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7e0801d4
编写于
12月 03, 2018
作者:
X
Xin Pan
提交者:
GitHub
12月 03, 2018
浏览文件
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差异文件
Merge pull request #14441 from baojun-nervana/intel/ngraph_op
Implementing ngraph engine
上级
96dc3d83
fc61bf1b
变更
11
隐藏空白更改
内联
并排
Showing
11 changed file
with
484 addition
and
48 deletion
+484
-48
cmake/external/ngraph.cmake
cmake/external/ngraph.cmake
+6
-12
cmake/inference_lib.cmake
cmake/inference_lib.cmake
+9
-0
paddle/fluid/framework/CMakeLists.txt
paddle/fluid/framework/CMakeLists.txt
+2
-1
paddle/fluid/framework/ngraph_bridge.cc
paddle/fluid/framework/ngraph_bridge.cc
+85
-3
paddle/fluid/framework/ngraph_bridge.h
paddle/fluid/framework/ngraph_bridge.h
+6
-8
paddle/fluid/framework/ngraph_operator.cc
paddle/fluid/framework/ngraph_operator.cc
+339
-8
paddle/fluid/framework/ngraph_operator.h
paddle/fluid/framework/ngraph_operator.h
+1
-6
paddle/fluid/framework/operator.cc
paddle/fluid/framework/operator.cc
+6
-0
paddle/fluid/framework/operator.h
paddle/fluid/framework/operator.h
+5
-0
paddle/fluid/inference/api/demo_ci/CMakeLists.txt
paddle/fluid/inference/api/demo_ci/CMakeLists.txt
+11
-1
python/setup.py.in
python/setup.py.in
+14
-9
未找到文件。
cmake/external/ngraph.cmake
浏览文件 @
7e0801d4
...
...
@@ -32,6 +32,8 @@ IF(NOT ${WITH_NGRAPH})
return
()
ENDIF
()
INCLUDE
(
GNUInstallDirs
)
INCLUDE
(
ExternalProject
)
SET
(
NGRAPH_PROJECT
"extern_ngraph"
)
...
...
@@ -40,10 +42,14 @@ SET(NGRAPH_GIT_TAG "f9fd9d4cc318dc59dd4b68448e7fbb5f67a28bd0")
SET
(
NGRAPH_SOURCES_DIR
${
THIRD_PARTY_PATH
}
/ngraph
)
SET
(
NGRAPH_INSTALL_DIR
${
THIRD_PARTY_PATH
}
/install/ngraph
)
SET
(
NGRAPH_INC_DIR
${
NGRAPH_INSTALL_DIR
}
/include
)
SET
(
NGRAPH_LIB_DIR
${
NGRAPH_INSTALL_DIR
}
/
${
CMAKE_INSTALL_LIBDIR
}
)
SET
(
NGRAPH_SHARED_LIB_NAME libngraph.so.
${
NGRAPH_VERSION
}
)
SET
(
NGRAPH_CPU_LIB_NAME libcpu_backend.so
)
SET
(
NGRAPH_TBB_LIB_NAME libtbb.so.2
)
SET
(
NGRAPH_GIT_REPO
"https://github.com/NervanaSystems/ngraph.git"
)
SET
(
NGRAPH_SHARED_LIB
${
NGRAPH_LIB_DIR
}
/
${
NGRAPH_SHARED_LIB_NAME
}
)
SET
(
NGRAPH_CPU_LIB
${
NGRAPH_LIB_DIR
}
/
${
NGRAPH_CPU_LIB_NAME
}
)
SET
(
NGRAPH_TBB_LIB
${
NGRAPH_LIB_DIR
}
/
${
NGRAPH_TBB_LIB_NAME
}
)
ExternalProject_Add
(
${
NGRAPH_PROJECT
}
...
...
@@ -63,18 +69,6 @@ ExternalProject_Add(
CMAKE_ARGS -DMKLDNN_LIB_DIR=
${
MKLDNN_INSTALL_DIR
}
/lib
)
if
(
UNIX AND NOT APPLE
)
include
(
GNUInstallDirs
)
SET
(
NGRAPH_LIB_DIR
${
NGRAPH_INSTALL_DIR
}
/
${
CMAKE_INSTALL_LIBDIR
}
)
else
()
SET
(
NGRAPH_LIB_DIR
${
NGRAPH_INSTALL_DIR
}
/lib
)
endif
()
MESSAGE
(
STATUS
"nGraph lib will be installed at:
${
NGRAPH_LIB_DIR
}
"
)
SET
(
NGRAPH_SHARED_LIB
${
NGRAPH_LIB_DIR
}
/
${
NGRAPH_SHARED_LIB_NAME
}
)
SET
(
NGRAPH_CPU_LIB
${
NGRAPH_LIB_DIR
}
/
${
NGRAPH_CPU_LIB_NAME
}
)
SET
(
NGRAPH_TBB_LIB
${
NGRAPH_LIB_DIR
}
/
${
NGRAPH_TBB_LIB_NAME
}
)
# Workaround for nGraph expecting mklml to be in mkldnn install directory.
ExternalProject_Add_Step
(
${
NGRAPH_PROJECT
}
...
