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415f5006
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PaddleDetection
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415f5006
编写于
6年前
作者:
X
Xin Pan
提交者:
Qiao Longfei
6年前
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Merge pull request #14103 from jacquesqiao/cpu-for-1.1-merge-with-shape
test=release/1.1 [1.1] Cpu for 1.1 merge with shape
上级
043f450a
变更
39
隐藏空白更改
内联
并排
Showing
39 changed file
with
1012 addition
and
545 deletion
+1012
-545
paddle/fluid/framework/attribute.cc
paddle/fluid/framework/attribute.cc
+7
-0
paddle/fluid/framework/attribute.h
paddle/fluid/framework/attribute.h
+115
-82
paddle/fluid/framework/details/broadcast_op_handle.cc
paddle/fluid/framework/details/broadcast_op_handle.cc
+4
-0
paddle/fluid/framework/details/multi_devices_graph_pass.cc
paddle/fluid/framework/details/multi_devices_graph_pass.cc
+2
-1
paddle/fluid/framework/framework.proto
paddle/fluid/framework/framework.proto
+2
-0
paddle/fluid/framework/op_desc.cc
paddle/fluid/framework/op_desc.cc
+7
-0
paddle/fluid/framework/parallel_executor.cc
paddle/fluid/framework/parallel_executor.cc
+4
-0
paddle/fluid/framework/type_defs.h
paddle/fluid/framework/type_defs.h
+1
-1
paddle/fluid/operators/fake_init_op.cc
paddle/fluid/operators/fake_init_op.cc
+86
-0
paddle/fluid/operators/fill_constant_op.cc
paddle/fluid/operators/fill_constant_op.cc
+5
-4
paddle/fluid/operators/gaussian_random_op.cc
paddle/fluid/operators/gaussian_random_op.cc
+4
-4
paddle/fluid/operators/listen_and_serv_op.cc
paddle/fluid/operators/listen_and_serv_op.cc
+10
-3
paddle/fluid/operators/lookup_table_op.cc
paddle/fluid/operators/lookup_table_op.cc
+1
-1
paddle/fluid/operators/math/selected_rows_functor.cc
paddle/fluid/operators/math/selected_rows_functor.cc
+85
-34
paddle/fluid/operators/math/selected_rows_functor.cu
paddle/fluid/operators/math/selected_rows_functor.cu
+74
-2
paddle/fluid/operators/math/selected_rows_functor.h
paddle/fluid/operators/math/selected_rows_functor.h
+3
-98
paddle/fluid/operators/math/selected_rows_functor_test.cc
paddle/fluid/operators/math/selected_rows_functor_test.cc
+60
-0
paddle/fluid/operators/math/selected_rows_functor_test.cu
paddle/fluid/operators/math/selected_rows_functor_test.cu
+64
-0
paddle/fluid/operators/merge_ids_op.cc
paddle/fluid/operators/merge_ids_op.cc
+19
-12
paddle/fluid/operators/merge_ids_op.h
paddle/fluid/operators/merge_ids_op.h
+54
-41
paddle/fluid/operators/split_ids_op.cc
paddle/fluid/operators/split_ids_op.cc
+42
-11
paddle/fluid/operators/split_ids_op.h
paddle/fluid/operators/split_ids_op.h
+30
-8
paddle/fluid/operators/split_selected_rows_op.cc
paddle/fluid/operators/split_selected_rows_op.cc
+3
-3
paddle/fluid/operators/split_selected_rows_op.h
paddle/fluid/operators/split_selected_rows_op.h
+5
-5
paddle/fluid/operators/sum_op.h
paddle/fluid/operators/sum_op.h
+37
-62
paddle/fluid/operators/uniform_random_op.cc
paddle/fluid/operators/uniform_random_op.cc
+3
-3
paddle/fluid/operators/uniform_random_op.cu
paddle/fluid/operators/uniform_random_op.cu
+1
-1
paddle/fluid/pybind/protobuf.cc
paddle/fluid/pybind/protobuf.cc
+14
-0
python/paddle/fluid/__init__.py
python/paddle/fluid/__init__.py
+3
-0
python/paddle/fluid/op.py
python/paddle/fluid/op.py
+2
-0
python/paddle/fluid/tests/unittests/test_dist_ctr.py
python/paddle/fluid/tests/unittests/test_dist_ctr.py
+1
-0
python/paddle/fluid/tests/unittests/test_dist_simnet_bow.py
python/paddle/fluid/tests/unittests/test_dist_simnet_bow.py
+1
-3
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
+31
-28
python/paddle/fluid/tests/unittests/test_fake_init_op.py
python/paddle/fluid/tests/unittests/test_fake_init_op.py
+52
-0
python/paddle/fluid/tests/unittests/test_merge_ids_op.py
python/paddle/fluid/tests/unittests/test_merge_ids_op.py
+22
-9
python/paddle/fluid/tests/unittests/test_split_ids_op.py
python/paddle/fluid/tests/unittests/test_split_ids_op.py
+7
-4
python/paddle/fluid/tests/unittests/test_split_selected_rows_op.py
...ddle/fluid/tests/unittests/test_split_selected_rows_op.py
+4
-4
python/paddle/fluid/tests/unittests/test_sum_op.py
python/paddle/fluid/tests/unittests/test_sum_op.py
+46
-22
python/paddle/fluid/transpiler/distribute_transpiler.py
python/paddle/fluid/transpiler/distribute_transpiler.py
+101
-99
未找到文件。
paddle/fluid/framework/attribute.cc
浏览文件 @
415f5006
...
...
@@ -64,6 +64,13 @@ Attribute GetAttrValue(const proto::OpDesc::Attr& attr_desc) {
case
proto
::
AttrType
::
LONG
:
{
return
attr_desc
.
l
();
}
case
proto
::
AttrType
::
LONGS
:
{
std
::
vector
<
int64_t
>
val
(
attr_desc
.
longs_size
());
for
(
int
i
=
0
;
i
<
attr_desc
.
longs_size
();
++
i
)
{
val
[
i
]
=
attr_desc
.
longs
(
i
);
}
return
val
;
}
default:
PADDLE_THROW
(
"Unsupport attr type %d"
,
attr_desc
.
type
());
}
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/framework/attribute.h
浏览文件 @
415f5006
...
...
@@ -26,6 +26,113 @@ limitations under the License. */
namespace
paddle
{
namespace
framework
{
template
<
typename
T
>
struct
ExtractAttribute
{
explicit
ExtractAttribute
(
const
std
::
string
&
attr_name
)
:
attr_name_
(
attr_name
)
{}
T
*
operator
()(
Attribute
&
attr
)
const
{
T
*
attr_value
=
nullptr
;
try
{
attr_value
=
&
boost
::
get
<
T
>
(
attr
);
}
catch
(
boost
::
bad_get
&
bad_get
)
{
PADDLE_THROW
(
"Cannot get attribute %s by type %s, its type is %s"
,
attr_name_
,
paddle
::
platform
::
demangle
(
typeid
(
T
).
name
()),
paddle
::
platform
::
demangle
(
attr
.
type
().
name
()));
}
return
attr_value
;
}
const
std
::
string
&
attr_name_
;
};
// special handle bool
// FIXME(yuyang18): Currently we cast bool into int in python binding. It is
// hard to change the logic there. In another way, we should correct handle
// if the user set `some_flag=1`.
//
// FIX ME anytime if there is a better solution.
template
<
>
struct
ExtractAttribute
<
bool
>
{
explicit
ExtractAttribute
(
const
std
::
string
&
attr_name
)
:
attr_name_
(
attr_name
)
{}
bool
*
operator
()(
Attribute
&
attr
)
const
{
if
(
attr
.
type
()
==
typeid
(
int
))
{
// NOLINT
int
val
=
boost
::
get
<
int
>
(
attr
);
attr
=
static_cast
<
bool
>
(
val
);
}
else
if
(
attr
.
type
()
==
typeid
(
float
))
{
// NOLINT
float
val
=
boost
::
get
<
float
>
(
attr
);
attr
=
static_cast
<
bool
>
(
val
);
}
bool
*
attr_value
=
nullptr
;
try
{
attr_value
=
&
boost
::
get
<
bool
>
(
attr
);
}
catch
(
boost
::
bad_get
&
bad_get
)
{
PADDLE_THROW
(
"Cannot get attribute %s by type bool, its type is %s"
,
attr_name_
,
paddle
::
platform
::
demangle
(
attr
.
type
().
name
()));
}
return
attr_value
;
}
const
std
::
string
&
attr_name_
;
};
template
<
>
struct
ExtractAttribute
<
int64_t
>
{
explicit
ExtractAttribute
(
const
std
::
string
&
attr_name
)
:
attr_name_
(
attr_name
)
{}
int64_t
*
operator
()(
Attribute
&
attr
)
const
{
if
(
attr
.
type
()
==
typeid
(
int
))
{
// NOLINT
int
val
=
boost
::
get
<
int
>
(
attr
);
attr
=
static_cast
<
int64_t
>
(
val
);
}
else
if
(
attr
.
type
()
==
typeid
(
float
))
{
// NOLINT
int
val
=
boost
::
get
<
float
>
(
attr
);
attr
=
static_cast
<
int64_t
>
(
val
);
}
int64_t
*
attr_value
=
nullptr
;
try
{
attr_value
=
&
boost
::
get
<
int64_t
>
(
attr
);
}
catch
(
boost
::
bad_get
&
bad_get
)
{
PADDLE_THROW
(
"Cannot get attribute %s by type int64_t, its type is %s"
,
attr_name_
,
paddle
::
platform
::
demangle
(
attr
.
type
().
name
()));
}
return
attr_value
;
}
const
std
::
string
&
attr_name_
;
};
template
<
>
struct
ExtractAttribute
<
std
::
vector
<
int64_t
>>
{
explicit
ExtractAttribute
(
const
std
::
string
&
attr_name
)
:
attr_name_
(
attr_name
)
{}
std
::
vector
<
int64_t
>*
operator
()(
Attribute
&
attr
)
const
{
if
(
attr
.
type
()
==
typeid
(
std
::
vector
<
int
>
))
{
// NOLINT
std
::
vector
<
int
>
val
=
boost
::
get
<
std
::
vector
<
int
>>
(
attr
);
std
::
vector
<
int64_t
>
vec
(
val
.
begin
(),
val
.
end
());
attr
=
vec
;
}
else
if
(
attr
.
type
()
==
typeid
(
std
::
vector
<
float
>
))
{
// NOLINT
std
::
vector
<
float
>
val
=
boost
::
get
<
std
::
vector
<
float
>>
(
attr
);
std
::
vector
<
int64_t
>
vec
(
val
.
begin
(),
val
.
end
());
attr
=
vec
;
}
std
::
vector
<
int64_t
>*
attr_value
=
nullptr
;
try
{
attr_value
=
&
boost
::
get
<
std
::
vector
<
int64_t
>>
(
attr
);
}
catch
(
boost
::
bad_get
&
bad_get
)
{
PADDLE_THROW
(
"Cannot get attribute %s by type int64_t, its type is %s"
,
attr_name_
,
paddle
::
platform
::
demangle
(
attr
.
type
().
name
()));
}
return
attr_value
;
}
const
std
::
string
&
attr_name_
;
};
template
<
typename
T
>
inline
proto
::
AttrType
AttrTypeID
()
{
Attribute
tmp
=
T
();
...
...
@@ -42,7 +149,11 @@ class AttrReader {
inline
const
T
&
Get
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE
(
attrs_
.
count
(
name
)
!=
0
,
"%s should be in AttributeMap"
,
name
);
return
boost
::
get
<
T
>
(
attrs_
.
at
(
name
));
Attribute
&
attr
=
const_cast
<
Attribute
&>
(
attrs_
.
at
(
name
));
ExtractAttribute
<
T
>
extract_attr
(
name
);
T
*
attr_value
=
extract_attr
(
attr
);
return
*
attr_value
;
}
private:
...
...
@@ -82,7 +193,7 @@ class DefaultValueSetter {
public:
explicit
DefaultValueSetter
(
T
default_value
)
:
default_value_
(
default_value
)
{}
void
operator
()(
T
&
value
)
const
{
value
=
default_value_
;
}
void
operator
()(
T
&
value
)
const
{
value
=
default_value_
;
}
// NOLINT
private:
T
default_value_
;
...
...
@@ -117,84 +228,6 @@ class EnumInContainer {
std
::
unordered_set
<
T
>
container_
;
};
template
<
typename
T
>
struct
ExtractAttribute
{
explicit
ExtractAttribute
(
const
std
::
string
&
attr_name
)
:
attr_name_
(
attr_name
)
{}
T
*
operator
()(
Attribute
&
attr
)
const
{
T
*
attr_value
=
nullptr
;
try
{
attr_value
=
&
boost
::
get
<
T
>
(
attr
);
}
catch
(
boost
::
bad_get
&
bad_get
)
{
PADDLE_THROW
(
"Cannot get attribute %s by type %s, its type is %s"
,
attr_name_
,
paddle
::
platform
::
demangle
(
typeid
(
T
).
name
()),
paddle
::
platform
::
demangle
(
attr
.
type
().
name
()));
}
return
attr_value
;
}
const
std
::
string
&
attr_name_
;
};
// special handle bool
// FIXME(yuyang18): Currently we cast bool into int in python binding. It is
// hard to change the logic there. In another way, we should correct handle
// if the user set `some_flag=1`.
