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ca5d96bb
编写于
1月 24, 2019
作者:
Q
Qiao Longfei
浏览文件
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电子邮件补丁
差异文件
complete send lod tensor
上级
be72940b
变更
5
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内联
并排
Showing
5 changed file
with
243 addition
and
1 deletion
+243
-1
paddle/fluid/framework/communicator.h
paddle/fluid/framework/communicator.h
+2
-0
paddle/fluid/operators/distributed/CMakeLists.txt
paddle/fluid/operators/distributed/CMakeLists.txt
+2
-1
paddle/fluid/operators/distributed/parameter_send.cc
paddle/fluid/operators/distributed/parameter_send.cc
+189
-0
paddle/fluid/operators/distributed/parameter_send.h
paddle/fluid/operators/distributed/parameter_send.h
+35
-0
paddle/fluid/operators/distributed_ops/send_op.cc
paddle/fluid/operators/distributed_ops/send_op.cc
+15
-0
未找到文件。
paddle/fluid/framework/communicator.h
浏览文件 @
ca5d96bb
...
...
@@ -41,6 +41,8 @@ class Communicator {
void
receive
()
{}
void
prefetch
()
{}
void
wait
()
{}
private:
...
...
paddle/fluid/operators/distributed/CMakeLists.txt
浏览文件 @
ca5d96bb
...
...
@@ -30,7 +30,7 @@ if(WITH_GRPC)
else
()
set
(
BRPC_SRCS brpc/brpc_client.cc brpc/brpc_server.cc brpc/brpc_sendrecvop_utils.cc brpc/brpc_variable_response.cc brpc/brpc_rdma_pool.cc
)
set_source_files_properties
(
${
BRPC_SRCS
}
parameter_prefetch.cc rpc_server_test.cc brpc/brpc_serde_test.cc collective_server.cc collective_server_test.cc collective_client.cc PROPERTIES COMPILE_FLAGS
${
DISTRIBUTE_COMPILE_FLAGS
}
)
set_source_files_properties
(
${
BRPC_SRCS
}
parameter_prefetch.cc
parameter_send.cc
rpc_server_test.cc brpc/brpc_serde_test.cc collective_server.cc collective_server_test.cc collective_client.cc PROPERTIES COMPILE_FLAGS
${
DISTRIBUTE_COMPILE_FLAGS
}
)
brpc_library
(
sendrecvop_rpc SRCS sendrecvop_utils.cc
request_handler_impl.cc rpc_client.cc rpc_server.cc
...
...
@@ -50,6 +50,7 @@ cc_test(rpc_server_test SRCS rpc_server_test.cc
DEPS
${
RPC_DEPS
}
executor proto_desc lookup_sparse_table_op SERIAL
)
cc_test
(
varhandle_test SRCS varhandle_test.cc DEPS profiler scope
)
cc_library
(
parameter_prefetch SRCS parameter_prefetch.cc DEPS sendrecvop_rpc memory
)
cc_library
(
parameter_send SRCS parameter_send.cc DEPS sendrecvop_rpc memory
)
if
(
WITH_GPU
)
cc_test
(
collective_server_test SRCS collective_server_test.cc
DEPS sendrecvop_rpc executor
${
RPC_DEPS
}
...
...
paddle/fluid/operators/distributed/parameter_send.cc
0 → 100644
浏览文件 @
ca5d96bb
// 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 <set>
#include <string>
#include <vector>
#include "paddle/fluid/operators/distributed/parameter_send.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/tensor.h"
#include "paddle/fluid/operators/distributed/distributed.h"
#include "paddle/fluid/operators/distributed/rpc_client.h"
#include "paddle/fluid/operators/distributed/variable_response.h"
#include "paddle/fluid/operators/distributed_ops/send_recv_util.h"
namespace
paddle
{
namespace
operators
{
namespace
distributed
{
using
LoDTensor
=
framework
::
LoDTensor
;
using
LoDTensor
=
framework
::
LoDTensor
;
using
SelectedRows
=
framework
::
SelectedRows
;
using
DDim
=
framework
::
DDim
;
static
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
;
}
static
std
::
vector
<
int64_t
>
ToAbsoluteSection
(
const
std
::
vector
<
int
>&
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
;
}
static
std
::
vector
<
std
::
vector
<
int64_t
>>
SplitIds
(
const
std
::
vector
<
int64_t
>&
ids_vector
,
const
std
::
vector
<
int
>&
height_section
,
framework
::
Scope
*
scope
)
{
std
::
set
<
int64_t
>
all_ids
;
for
(
auto
id
:
ids_vector
)
{
all_ids
.