...
cmake/inference_lib.cmake
浏览文件 @
7e0801d4
...
...
@@ -129,6 +129,15 @@ if (WITH_MKLDNN)
)
endif
()
if
(
WITH_NGRAPH
)
set
(
dst_dir
"
${
FLUID_INSTALL_DIR
}
/third_party/install/ngraph"
)
copy
(
ngraph_lib
SRCS
${
NGRAPH_INC_DIR
}
${
NGRAPH_LIB_DIR
}
DSTS
${
dst_dir
}
${
dst_dir
}
DEPS ngraph
)
endif
()
if
(
NOT WIN32
)
if
(
NOT MOBILE_INFERENCE AND NOT RPI
)
set
(
dst_dir
"
${
FLUID_INSTALL_DIR
}
/third_party/install/snappy"
)
...
...
paddle/fluid/framework/CMakeLists.txt
浏览文件 @
7e0801d4
...
...
@@ -127,8 +127,9 @@ cc_library(version SRCS version.cc)
cc_test
(
version_test SRCS version_test.cc DEPS version
)
cc_library
(
proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS shape_inference op_info operator glog version
)
cc_library
(
ngraph_bridge SRCS ngraph_bridge.cc DEPS operator framework_proto
)
if
(
NOT WIN32
)
cc_library
(
ngraph_bridge SRCS ngraph_bridge.cc DEPS operator framework_proto ngraph
)
cc_library
(
ngraph_operator SRCS ngraph_operator.cc DEPS ngraph_bridge operator op_info device_context tensor scope glog
shape_inference data_transform lod_tensor profiler
)
endif
(
NOT WIN32
)
...
...
paddle/fluid/framework/ngraph_bridge.cc
浏览文件 @
7e0801d4
...
...
@@ -15,23 +15,105 @@ limitations under the License. */
#ifdef PADDLE_WITH_NGRAPH
#include <algorithm>
#include <functional>
#include <vector>
#include "paddle/fluid/framework/ngraph_bridge.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/platform/enforce.h"
#include "ngraph/ngraph.hpp"
namespace
paddle
{
namespace
framework
{
static
std
::
shared_ptr
<
ngraph
::
Node
>
GetNode
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
,
const
std
::
string
prm
,
const
VariableNameMap
&
var_map
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
&
var_names
=
var_map
.
at
(
prm
);
PADDLE_ENFORCE_EQ
(
var_names
.
size
(),
1
,
"op %s prm %s expects one associated var"
,
op
->
Type
(),
prm
);
if
(
ngb_node_map
->
find
(
var_names
[
0
])
!=
ngb_node_map
->
end
())
{
return
(
*
ngb_node_map
)[
var_names
[
0
]];
}
else
{
return
nullptr
;
}
}
static
std
::
shared_ptr
<
ngraph
::
Node
>
GetInputNode
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
,
const
std
::
string
prm
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
return
GetNode
(
op
,
prm
,
op
->
Inputs
(),
ngb_node_map
);
}
static
std
::
shared_ptr
<
ngraph
::
Node
>
GetOutputNode
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
,
const
std
::
string
prm
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
return
GetNode
(
op
,
prm
,
op
->
Outputs
(),
ngb_node_map
);
}
static
void
SetOutputNode
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
,
const
std
::
string
prm
,
std
::
shared_ptr
<
ngraph
::
Node
>
node
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
&
var_names
=
op
->
Outputs
().
at
(
prm
);
if
(
var_names
.
size
()
==
1
)
{
(
*
ngb_node_map
)[
var_names
[
0
]]
=
node
;
}
else
if
(
var_names
.
size
()
==
0
)
{
(
*
ngb_node_map
)[
""
]
=
node
;
}
else
{
PADDLE_THROW
(
"prm %s has more than 1 var_names."
,
prm
);
}
}
static
bool
HasOutput
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
,
const
std
::
string
prm
)
{
auto
&
outputs
=
op
->
Outputs
();
if
(
outputs
.
find
(
prm
)
==
outputs
.
end
())
return
false
;
return
outputs
.
at
(
prm
).