//
// FIX ME anytime if there is a better solution.
template
<
>
struct
ExtractAttribute
<
bool
>
{
explicit
ExtractAttribute
(
const
std
::
string
&
attr_name
)
:
attr_name_
(
attr_name
)
{}
bool
*
operator
()(
Attribute
&
attr
)
const
{
if
(
attr
.
type
()
==
typeid
(
int
))
{
// NOLINT
int
val
=
boost
::
get
<
int
>
(
attr
);
attr
=
static_cast
<
bool
>
(
val
);
}
else
if
(
attr
.
type
()
==
typeid
(
float
))
{
// NOLINT
float
val
=
boost
::
get
<
float
>
(
attr
);
attr
=
static_cast
<
bool
>
(
val
);
}
bool
*
attr_value
=
nullptr
;
try
{
attr_value
=
&
boost
::
get
<
bool
>
(
attr
);
}
catch
(
boost
::
bad_get
&
bad_get
)
{
PADDLE_THROW
(
"Cannot get attribute %s by type bool, its type is %s"
,
attr_name_
,
paddle
::
platform
::
demangle
(
attr
.
type
().
name
()));
}
return
attr_value
;
}
const
std
::
string
&
attr_name_
;
};
template
<
>
struct
ExtractAttribute
<
int64_t
>
{
explicit
ExtractAttribute
(
const
std
::
string
&
attr_name
)
:
attr_name_
(
attr_name
)
{}
int64_t
*
operator
()(
Attribute
&
attr
)
const
{
if
(
attr
.
type
()
==
typeid
(
int
))
{
// NOLINT
int
val
=
boost
::
get
<
int
>
(
attr
);
attr
=
static_cast
<
int64_t
>
(
val
);
}
else
if
(
attr
.
type
()
==
typeid
(
float
))
{
// NOLINT
int
val
=
boost
::
get
<
float
>
(
attr
);
attr
=
static_cast
<
int64_t
>
(
val
);
}
int64_t
*
attr_value
=
nullptr
;
try
{
attr_value
=
&
boost
::
get
<
int64_t
>
(
attr
);
}
catch
(
boost
::
bad_get
&
bad_get
)
{
PADDLE_THROW
(
"Cannot get attribute %s by type int64_t, its type is %s"
,
attr_name_
,
paddle
::
platform
::
demangle
(
attr
.
type
().
name
()));
}
return
attr_value
;
}
const
std
::
string
&
attr_name_
;
};
// check whether a certain attribute fit its limits
// an attribute can have more than one limits
template
<
typename
T
>
...
...
@@ -235,7 +268,7 @@ class TypedAttrChecker {
return
*
this
;
}
void
operator
()(
AttributeMap
&
attr_map
)
const
{
void
operator
()(
AttributeMap
&
attr_map
)
const
{
// NOLINT
if
(
!
attr_map
.
count
(
attr_name_
))
{
// user do not set this attr
PADDLE_ENFORCE
(
!
default_value_setter_
.
empty
(),
...
...
@@ -271,7 +304,7 @@ class OpAttrChecker {
return
*
(
checker
.
target
<
TypedAttrChecker
<
T
>>
());
}
void
Check
(
AttributeMap
&
attr_map
)
const
{
void
Check
(
AttributeMap
&
attr_map
)
const
{
// NOLINT
for
(
const
auto
&
checker
:
attr_checkers_
)
{
checker
(
attr_map
);
}
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/framework/details/broadcast_op_handle.cc
浏览文件 @
415f5006
...
...
@@ -52,6 +52,10 @@ void BroadcastOpHandle::RunImpl() {
var_scopes
.
at
(
in_var_handle
->
scope_idx_
)
->
FindVar
(
in_var_handle
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
in_var
);
Tensor
&
in_tensor
=
VariableVisitor
::
GetMutableTensor
(
in_var
);
if
(
UNLIKELY
(
!
in_tensor
.
IsInitialized
()))
{
VLOG
(
3
)
<<
"in var "
<<
in_var_handle
.
name_
<<
"not inited, return!"
;
return
;
}
InitOutputValue
(
*
in_var_handle
,
out_var_handles
);
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/framework/details/multi_devices_graph_pass.cc
浏览文件 @
415f5006
...
...
@@ -680,7 +680,8 @@ int MultiDevSSAGraphBuilder::CreateDistTrainOp(ir::Graph *result,
}
if
(
node
->
Op
()
->
Type
()
==
"split_byref"
||
node
->
Op
()
->
Type
()
==
"split_selected_rows"
)
{
node
->
Op
()
->
Type
()
==
"split_selected_rows"
||
node
->
Op
()
->
Type
()
==
"split_ids"
)
{
// TODO(paddle-dev): getting the first var is not safe.
op_dev_id
=
GetVarDeviceID
(
*
result
,
input_var_names
[
0
]);
if
(
strategy_
.
reduce_
==
BuildStrategy
::
ReduceStrategy
::
kAllReduce
)
{
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/framework/framework.proto
浏览文件 @
415f5006
...
...
@@ -35,6 +35,7 @@ enum AttrType {
BLOCK
=
8
;
LONG
=
9
;
BLOCKS
=
10
;
LONGS
=
11
;
}
// OpDesc describes an instance of a C++ framework::OperatorBase
...
...
@@ -55,6 +56,7 @@ message OpDesc {
optional
int32
block_idx
=
12
;
optional
int64
l
=
13
;
repeated
int32
blocks_idx
=
14
;
repeated
int64
longs
=
15
;
};
message
Var
{
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/framework/op_desc.cc
浏览文件 @
415f5006
...
...
@@ -419,8 +419,15 @@ struct SetAttrDescVisitor : public boost::static_visitor<void> {
}
VectorToRepeated
(
blocks_idx
,
attr_
->
mutable_blocks_idx
());
}
void
operator
()(
BlockDesc
*
desc
)
const
{
attr_
->
set_block_idx
(
desc
->
ID
());
}
void
operator
()(
int64_t
v
)
const
{
attr_
->
set_l
(
v
);
}
void
operator
()(
const
std
::
vector
<
int64_t
>
&
v
)
const
{
VectorToRepeated
(
v
,
attr_
->
mutable_longs
());
}
void
operator
()(
boost
::
blank
)
const
{
PADDLE_THROW
(
"Unexpected branch"
);
}
};
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/framework/parallel_executor.cc
浏览文件 @
415f5006
...
...
@@ -185,6 +185,10 @@ void ParallelExecutor::BCastParamsToDevices(
}
auto
&
main_tensor
=
main_var
->
Get
<
LoDTensor
>
();
if
(
!
main_tensor
.
IsInitialized
())
{
VLOG
(
3
)
<<
"one in var not inited, return!"
;
continue
;
}
auto
&
dims
=
main_tensor
.
dims
();
if
(
paddle
::
platform
::
is_gpu_place
(
main_tensor
.
place
()))
{
#ifdef PADDLE_WITH_CUDA
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/framework/type_defs.h
浏览文件 @
415f5006
...
...
@@ -36,7 +36,7 @@ using Attribute =
boost
::
variant
<
boost
::
blank
,
int
,
float
,
std
::
string
,
std
::
vector
<
int
>
,
std
::
vector
<
float
>
,
std
::
vector
<
std
::
string
>
,
bool
,
std
::
vector
<
bool
>
,
BlockDesc
*
,
int64_t
,
std
::
vector
<
BlockDesc
*>>
;
std
::
vector
<
BlockDesc
*>
,
std
::
vector
<
int64_t
>
>
;
using
AttributeMap
=
std
::
unordered_map
<
std
::
string
,
Attribute
>
;
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/fake_init_op.cc
0 → 100644
浏览文件 @
415f5006
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/math_function.h"
namespace
paddle
{
namespace
operators
{
class
FakeInitInferShape
:
public
framework
::
InferShapeBase
{
public:
void
operator
()(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of FakeInitOp should not be null."
);
auto
&
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int64_t
>>
(
"shape"
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
shape
));
}
};
class
FakeInitOp
:
public
framework
::
OperatorBase
{
public:
using
framework
::
OperatorBase
::
OperatorBase
;
private:
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
dev_place
)
const
override
{
framework
::
Tensor
*
tensor
=
nullptr
;
auto
&
out_var
=
*
scope
.
FindVar
(
Output
(
"Out"
));
if
(
out_var
.
IsType
<
framework
::
LoDTensor
>
())
{
tensor
=
out_var
.
GetMutable
<
framework
::
LoDTensor
>
();
tensor
->
Resize
(
framework
::
make_ddim
(
Attr
<
std
::
vector
<
int64_t
>>
(
"shape"
)));
}
else
if
(
out_var
.
IsType
<
framework
::
SelectedRows
>
())
{
tensor
=
out_var
.
GetMutable
<
framework
::
SelectedRows
>
()
->
mutable_value
();
tensor
->
Resize
(
framework
::
make_ddim
(
Attr
<
std
::
vector
<
int64_t
>>
(
"shape"
)));
}
else
{
PADDLE_THROW
(
"fake init op's output only"
"supports SelectedRows and LoDTensor"
);
}
}
};
class
FakeInitOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{}
};
class
FakeInitOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddAttr
<
std
::
vector
<
int64_t
>>
(
"shape"
,
"(vector<int64_t>) The shape of the output"
);
AddOutput
(
"Out"
,
"(Tensor) Tensor of specified shape will be filled "
"with the specified value"
);
AddComment
(
R"DOC(
FakeInit Operator.
Init an variable but not alloc memory for it, it is used for init the
table parameter at trainer side in distributed lookup table.
)DOC"
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
fake_init
,
ops
::
FakeInitOp
,
ops
::
FakeInitInferShape
,
ops
::
FakeInitOpMaker
,
paddle
::
framework
::
EmptyGradOpMaker
,
ops
::
FakeInitOpVarTypeInference
);
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/fill_constant_op.cc
浏览文件 @
415f5006
...
...
@@ -24,7 +24,7 @@ class FillConstantInferShape : public framework::InferShapeBase {
void
operator
()(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of FillConstantOp should not be null."
);
auto
&
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
auto
&
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
64_t
>>
(
"shape"
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
shape
));
}
};
...
...
@@ -47,10 +47,10 @@ class FillConstantOp : public framework::OperatorBase {
if
(
out_var
.
IsType
<
framework
::
LoDTensor
>
())
{
tensor
=
out_var
.
GetMutable
<
framework
::
LoDTensor
>
();
tensor
->
Resize
(
framework
::
make_ddim
(
Attr
<
std
::
vector
<
int
>>
(
"shape"
)));
tensor
->
Resize
(
framework
::
make_ddim
(
Attr
<
std
::
vector
<
int
64_t
>>
(
"shape"
)));
}
else
if
(
out_var
.
IsType
<
framework
::
SelectedRows
>
())
{
tensor
=
out_var
.
GetMutable
<
framework
::
SelectedRows
>
()
->
mutable_value
();
tensor
->
Resize
(
framework
::
make_ddim
(
Attr
<
std
::
vector
<
int
>>
(
"shape"
)));
tensor
->
Resize
(
framework
::
make_ddim
(
Attr
<
std
::
vector
<
int
64_t
>>
(
"shape"
)));
}
else
{
PADDLE_THROW
(
"fill constant op's output only"
...
...
@@ -83,7 +83,8 @@ class FillConstantOpMaker : public framework::OpProtoAndCheckerMaker {
"(int, default 5 (FP32)) "
"Output data type"
)
.
SetDefault
(
framework
::
proto
::
VarType
::
FP32
);
AddAttr
<
std
::
vector
<
int
>>
(
"shape"
,
"(vector<int>) The shape of the output"
);
AddAttr
<
std
::
vector
<
int64_t
>>
(
"shape"
,
"(vector<int64_t>) The shape of the output"
);
AddAttr
<
float
>
(
"value"
,
"(float, default 0) The value to be filled"
)
.
SetDefault
(
0.0
f
);
AddAttr
<
bool
>
(
"force_cpu"
,
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/gaussian_random_op.cc
浏览文件 @
415f5006
...
...
@@ -52,7 +52,7 @@ class GaussianRandomOp : public framework::OperatorWithKernel {
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of GaussianRandomOp should not be null."
);
auto
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
auto
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
64_t
>>
(
"shape"
);
std
::
vector
<
int64_t
>
temp
;
temp
.
reserve
(
shape
.
size
());
for
(
auto
dim
:
shape
)
{
...
...
@@ -88,9 +88,9 @@ class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
void
Make
()
override
{
AddOutput
(
"Out"
,
"Output matrix of gaussian random op"
);
AddAttr
<
std
::
vector
<
int
>>
(
"shape"
,
"(vector<in
t>) "
"The dimension of random tensor."
);
AddAttr
<
std
::
vector
<
int
64_t
>>
(
"shape"
,
"(vector<int64_
t>) "
"The dimension of random tensor."
);
AddAttr
<
float
>
(
"mean"
,
"(float, default 0.0) "
"mean of random tensor."
)
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/listen_and_serv_op.cc
浏览文件 @
415f5006
...
...
@@ -27,6 +27,10 @@ limitations under the License. */
#include "paddle/fluid/operators/distributed/request_handler_impl.h"
#include "paddle/fluid/operators/listen_and_serv_op.h"
DEFINE_int32
(
rpc_send_thread_num
,
5
,
"number of threads for rpc send"
);
DEFINE_int32
(
rpc_get_thread_num
,
5
,
"number of threads for rpc get"
);
DEFINE_int32
(
rpc_prefetch_thread_num
,
5
,
"number of threads for rpc prefetch"
);
namespace
paddle
{
namespace
operators
{
...
...
@@ -332,11 +336,14 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope,
sync_mode
,
checkpoint_block_id
));
rpc_service_
->
RegisterRPC
(
distributed
::
kRequestSend
,
request_send_handler_
.
get
());
request_send_handler_
.
get
(),
FLAGS_rpc_send_thread_num
);
rpc_service_
->
RegisterRPC
(
distributed
::
kRequestGet
,
request_get_handler_
.
get
());
request_get_handler_
.
get
(),
FLAGS_rpc_get_thread_num
);
rpc_service_
->
RegisterRPC
(
distributed
::
kRequestPrefetch
,
request_prefetch_handler_
.
get
());
request_prefetch_handler_
.
get
(),
FLAGS_rpc_prefetch_thread_num
);
rpc_service_
->
RegisterRPC
(
distributed
::
kRequestCheckpoint
,
request_checkpoint_handler_
.
get
());
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/lookup_table_op.cc
浏览文件 @
415f5006
...
...
@@ -121,7 +121,7 @@ class LookupTableOpGrad : public framework::OperatorWithKernel {
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
data_type
=
framework
::
GetDataTypeOfVar
(
ctx
.
InputVar
(
"
W
"
));
auto
data_type
=
framework
::
GetDataTypeOfVar
(
ctx
.
InputVar
(
"
Out
"
));
return
framework
::
OpKernelType
(
data_type
,
ctx
.
device_context
());
}
};
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/math/selected_rows_functor.cc
浏览文件 @
415f5006
...
...
@@ -12,9 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <map>
#include <set>
#include <
vector
>
#include <
unordered_map
>
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/operators/math/selected_rows_functor.h"
...
...
