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9d276fe8
编写于
11月 25, 2018
作者:
Q
Qiao Longfei
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
add parameter prefetch
上级
9851a534
变更
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Showing
2 changed file
with
261 addition
and
0 deletion
+261
-0
paddle/fluid/operators/distributed/parameter_prefetch.h
paddle/fluid/operators/distributed/parameter_prefetch.h
+209
-0
paddle/fluid/operators/distributed_ops/lookup_remote_table_op.h
.../fluid/operators/distributed_ops/lookup_remote_table_op.h
+52
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未找到文件。
paddle/fluid/operators/distributed/parameter_prefetch.h
0 → 100644
浏览文件 @
9d276fe8
// 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.
#pragma once
#include <set>
#include <string>
#include <vector>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/framework/var_type.h"
#include "paddle/fluid/operators/distributed/send_recv.grpc.pb.h"
#include "paddle/fluid/operators/distributed/send_recv.pb.h"
#include "google/protobuf/io/coded_stream.h"
#include "google/protobuf/io/zero_copy_stream.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/operators/distributed/grpc_bytebuffer_stream.h"
#include "paddle/fluid/operators/distributed/variable_response.h"
namespace
paddle
{
namespace
operators
{
namespace
distributed
{
using
Tensor
=
framework
::
Tensor
;
using
LoDTensor
=
framework
::
LoDTensor
;
using
SelectedRows
=
framework
::
SelectedRows
;
using
DDim
=
framework
::
DDim
;
constexpr
int64_t
kNoPadding
=
-
1
;
inline
size_t
GetSectionIndex
(
int64_t
id
,
const
std
::
vector
<
int64_t
>&
abs_sections
)
{
for
(
size_t
i
=
1
;
i
<
abs_sections
.
size
();
++
i
)
{
if
(
id
<
abs_sections
[
i
])
{
return
i
-
1
;
}
}
return
abs_sections
.
size
()
-
1
;
}
inline
std
::
vector
<
int64_t
>
ToAbsoluteSection
(
const
std
::
vector
<
int64_t
>&
height_sections
)
{
std
::
vector
<
int64_t
>
abs_sections
;
abs_sections
.
resize
(
height_sections
.
size
());
abs_sections
[
0
]
=
0
;
for
(
size_t
i
=
1
;
i
<
height_sections
.
size
();
++
i
)
{
abs_sections
[
i
]
=
height_sections
[
i
-
1
]
+
abs_sections
[
i
-
1
];
}
return
abs_sections
;
}
inline
std
::
vector
<
std
::
vector
<
int64_t
>>
SplitIds
(
const
std
::
string
&
id_name
,
const
std
::
vector
<
int64_t
>&
height_section
,
framework
::
Scope
*
scope
)
{
auto
&
id_tensor
=
scope
->
Var
(
id_name
)
->
Get
<
framework
::
LoDTensor
>
();
auto
*
id_data
=
id_tensor
.
data
<
int64_t
>
();
std
::
set
<
int64_t
>
all_ids
;
for
(
size_t
i
=
0
;
i
<
id_tensor
.
numel
();
++
i
)
{
all_ids
.
insert
(
id_data
[
i
]);
}
auto
abs_sections
=
ToAbsoluteSection
(
height_section
);
std
::
vector
<
std
::
vector
<
int64_t
>>
splited_ids
;
splited_ids
.
resize
(
height_section
.
size
()
+
1
);
for
(
auto
&
id
:
all_ids
)
{
auto
section_index
=
GetSectionIndex
(
id
,
abs_sections
);
splited_ids
[
section_index
].
push_back
(
id
-
abs_sections
[
section_index
]);
}
return
splited_ids
;
}
inline
void
SplitIdsIntoMultipleVarsBySection
(
const
std
::
string
&
id_name
,
const
std
::
vector
<
std
::
string
>&
in_var_names
,
const
std
::
vector
<
int64_t
>&
height_section
,
const
std
::
vector
<
std
::
vector
<
int64_t
>>&
splited_ids
,
framework
::
Scope
*
scope
)
{
PADDLE_ENFORCE_EQ
(
in_var_names
.
size
(),
height_section
.
size
()
+
1
,
""
);
auto
place
=
platform
::
CPUPlace
();
for
(
size_t
i
=
0
;
i
<
in_var_names
.
size
();
++
i
)
{
auto
*
id_tensor
=
scope
->
Var
(
in_var_names
[
i
])
->
GetMutable
<
framework
::
LoDTensor
>
();
auto
&
ids
=
splited_ids
[
i
];
if
(
!
ids
.