size
()
>
0
;
}
template
<
typename
T
>
static
void
BuildBinaryNode
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
x
=
GetInputNode
(
op
,
"X"
,
ngb_node_map
);
auto
y
=
GetInputNode
(
op
,
"Y"
,
ngb_node_map
);
auto
out
=
std
::
make_shared
<
T
>
(
x
,
y
);
SetOutputNode
(
op
,
"Out"
,
out
,
ngb_node_map
);
}
template
<
typename
T
>
static
void
BuildUnaryNode
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
input
=
GetInputNode
(
op
,
"X"
,
ngb_node_map
);
auto
out
=
std
::
make_shared
<
T
>
(
input
);
SetOutputNode
(
op
,
"Out"
,
out
,
ngb_node_map
);
}
std
::
map
<
std
::
string
,
std
::
function
<
void
(
const
std
::
shared_ptr
<
OperatorBase
>&
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
)
>>
NgraphBridge
::
NG_NODE_MAP
=
{};
NgraphBridge
::
NG_NODE_MAP
=
{{
"relu"
,
BuildUnaryNode
<
ngraph
::
op
::
Relu
>
},
{
"tanh"
,
BuildUnaryNode
<
ngraph
::
op
::
Tanh
>
}};
void
NgraphBridge
::
build_graph
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
)
{
void
NgraphBridge
::
BuildNgNode
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
)
{
auto
&
op_type
=
op
->
Type
();
NG_NODE_MAP
[
op_type
](
op
,
ngb_node_map
);
NG_NODE_MAP
[
op_type
](
op
,
ngb_node_map
_
);
}
}
// namespace framework
...
...
paddle/fluid/framework/ngraph_bridge.h
浏览文件 @
7e0801d4
...
...
@@ -20,16 +20,14 @@ limitations under the License. */
#include <map>
#include <string>
#include <unordered_map>
#include <vector>
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/platform/enforce.h"
#include "ngraph/ngraph.hpp"
#include "ngraph/node.hpp"
namespace
paddle
{
namespace
framework
{
class
OperatorBase
;
class
NgraphBridge
{
public:
static
std
::
map
<
...
...
@@ -43,14 +41,14 @@ class NgraphBridge {
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
var_node_map
)
:
ngb_node_map
(
var_node_map
)
{}
:
ngb_node_map
_
(
var_node_map
)
{}
void
build_graph
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
);
void
BuildNgNode
(
const
std
::
shared_ptr
<
OperatorBase
>&
op
);
private:
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
;
ngb_node_map
_
;
};
}
// namespace framework
...
...
paddle/fluid/framework/ngraph_operator.cc
浏览文件 @
7e0801d4
...
...
@@ -19,14 +19,29 @@ limitations under the License. */
#include <map>
#include "paddle/fluid/framework/feed_fetch_type.h"
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/ngraph_bridge.h"
#include "paddle/fluid/framework/ngraph_operator.h"
#include "paddle/fluid/framework/
shape_inference
.h"
#include "paddle/fluid/framework/
tensor
.h"
#include "paddle/fluid/framework/var_desc.h"
#include "paddle/fluid/framework/var_type.h"
#include "ngraph/ngraph.hpp"
namespace
paddle
{
namespace
framework
{
static
ngraph
::
Shape
Ddim2Shape
(
const
DDim
&
dims
)
{
ngraph
::
Shape
sp
;
for
(
int
i
=
0
;
i
<
dims
.
size
();
++
i
)
{
int
k
=
dims
[
i
];
k
=
k
==
0
?
1
:
k
;
sp
.
push_back
(
k
);
}
return
sp
;
}
static
std
::
map
<
proto
::
VarType
::
Type
,
ngraph
::
element
::
Type
>
pd2ng_type_map
=
{
{
proto
::
VarType
::
FP32
,
ngraph
::
element
::
f32
},
{
proto
::
VarType
::
FP64
,
ngraph
::
element
::
f64
},
...
...
@@ -42,6 +57,7 @@ typedef enum { /* nGraph support state on ops */
PARTIAL_TEST
/* Support partial list of ops for test */
}
op_state
;
// perform graph build through bridge and execute computation
class
NgraphOperator
{
public:
explicit
NgraphOperator
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
,
...
...
@@ -59,13 +75,23 @@ class NgraphOperator {
persistables_
(
persist
),
fetches_
(
fetches
),
post_op_inputs_
(
post_op_inputs
),
ng_op_state_
(
ng_op_state
)
{}
ng_op_state_
(
ng_op_state
)
{
var_in_node_map_
=
std
::
make_shared
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
();
var_node_map_
=
std
::
make_shared
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
();
BuildNgIO
();
GetNgFunction
();
}
void
Run
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
;
private:
static
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Function
>>
func_cache
;
func_cache
_
;
const
Scope
&
scope_
;
const
platform
::
Place
&
place_
;
std
::
vector
<
std
::
shared_ptr
<
OperatorBase
>>
fused_ops_
;
...
...