@@ -230,8 +229,24 @@ template struct SelectedRowsAddToTensor<platform::CPUDeviceContext, int64_t>;
// add or mul.
namespace
scatter
{
size_t
FindPos
(
const
std
::
vector
<
int64_t
>&
rows
,
int64_t
value
)
{
return
std
::
find
(
rows
.
begin
(),
rows
.
end
(),
value
)
-
rows
.
begin
();
template
<
typename
DeviceContext
,
typename
T
>
typename
std
::
enable_if
<
std
::
is_floating_point
<
T
>::
value
&&
std
::
is_same
<
DeviceContext
,
platform
::
CPUDeviceContext
>::
value
>::
type
elementwise_add_to
(
const
DeviceContext
&
ctx
,
BlasT
<
DeviceContext
,
T
>*
blas
,
size_t
data_len
,
const
T
*
in
,
T
*
out
)
{
blas
->
AXPY
(
data_len
,
1.
,
in
,
out
);
}
template
<
typename
DeviceContext
,
typename
T
>
typename
std
::
enable_if
<
!
std
::
is_floating_point
<
T
>::
value
&&
std
::
is_same
<
DeviceContext
,
platform
::
CPUDeviceContext
>::
value
>::
type
elementwise_add_to
(
const
DeviceContext
&
ctx
,
BlasT
<
DeviceContext
,
T
>*
blas
,
size_t
data_len
,
const
T
*
in
,
T
*
out
)
{
for
(
int64_t
i
=
0
;
i
<
data_len
;
i
++
)
{
out
[
i
]
+=
in
[
i
];
}
}
template
<
typename
T
>
...
...
@@ -246,48 +261,84 @@ struct MergeAdd<platform::CPUDeviceContext, T> {
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
,
framework
::
SelectedRows
*
output
)
{
framework
::
SelectedRows
&
out
=
*
output
;
std
::
vector
<
int64_t
>
input_rows
(
input
.
rows
());
std
::
vector
<
const
framework
::
SelectedRows
*>
inputs
;
inputs
.
push_back
(
&
input
);
(
*
this
)(
context
,
inputs
,
output
);
}
std
::
map
<
int64_t
,
std
::
vector
<
int64_t
>>
merge_row_map
;
for
(
size_t
i
=
0
;
i
<
input_rows
.
size
();
++
i
)
{
merge_row_map
[
input_rows
[
i
]].
push_back
(
i
);
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
std
::
vector
<
const
framework
::
SelectedRows
*>&
inputs
,
framework
::
SelectedRows
*
output
)
{
if
(
inputs
.
size
()
==
0
)
{
VLOG
(
3
)
<<
"no input! return"
;
return
;
}
std
::
vector
<
int64_t
>
merge_rows
(
merge_row_map
.
size
());
size_t
idx
=
0
;
int64_t
input_width
=
input
.
value
().
dims
()[
1
];
out
.
set_height
(
input
.
height
());
T
*
out_data
=
out
.
mutable_value
()
->
mutable_data
<
T
>
(
const
framework
::
SelectedRows
*
has_value_input
=
nullptr
;
for
(
auto
*
in
:
inputs
)
{
if
(
in
->
rows
().
size
()
>
0
)
{
has_value_input
=
in
;
break
;
}
}
if
(
has_value_input
==
nullptr
)
{
VLOG
(
3
)
<<
"no input has value! just return"
<<
std
::
endl
;
return
;
}
auto
input_width
=
has_value_input
->
value
().
dims
()[
1
];
auto
input_height
=
has_value_input
->
height
();
framework
::
SelectedRows
&
out
=
*
output
;
std
::
set
<
int64_t
>
merged_row_set
;
for
(
auto
*
input
:
inputs
)
{
if
(
input
->
rows
().
size
()
==
0
)
{
continue
;
}
PADDLE_ENFORCE_EQ
(
input_width
,
input
->
value
().
dims
()[
1
],
"all input should have same "
"dimension except for the first one"
);
PADDLE_ENFORCE_EQ
(
input_height
,
input
->
height
(),
"all input should have same height"
);
merged_row_set
.
insert
(
input
->
rows
().
begin
(),
input
->
rows
().
end
());
}
std
::
vector
<
int64_t
>
merge_rows
(
merged_row_set
.
begin
(),
merged_row_set
.
end
());
std
::
unordered_map
<
int64_t
,
size_t
>
rows_to_id
;
for
(
size_t
i
=
0
;
i
<
merge_rows
.
size
();
++
i
)
{
rows_to_id
[
merge_rows
[
i
]]
=
i
;
}
out
.
set_rows
(
merge_rows
);
out
.
set_height
(
input_height
);
out
.
mutable_value
()
->
mutable_data
<
T
>
(
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
merge_rows
.
size
()),
input_width
}),
context
.
GetPlace
());
const
T
*
in_data
=
input
.
value
().
data
<
T
>
();
for
(
auto
&
row_pair
:
merge_row_map
)
{
auto
*
out_ptr
=
out_data
+
idx
*
input_width
;
auto
&
rows
=
row_pair
.
second
;
merge_rows
[
idx
]
=
row_pair
.
first
;
++
idx
;
// rows.size() is always larger than 0
std
::
memcpy
(
out_ptr
,
in_data
+
rows
[
0
]
*
input_width
,
sizeof
(
T
)
*
input_width
);
for
(
size_t
i
=
1
;
i
<
rows
.
size
();
++
i
)
{
auto
*
in_ptr
=
in_data
+
rows
[
i
]
*
input_width
;
for
(
int64_t
j
=
0
;
j
<
input_width
;
++
j
)
{
out_ptr
[
j
]
+=
in_ptr
[
j
];
}
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
constant_functor
;
constant_functor
(
context
,
out
.
mutable_value
(),
0.0
);
auto
*
out_data
=
out
.
mutable_value
()
->
data
<
T
>
();
auto
blas
=
math
::
GetBlas
<
platform
::
CPUDeviceContext
,
T
>
(
context
);
for
(
auto
*
input
:
inputs
)
{
if
(
input
->
rows
().
size
()
==
0
)
{
continue
;
}
auto
*
input_data
=
input
->
value
().
data
<
T
>
();
auto
&
input_rows
=
input
->
rows
();
for
(
size_t
i
=
0
;
i
<
input_rows
.
size
();
i
++
)
{
size_t
out_i
=
rows_to_id
[
input_rows
[
i
]];
elementwise_add_to
<
platform
::
CPUDeviceContext
,
T
>
(
context
,
&
blas
,
static_cast
<
size_t
>
(
input_width
),
&
input_data
[
i
*
input_width
],
&
out_data
[
out_i
*
input_width
]);
}
}
out
.
set_rows
(
merge_rows
);
}
};
template
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
int
>;
template
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
int64_t
>;
template
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
float
>;
template
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
double
>;
template
<
typename
T
>
struct
UpdateToTensor
<
platform
::
CPUDeviceContext
,
T
>
{
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/math/selected_rows_functor.cu
浏览文件 @
415f5006
...
...
@@ -267,10 +267,15 @@ struct MergeAdd<platform::CUDADeviceContext, T> {
void
operator
()(
const
platform
::
CUDADeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
,
framework
::
SelectedRows
*
output
)
{
framework
::
SelectedRows
&
out
=
*
output
;
framework
::
Vector
<
int64_t
>
input_rows
(
input
.
rows
());
if
(
input_rows
.
size
()
==
0
)
{
return
;
}
framework
::
SelectedRows
&
out
=
*
output
;
std
::
set
<
int64_t
>
row_set
(
input_rows
.
begin
(),
input_rows
.
end
());
std
::
vector
<
int64_t
>
merge_rows
(
row_set
.
begin
(),
row_set
.
end
());
std
::
vector
<
int64_t
>
merge_rows_cpu
(
row_set
.
begin
(),
row_set
.
end
());
framework
::
Vector
<
int64_t
>
merge_rows
(
merge_rows_cpu
);
auto
input_width
=
input
.
value
().
dims
()[
1
];
...
...
@@ -296,6 +301,73 @@ struct MergeAdd<platform::CUDADeviceContext, T> {
out
.
mutable_rows
()
->
CUDAMutableData
(
context
.
GetPlace
()),
out
.
rows
().
size
(),
input_width
);
}
void
operator
()(
const
platform
::
CUDADeviceContext
&
context
,
const
std
::
vector
<
const
framework
::
SelectedRows
*>&
inputs
,
framework
::
SelectedRows
*
output
)
{
if
(
inputs
.
size
()
==
0
)
{
VLOG
(
3
)
<<
"no input! return"
;
return
;
}
const
framework
::
SelectedRows
*
has_value_input
=
nullptr
;
for
(
auto
*
in
:
inputs
)
{
if
(
in
->
rows
().
size
()
>
0
)
{
has_value_input
=
in
;
break
;
}
}
if
(
has_value_input
==
nullptr
)
{
VLOG
(
3
)
<<
"no input has value! just return"
<<
std
::
endl
;
return
;
}
auto
input_width
=
has_value_input
->
value
().
dims
()[
1
];
auto
input_height
=
has_value_input
->
height
();
framework
::
SelectedRows
&
out
=
*
output
;
std
::
set
<
int64_t
>
merged_row_set
;
for
(
auto
*
input
:
inputs
)
{
if
(
input
->
rows
().
size
()
==
0
)
{
continue
;
}
PADDLE_ENFORCE_EQ
(
input_width
,
input
->
value
().
dims
()[
1
],
"all input should have same "
"dimension except for the first one"
);
PADDLE_ENFORCE_EQ
(
input_height
,
input
->
height
(),
"all input should have same height"
);
merged_row_set
.
insert
(
input
->
rows
().
begin
(),
input
->
rows
().
end
());
}
std
::
vector
<
int64_t
>
merge_rows_cpu
(
merged_row_set
.
begin
(),
merged_row_set
.
end
());
framework
::
Vector
<
int64_t
>
merge_rows
(
merge_rows_cpu
);
out
.
set_rows
(
merge_rows
);
out
.
set_height
(
input_height
);
out
.
mutable_value
()
->
mutable_data
<
T
>
(
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
merge_rows
.
size
()),
input_width
}),
context
.
GetPlace
());
math
::
SetConstant
<
platform
::
CUDADeviceContext
,
T
>
constant_functor
;
constant_functor
(
context
,
out
.
mutable_value
(),
0.0
);
auto
*
out_data
=
out
.
mutable_value
()
->
data
<
T
>
();
const
int
block_size
=
256
;
dim3
threads
(
block_size
,
1
);
for
(
auto
*
input
:
inputs
)
{
if
(
input
->
rows
().
size
()
==
0
)
{
continue
;
}
auto
*
input_data
=
input
->
value
().
data
<
T
>
();
auto
&
input_rows
=
input
->
rows
();
dim3
grid1
(
input_rows
.
size
(),
1
);
MergeAddKernel
<
T
,
256
><<<
grid1
,
threads
,
0
,
context
.
stream
()
>>>
(
input_data
,
input_rows
.
CUDAData
(
context
.
GetPlace
()),
out_data
,
out
.
mutable_rows
()
->
CUDAMutableData
(
context
.
GetPlace
()),
out
.
rows
().
size
(),
input_width
);
}
}
};
template
struct
MergeAdd
<
platform
::
CUDADeviceContext
,
float
>;
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/math/selected_rows_functor.h
浏览文件 @
415f5006
...
...
@@ -83,104 +83,9 @@ struct MergeAdd {
void
operator
()(
const
DeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
,
framework
::
SelectedRows
*
output
);
};
template
<
>
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
float
>
{
framework
::
SelectedRows
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
)
{
framework
::
SelectedRows
out
;
(
*
this
)(
context
,
input
,
&
out
);
return
out
;
}
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
,
framework
::
SelectedRows
*
output
)
{
framework
::
SelectedRows
&
out
=
*
output
;
std
::
vector
<
int64_t
>
input_rows
(
input
.
rows
());
std
::
map
<
int64_t
,
std
::
vector
<
int64_t
>>
merge_row_map
;
for
(
size_t
i
=
0
;
i
<
input_rows
.
size
();
++
i
)
{
merge_row_map
[
input_rows
[
i
]].
push_back
(
i
);
}
std
::
vector
<
int64_t
>
merge_rows
(
merge_row_map
.
size
());
size_t
idx
=
0
;
int64_t
input_width
=
input
.
value
().
dims
()[
1
];
out
.
set_height
(
input
.
height
());
auto
*
out_data
=
out
.
mutable_value
()
->
mutable_data
<
float
>
(
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
merge_rows
.
size
()),
input_width
}),
context
.
GetPlace
());
auto
*
in_data
=
input
.
value
().
data
<
float
>
();
auto
blas
=
GetBlas
<
platform
::
CPUDeviceContext
,
float
>
(
context
);
for
(
auto
&
row_pair
:
merge_row_map
)
{
auto
*
out_ptr
=
out_data
+
idx
*
input_width
;
auto
&
rows
=
row_pair
.
second
;
merge_rows
[
idx
]
=
row_pair
.
first
;
++
idx
;
// rows.size() is always larger than 0
blas
.
VCOPY
(
input_width
,
in_data
+
rows
[
0
]
*
input_width
,
out_ptr
);
for
(
size_t
i
=
1
;
i
<
rows
.
size
();
++
i
)
{
blas
.
AXPY
(
input_width
,
1.
,
in_data
+
rows
[
i
]
*
input_width
,
out_ptr
);
}
}
out
.
set_rows
(
merge_rows
);
}
};
template
<
>
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
double
>
{
framework
::
SelectedRows
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
)
{
framework
::
SelectedRows
out
;
(
*
this
)(
context
,
input
,
&
out
);
return
out
;
}
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
,
framework
::
SelectedRows
*
output
)
{
framework
::
SelectedRows
&
out
=
*
output
;
std
::
vector
<
int64_t
>
input_rows
(
input
.
rows
());
std
::
map
<
int64_t
,
std
::
vector
<
int64_t
>>
merge_row_map
;
for
(
size_t
i
=
0
;
i
<
input_rows
.
size
();
++
i
)
{
merge_row_map
[
input_rows
[
i
]].
push_back
(
i
);
}
std
::
vector
<
int64_t
>
merge_rows
(
merge_row_map
.
size
());
size_t
idx
=
0
;
int64_t
input_width
=
input
.
value
().
dims
()[
1
];
out
.
set_height
(
input
.
height
());
auto
*
out_data
=
out
.
mutable_value
()
->
mutable_data
<
double
>
(
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
merge_rows
.
size
()),
input_width
}),
context
.
