);
}
}
SetOp
(
&
prog
,
"conv2d"
,
{
"a"
,
"weights"
},
{
"b"
});
SetOp
(
&
prog
,
"elementwise_add"
,
{
"b"
,
"c"
},
{
"d"
});
return
prog
;
};
auto
prog
=
build_program_desc
();
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
prog
));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_elementwise_add_mkldnn_fuse_pass"
);
int
original_nodes_num
=
graph
->
Nodes
().
size
();
graph
=
pass
->
Apply
(
std
::
move
(
graph
));
int
current_nodes_num
=
graph
->
Nodes
().
size
();
EXPECT_EQ
(
original_nodes_num
-
2
,
current_nodes_num
);
EXPECT_EQ
(
original_nodes_num
-
4
+
1
,
current_nodes_num
);
// Assert conv_relu op in newly generated graph
int
conv_elementwise_add_count
=
0
;
int
conv_count
=
0
;
int
elementwise_add_count
=
0
;
for
(
auto
*
node
:
graph
->
Nodes
())
{
if
(
node
->
IsOp
()
&&
node
->
Op
()
->
Type
()
==
"conv2d"
)
{
++
conv_count
;
}
if
(
node
->
IsOp
()
&&
node
->
Op
()
->
Type
()
==
"elementwise_add"
)
{
++
elementwise_add_count
;
}
/*
if (node->Op()->HasAttr("use_mkldnn")) {
bool use_mkldnn = boost::get<bool>(node->Op()->GetAttr("use_mkldnn"));
if (use_mkldnn) {
// TODO tpatejko: it is commented because convolution does not support this attribute
if
(
true
/*node->Op()->HasAttr("fuse_sum")*/
)
{
if (node->Op()->HasAttr("fuse_sum")) {
// bool fuse_sum = boost::get<bool>(node->Op()->GetAttr("fuse_sum"));
if
(
true
/*fuse_sum*/
)
{
if (
fuse_sum
) {
++conv_elementwise_add_count;
}
}
}
}
}
*/
}
EXPECT_EQ
(
conv_elementwise_add_count
,
1
);
EXPECT_EQ
(
conv_count
,
1
);
EXPECT_EQ
(
elementwise_add_count
,
0
);
}
}
// namespace ir
...
...
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