@@ -74,6 +100,35 @@ class NgraphOperator {
std
::
unordered_set
<
std
::
string
>
fetches_
;
std
::
unordered_set
<
std
::
string
>
post_op_inputs_
;
op_state
ng_op_state_
;
// ngraph backend eg. CPU
static
std
::
shared_ptr
<
ngraph
::
runtime
::
Backend
>
backend_
;
// ngraph function to call and execute
std
::
shared_ptr
<
ngraph
::
Function
>
ngraph_function_
;
// var_name of inputs
std
::
vector
<
std
::
string
>
var_in_
;
// var_name of outputs from fetch in order
std
::
vector
<
std
::
string
>
var_out_
;
// map input vars to nodes
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
var_in_node_map_
;
// map each var name with a ngraph node
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
var_node_map_
;
// cache key to check if function is cached
std
::
shared_ptr
<
std
::
string
>
GetCacheKey
();
// get ngraph input and define ngraph input parameters
void
GetNgInputShape
(
std
::
shared_ptr
<
OperatorBase
>
op
);
// Call ngraph bridge to map ops
void
BuildNgNodes
();
// get the ngraph input and output var list
void
BuildNgIO
();
// build ngraph function call
void
BuildNgFunction
();
// Check cache for ngraph function or otherwise build the function
void
GetNgFunction
();
};
std
::
vector
<
std
::
vector
<
std
::
vector
<
std
::
unique_ptr
<
OperatorBase
>>::
iterator
>>
...
...
@@ -86,7 +141,7 @@ FusedOperator::FusedOpIntervals(
}
size_t
size
=
ops
->
size
();
size_t
left
=
0
;
while
(
left
<
size
&&
ops
.
at
(
left
)
->
Type
()
!=
kFeedOpType
)
{
while
(
left
<
size
&&
ops
->
at
(
left
)
->
Type
()
!=
kFeedOpType
)
{
++
left
;
}
if
(
left
==
size
)
{
...
...
@@ -116,7 +171,7 @@ FusedOperator::FusedOpIntervals(
size_t
start
=
pivot
,
end
=
start
;
while
(
pivot
<
right
&&
(
paddle
::
framework
::
NgraphBridge
::
NG_NODE_MAP
.
find
(
ops
.
at
(
pivot
)
->
Type
())
!=
ops
->
at
(
pivot
)
->
Type
())
!=
paddle
::
framework
::
NgraphBridge
::
NG_NODE_MAP
.
end
()))
{
++
pivot
;
++
end
;
...
...
@@ -136,7 +191,9 @@ FusedOperator::FusedOperator(
std
::
vector
<
std
::
unique_ptr
<
OperatorBase
>>::
iterator
end
,
const
std
::
string
&
type
,
const
VariableNameMap
&
inputs
,
const
VariableNameMap
&
outputs
,
const
AttributeMap
&
attrs
)
:
OperatorBase
(
type
,
inputs
,
outputs
,
attrs
),
pdesc
(
prog
),
block
(
block_id
)
{
:
OperatorBase
(
type
,
inputs
,
outputs
,
attrs
),
pdesc_
(
prog
),
block_
(
block_id
)
{
for
(
std
::
vector
<
std
::
unique_ptr
<
OperatorBase
>>::
iterator
it
=
start
;
it
!=
end
;
++
it
)
{
fused_ops_
.
push_back
(
std
::
move
(
*
it
));
...
...
@@ -152,7 +209,7 @@ FusedOperator::FusedOperator(
}
if
((
*
(
start
-
1
))
->
Type
()
==
kFeedOpType
&&
(
*
end
)
->
Type
()
==
kFetchOpType
)
{
is_
complete
=
true
;
is_
full_
=
true
;
}
Process
();
...
...
@@ -205,7 +262,7 @@ void FusedOperator::RunImpl(const Scope& scope,
}
}
if
(
is_full
)
{
if
(
is_full
_
)
{
ng_op_state
=
ng_op_state
==
PARTIAL_TEST
?
FULL_TEST
:
FULL_TRAIN
;
}
...
...
@@ -215,6 +272,280 @@ void FusedOperator::RunImpl(const Scope& scope,
ngraph_op
.
Run
(
scope
,
place
);
}
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Function
>>
NgraphOperator
::
func_cache_
=
{};
std
::
shared_ptr
<
ngraph
::
runtime
::
Backend
>
NgraphOperator
::
backend_
=
ngraph
::
runtime
::
Backend
::
create
(
"CPU"
);
void
NgraphOperator
::
GetNgInputShape
(
std
::
shared_ptr
<
OperatorBase
>
op
)
{
op
->
RuntimeInferShape
(
scope_
,
place_
);
for
(
auto
&
var_name_item
:
op
->
Inputs
())
{
for
(
auto
&
var_name
:
var_name_item
.
second
)
{
auto
*
var
=
scope_
.
FindVar
(
var_name
);
if
(
var
&&
var
->
IsType
<
LoDTensor
>
())
{
auto
*
tensor_pd
=
GetLoDTensorOrSelectedRowsValueFromVar
(
*
var
);
auto
sp
=
Ddim2Shape
(
tensor_pd
->
dims
());
if
(
std
::
find
(
var_in_
.
begin
(),
var_in_
.
end
(),
var_name
)
!=
var_in_
.
end
())
{
if
(
var_node_map_
->
find
(
var_name
)
==
var_node_map_
->
end
())
{
auto
ng_type
=
var_type_map_
.
at
(
var_name
);
auto
prm
=
std
::
make_shared
<
ngraph
::
op
::
Parameter
>
(
ng_type
,
sp
,
true
);
(
*
var_node_map_
)[
var_name
]
=
prm
;
(
*
var_in_node_map_
)[
var_name
]
=
prm
;
}
}
}
}
}
}
void
NgraphOperator
::
BuildNgNodes
()
{
for
(
auto
&
var_name
:
var_out_
)
{
if
(
var_node_map_
->
find
(
var_name
)
==
var_node_map_
->
end
())
{
auto
*
var
=
scope_
.