GetPlace
());
auto
*
in_data
=
input
.
value
().
data
<
double
>
();
auto
blas
=
GetBlas
<
platform
::
CPUDeviceContext
,
double
>
(
context
);
for
(
auto
&
row_pair
:
merge_row_map
)
{
auto
*
out_ptr
=
out_data
+
idx
*
input_width
;
auto
&
rows
=
row_pair
.
second
;
merge_rows
[
idx
]
=
row_pair
.
first
;
++
idx
;
// rows.size() is always larger than 0
blas
.
VCOPY
(
input_width
,
in_data
+
rows
[
0
]
*
input_width
,
out_ptr
);
for
(
size_t
i
=
1
;
i
<
rows
.
size
();
++
i
)
{
blas
.
AXPY
(
input_width
,
1.
,
in_data
+
rows
[
i
]
*
input_width
,
out_ptr
);
}
}
out
.
set_rows
(
merge_rows
);
}
void
operator
()(
const
DeviceContext
&
context
,
const
std
::
vector
<
const
framework
::
SelectedRows
*>&
inputs
,
framework
::
SelectedRows
*
output
);
};
template
<
typename
DeviceContext
,
typename
T
>
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/math/selected_rows_functor_test.cc
浏览文件 @
415f5006
...
...
@@ -302,6 +302,64 @@ TEST(selected_rows_functor, cpu_merge_add_int) {
EXPECT_EQ
(
out_data
[
1
*
row_numel
],
2
);
EXPECT_EQ
(
out_data
[
2
*
row_numel
],
1
);
}
TEST
(
selected_rows_functor
,
cpu_merge_add_multi
)
{
paddle
::
platform
::
CPUPlace
cpu_place
;
paddle
::
platform
::
CPUDeviceContext
ctx
(
cpu_place
);
paddle
::
operators
::
math
::
SetConstant
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
set_const
;
int64_t
height
=
10
;
int64_t
row_numel
=
8
;
std
::
vector
<
int64_t
>
rows1
{
5
,
2
,
5
,
3
,
5
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows1
{
new
paddle
::
framework
::
SelectedRows
(
rows1
,
height
)};
auto
*
in1_value
=
selected_rows1
->
mutable_value
();
in1_value
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows1
.
size
()),
row_numel
}),
cpu_place
);
set_const
(
ctx
,
in1_value
,
1.0
);
std
::
vector
<
int64_t
>
rows2
{
2
,
5
,
3
,
5
,
3
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows2
{
new
paddle
::
framework
::
SelectedRows
(
rows2
,
height
)};
auto
*
in2_value
=
selected_rows2
->
mutable_value
();
in2_value
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows2
.
size
()),
row_numel
}),
cpu_place
);
set_const
(
ctx
,
in2_value
,
1.0
);
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
output
{
new
paddle
::
framework
::
SelectedRows
()};
output
->
set_height
(
height
);
paddle
::
operators
::
math
::
scatter
::
MergeAdd
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
merge_add_functor
;
std
::
vector
<
const
paddle
::
framework
::
SelectedRows
*>
inputs
;
inputs
.
push_back
(
selected_rows1
.
get
());
inputs
.
push_back
(
selected_rows2
.
get
());
merge_add_functor
(
ctx
,
inputs
,
output
.
get
());
EXPECT_EQ
(
output
->
height
(),
height
);
EXPECT_EQ
(
output
->
value
().
dims
(),
paddle
::
framework
::
make_ddim
({
3
,
row_numel
}));
std
::
vector
<
int64_t
>
ret_rows
{
2
,
3
,
5
};
EXPECT_EQ
(
output
->
rows
(),
ret_rows
);
auto
*
out_data
=
output
->
value
().
data
<
float
>
();
for
(
size_t
i
=
0
;
i
<
ret_rows
.
size
();
++
i
)
{
for
(
size_t
j
=
0
;
j
<
row_numel
;
++
j
)
{
EXPECT_EQ
(
out_data
[
i
*
row_numel
+
j
],
ret_rows
[
i
]);
}
}
}
TEST
(
selected_rows_functor
,
cpu_sum_to
)
{
paddle
::
platform
::
CPUPlace
cpu_place
;
paddle
::
platform
::
CPUDeviceContext
ctx
(
cpu_place
);
...
...
@@ -318,6 +376,7 @@ TEST(selected_rows_functor, cpu_sum_to) {
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows1
.
size
()),
row_numel
}),
cpu_place
);
functor
(
ctx
,
in1_value
,
1.0
);
std
::
vector
<
int64_t
>
rows2
{
0
,
5
,
7
,
9
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows2
{
...
...
@@ -327,6 +386,7 @@ TEST(selected_rows_functor, cpu_sum_to) {
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows2
.
size
()),
row_numel
}),
cpu_place
);
functor
(
ctx
,
in2_value
,
2.0
);
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
output
{
new
paddle
::
framework
::
SelectedRows
()};
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/math/selected_rows_functor_test.cu
浏览文件 @
415f5006
...
...
@@ -241,3 +241,67 @@ TEST(selected_rows_functor, gpu_add_to) {
// row9: 2.0 + 3.0
EXPECT_EQ
(
tensor1_cpu_data
[
9
*
row_numel
+
6
],
5.0
);
}
TEST
(
selected_rows_functor
,
gpu_merge_add
)
{
paddle
::
platform
::
CUDAPlace
gpu_place
(
0
);
paddle
::
platform
::
CPUPlace
cpu_place
;
paddle
::
platform
::
CUDADeviceContext
&
ctx
=
*
reinterpret_cast
<
paddle
::
platform
::
CUDADeviceContext
*>
(
paddle
::
platform
::
DeviceContextPool
::
Instance
().
Get
(
gpu_place
));
paddle
::
operators
::
math
::
SetConstant
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
set_const
;
int64_t
height
=
10
;
int64_t
row_numel
=
8
;
std
::
vector
<
int64_t
>
rows1
{
5
,
2
,
5
,
3
,
5
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows1
{
new
paddle
::
framework
::
SelectedRows
(
rows1
,
height
)};
auto
*
in1_value
=
selected_rows1
->
mutable_value
();
in1_value
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows1
.
size
()),
row_numel
}),
gpu_place
);
set_const
(
ctx
,
in1_value
,
1.0
);
std
::
vector
<
int64_t
>
rows2
{
2
,
5
,
3
,
5
,
3
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows2
{
new
paddle
::
framework
::
SelectedRows
(
rows2
,
height
)};
auto
*
in2_value
=
selected_rows2
->
mutable_value
();
in2_value
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows2
.
size
()),
row_numel
}),
gpu_place
);
set_const
(
ctx
,
in2_value
,
1.0
);
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
output
{
new
paddle
::
framework
::
SelectedRows
()};
output
->
set_height
(
height
);
paddle
::
operators
::
math
::
scatter
::
MergeAdd
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
merge_add_functor
;
std
::
vector
<
const
paddle
::
framework
::
SelectedRows
*>
inputs
;
inputs
.
push_back
(
selected_rows1
.
get
());
inputs
.
push_back
(
selected_rows2
.
get
());
merge_add_functor
(
ctx
,
inputs
,
output
.
get
());
paddle
::
framework
::
Tensor
output_cpu
;
paddle
::
framework
::
TensorCopy
(
output
->
value
(),
cpu_place
,
ctx
,
&
output_cpu
);
ctx
.
Wait
();
EXPECT_EQ
(
output
->
height
(),
height
);
EXPECT_EQ
(
output
->
value
().
dims
(),
paddle
::
framework
::
make_ddim
({
3
,
row_numel
}));
std
::
vector
<
int64_t
>
ret_rows
{
2
,
3
,
5
};
EXPECT_EQ
(
output
->
rows
(),
ret_rows
);
auto
*
out_data
=
output_cpu
.
data
<
float
>
();
for
(
size_t
i
=
0
;
i
<
ret_rows
.
size
();
++
i
)
{
for
(
size_t
j
=
0
;
j
<
row_numel
;
++
j
)
{
EXPECT_EQ
(
out_data
[
i
*
row_numel
+
j
],
ret_rows
[
i
]);
}
}
}
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/merge_ids_op.cc
浏览文件 @
415f5006
...
...
@@ -20,13 +20,16 @@ namespace operators {
class
MergeIdsOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"Ids"
,
"(LoDTensor) the input ids with shape{batch_num, 1}"
);
AddInput
(
"X"
,
"(LoDTensors) multi input tensor with shape{batch_num, N}, N is the "
"size of embedding table"
)
AddInput
(
"Ids"
,
"(LoDTensor) the input ids with shape{batch_num, 1}"
)
.
AsDuplicable
();
AddInput
(
"Rows"
,
"(LoDTensor) the input ids with shape{row_size, 1}, "
)
.
AsDuplicable
();
AddInput
(
"X"
,
"(LoDTensors) multi input tensor with shape{Rows, N}, N is the "
"size of embedding table"
)
.
AsDuplicable
();
AddOutput
(
"Out"
,
"(LoDTensor) The merged outputs of the input tensors."
)
.
AsDuplicable
();
AddOutput
(
"Out"
,
"(LoDTensor) The merged outputs of the input tensors."
);
AddComment
(
R"DOC(
Merge multi LoDTensor's into one according to Ids's shard num.
...
...
@@ -79,15 +82,19 @@ class MergeIdsOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Ids"
),
"MergeIdsOp must has input Ids."
);
PADDLE_ENFORCE
(
ctx
->
HasInputs
(
"X"
),
"MergeIdsOp must has input X."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"MergeIdsOp must has output Out."
);
PADDLE_ENFORCE
(
ctx
->
HasInputs
(
"Ids"
),
"MergeIdsOp must has multi input Ids."
);
PADDLE_ENFORCE
(
ctx
->
HasInputs
(
"Rows"
),
"MergeIdsOp must has multi input Rows."
);
PADDLE_ENFORCE
(
ctx
->
HasInputs
(
"X"
),
"MergeIdsOp must has multi input X."
);
PADDLE_ENFORCE
(
ctx
->
HasOutputs
(
"Out"
),
"MergeIdsOp must has multi output Out."
);
auto
ids_var_type
=
ctx
->
GetInputsVarType
(
"Ids"
).
front
();
auto
ids_dims
=
ctx
->
GetInputDim
(
"Ids"
);
auto
ids_dims
=
ctx
->
GetInput
s
Dim
(
"Ids"
);
if
(
ids_var_type
==
framework
::
proto
::
VarType
::
LOD_TENSOR
)
{
PADDLE_ENFORCE_EQ
(
ids_dims
.
size
(),
2
);
PADDLE_ENFORCE_EQ
(
ids_dims
[
1
],
1
);
PADDLE_ENFORCE_EQ
(
ids_dims
[
0
]
.
size
(),
2
);
PADDLE_ENFORCE_EQ
(
ids_dims
[
0
][
1
],
1
);
}
auto
x_var_type
=
ctx
->
GetInputsVarType
(
"X"
);
for
(
auto
&
var_type
:
x_var_type
)
{
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/merge_ids_op.h
浏览文件 @
415f5006
...
...
@@ -14,6 +14,8 @@ limitations under the License. */
#pragma once
#include <tuple>
#include <unordered_map>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/tensor_util.h"
...
...
@@ -30,59 +32,70 @@ class MergeIdsOpKernel : public framework::OpKernel<T> {
if
(
!
platform
::
is_cpu_place
(
place
))
{
PADDLE_THROW
(
"MergeIds do not support GPU kernel"
);
}
VLOG
(
3
)
<<
"run in MergeIdsOpKernel"
;
const
auto
*
ids_var
=
ctx
.
InputVar
(
"Ids"
);
PADDLE_ENFORCE
(
ids_var
->
IsType
<
framework
::
LoDTensor
>
(),
"only support to merge Ids of LoDTensor"
);
const
auto
ids
=
ctx
.
MultiInput
<
framework
::
LoDTensor
>
(
"Ids"
);
const
auto
row_ids
=
ctx
.
MultiInput
<
framework
::
LoDTensor
>
(
"Rows"
);
const
auto
x_tensors
=
ctx
.
MultiInput
<
framework
::
LoDTensor
>
(
"X"
);
auto
outs
=
ctx
.
MultiOutput
<
framework
::
LoDTensor
>
(
"Out"
);
const
auto
&
ids_tensor
=
ids_var
->
Get
<
framework
::
LoDTensor
>
();
const
auto
&
ids_dims
=
ids_tensor
.
dims
();
const
int64_t
*
ids
=
ids_tensor
.
data
<
int64_t
>
();
PADDLE_ENFORCE_EQ
(
row_ids
.
size
(),
x_tensors
.
size
(),
"the number of Rows and X should be the same"
);
PADDLE_ENFORCE_EQ
(
ids
.
size
(),
outs
.
size
(),
"the number of Ids and Out should be the same"
);
auto
x_tensors
=
ctx
.