empty
())
{
auto
*
id_tensor_data
=
id_tensor
->
mutable_data
<
int64_t
>
(
framework
::
make_ddim
({
static_cast
<
int64_t
>
(
ids
.
size
()),
1
}),
place
);
memcpy
(
id_tensor_data
,
ids
.
data
(),
sizeof
(
int64_t
)
*
ids
.
size
());
}
}
}
inline
void
MergeMultipleVarsIntoOnBySection
(
const
std
::
string
&
id_name
,
const
std
::
string
&
out_name
,
const
std
::
vector
<
std
::
string
>&
out_var_names
,
const
std
::
vector
<
int64_t
>&
height_section
,
const
std
::
vector
<
std
::
vector
<
int64_t
>>&
splited_ids
,
const
framework
::
ExecutionContext
&
context
,
framework
::
Scope
*
scope
)
{
PADDLE_ENFORCE_EQ
(
out_var_names
.
size
(),
height_section
.
size
()
+
1
,
""
);
auto
cpu_place
=
platform
::
CPUPlace
();
auto
abs_sections
=
ToAbsoluteSection
(
height_section
);
auto
&
id_tensor
=
scope
->
Var
(
id_name
)
->
Get
<
framework
::
LoDTensor
>
();
auto
*
id_data
=
id_tensor
.
data
<
int64_t
>
();
std
::
unordered_map
<
int64_t
,
std
::
vector
<
size_t
>>
id_to_offset
;
for
(
size_t
i
=
0
;
i
<
id_tensor
.
numel
();
++
i
)
{
id_to_offset
[
id_data
[
i
]].
push_back
(
i
);
}
auto
*
out_tensor
=
scope
->
Var
(
out_name
)
->
GetMutable
<
framework
::
LoDTensor
>
();
auto
*
out_tensor_data
=
out_tensor
->
mutable_data
<
float
>
(
context
.
GetPlace
());
for
(
size_t
section_idx
=
0
;
section_idx
<
out_var_names
.
size
();
++
section_idx
)
{
auto
&
ids_in_this_section
=
splited_ids
[
section_idx
];
auto
&
prefetch_out_var
=
scope
->
Var
(
out_var_names
[
section_idx
])
->
Get
<
framework
::
LoDTensor
>
();
const
auto
*
out_var_data
=
prefetch_out_var
.
data
<
float
>
();
auto
&
dims
=
prefetch_out_var
.
dims
();
PADDLE_ENFORCE_EQ
(
dims
.
size
(),
2
,
""
);
PADDLE_ENFORCE_EQ
(
ids_in_this_section
.
size
(),
dims
[
0
]);
auto
row_numel
=
dims
[
1
];
for
(
size_t
i
=
0
;
i
<
dims
[
0
];
++
i
)
{
auto
id
=
ids_in_this_section
[
i
];
auto
origin_id
=
id
+
abs_sections
[
section_idx
];
auto
&
offsets
=
id_to_offset
[
origin_id
];
for
(
auto
&
offset
:
offsets
)
{
// should support GPU tensor
memory
::
Copy
(
cpu_place
,
out_tensor_data
+
offset
*
row_numel
,
cpu_place
,
out_var_data
+
i
*
row_numel
,
sizeof
(
float
)
*
row_numel
);
}
}
}
}
void
prefetch
(
const
std
::
string
&
id_name
,
const
std
::
string
&
out_name
,
const
std
::
string
&
table_name
,
const
std
::
vector
<
std
::
string
>&
epmap
,
const
std
::
vector
<
int64_t
>&
height_sections
,
const
framework
::
ExecutionContext
&
context
)
{
auto
&
local_scope
=
context
.
scope
().
NewScope
();
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
&
ctx
=
*
pool
.
Get
(
context
.
GetPlace
());
distributed
::
RPCClient
*
rpc_client
=
distributed
::
RPCClient
::
GetInstance
<
RPCCLIENT_T
>
(
context
.
Attr
<
int
>
(
"trainer_id"
));
std
::
vector
<
std
::
string
>
in_var_names
;
std
::
vector
<
std
::
string
>
out_var_names
;
for
(
size_t
i
=
0
;
i
<
epmap
.
size
();
++
i
)
{
in_var_names
.
push_back
(
id_name
+
"@"
+
epmap
[
i
]);
out_var_names
.
push_back
(
out_name
+
"@"
+
epmap
[
i
]);
}
auto
splited_ids
=
SplitIds
(
id_name
,
height_sections
,
&
local_scope
);
SplitIdsIntoMultipleVarsBySection
(
id_name
,
in_var_names
,
height_sections
,
splited_ids
,
&
local_scope
);
// create output var in local scope
for
(
auto
&
name
:
out_var_names
)
{
local_scope
.