FindVar
(
var_name
);
if
(
var
&&
var
->
IsType
<
LoDTensor
>
())
{
auto
*
tensor_pd
=
GetLoDTensorOrSelectedRowsValueFromVar
(
*
var
);
auto
&
ddim
=
tensor_pd
->
dims
();
auto
ng_shape
=
Ddim2Shape
(
ddim
);
auto
ng_type
=
var_type_map_
.
at
(
var_name
);
auto
prm
=
std
::
make_shared
<
ngraph
::
op
::
Parameter
>
(
ng_type
,
ng_shape
,
true
);
(
*
var_node_map_
)[
var_name
]
=
prm
;
}
}
}
paddle
::
framework
::
NgraphBridge
ngb
(
var_node_map_
);
for
(
auto
&
op
:
fused_ops_
)
{
ngb
.
BuildNgNode
(
op
);
}
}
void
NgraphOperator
::
BuildNgIO
()
{
std
::
unordered_set
<
std
::
string
>
inputs
;
std
::
unordered_set
<
std
::
string
>
outputs
;
for
(
auto
&
op
:
fused_ops_
)
{
for
(
auto
&
var_name_item
:
op
->
Inputs
())
{
for
(
auto
&
var_name
:
var_name_item
.
second
)
{
inputs
.
insert
(
var_name
);
const
bool
is_output
=
outputs
.
find
(
var_name
)
!=
outputs
.
end
();
if
(
!
is_output
&&
std
::
find
(
var_in_
.
begin
(),
var_in_
.
end
(),
var_name
)
==
var_in_
.
end
())
{
// fill var_in here to keep lhs and rhs order
var_in_
.
push_back
(
var_name
);
}
}
}
if
(
op
->
Type
()
!=
"fill_constant"
)
{
GetNgInputShape
(
op
);
}
for
(
auto
&
var_name_item
:
op
->
Outputs
())
{
PADDLE_ENFORCE_LE
(
var_name_item
.
second
.
size
(),
1
,
"op %s has more than 1 output - Not handling yet"
,
op
->
Type
());
for
(
auto
&
var_name
:
var_name_item
.
second
)
{
outputs
.
insert
(
var_name
);
}
}
}
// var_out.clear();
for
(
auto
&
op
:
fused_ops_
)
{
for
(
auto
&
var_name_item
:
op
->
Outputs
())
{
PADDLE_ENFORCE_LE
(
var_name_item
.
second
.
size
(),
1
,
"op %s has more than 1 output - Not handling yet"
,
op
->
Type
());
for
(
auto
&
var_name
:
var_name_item
.
second
)
{
switch
(
ng_op_state_
)
{
case
PARTIAL_TEST
:
if
(
post_op_inputs_
.
find
(
var_name
)
!=
post_op_inputs_
.
end
()
||
fetches_
.
find
(
var_name
)
!=
fetches_
.
end
())
{
var_out_
.
push_back
(
var_name
);
}
break
;
case
FULL_TEST
:
if
(
fetches_
.
find
(
var_name
)
!=
fetches_
.
end
())
{
var_out_
.
push_back
(
var_name
);
}
break
;
case
PARTIAL_TRAIN
:
if
(
fetches_
.
find
(
var_name
)
!=
fetches_
.
end
()
||
post_op_inputs_
.
find
(
var_name
)
!=
post_op_inputs_
.
end
()
||
persistables_
.
find
(
var_name
)
!=
persistables_
.
end
())
{
var_out_
.
push_back
(
var_name
);
}
break
;
case
FULL_TRAIN
:
if
(
fetches_
.
find
(
var_name
)
!=
fetches_
.
end
()
||
persistables_
.
find
(
var_name
)
!=
persistables_
.
end
())
{
var_out_
.
push_back
(
var_name
);
}
break
;
default:
var_out_
.
push_back
(
var_name
);
}
}
}
}
}
void
NgraphOperator
::
BuildNgFunction
()
{
BuildNgNodes
();
ngraph_function_
=
nullptr
;
ngraph
::
NodeVector
func_outputs
;
ngraph
::
op
::
ParameterVector
func_inputs
;
for
(
auto
&
vo
:
var_out_
)
{
func_outputs
.
push_back
(
var_node_map_
->
at
(
vo
));
}
for
(
auto
&
vi
:
var_in_
)
{
std
::
shared_ptr
<
ngraph
::
op
::
Parameter
>
prm
=
std
::
dynamic_pointer_cast
<
ngraph
::
op
::
Parameter
>
(
var_in_node_map_
->
at
(
vi
));
func_inputs
.