MultiInput
<
framework
::
LoDTensor
>
(
"X"
);
int
row_ids_size
=
0
;
int
row_size
=
0
;
int
embedding_size
=
0
;
auto
*
out
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
for
(
int
i
=
0
;
i
<
x_tensors
.
size
();
++
i
)
{
const
auto
*
x_tensor
=
x_tensors
[
i
];
const
auto
*
row_id
=
row_ids
[
i
];
int
batch_size
=
0
;
int
embedding_size
=
0
;
for
(
auto
&
input
:
x_tensors
)
{
if
(
framework
::
product
(
input
->
dims
())
!=
0
)
{
if
(
embedding_size
==
0
)
{
embedding_size
=
input
->
dims
()[
1
];
}
PADDLE_ENFORCE_EQ
(
embedding_size
,
input
->
dims
()[
1
],
"embedding size of all input should be the same"
);
batch_size
+=
input
->
dims
()[
0
];
if
(
embedding_size
==
0
)
{
embedding_size
=
x_tensor
->
dims
()[
1
];
}
PADDLE_ENFORCE_EQ
(
embedding_size
,
x_tensor
->
dims
()[
1
],
"embedding size of all input should be the same"
);
row_size
+=
x_tensor
->
dims
()[
0
];
row_ids_size
+=
row_id
->
dims
()[
0
];
}
PADDLE_ENFORCE_EQ
(
batch_size
,
ids_dims
[
0
],
"the batch size of ids and merged embedding value should be the same"
);
row_size
,
row_ids_size
,
"the merged X dim[0] and merged Rows dim[0] should be the same"
);
std
::
unordered_map
<
int64_t
,
std
::
tuple
<
int64_t
,
int64_t
>>
selected_rows_idx_map
;
for
(
int
i
=
0
;
i
<
x_tensors
.
size
();
++
i
)
{
const
auto
*
row_id
=
row_ids
[
i
];
for
(
int
j
=
0
;
j
<
row_id
->
numel
();
++
j
)
{
int64_t
key
=
row_id
->
data
<
int64_t
>
()[
j
];
std
::
tuple
<
int64_t
,
int64_t
>
val
=
std
::
make_tuple
(
i
,
j
);
selected_rows_idx_map
.
insert
(
std
::
make_pair
(
key
,
val
));
}
}
PADDLE_ENFORCE_EQ
(
row_ids_size
,
selected_rows_idx_map
.
size
(),
"the rows and tensor map size should be the same"
);
for
(
int
i
=
0
;
i
<
outs
.
size
();
++
i
)
{
auto
*
out_ids
=
ids
[
i
];
auto
*
out
=
outs
[
i
];
const
size_t
shard_num
=
x_tensors
.
size
(
);
out
->
set_lod
(
out_ids
->
lod
()
);
if
(
shard_num
==
1
)
{
VLOG
(
3
)
<<
"only one shard, we can copy the data directly"
;
TensorCopy
(
*
x_tensors
[
0
],
place
,
out
);
}
else
{
std
::
vector
<
int
>
in_indexs
(
shard_num
,
0
);
int
nums
=
static_cast
<
int
>
(
out_ids
->
dims
()[
0
]);
auto
*
out_data
=
out
->
mutable_data
<
T
>
(
framework
::
make_ddim
({
batch_size
,
embedding_size
}),
place
);
// copy data from ins[shard_num] to out.
for
(
int
i
=
0
;
i
<
ids_dims
[
0
];
++
i
)
{
int64_t
id
=
ids
[
i
];
size_t
shard_id
=
static_cast
<
size_t
>
(
id
)
%
shard_num
;
int
index
=
in_indexs
[
shard_id
];
memcpy
(
out_data
+
embedding_size
*
i
,
x_tensors
[
shard_id
]
->
data
<
T
>
()
+
index
*
embedding_size
,
framework
::
make_ddim
({
nums
,
embedding_size
}),
place
);
for
(
int
j
=
0
;
j
<
nums
;
++
j
)
{
int
id
=
out_ids
->
data
<
int64_t
>
()[
j
];
auto
row_tuple
=
selected_rows_idx_map
[
id
];
int64_t
row_idx
=
std
::
get
<
1
>
(
row_tuple
);
const
auto
*
x_tensor
=
x_tensors
[
std
::
get
<
0
>
(
row_tuple
)];
memcpy
(
out_data
+
embedding_size
*
j
,
x_tensor
->
data
<
T
>
()
+
row_idx
*
embedding_size
,
sizeof
(
T
)
*
embedding_size
);
in_indexs
[
shard_id
]
+=
1
;
}
for
(
size_t
i
=
0
;
i
<
shard_num
;
++
i
)
{
PADDLE_ENFORCE_EQ
(
in_indexs
[
i
],
x_tensors
[
i
]
->
dims
()[
0
],
"after merge, all data in x_tensor should be used"
);
}
}
}
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/split_ids_op.cc
浏览文件 @
415f5006
...
...
@@ -20,20 +20,27 @@ namespace operators {
class
SplitIdsOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"Ids"
,
"(LoDTensor) the input ids with shape{batch_num, 1}"
);
AddOutput
(
"Out"
,
"(LoDTensor) The outputs of the input Ids."
)
AddInput
(
"Ids"
,
"(LoDTensor) the input ids with shape{batch_num, 1}"
)
.
AsDuplicable
();
AddOutput
(
"Out"
,
"(LoDTensors) The outputs of the input Ids."
)
.
AsDuplicable
();
AddComment
(
R"DOC(
Split a LoDTensor of Ids into multi LoDTensors, the number is pserver's number
Example:
Input:
X = [
1,2,3,4,5,6
]
X = [
[1,2,3,4,5,6],[2,3]
]
Out(3 output):
out0 = [3, 6]
out1 = [1, 4]
out2 = [2, 5]
if compress is True:
out0 = [3, 3, 6]
out1 = [1, 4]
out2 = [2, 2, 5]
else:
out0 = [3, 6]
out1 = [1, 4]
out2 = [2, 5]
)DOC"
);
}
};
...
...
@@ -43,16 +50,24 @@ class SplitIdsOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Ids"
),
"SplitIdsOp must has input Ids."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
s
(
"Ids"
),
"SplitIdsOp must has input Ids."
);
PADDLE_ENFORCE
(
ctx
->
HasOutputs
(
"Out"
),
"SplitIdsOp must has output Out."
);
auto
ids_var_type
=
ctx
->
GetInputsVarType
(
"Ids"
).
front
();
auto
ids_dims
=
ctx
->
GetInputDim
(
"Ids"
);
auto
ids_dims
=
ctx
->
GetInput
s
Dim
(
"Ids"
);
if
(
ids_var_type
==
framework
::
proto
::
VarType
::
LOD_TENSOR
)
{
PADDLE_ENFORCE_EQ
(
ids_dims
.
size
(),
2
);
PADDLE_ENFORCE_EQ
(
ids_dims
[
1
],
1
);
PADDLE_ENFORCE_EQ
(
ids_dims
[
0
].
size
(),
2
);
}
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
MultiInput
<
framework
::
Tensor
>
(
"Ids"
).
front
()
->
type
()),
ctx
.
GetPlace
());
}
};
class
SplitIdsOpInferVarType
:
public
framework
::
VarTypeInference
{
...
...
@@ -66,12 +81,28 @@ class SplitIdsOpInferVarType : public framework::VarTypeInference {
}
};
class
SplitIdsOpGradMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
auto
grad
=
new
framework
::
OpDesc
();
grad
->
SetType
(
"concat"
);
grad
->
SetInput
(
"X"
,
OutputGrad
(
"Out"
));
grad
->
SetOutput
(
"Out"
,
InputGrad
(
"Ids"
));
grad
->
SetAttr
(
"axis"
,
0
);
return
std
::
unique_ptr
<
framework
::
OpDesc
>
(
grad
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
split_ids
,
ops
::
SplitIdsOp
,
ops
::
SplitIdsOpMaker
,
ops
::
SplitIdsOpInferVarType
);
ops
::
SplitIdsOpGradMaker
,
ops
::
SplitIdsOpInferVarType
);
REGISTER_OP_CPU_KERNEL
(
split_ids
,
ops
::
SplitIdsOpKernel
<
paddle
::
platform
::
CPUPlace
,
int64_t
>
,
ops
::
SplitIdsOpKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/split_ids_op.h
浏览文件 @
415f5006
...
...
@@ -14,6 +14,8 @@ limitations under the License. */
#pragma once
#include <iterator>
#include <set>
#include <unordered_map>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
...
...
@@ -31,19 +33,39 @@ class SplitIdsOpKernel : public framework::OpKernel<T> {
PADDLE_THROW
(
"SplitIds do not support GPU kernel"
);
}
const
auto
*
ids_var
=
ctx
.
InputVar
(
"Ids"
);
const
auto
ids_vars
=
ctx
.
MultiInputVar
(
"Ids"
);
PADDLE_ENFORCE_GT
(
ids_vars
.
size
(),
0
,
"The number of Ids should > 0"
);
auto
*
ids_var
=
ids_vars
[
0
];
if
(
ids_var
->
IsType
<
framework
::
LoDTensor
>
())
{
const
auto
&
ids_dims
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"Ids"
)
->
dims
();
const
T
*
ids
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"Ids"
)
->
data
<
T
>
();
int
batch_size
=
0
;
const
auto
ids_tensors
=
ctx
.
MultiInput
<
framework
::
LoDTensor
>
(
"Ids"
);
for
(
size_t
i
=
0
;
i
<
ids_tensors
.
size
();
++
i
)
{
batch_size
+=
ids_tensors
[
i
]
->
dims
()[
0
];
}
VLOG
(
4
)
<<
"Get Total BatchSize is: "
<<
batch_size
;
std
::
vector
<
T
>
all_ids
(
batch_size
);
int
offset
=
0
;
for
(
size_t
i
=
0
;
i
<
ids_tensors
.
size
();
++
i
)
{
const
auto
*
ids
=
ids_tensors
[
i
];
std
::
memcpy
(
all_ids
.
data
()
+
offset
,
ids
->
data
<
T
>
(),
ids
->
numel
()
*
sizeof
(
T
));
offset
+=
ids
->
numel
();
}
std
::
set
<
T
>
st
(
all_ids
.
begin
(),
all_ids
.
end
());
all_ids
.
assign
(
st
.
begin
(),
st
.
end
());
auto
outs
=
ctx
.
MultiOutput
<
framework
::
LoDTensor
>
(
"Out"
);
const
size_t
shard_num
=
outs
.
size
();
std
::
vector
<
std
::
vector
<
T
>>
out_ids
;
out_ids
.
resize
(
outs
.
size
());
// split id by their shard_num.
for
(
int
i
=
0
;
i
<
ids_dims
[
0
]
;
++
i
)
{
T
id
=
ids
[
i
];
for
(
int
i
=
0
;
i
<
all_ids
.
size
()
;
++
i
)
{
T
id
=
all_
ids
[
i
];
size_t
shard_id
=
static_cast
<
size_t
>
(
id
)
%
shard_num
;
out_ids
[
shard_id
].
push_back
(
id
);
}
...
...
@@ -64,7 +86,7 @@ class SplitIdsOpKernel : public framework::OpKernel<T> {
PADDLE_ENFORCE_EQ
(
ids_dims
[
0
],
static_cast
<
int64_t
>
(
ids_selected_rows
->
rows
().
size
()),
""
);
const
T
*
ids
=
ids_selected_rows
->
value
().
data
<
T
>
();
const
T
*
ids
_data
=
ids_selected_rows
->
value
().
data
<
T
>
();
const
auto
&
ids_rows
=
ids_selected_rows
->
rows
();
auto
outs
=
ctx
.
MultiOutput
<
framework
::
SelectedRows
>
(
"Out"
);
const
size_t
shard_num
=
outs
.
size
();
...
...
@@ -87,7 +109,7 @@ class SplitIdsOpKernel : public framework::OpKernel<T> {
T
*
output
=
out
->
mutable_value
()
->
mutable_data
<
T
>
(
ddim
,
place
);
for
(
int64_t
i
=
0
;
i
<
ddim
[
0
];
++
i
)
{
memcpy
(
output
+
i
*
row_width
,
ids
+
id_to_index
[
out
->
rows
()[
i
]]
*
row_width
,
ids
_data
+
id_to_index
[
out
->
rows
()[
i
]]
*
row_width
,
row_width
*
sizeof
(
T
));
}
}
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/split_selected_rows_op.cc
浏览文件 @
415f5006
...
...
@@ -22,9 +22,9 @@ class SplitSelectedRowsOpMaker : public framework::OpProtoAndCheckerMaker {
void
Make
()
override
{
AddInput
(
"X"
,
"The input SelectedRows."
);
AddOutput
(
"Out"
,
"The outputs of the input SelectedRows."
).
AsDuplicable
();
AddAttr
<
std
::
vector
<
int
>>
(
"height_sections"
,
"Height for each output SelectedRows."
)
.
SetDefault
(
std
::
vector
<
int
>
({}));
AddAttr
<
std
::
vector
<
int
64_t
>>
(
"height_sections"
,
"Height for each output SelectedRows."
)
.
SetDefault
(
std
::
vector
<
int
64_t
>
({}));
AddComment
(
R"DOC(
Split a SelectedRows with a specified rows section.
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/split_selected_rows_op.h
浏览文件 @
415f5006
...
...
@@ -21,7 +21,7 @@ limitations under the License. */
namespace
paddle
{
namespace
operators
{
static
int
FindOutIdx
(
int
row
,
const
std
::
vector
<
int
>&
abs_sections
)
{
static
int
FindOutIdx
(
int
row
,
const
std
::
vector
<
int
64_t
>&
abs_sections
)
{
for
(
size_t
i
=
1
;
i
<
abs_sections
.
size
();
++
i
)
{
if
(
row
<
abs_sections
[
i
])
{
return
i
-
1
;
...
...
@@ -30,9 +30,9 @@ static int FindOutIdx(int row, const std::vector<int>& abs_sections) {
return
abs_sections
.
size
()
-
1
;
}
static
std
::
vector
<
int
>
ToAbsoluteSection
(
const
std
::
vector
<
int
>&
height_sections
)
{
std
::
vector
<
int
>
abs_sections
;
static
std
::
vector
<
int
64_t
>
ToAbsoluteSection
(
const
std
::
vector
<
int
64_t
>&
height_sections
)
{
std
::
vector
<
int
64_t
>
abs_sections
;
abs_sections
.
resize
(
height_sections
.
size
());
abs_sections
[
0
]
=
0
;
for
(
size_t
i
=
1
;
i
<
height_sections
.
size
();
++
i
)
{
...
...
@@ -47,7 +47,7 @@ class SplitSelectedRowsOpKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
x
=
ctx
.
Input
<
framework
::
SelectedRows
>
(
"X"
);
auto
outs
=
ctx
.
MultiOutput
<
framework
::
SelectedRows
>
(
"Out"
);
auto
height_sections
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"height_sections"
);
auto
height_sections
=
ctx
.
Attr
<
std
::
vector
<
int
64_t
>>
(
"height_sections"
);
auto
abs_sections
=
ToAbsoluteSection
(
height_sections
);
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/sum_op.h
浏览文件 @
415f5006
...
...