Var
(
name
)
->
GetMutable
<
framework
::
LoDTensor
>
();
}
std
::
vector
<
distributed
::
VarHandlePtr
>
rets
;
for
(
size_t
i
=
0
;
i
<
in_var_names
.
size
();
i
++
)
{
if
(
NeedSend
(
local_scope
,
in_var_names
[
i
]))
{
VLOG
(
30
)
<<
"sending "
<<
in_var_names
[
i
]
<<
" to "
<<
epmap
[
i
]
<<
" to get "
<<
out_var_names
[
i
]
<<
" back"
;
rets
.
push_back
(
rpc_client
->
AsyncPrefetchVar
(
epmap
[
i
],
ctx
,
local_scope
,
in_var_names
[
i
],
out_var_names
[
i
]));
}
else
{
VLOG
(
30
)
<<
"don't send no-initialied variable: "
<<
out_var_names
[
i
];
}
}
for
(
size_t
i
=
0
;
i
<
rets
.
size
();
i
++
)
{
PADDLE_ENFORCE
(
rets
[
i
]
->
Wait
(),
"internal error in RPCClient"
);
}
MergeMultipleVarsIntoOnBySection
(
id_name
,
out_name
,
out_var_names
,
height_sections
,
splited_ids
,
context
,
&
local_scope
);
context
.
scope
().
DeleteScope
(
&
local_scope
);
}
};
// namespace distributed
};
// namespace operators
};
// namespace paddle
paddle/fluid/operators/distributed_ops/lookup_remote_table_op.h
浏览文件 @
9d276fe8
...
...
@@ -149,6 +149,58 @@ inline void MergeMultipleVarsIntoOnBySection(
}
}
void
prefetch
(
const
std
::
string
&
id_name
,
const
std
::
string
&
out_name
,
const
std
::
string
&
table_name
,
const
std
::
vector
<
std
::
string
>&
epmap
,
const
std
::
vector
<
int64_t
>&
height_sections
,
const
framework
::
ExecutionContext
&
context
)
{
auto
&
local_scope
=
context
.
scope
().
NewScope
();
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
&
ctx
=
*
pool
.
Get
(
context
.
GetPlace
());
distributed
::
RPCClient
*
rpc_client
=
distributed
::
RPCClient
::
GetInstance
<
RPCCLIENT_T
>
(
context
.
Attr
<
int
>
(
"trainer_id"
));
std
::
vector
<
std
::
string
>
in_var_names
;
std
::
vector
<
std
::
string
>
out_var_names
;
for
(
size_t
i
=
0
;
i
<
epmap
.
size
();
++
i
)
{
in_var_names
.
push_back
(
id_name
+
"@"
+
epmap
[
i
]);
out_var_names
.
push_back
(
out_name
+
"@"
+
epmap
[
i
]);
}
auto
splited_ids
=
SplitIds
(
id_name
,
height_sections
,
&
local_scope
);
SplitIdsIntoMultipleVarsBySection
(
id_name
,
in_var_names
,
height_sections
,
splited_ids
,
&
local_scope
);
// create output var in local scope
for
(
auto
&
name
:
out_var_names
)
{
local_scope
.
Var
(
name
)
->
GetMutable
<
framework
::
LoDTensor
>
();
}
std
::
vector
<
distributed
::
VarHandlePtr
>
rets
;
for
(
size_t
i
=
0
;
i
<
in_var_names
.
size
();
i
++
)
{
if
(
NeedSend
(
local_scope
,
in_var_names
[
i
]))
{
VLOG
(
30
)
<<
"sending "
<<
in_var_names
[
i
]
<<
" to "
<<
epmap
[
i
]
<<
" to get "
<<
out_var_names
[
i
]
<<
" back"
;
rets
.
push_back
(
rpc_client
->
AsyncPrefetchVar
(
epmap
[
i
],
ctx
,
local_scope
,
in_var_names
[
i
],
out_var_names
[
i
]));
}
else
{
VLOG
(
30
)
<<
"don't send no-initialied variable: "
<<
out_var_names
[
i
];
}
}
for
(
size_t
i
=
0
;
i
<
rets
.
size
();
i
++
)
{
PADDLE_ENFORCE
(
rets
[
i
]
->
Wait
(),
"internal error in RPCClient"
);
}
MergeMultipleVarsIntoOnBySection
(
id_name
,
out_name
,
out_var_names
,
height_sections
,
splited_ids
,
context
,
&
local_scope
);
context
.
scope
().
DeleteScope
(
&
local_scope
);
}
template
<
typename
T
>
class
LookupRemoteTableKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
...
...
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