push_back
(
prm
);
}
ngraph_function_
=
std
::
make_shared
<
ngraph
::
Function
>
(
func_outputs
,
func_inputs
);
}
std
::
shared_ptr
<
std
::
string
>
NgraphOperator
::
GetCacheKey
()
{
auto
cache_key
=
std
::
make_shared
<
std
::
string
>
(
""
);
*
cache_key
+=
std
::
to_string
(
fused_ops_
.
size
());
for
(
auto
&
op
:
fused_ops_
)
{
*
cache_key
+=
op
->
Type
();
}
for
(
auto
&
var_name
:
var_in_
)
{
auto
shape
=
var_node_map_
->
at
(
var_name
)
->
get_shape
();
*
cache_key
+=
var_name
;
*
cache_key
+=
var_type_map_
.
at
(
var_name
).
c_type_string
();
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
*
cache_key
+=
std
::
to_string
(
shape
.
at
(
i
));
}
}
for
(
auto
&
var_name
:
var_out_
)
{
auto
*
var
=
scope_
.
FindVar
(
var_name
);
if
(
var
&&
var
->
IsType
<
LoDTensor
>
())
{
auto
*
tensor_pd
=
GetLoDTensorOrSelectedRowsValueFromVar
(
*
var
);
auto
&
ddim
=
tensor_pd
->
dims
();
for
(
int
i
=
0
;
i
<
ddim
.
size
();
++
i
)
{
*
cache_key
+=
std
::
to_string
(
ddim
[
i
]);
}
}
}
return
cache_key
;
}
void
NgraphOperator
::
GetNgFunction
()
{
bool
cache_on
=
true
;
if
(
cache_on
)
{
std
::
string
cache_key_val
=
*
GetCacheKey
();
if
(
func_cache_
.
find
(
cache_key_val
)
!=
func_cache_
.
end
())
{
ngraph_function_
=
func_cache_
.
at
(
cache_key_val
);
}
else
{
BuildNgFunction
();
func_cache_
[
cache_key_val
]
=
ngraph_function_
;
}
}
else
{
BuildNgFunction
();
}
}
void
NgraphOperator
::
Run
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
{
std
::
vector
<
std
::
shared_ptr
<
ngraph
::
runtime
::
Tensor
>>
t_in
;
std
::
vector
<
std
::
shared_ptr
<
ngraph
::
runtime
::
Tensor
>>
t_out
;
for
(
size_t
i
=
0
;
i
<
var_in_
.
size
();
++
i
)
{
auto
vi
=
var_in_
.
at
(
i
);
auto
sp
=
var_node_map_
->
at
(
vi
)
->
get_shape
();
std
::
shared_ptr
<
ngraph
::
runtime
::
Tensor
>
ti
;
auto
*
var
=
scope
.
FindVar
(
vi
);
if
(
var
&&
var
->
IsType
<
LoDTensor
>
())
{
auto
*
tensor_pd
=
GetLoDTensorOrSelectedRowsValueFromVar
(
*
var
);
PADDLE_ENFORCE
(
sp
==
Ddim2Shape
(
tensor_pd
->
dims
()),
"Ensure ngraph tensor layout align with paddle tensor"
);
if
(
tensor_pd
->
type
().
hash_code
()
==
typeid
(
float
).
hash_code
())
{
// NOLINT
const
float
*
arr
=
tensor_pd
->
data
<
float
>
();
ti
=
backend_
->
create_tensor
(
ngraph
::
element
::
f32
,
sp
,
const_cast
<
float
*>
(
arr
));
}
else
if
(
tensor_pd
->
type
().
hash_code
()
==
typeid
(
int
).
hash_code
())
{
// NOLINT
const
int
*
arr
=
tensor_pd
->
data
<
int
>
();
ti
=
backend_
->
create_tensor
(
ngraph
::
element
::
i32
,
sp
,
const_cast
<
int
*>
(
arr
));
}
else
if
(
tensor_pd
->
type
().
hash_code
()
==
typeid
(
int64_t
).
hash_code
())
{
const
int64_t
*
arr
=
tensor_pd
->
data
<
int64_t
>
();
ti
=
backend_
->
create_tensor
(
ngraph
::
element
::
i64
,
sp
,
const_cast
<
int64_t
*>
(
arr
));
}
else
if
(
tensor_pd
->
type
().
hash_code
()
==
typeid
(
double
).
hash_code
())
{
// NOLINT
const
double
*
arr
=
tensor_pd
->
data
<
double
>
();
ti
=
backend_
->
create_tensor
(
ngraph
::
element
::
f64
,
sp
,
const_cast
<
double
*>
(
arr
));
}
else
if
(
tensor_pd
->
type
().
hash_code
()
==
typeid
(
bool
).