@@ -83,79 +83,54 @@ class SumKernel : public framework::OpKernel<T> {
}
}
}
else
if
(
out_var
->
IsType
<
framework
::
SelectedRows
>
())
{
std
::
unique_ptr
<
framework
::
SelectedRows
>
in0
;
if
(
in_place
)
{
// If is in_place, we store the input[0] to in0
auto
&
in_sel0
=
in_vars
[
0
]
->
Get
<
SelectedRows
>
();
auto
&
rows
=
in_sel0
.
rows
();
#ifdef PADDLE_WITH_CUDA
std
::
vector
<
int64_t
>
rows_in_cpu
;
rows_in_cpu
.
reserve
(
rows
.
size
());
for
(
auto
item
:
rows
)
{
rows_in_cpu
.
push_back
(
item
);
}
in0
.
reset
(
new
framework
::
SelectedRows
(
rows_in_cpu
,
in_sel0
.
height
()));
#else
in0
.
reset
(
new
framework
::
SelectedRows
(
rows
,
in_sel0
.
height
()));
#endif
in0
->
mutable_value
()
->
ShareDataWith
(
in_sel0
.
value
());
if
(
in_place
&&
in_vars
.
size
()
<
2
)
{
return
;
}
auto
get_selected_row
=
[
&
](
size_t
i
)
->
const
SelectedRows
&
{
if
(
i
==
0
&&
in0
)
{
return
*
in0
.
get
();
}
else
{
return
in_vars
[
i
]
->
Get
<
SelectedRows
>
();
std
::
vector
<
const
paddle
::
framework
::
SelectedRows
*>
inputs
;
SelectedRows
temp_in0
;
if
(
in_place
)
{
auto
&
in0
=
in_vars
[
0
]
->
Get
<
SelectedRows
>
();
temp_in0
.
set_height
(
in0
.
height
());
temp_in0
.
set_rows
(
in0
.
rows
());
framework
::
TensorCopy
(
in0
.
value
(),
in0
.
place
(),
context
.
device_context
(),
temp_in0
.
mutable_value
());
inputs
.
push_back
(
&
temp_in0
);
for
(
size_t
i
=
1
;
i
<
in_vars
.
size
();
++
i
)
{
auto
&
in
=
in_vars
[
i
]
->
Get
<
SelectedRows
>
();
if
(
in
.
rows
().
size
()
>
0
)
{
inputs
.
push_back
(
&
in
);
}
}
}
else
{
for
(
auto
&
in_var
:
in_vars
)
{
auto
&
in
=
in_var
->
Get
<
SelectedRows
>
();
if
(
in
.
rows
().
size
()
>
0
)
{
inputs
.
push_back
(
&
in_var
->
Get
<
SelectedRows
>
());
}
}
}
;
}
auto
*
out
=
context
.
Output
<
SelectedRows
>
(
"Out"
);
out
->
mutable_rows
()
->
clear
();
auto
*
out_value
=
out
->
mutable_value
();
// Runtime InferShape
size_t
first_dim
=
0
;
for
(
size_t
i
=
0
;
i
<
in_num
;
i
++
)
{
auto
&
sel_row
=
get_selected_row
(
i
);
first_dim
+=
sel_row
.
rows
().
size
();
}
std
::
vector
<
int64_t
>
in_dim
;
for
(
size_t
i
=
0
;
i
<
in_num
;
i
++
)
{
auto
&
sel_row
=
get_selected_row
(
i
);
if
(
sel_row
.
rows
().
size
()
>
0
)
{
in_dim
=
framework
::
vectorize
(
sel_row
.
value
().
dims
());
bool
has_data
=
false
;
for
(
auto
&
in
:
inputs
)
{
if
(
in
->
rows
().
size
()
>
0
)
{
has_data
=
true
;
break
;
}
}
if
(
in_dim
.
empty
()
)
{
VLOG
(
3
)
<<
"WARNING: all the inputs are empty"
;
in_dim
=
framework
::
vectorize
(
get_selected_row
(
in_num
-
1
).
value
().
dims
()
);
if
(
has_data
)
{
math
::
scatter
::
MergeAdd
<
DeviceContext
,
T
>
merge_add
;
merge_add
(
context
.
template
device_context
<
DeviceContext
>(),
inputs
,
out
);
}
else
{
in_dim
[
0
]
=
static_cast
<
int64_t
>
(
first_dim
);
}
out_value
->
Resize
(
framework
::
make_ddim
(
in_dim
));
out_value
->
mutable_data
<
T
>
(
context
.
GetPlace
());
// if all the input sparse vars are empty, no need to
// merge these vars.
if
(
first_dim
==
0UL
)
{
return
;
}
math
::
SelectedRowsAddTo
<
DeviceContext
,
T
>
functor
;
int64_t
offset
=
0
;
for
(
size_t
i
=
0
;
i
<
in_num
;
i
++
)
{
auto
&
sel_row
=
get_selected_row
(
i
);
if
(
sel_row
.
rows
().
size
()
==
0
)
{
continue
;
}
PADDLE_ENFORCE_EQ
(
out
->
height
(),
sel_row
.
height
());
functor
(
context
.
template
device_context
<
DeviceContext
>(),
sel_row
,
offset
,
out
);
offset
+=
sel_row
.
value
().
numel
();
// no data, just set a empty out tensor.
out
->
mutable_value
()
->
mutable_data
<
T
>
(
framework
::
make_ddim
({
0
}),
context
.
GetPlace
());
}
}
else
if
(
out_var
->
IsType
<
framework
::
LoDTensorArray
>
())
{
auto
&
out_array
=
*
out_var
->
GetMutable
<
framework
::
LoDTensorArray
>
();
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/uniform_random_op.cc
浏览文件 @
415f5006
...
...
@@ -29,7 +29,7 @@ class CPUUniformRandomKernel : public framework::OpKernel<T> {
if
(
out_var
->
IsType
<
framework
::
LoDTensor
>
())
{
tensor
=
out_var
->
GetMutable
<
framework
::
LoDTensor
>
();
}
else
if
(
out_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
shape
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"shape"
);
auto
shape
=
ctx
.
Attr
<
std
::
vector
<
int
64_t
>>
(
"shape"
);
auto
*
selected_rows
=
out_var
->
GetMutable
<
framework
::
SelectedRows
>
();
tensor
=
selected_rows
->
mutable_value
();
tensor
->
Resize
(
framework
::
make_ddim
(
shape
));
...
...
@@ -67,7 +67,7 @@ class UniformRandomOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
->
Attrs
().
Get
<
float
>
(
"min"
)
<
ctx
->
Attrs
().
Get
<
float
>
(
"max"
),
"uniform_random's min must less then max"
);
auto
&
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
auto
&
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
64_t
>>
(
"shape"
);
std
::
vector
<
int64_t
>
temp
;
temp
.
reserve
(
shape
.
size
());
for
(
auto
dim
:
shape
)
{
...
...
@@ -94,7 +94,7 @@ This operator initializes a tensor with random values sampled from a
uniform distribution. The random result is in set [min, max].
)DOC"
);
AddAttr
<
std
::
vector
<
int
>>
(
"shape"
,
"The shape of the output tensor"
);
AddAttr
<
std
::
vector
<
int
64_t
>>
(
"shape"
,
"The shape of the output tensor"
);
AddAttr
<
float
>
(
"min"
,
"Minimum value of uniform random. [default -1.0]."
)
.
SetDefault
(
-
1.0
f
);
AddAttr
<
float
>
(
"max"
,
"Maximun value of uniform random. [default 1.0]."
)
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/operators/uniform_random_op.cu
浏览文件 @
415f5006
...
...
@@ -48,7 +48,7 @@ class GPUUniformRandomKernel : public framework::OpKernel<T> {
if
(
out_var
->
IsType
<
framework
::
LoDTensor
>
())
{
tensor
=
out_var
->
GetMutable
<
framework
::
LoDTensor
>
();
}
else
if
(
out_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
shape
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"shape"
);
auto
shape
=
context
.
Attr
<
std
::
vector
<
int
64_t
>>
(
"shape"
);
tensor
=
out_var
->
GetMutable
<
framework
::
SelectedRows
>
()
->
mutable_value
();
tensor
->
Resize
(
framework
::
make_ddim
(
shape
));
}
else
{
...
...
This diff is collapsed.
Click to expand it.
paddle/fluid/pybind/protobuf.cc
浏览文件 @
415f5006
...
...
@@ -57,6 +57,18 @@ struct variant_caster<V<Ts...>> {
auto
caster
=
make_caster
<
T
>
();
if
(
!
load_success_
&&
caster
.
load
(
src
,
convert
))
{
load_success_
=
true
;
if
(
std
::
is_same
<
T
,
std
::
vector
<
float
>>::
value
)
{
auto
caster_ints
=
make_caster
<
std
::
vector
<
int64_t
>>
();
if
(
caster_ints
.
load
(
src
,
convert
))
{
VLOG
(
4
)
<<
"This value are floats and int64_ts satisfy "
"simultaneously, will set it's type to "
"std::vector<int64_t>"
;
value
=
cast_op
<
std
::
vector
<
int64_t
>>
(
caster_ints
);
return
true
;
}
}
value
=
cast_op
<
T
>
(
caster
);
return
true
;
}
...
...
@@ -259,6 +271,8 @@ void BindOpDesc(pybind11::module *m) {
pybind11
::
enum_
<
pd
::
proto
::
AttrType
>
(
*
m
,
"AttrType"
,
""
)
.
value
(
"INT"
,
pd
::
proto
::
AttrType
::
INT
)
.
value
(
"INTS"
,
pd
::
proto
::
AttrType
::
INTS
)
.
value
(
"LONG"
,
pd
::
proto
::
AttrType
::
LONG
)
.
value
(
"LONGS"
,
pd
::
proto
::
AttrType
::
LONGS
)
.
value
(
"FLOAT"
,
pd
::
proto
::
AttrType
::
FLOAT
)
.
value
(
"FLOATS"
,
pd
::
proto
::
AttrType
::
FLOATS
)
.
value
(
"STRING"
,
pd
::
proto
::
AttrType
::
STRING
)
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/__init__.py
浏览文件 @
415f5006
...
...
@@ -121,6 +121,9 @@ def __bootstrap__():
read_env_flags
.
append
(
'rpc_server_profile_period'
)
read_env_flags
.
append
(
'rpc_server_profile_path'
)
read_env_flags
.
append
(
'enable_rpc_profiler'
)
read_env_flags
.
append
(
'rpc_send_thread_num'
)
read_env_flags
.
append
(
'rpc_get_thread_num'
)
read_env_flags
.
append
(
'rpc_prefetch_thread_num'
)
if
core
.
is_compiled_with_cuda
():
read_env_flags
+=
[
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/op.py
浏览文件 @
415f5006
...
...
@@ -120,6 +120,8 @@ class OpDescCreationMethod(object):
new_attr
.
strings
.
extend
(
user_defined_attr
)
elif
attr
.
type
==
framework_pb2
.
BOOLEANS
:
new_attr
.
bools
.
extend
(
user_defined_attr
)
elif
attr
.
type
==
framework_pb2
.
LONGS
:
new_attr
.
longs
.
extend
(
user_defined_attr
)
elif
attr
.
type
==
framework_pb2
.
INT_PAIRS
:
for
p
in
user_defined_attr
:
pair
=
new_attr
.
int_pairs
.
add
()
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/tests/unittests/test_dist_ctr.py
浏览文件 @
415f5006
...
...
@@ -18,6 +18,7 @@ import unittest
from
test_dist_base
import
TestDistBase
# FIXME(tangwei): sum op can not handle when inputs is empty.
class
TestDistCTR2x2
(
TestDistBase
):
def
_setup_config
(
self
):
self
.
_sync_mode
=
True
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/tests/unittests/test_dist_simnet_bow.py
浏览文件 @
415f5006
...
...
@@ -42,7 +42,6 @@ class TestDistSimnetBow2x2DenseAsync(TestDistBase):
self
.
_sync_mode
=
False
self
.
_enforce_place
=
"CPU"
#FIXME(typhoonzero): fix async tests later
def
no_test_simnet_bow
(
self
):
need_envs
=
{
"IS_DISTRIBUTED"
:
'0'
,
...
...
@@ -93,7 +92,6 @@ class TestDistSimnetBow2x2SparseAsync(TestDistBase):
# FIXME(tangwei): Learningrate variable is not created on pserver.
"""
class
TestDistSimnetBow2x2LookupTableSync
(
TestDistBase
):
def
_setup_config
(
self
):
self
.
_sync_mode
=
True
...
...
@@ -146,7 +144,7 @@ class TestDistSimnetBow2x2LookupTableNotContainLRSync(TestDistBase):
delta
=
1e-5
,
check_error_log
=
False
,
need_envs
=
need_envs
)
"""
if
__name__
==
"__main__"
:
unittest
.
main
()
This diff is collapsed.
Click to expand it.
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
浏览文件 @
415f5006
...
...
@@ -480,7 +480,7 @@ class TestDistLookupTable(TestDistLookupTableBase):
def
transpiler_test_impl
(
self
):
pserver1
,
startup1
=
self
.
get_pserver
(
self
.
pserver1_ep
)
self
.
assertEqual
(
len
(
pserver1
.
blocks
),
6
)
self
.
assertEqual
(
len
(
pserver1
.
blocks
),
5
)
# 0 listen_and_serv
# 1 optimize for fc_w or fc_b adam
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
1
].
ops
],
...
...
@@ -491,26 +491,32 @@ class TestDistLookupTable(TestDistLookupTableBase):
# 3 prefetch -> lookup_sparse_table for data0
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
3
].
ops
],
[
"lookup_sparse_table"
])
# 4 prefetch -> lookup_sparse_table for data1
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
4
].
ops
],
[
"lookup_sparse_table"
])
# 5 save table
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
5
].
ops
],
[
"save"
])
# 4 save table
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
4
].
ops
],
[
"save"
])
trainer
,
_
=
self
.
get_trainer
()
trainer
,
trainer_startup
=
self
.
get_trainer
()
self
.
assertEqual
(
len
(
trainer
.
blocks
),
1
)
ops
=
[
'split_ids'
,
'prefetch'
,
'merge_ids'
,
'sequence_pool'
,
'split_ids'
,
'prefetch'
,
'merge_ids'
,
'sequence_pool'
,
'concat'
,
'mul'
,
'elementwise_add'
,
'cross_entropy'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'send'
,
'concat_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sum'
,
'split_ids'
,
'send'
,
'send_barrier'
,
'recv'
,
'recv'
,
'fetch_barrier'
'split_ids'
,
'prefetch'
,
'merge_ids'
,
'sequence_pool'
,
'sequence_pool'
,
'concat'
,
'mul'
,
'elementwise_add'
,
'cross_entropy'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'send'
,
'concat_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sum'
,
'split_ids'
,
'send'
,
'send_barrier'
,
'recv'
,
'recv'
,
'fetch_barrier'
]
self
.
assertEqual
([
op
.
type
for
op
in
trainer
.
blocks
[
0
].
ops
],
ops
)
startup_ops
=
[
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'fill_constant'
,
'uniform_random'
,
'recv'
,
'recv'
,
'fetch_barrier'
,
'fake_init'
]
self
.
assertEqual
([
op
.
type
for
op
in
trainer_startup
.
blocks
[
0
].
ops
],
startup_ops
)
class
TestAsyncLocalLookupTable
(
TestDistLookupTableBase
):
def
net_conf
(
self
):
...
...
@@ -553,7 +559,7 @@ class TestAsyncDistLookupTable(TestDistLookupTableBase):
pserver1
,
startup1
=
self
.
get_pserver
(
self
.
pserver1_ep
,
config
,
False
)
self
.
assertEqual
(
len
(
pserver1
.
blocks
),
6
)
self
.
assertEqual
(
len
(
pserver1
.
blocks
),
5
)
# 0 listen_and_serv
# 1 optimize for fc_w or fc_b adam
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
1
].
ops
],
...
...
@@ -563,22 +569,19 @@ class TestAsyncDistLookupTable(TestDistLookupTableBase):
# 3 prefetch -> lookup_sparse_table for data0
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
3
].
ops
],
[
"lookup_sparse_table"
])
# 4 prefetch -> lookup_sparse_table for data1
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
4
].
ops
],
[
"lookup_sparse_table"
])
# 5 save table
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
5
].
ops
],
[
"save"
])
# 4 save table
self
.
assertEqual
([
op
.
type
for
op
in
pserver1
.
blocks
[
4
].
ops
],
[
"save"
])
trainer
,
_
=
self
.
get_trainer
(
config
)
self
.
assertEqual
(
len
(
trainer
.
blocks
),
1
)
ops
=
[
'split_ids'
,
'prefetch'
,
'merge_ids'
,
'sequence_pool'
,
'split_ids'
,
'
prefetch'
,
'merge_ids'
,
'sequence_pool'
,
'concat'
,
'mul
'
,
'
elementwise_add'
,
'cross_entropy'
,
'mean'
,
'fill_constant
'
,
'
mean_grad'
,
'cross_entropy_grad'
,
'elementwise_add_grad'
,
'sen
d'
,
'
mul_grad'
,
'send'
,
'concat_grad'
,
'sequence_pool
_grad'
,
'
lookup_table_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad
'
,
's
um'
,
'split_ids'
,
's
end'
,
'recv'
,
'recv'
'split_ids'
,
'prefetch'
,
'merge_ids'
,
'sequence_pool'
,
'
sequence_pool'
,
'concat'
,
'mul'
,
'elementwise_add
'
,
'
cross_entropy'
,
'mean'
,
'fill_constant'
,
'mean_grad
'
,
'
cross_entropy_grad'
,
'elementwise_add_grad'
,
'send'
,
'mul_gra
d'
,
'
send'
,
'concat_grad'
,
'sequence_pool_grad'
,
'lookup_table
_grad'
,
'
sequence_pool_grad'
,
'lookup_table_grad'
,
'sum'
,
'split_ids
'
,
'send'
,
'recv'
,
'recv'
]
self
.
assertEqual
([
op
.
type
for
op
in
trainer
.
blocks
[
0
].
ops
],
ops
)
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/tests/unittests/test_fake_init_op.py
0 → 100644
浏览文件 @
415f5006
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from
__future__
import
print_function
import
unittest
import
paddle.fluid.core
as
core
from
paddle.fluid.op
import
Operator
class
TestFakeInitOpSelectedRows
(
unittest
.
TestCase
):
def
check_with_place
(
self
,
place
,
is_selected_rows
):
scope
=
core
.
Scope
()
out_var_name
=
'Out'
if
is_selected_rows
:
out_tensor
=
scope
.
var
(
out_var_name
).
get_selected_rows
().
get_tensor
(
)
else
:
out_tensor
=
scope
.
var
(
out_var_name
).
get_tensor
()
var_shape
=
[
4
,
784
]
# create and run fake_init_op
fake_init_op
=
Operator
(
"fake_init"
,
Out
=
out_var_name
,
shape
=
var_shape
)
fake_init_op
.
run
(
scope
,
place
)
self
.
assertEqual
(
var_shape
,
out_tensor
.
_get_dims
())
def
test_fake_init_selected_rows
(
self
):
places
=
[
core
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
core
.
CUDAPlace
(
0
))
for
place
in
places
:
for
is_selected_rows
in
[
True
,
False
]:
self
.
check_with_place
(
place
,
is_selected_rows
)
if
__name__
==
"__main__"
:
unittest
.
main
()
This diff is collapsed.
Click to expand it.
python/paddle/fluid/tests/unittests/test_merge_ids_op.py
浏览文件 @
415f5006
...
...
@@ -22,15 +22,28 @@ from op_test import OpTest
class
TestMergeIdsOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"merge_ids"
ids
=
np
.
array
([[
0
],
[
2
],
[
2
],
[
3
],
[
5
],
[
5
],
[
6
]]).
astype
(
'int64'
)
x0
=
np
.
array
([[
0.1
,
0.2
],
[
0.2
,
0.3
],
[
0.3
,
0.4
]]).
astype
(
'float32'
)
x1
=
np
.
array
([]).
astype
(
'float32'
)
x2
=
np
.
array
([[
0.4
,
0.5
],
[
0.4
,
0.5
],
[
0.5
,
0.6
],
[
0.5
,
0.6
]]).
astype
(
'float32'
)
out
=
np
.
array
([[
0.1
,
0.2
],
[
0.4
,
0.5
],
[
0.4
,
0.5
],
[
0.2
,
0.3
],
[
0.5
,
0.6
],
[
0.5
,
0.6
],
[
0.3
,
0.4
]]).
astype
(
'float32'
)
self
.
inputs
=
{
'Ids'
:
ids
,
"X"
:
[(
'x0'
,
x0
),
(
'x1'
,
x1
),
(
'x2'
,
x2
)]}
self
.
outputs
=
{
'Out'
:
out
}
ids1
=
np
.
array
([[
0
],
[
2
],
[
5
],
[
6
]]).
astype
(
'int64'
)
ids2
=
np
.
array
([[
0
],
[
2
],
[
2
],
[
3
]]).
astype
(
'int64'
)
rows1
=
np
.
array
([[
0
],
[
2
]]).
astype
(
'int64'
)
rows2
=
np
.
array
([[
3
],
[
5
]]).
astype
(
'int64'
)
rows3
=
np
.
array
([[
6
]]).
astype
(
'int64'
)
x0
=
np
.
array
([[
0.1
,
0.2
],
[
0.2
,
0.3
]]).
astype
(
'float32'
)
x1
=
np
.
array
([[
0.3
,
0.4
],
[
0.4
,
0.5
]]).
astype
(
'float32'
)
x2
=
np
.
array
([[
0.5
,
0.6
]]).
astype
(
'float32'
)
out1
=
np
.
array
(
[[
0.1
,
0.2
],
[
0.2
,
0.3
],
[
0.4
,
0.5
],
[
0.5
,
0.6
]]).
astype
(
'float32'
)
out2
=
np
.
array
(
[[
0.1
,
0.2
],
[
0.2
,
0.3
],
[
0.2
,
0.3
],
[
0.3
,
0.4
]]).
astype
(
'float32'
)
self
.
inputs
=
{
'Ids'
:
[(
'ids1'
,
ids1
),
(
'ids2'
,
ids2
)],
"Rows"
:
[(
'rows1'
,
rows1
),
(
'rows2'
,
rows2
),
(
'rows3'
,
rows3
)],
"X"
:
[(
'x0'
,
x0
),
(
'x1'
,
x1
),
(
'x2'
,
x2
)]
}
self
.
outputs
=
{
'Out'
:
[(
'out1'
,
out1
),
(
'out2'
,
out2
)]}
def
test_check_output
(
self
):
self
.
check_output
()
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/tests/unittests/test_split_ids_op.py
浏览文件 @
415f5006
...
...
@@ -25,18 +25,21 @@ from paddle.fluid.op import Operator
class
TestSplitIdsOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"split_ids"
ids
=
np
.
array
([[
0
],
[
2
],
[
2
],
[
3
],
[
5
],
[
5
],
[
6
]]).
astype
(
'int64'
)
ids1
=
np
.
array
([[
0
],
[
2
],
[
2
],
[
3
],
[
5
],
[
5
],
[
6
]]).
astype
(
'int64'
)
ids2
=
np
.
array
([[
6
],
[
2
],
[
3
],
[
3
],
[
5
],
[
2
],
[
6
]]).
astype
(
'int64'
)
ids3
=
np
.
array
([[
2
],
[
2
],
[
2
],
[
3
],
[
5
],
[
5
],
[
6
]]).
astype
(
'int64'
)
out0
=
np
.
array
([[
0
],
[
3
],
[
6
]]).
astype
(
'int64'
)
out1
=
np
.
array
([[]]).
astype
(
'int64'
)
out2
=
np
.
array
([[
2
],
[
2
],
[
5
],
[
5
]]).
astype
(
'int64'
)
self
.
inputs
=
{
'Ids'
:
ids
}
out2
=
np
.
array
([[
2
],
[
5
]]).
astype
(
'int64'
)
self
.
inputs
=
{
'Ids'
:
[(
'ids1'
,
ids1
),
(
'ids2'
,
ids2
),
(
'ids3'
,
ids3
)]
}
self
.
outputs
=
{
'Out'
:
[(
'out0'
,
out0
),
(
'out1'
,
out1
),
(
'out2'
,
out2
)]}
def
test_check_output
(
self
):
self
.
check_output
()
class
TestSplit
eId
s
(
unittest
.
TestCase
):
class
TestSplit
SelectedRow
s
(
unittest
.
TestCase
):
def
get_places
(
self
):
places
=
[
core
.
CPUPlace
()]
return
places
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/tests/unittests/test_split_selected_rows_op.py
浏览文件 @
415f5006
...
...
@@ -99,7 +99,6 @@ class TestSpliteSelectedRows(unittest.TestCase):
out0_grad
.
set_height
(
height
)
out0_grad_tensor
=
out0_grad
.
get_tensor
()
np_array
=
np
.
ones
((
len
(
rows0
),
row_numel
)).
astype
(
"float32"
)
np_array
[
0
,
0
]
=
2.0
out0_grad_tensor
.
set
(
np_array
,
place
)
out1_grad
=
scope
.
var
(
"out1@GRAD"
).
get_selected_rows
()
...
...
@@ -108,7 +107,6 @@ class TestSpliteSelectedRows(unittest.TestCase):
out1_grad
.
set_height
(
height
)
out1_grad_tensor
=
out1_grad
.
get_tensor
()
np_array
=
np
.
ones
((
len
(
rows1
),
row_numel
)).
astype
(
"float32"
)
np_array
[
0
,
1
]
=
4.0
out1_grad_tensor
.
set
(
np_array
,
place
)
x_grad
=
scope
.
var
(
"X@GRAD"
).
get_selected_rows
()
...
...
@@ -121,11 +119,13 @@ class TestSpliteSelectedRows(unittest.TestCase):
grad_op
.
run
(
scope
,
place
)
self
.
assertEqual
(
x_grad
.
rows
(),
rows0
+
rows1
)
merged_rows
=
set
(
rows0
+
rows1
)
self
.
assertEqual
(
set
(
x_grad
.
rows
()),
set
(
rows0
+
rows1
))
self
.
assertEqual
(
x_grad
.
height
(),
height
)
print
(
np
.
array
(
x_grad
.
get_tensor
()))
self
.
assertAlmostEqual
(
2.0
,
np
.
array
(
x_grad
.
get_tensor
())[
0
,
0
])
self
.
assertAlmostEqual
(
4
.0
,
np
.
array
(
x_grad
.
get_tensor
())[
2
,
1
])
self
.
assertAlmostEqual
(
1
.0
,
np
.
array
(
x_grad
.
get_tensor
())[
2
,
1
])
if
__name__
==
"__main__"
:
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/tests/unittests/test_sum_op.py
浏览文件 @
415f5006
...
...
@@ -45,16 +45,30 @@ class TestSumOp(OpTest):
class
TestSelectedRowsSumOp
(
OpTest
):
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
self
.
check_input_and_optput
(
scope
,
place
,
True
,
True
,
True
)
self
.
check_input_and_optput
(
scope
,
place
,
False
,
True
,
True
)
self
.
check_input_and_optput
(
scope
,
place
,
False
,
False
,
True
)
self
.
check_input_and_optput
(
scope
,
place
,
False
,
False
,
False
)
def
check_with_place
(
self
,
place
,
inplace
):
self
.
height
=
10
self
.
row_numel
=
12
self
.
rows
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
]
self
.
check_input_and_optput
(
core
.
Scope
(),
place
,
inplace
,
True
,
True
,
True
)
self
.
check_input_and_optput
(
core
.
Scope
(),
place
,
inplace
,
False
,
True
,
True
)
self
.
check_input_and_optput
(
core
.
Scope
(),
place
,
inplace
,
False
,
False
,
True
)
self
.
check_input_and_optput
(
core
.
Scope
(),
place
,
inplace
,
False
,
False
,
False
)
def
_get_array
(
self
,
row_num
,
row_numel
):
array
=
np
.
ones
((
row_num
,
row_numel
)).
astype
(
"float32"
)
for
i
in
range
(
row_num
):
array
[
i
]
*=
i
return
array
def
check_input_and_optput
(
self
,
scope
,
place
,
inplace
,
w1_has_data
=
False
,
w2_has_data
=
False
,
w3_has_data
=
False
):
...
...
@@ -64,35 +78,43 @@ class TestSelectedRowsSumOp(OpTest):
self
.
create_selected_rows
(
scope
,
place
,
"W3"
,
w3_has_data
)
# create Out Variable
out
=
scope
.
var
(
'Out'
).
get_selected_rows
()
if
inplace
:
out_var_name
=
"W1"
else
:
out_var_name
=
"Out"
out
=
scope
.
var
(
out_var_name
).
get_selected_rows
()
# create and run sum operator
sum_op
=
Operator
(
"sum"
,
X
=
[
"W1"
,
"W2"
,
"W3"
],
Out
=
'Out'
)
sum_op
=
Operator
(
"sum"
,
X
=
[
"W1"
,
"W2"
,
"W3"
],
Out
=
out_var_name
)
sum_op
.
run
(
scope
,
place
)
has_data_w_num
=
0
for
w
in
[
w1_has_data
,
w2_has_data
,
w3_has_data
]:
if
not
w
:
for
has_data
in
[
w1_has_data
,
w2_has_data
,
w3_has_data
]:
if
has_data
:
has_data_w_num
+=
1
self
.
assertEqual
(
7
*
has_data_w_num
,
len
(
out
.
rows
()))
if
has_data_w_num
>
0
:
self
.
assertEqual
(
len
(
out
.
rows
()),
7
)
self
.
assertTrue
(
np
.
array_equal
(
np
.
array
(
out
.
get_tensor
()),
self
.