hash_code
())
{
// NOLINT
const
bool
*
arr
=
tensor_pd
->
data
<
bool
>
();
ti
=
backend_
->
create_tensor
(
ngraph
::
element
::
boolean
,
sp
,
const_cast
<
bool
*>
(
arr
));
}
else
{
PADDLE_THROW
(
"Data type not handling for var %s"
,
vi
);
}
}
else
{
PADDLE_THROW
(
"Cannot find var or tensor with var name %s"
,
vi
);
}
bool
is_test
=
(
ng_op_state_
==
PARTIAL_TEST
||
ng_op_state_
==
FULL_TEST
)
?
true
:
false
;
bool
is_persistable
=
(
persistables_
.
find
(
vi
)
!=
persistables_
.
end
())
?
true
:
false
;
if
(
is_test
&&
is_persistable
)
{
ti
->
set_stale
(
false
);
}
t_in
.
push_back
(
ti
);
}
for
(
size_t
i
=
0
;
i
<
var_out_
.
size
();
++
i
)
{
auto
var_name
=
var_out_
[
i
];
auto
*
var
=
scope
.
FindVar
(
var_name
);
std
::
shared_ptr
<
ngraph
::
runtime
::
Tensor
>
to
;
if
(
var
&&
var
->
IsType
<
LoDTensor
>
())
{
auto
*
tensor_pd
=
GetMutableLoDTensorOrSelectedRowsValueFromVar
(
var
);
auto
dd
=
tensor_pd
->
dims
();
ngraph
::
Shape
sp
=
Ddim2Shape
(
dd
);
auto
ng_type
=
var_type_map_
.
at
(
var_name
);
if
(
ng_type
==
ngraph
::
element
::
f32
)
{
auto
pd_arr
=
tensor_pd
->
mutable_data
<
float
>
(
place
);
to
=
backend_
->
create_tensor
(
ngraph
::
element
::
f32
,
sp
,
pd_arr
);
}
else
if
(
ng_type
==
ngraph
::
element
::
i64
)
{
auto
pd_arr
=
tensor_pd
->
mutable_data
<
int64_t
>
(
place
);
to
=
backend_
->
create_tensor
(
ngraph
::
element
::
i64
,
sp
,
pd_arr
);
}
else
if
(
ng_type
==
ngraph
::
element
::
f64
)
{
auto
pd_arr
=
tensor_pd
->
mutable_data
<
double
>
(
place
);
to
=
backend_
->
create_tensor
(
ngraph
::
element
::
f64
,
sp
,
pd_arr
);
}
else
if
(
ng_type
==
ngraph
::
element
::
boolean
)
{
auto
pd_arr
=
tensor_pd
->
mutable_data
<
bool
>
(
place
);
to
=
backend_
->
create_tensor
(
ngraph
::
element
::
boolean
,
sp
,
pd_arr
);
}
else
{
PADDLE_THROW
(
"Data type not handled in for var %s"
,
var_name
);
}
t_out
.
push_back
(
to
);
}
else
{
PADDLE_THROW
(
"Cannot find var or tensor with var name %s"
,
var_name
);
}
}
backend_
->
call
(
ngraph_function_
,
t_out
,
t_in
);
}
// NgraphOperator::RunImpl
}
// namespace framework
}
// namespace paddle
#endif
paddle/fluid/framework/ngraph_operator.h
浏览文件 @
7e0801d4
...
...
@@ -17,24 +17,19 @@ limitations under the License. */
#ifdef PADDLE_WITH_NGRAPH
#include <algorithm>
#include <atomic>
#include <string>
#include <unordered_map>
#include <vector>
#include "paddle/fluid/framework/attribute.h"
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/ngraph_bridge.h"
#include "paddle/fluid/framework/op_info.h"
#include "paddle/fluid/framework/op_kernel_type.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/platform/variant.h"
#include "ngraph/
ngraph
.hpp"
#include "ngraph/
type/element_type
.hpp"
namespace
paddle
{
namespace
framework
{
...
...
paddle/fluid/framework/operator.cc
浏览文件 @
7e0801d4
...
...
@@ -695,6 +695,12 @@ static void CheckTensorNANOrInf(const std::string& name,
"Tensor %s contains NAN"
,
name
);
}
void
OperatorWithKernel
::
RuntimeInferShape
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
{
RuntimeInferShapeContext
infer_shape_ctx
(
*
this
,
scope
);
this
->
InferShape
(
&
infer_shape_ctx
);
}
void
OperatorWithKernel
::
RunImpl
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
{
RuntimeInferShapeContext
infer_shape_ctx
(
*
this
,
scope
);
...
...
paddle/fluid/framework/operator.h
浏览文件 @
7e0801d4
...
...
@@ -128,6 +128,8 @@ class OperatorBase {
virtual
std
::
vector
<
std
::
string
>
OutputVars
(
bool
has_intermediate
)
const
;
void
SetIsCalledByExecutor
(
bool
x
)
{
run_by_executor_
=
x
;
}
virtual
void
RuntimeInferShape
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
{}
protected:
std
::
string
type_
;
...