_get_array
(
len
(
self
.
rows
),
self
.
row_numel
)
*
has_data_w_num
))
else
:
self
.
assertEqual
(
len
(
out
.
rows
()),
0
)
def
create_selected_rows
(
self
,
scope
,
place
,
var_name
,
isEmpty
):
def
create_selected_rows
(
self
,
scope
,
place
,
var_name
,
has_data
):
# create and initialize W Variable
if
not
isEmpty
:
rows
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
]
row_numel
=
12
if
has_data
:
rows
=
self
.
rows
else
:
rows
=
[]
row_numel
=
12
var
=
scope
.
var
(
var_name
)
w_selected_rows
=
var
.
get_selected_rows
()
w_selected_rows
.
set_height
(
len
(
rows
)
)
w_selected_rows
.
set_height
(
self
.
height
)
w_selected_rows
.
set_rows
(
rows
)
w_array
=
np
.
ones
((
len
(
rows
),
row_numel
)).
astype
(
"float32"
)
for
i
in
range
(
len
(
rows
)):
w_array
[
i
]
*=
i
w_array
=
self
.
_get_array
(
len
(
rows
),
self
.
row_numel
)
w_tensor
=
w_selected_rows
.
get_tensor
()
w_tensor
.
set
(
w_array
,
place
)
...
...
@@ -100,9 +122,11 @@ class TestSelectedRowsSumOp(OpTest):
def
test_w_is_selected_rows
(
self
):
places
=
[
core
.
CPUPlace
()]
# currently only support CPU
if
core
.
is_compiled_with_cuda
():
places
.
append
(
core
.
CUDAPlace
(
0
))
for
place
in
places
:
self
.
check_with_place
(
place
)
for
inplace
in
[
True
,
False
]:
self
.
check_with_place
(
place
,
inplace
)
if
__name__
==
"__main__"
:
...
...
This diff is collapsed.
Click to expand it.
python/paddle/fluid/transpiler/distribute_transpiler.py
浏览文件 @
415f5006
...
...
@@ -475,6 +475,26 @@ class DistributeTranspiler(object):
delete_ops
(
self
.
origin_program
.
global_block
(),
self
.
optimize_ops
)
delete_ops
(
self
.
origin_program
.
global_block
(),
lr_ops
)
# delete table init op
if
self
.
has_distributed_lookup_table
:
table_var
=
self
.
startup_program
.
global_block
().
vars
[
self
.
table_name
]
table_param_init_op
=
[]
for
op
in
self
.
startup_program
.
global_block
().
ops
:
if
self
.
table_name
in
op
.
output_arg_names
:
table_param_init_op
.
append
(
op
)
init_op_num
=
len
(
table_param_init_op
)
if
init_op_num
!=
1
:
raise
ValueError
(
"table init op num should be 1, now is "
+
str
(
init_op_num
))
table_init_op
=
table_param_init_op
[
0
]
self
.
startup_program
.
global_block
().
append_op
(
type
=
"fake_init"
,
inputs
=
{},
outputs
=
{
"Out"
:
table_var
},
attrs
=
{
"shape"
:
table_init_op
.
attr
(
'shape'
)})
delete_ops
(
self
.
startup_program
.
global_block
(),
table_param_init_op
)
self
.
origin_program
.
__str__
()
if
wait_port
:
...
...
@@ -713,7 +733,7 @@ in a single call.")
for
_
,
op
in
enumerate
(
self
.
optimize_ops
):
# optimizer is connected to itself
if
op
.
attr
(
OP_ROLE_VAR_ATTR_NAME
)[
0
]
==
optimize_target_param_name
and
\
op
not
in
global_ops
:
op
not
in
global_ops
:
log
(
"append opt op: "
,
op
.
type
,
op
.
input_arg_names
,
merged_var
)
__append_optimize_op__
(
op
,
per_opt_block
,
...
...
@@ -1034,15 +1054,11 @@ to transpile() call.")
def
_replace_lookup_table_op_with_prefetch
(
self
,
program
,
pserver_endpoints
):
# 1. replace lookup_table_op with split_ids_op -> prefetch_op -> sum_op
# self.all_prefetch_input_vars =
# [[var0_prefetch_in_pserver0, var0_prefetch_in_pserver1]
# [var1_prefetch_in_pserver0, var1_prefetch_in_pserver1]]
self
.
all_in_ids_vars
=
[]
self
.
all_prefetch_input_vars
=
[]
# self.all_prefetch_input_vars =
# [[var0_prefetch_in_pserver0, var0_prefetch_in_pserver1]
# [var1_prefetch_in_pserver0, var1_prefetch_in_pserver1]]
self
.
all_prefetch_output_vars
=
[]
self
.
all_out_emb_vars
=
[]
lookup_table_op_index
=
-
1
continue_search_lookup_table_op
=
True
while
continue_search_lookup_table_op
:
...
...
@@ -1052,72 +1068,68 @@ to transpile() call.")
if
op
.
type
==
LOOKUP_TABLE_TYPE
:
continue_search_lookup_table_op
=
True
lookup_table_op_index
=
list
(
all_ops
).
index
(
op
)
lookup_table_op_index
=
lookup_table_op_index
if
lookup_table_op_index
!=
-
1
else
list
(
all_ops
).
index
(
op
)
ids_name
=
op
.
input
(
"Ids"
)
out_name
=
op
.
output
(
"Out"
)
ids_var
=
program
.
global_block
().
vars
[
ids_name
[
0
]]
prefetch_input_vars
=
self
.
_create_splited_vars
(
source_var
=
ids_var
,
block
=
program
.
global_block
(),
tag
=
"_prefetch_in_"
)
self
.
all_prefetch_input_vars
.
append
(
prefetch_input_vars
)
self
.
all_in_ids_vars
.
append
(
ids_var
)
out_var
=
program
.
global_block
().
vars
[
out_name
[
0
]]
prefetch_output_vars
=
self
.
_create_splited_vars
(
source_var
=
out_var
,
block
=
program
.
global_block
(),
tag
=
"_prefetch_out_"
)
self
.
all_prefetch_output_vars
.
append
(
prefetch_output_vars
)
# insert split_ids_op
program
.
global_block
().
_insert_op
(
index
=
lookup_table_op_index
,
type
=
"split_ids"
,
inputs
=
{
'Ids'
:
[
program
.
global_block
().
vars
[
varname
]
for
varname
in
ids_name
]
},
outputs
=
{
"Out"
:
prefetch_input_vars
})
# insert prefetch_op
program
.
global_block
().
_insert_op
(
index
=
lookup_table_op_index
+
1
,
type
=
"prefetch"
,
inputs
=
{
'X'
:
prefetch_input_vars
},
outputs
=
{
"Out"
:
prefetch_output_vars
},
attrs
=
{
"epmap"
:
pserver_endpoints
,
# FIXME(qiao) temporarily disable this config because prefetch
# is not act as other rpc op, it's more like a forward op
# RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE
})
# insert concat_op
program
.
global_block
().
_insert_op
(
index
=
lookup_table_op_index
+
2
,
type
=
"merge_ids"
,
inputs
=
{
'Ids'
:
[
program
.
global_block
().
vars
[
varname
]
for
varname
in
ids_name
],
'X'
:
prefetch_output_vars
},
outputs
=
{
"Out"
:
[
program
.
global_block
().
vars
[
varname
]
for
varname
in
out_name
]
})
self
.
all_out_emb_vars
.
append
(
out_var
)
# delete lookup_table_op
delete_ops
(
program
.
global_block
(),
[
op
])
# break for loop
break
for
index
in
range
(
len
(
self
.
pserver_endpoints
)):
in_var
=
program
.
global_block
().
create_var
(
name
=
str
(
"prefetch_compress_in_tmp_"
+
str
(
index
)),
type
=
self
.
all_in_ids_vars
[
0
].
type
,
shape
=
self
.
all_in_ids_vars
[
0
].
shape
,
dtype
=
self
.
all_in_ids_vars
[
0
].
dtype
)
self
.
all_prefetch_input_vars
.
append
(
in_var
)
out_var
=
program
.
global_block
().
create_var
(
name
=
str
(
"prefetch_compress_out_tmp_"
+
str
(
index
)),
type
=
self
.
all_out_emb_vars
[
0
].
type
,
shape
=
self
.
all_out_emb_vars
[
0
].
shape
,
dtype
=
self
.
all_out_emb_vars
[
0
].
dtype
)
self
.
all_prefetch_output_vars
.
append
(
out_var
)
# insert split_ids_op
program
.
global_block
().
_insert_op
(
index
=
lookup_table_op_index
,
type
=
"split_ids"
,
inputs
=
{
'Ids'
:
self
.
all_in_ids_vars
},
outputs
=
{
"Out"
:
self
.
all_prefetch_input_vars
})
# insert prefetch_op
program
.
global_block
().
_insert_op
(
index
=
lookup_table_op_index
+
1
,
type
=
"prefetch"
,
inputs
=
{
'X'
:
self
.
all_prefetch_input_vars
},
outputs
=
{
"Out"
:
self
.
all_prefetch_output_vars
},
attrs
=
{
"epmap"
:
pserver_endpoints
,
# FIXME(qiao) temporarily disable this config because prefetch
# is not act as other rpc op, it's more like a forward op
# RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE
})
# insert concat_op
program
.
global_block
().
_insert_op
(
index
=
lookup_table_op_index
+
2
,
type
=
"merge_ids"
,
inputs
=
{
'Ids'
:
self
.
all_in_ids_vars
,
'Rows'
:
self
.
all_prefetch_input_vars
,
'X'
:
self
.
all_prefetch_output_vars
},
outputs
=
{
"Out"
:
self
.
all_out_emb_vars
})
def
_split_table_grad_and_add_send_vars
(
self
,
program
,
pserver_endpoints
):
# 2. add split_ids_op and send_op to send gradient to pservers
...
...
@@ -1134,7 +1146,8 @@ to transpile() call.")
inputs
=
{
'Ids'
:
[
program
.
global_block
().
vars
[
table_grad_name
]]
},
outputs
=
{
"Out"
:
self
.
trainer_side_table_grad_list
})
outputs
=
{
"Out"
:
self
.
trainer_side_table_grad_list
},
attrs
=
{
RPC_OP_ROLE_ATTR_NAME
:
DIST_OP_ROLE_ATTR_VALUE
})
program
.
global_block
().
_insert_op
(
index
=
op_index
+
2
,
type
=
"send"
,
...
...
@@ -1160,32 +1173,31 @@ to transpile() call.")
# STEP: create prefetch block
table_var
=
pserver_program
.
global_block
().
vars
[
self
.
table_name
]
prefetch_var_name_to_block_id
=
[]
for
index
in
range
(
len
(
self
.
all_prefetch_input_vars
)):
prefetch_block
=
pserver_program
.
_create_block
(
optimize_block
.
idx
)
trainer_ids
=
self
.
all_prefetch_input_vars
[
index
][
pserver_index
]
pserver_ids
=
pserver_program
.
global_block
().
create_var
(
name
=
trainer_ids
.
name
,
type
=
trainer_ids
.
type
,
shape
=
trainer_ids
.
shape
,
dtype
=
trainer_ids
.
dtype
)
trainer_out
=
self
.
all_prefetch_output_vars
[
index
][
pserver_index
]
pserver_out
=
pserver_program
.
global_block
().
create_var
(
name
=
trainer_out
.
name
,
type
=
trainer_out
.
type
,
shape
=
trainer_out
.
shape
,
dtype
=
trainer_out
.
dtype
)
prefetch_block
.
append_op
(
type
=
"lookup_sparse_table"
,
inputs
=
{
'Ids'
:
pserver_ids
,
"W"
:
table_var
},
outputs
=
{
"Out"
:
pserver_out
},
attrs
=
{
"is_sparse"
:
True
,
# has no effect on lookup_table op
"is_distributed"
:
True
,
"padding_idx"
:
-
1
})
prefetch_var_name_to_block_id
.
append
(
trainer_ids
.
name
+
":"
+
str
(
prefetch_block
.
idx
))
prefetch_block
=
pserver_program
.
_create_block
(
optimize_block
.
idx
)
trainer_ids
=
self
.
all_prefetch_input_vars
[
pserver_index
]
pserver_ids
=
pserver_program
.
global_block
().
create_var
(
name
=
trainer_ids
.
name
,
type
=
trainer_ids
.
type
,
shape
=
trainer_ids
.
shape
,
dtype
=
trainer_ids
.
dtype
)
trainer_out
=
self
.
all_prefetch_output_vars
[
pserver_index
]
pserver_out
=
pserver_program
.
global_block
().
create_var
(
name
=
trainer_out
.
name
,
type
=
trainer_out
.
type
,
shape
=
trainer_out
.
shape
,
dtype
=
trainer_out
.
dtype
)
prefetch_block
.
append_op
(
type
=
"lookup_sparse_table"
,
inputs
=
{
'Ids'
:
pserver_ids
,
"W"
:
table_var
},
outputs
=
{
"Out"
:
pserver_out
},
attrs
=
{
"is_sparse"
:
True
,
# has no effect on lookup_table op
"is_distributed"
:
True
,
"padding_idx"
:
-
1
})
prefetch_var_name_to_block_id
.
append
(
trainer_ids
.
name
+
":"
+
str
(
prefetch_block
.
idx
))
return
prefetch_var_name_to_block_id
def
_create_table_optimize_block
(
self
,
pserver_index
,
pserver_program
,
...
...
@@ -1364,16 +1376,6 @@ to transpile() call.")
program
.
global_block
().
_sync_with_cpp
()
return
var_mapping
def
_create_splited_vars
(
self
,
source_var
,
block
,
tag
):
return
[
block
.
create_var
(
name
=
str
(
source_var
.
name
+
tag
+
str
(
index
)),
type
=
source_var
.
type
,
shape
=
source_var
.
shape
,
dtype
=
source_var
.
dtype
)
for
index
in
range
(
len
(
self
.
pserver_endpoints
))
]
def
_clone_var
(
self
,
block
,
var
,
persistable
=
True
):
return
block
.
create_var
(
name
=
var
.
name
,
...
...
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