...
@@ -348,6 +350,9 @@ class OperatorWithKernel : public OperatorBase {
OpInfoMap
::
Instance
().
Get
(
Type
()).
infer_shape_
(
ctx
);
}
void
RuntimeInferShape
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
override
;
protected:
virtual
OpKernelType
GetExpectedKernelType
(
const
ExecutionContext
&
ctx
)
const
;
virtual
OpKernelType
GetKernelTypeForVar
(
...
...
paddle/fluid/inference/api/demo_ci/CMakeLists.txt
浏览文件 @
7e0801d4
...
...
@@ -79,6 +79,16 @@ link_directories("${PADDLE_LIB}/third_party/install/gflags/lib")
link_directories
(
"
${
PADDLE_LIB
}
/third_party/install/xxhash/lib"
)
link_directories
(
"
${
PADDLE_LIB
}
/paddle/lib"
)
if
(
NOT WIN32
)
set
(
NGRAPH_PATH
"
${
PADDLE_LIB
}
/third_party/install/ngraph"
)
if
(
EXISTS
${
NGRAPH_PATH
}
)
include
(
GNUInstallDirs
)
include_directories
(
"
${
NGRAPH_PATH
}
/include"
)
link_directories
(
"
${
NGRAPH_PATH
}
/
${
CMAKE_INSTALL_LIBDIR
}
"
)
set
(
NGRAPH_LIB
${
NGRAPH_PATH
}
/
${
CMAKE_INSTALL_LIBDIR
}
/libngraph
${
CMAKE_SHARED_LIBRARY_SUFFIX
}
)
endif
()
endif
()
add_executable
(
${
DEMO_NAME
}
${
DEMO_NAME
}
.cc
)
if
(
WITH_MKL
)
...
...
@@ -106,7 +116,7 @@ endif()
if
(
NOT WIN32
)
set
(
EXTERNAL_LIB
"-lrt -ldl -lpthread"
)
set
(
DEPS
${
DEPS
}
${
MATH_LIB
}
${
MKLDNN_LIB
}
${
MATH_LIB
}
${
MKLDNN_LIB
}
${
NGRAPH_LIB
}
glog gflags protobuf snappystream snappy z xxhash
${
EXTERNAL_LIB
}
)
else
()
...
...
python/setup.py.in
浏览文件 @
7e0801d4
...
...
@@ -165,9 +165,9 @@ if '${WITH_MKL}' == 'ON':
shutil.copy('${MKLML_LIB}', libs_path)
shutil.copy('${MKLML_IOMP_LIB}', libs_path)
package_data['paddle.libs']+=['libmklml_intel' + ext_name,'libiomp5' + ext_name]
if '${
CMAKE_BUILD_TYPE}' == 'Release
':
# only change rpath in Release mode.
if '${WITH_MKLDNN}' == 'ON':
if '${
WITH_MKLDNN}' == 'ON
':
if '${CMAKE_BUILD_TYPE}' == 'Release':
# only change rpath in Release mode.
# TODO(typhoonzero): use install_name_tool to patch mkl libs once
# we can support mkl on mac.
#
...
...
@@ -177,14 +177,19 @@ if '${CMAKE_BUILD_TYPE}' == 'Release':
command = "patchelf --set-rpath '$ORIGIN/' ${MKLDNN_SHARED_LIB}"
if os.system(command) != 0:
raise Exception("patch libmkldnn.so failed, command: %s" % command)
package_data['paddle.libs']+=['libmkldnn.so.0']
shutil.copy('${MKLDNN_SHARED_LIB}', libs_path)
package_data['paddle.libs']+=['libmkldnn.so.0']
shutil.copy('${MKLDNN_SHARED_LIB}', libs_path)
if '${WITH_NGRAPH}' == 'ON':
# only change rpath in Release mode,
# since in Debug mode, nGraph lib may be too large to be changed?
if '${CMAKE_BUILD_TYPE}' == 'Release':
# only change rpath in Release mode.
command = "patchelf --set-rpath '$ORIGIN/' ${NGRAPH_SHARED_LIB}"
if os.system(command) != 0:
raise Exception("patch ${NGRAPH_SHARED_LIB_NAME} failed, command: %s" % command)
if os.name != 'nt':
if "@APPLE@" == "1":
command = "install_name_tool -id \"@loader_path/\" ${NGRAPH_SHARED_LIB}"
else:
command = "patchelf --set-rpath '$ORIGIN/' ${NGRAPH_SHARED_LIB}"
if os.system(command) != 0:
raise Exception("patch ${NGRAPH_SHARED_LIB_NAME} failed, command: %s" % command)
shutil.copy('${NGRAPH_SHARED_LIB}', libs_path)
shutil.copy('${NGRAPH_CPU_LIB}', libs_path)
shutil.copy('${NGRAPH_TBB_LIB}', libs_path)
...
...
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