insert
(
id
);
}
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
;
}
static
void
SplitIdsIntoMultipleVarsBySection
(
const
std
::
vector
<
std
::
string
>&
in_var_names
,
const
std
::
vector
<
int
>&
height_section
,
const
std
::
vector
<
std
::
vector
<
int64_t
>>&
splited_ids
,
framework
::
Scope
*
scope
)
{
PADDLE_ENFORCE_EQ
(
in_var_names
.
size
(),
height_section
.
size
(),
""
);
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
());
}
}
}
void
send
(
const
std
::
string
&
var_name
,
const
std
::
vector
<
std
::
string
>&
send_varnames
,
const
std
::
vector
<
std
::
string
>&
epmap
,
const
std
::
vector
<
int
>&
height_sections
,
const
framework
::
ExecutionContext
&
context
,
const
framework
::
Scope
&
scope
,
bool
sync
)
{
framework
::
Scope
*
local_scope
=
scope
.
NewTmpScope
();
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
&
cpu_ctx
=
*
pool
.
Get
(
platform
::
CPUPlace
());
auto
&
actual_ctx
=
*
pool
.
Get
(
context
.
GetPlace
());
distributed
::
RPCClient
*
rpc_client
=
distributed
::
RPCClient
::
GetInstance
<
RPCCLIENT_T
>
(
context
.
Attr
<
int
>
(
"trainer_id"
));
auto
*
send_var
=
scope
.
FindVar
(
var_name
);
size_t
out_num
=
send_varnames
.
size
();
if
(
send_var
->
IsType
<
framework
::
LoDTensor
>
())
{
auto
&
send_tensor
=
send_var
->
Get
<
framework
::
LoDTensor
>
();
auto
&
send_tensor_dims
=
send_tensor
.
dims
();
std
::
vector
<
framework
::
DDim
>
outs_dims
;
outs_dims
.
reserve
(
out_num
);
// infer output shape
int
num
=
context
.
Attr
<
int
>
(
"num"
);
if
(
num
>
0
)
{
int64_t
in_axis_dim
=
send_tensor_dims
[
0
];
PADDLE_ENFORCE_EQ
(
in_axis_dim
%
num
,
0
,
"tensor split does not result"
" in an equal division"
);
size_t
out_axis_dim
=
in_axis_dim
/
num
;
for
(
size_t
i
=
0
;
i
<
out_num
;
++
i
)
{
auto
dim
=
send_tensor_dims
;
dim
[
0
]
=
out_axis_dim
;
outs_dims
.
push_back
(
dim
);
}
}
else
if
(
height_sections
.
size
()
>
0
)
{
PADDLE_ENFORCE_EQ
(
height_sections
.
size
(),
out_num
,
"tensor split sections size"
"should be equal to output size."
);
for
(
size_t
i
=
0
;
i
<
out_num
;
++
i
)
{
auto
dim
=
send_tensor_dims
;
dim
[
0
]
=
height_sections
[
i
];
outs_dims
.
push_back
(
dim
);
}
}
// create output var in local scope
size_t
row_offset
=
0
;
for
(
auto
i
=
0
;
i
<
out_num
;
++
i
)
{
auto
*
out
=
local_scope
->
Var
(
send_varnames
[
i
])
->
GetMutable
<
framework
::
Tensor
>
();
*
out
=
send_tensor
.
Slice
(
row_offset
,
row_offset
+
outs_dims
[
i
][
0
]);
row_offset
+=
outs_dims
[
i
][
0
];
}
}
else
if
(
send_var
->
IsType
<
framework
::
LoDTensor
>
())
{
// create output var in local scope
for
(
auto
&
name
:
send_varnames
)
{
local_scope
->
Var
(
name
)
->
GetMutable
<
framework
::
SelectedRows
>
();
}
}
else
{
PADDLE_THROW
(
"unsupported var type"
);
}
std
::
vector
<
distributed
::
VarHandlePtr
>
rets
;
for
(
size_t
i
=
0
;
i
<
send_varnames
.
size
();
i
++
)
{
auto
&
send_var_name
=
send_varnames
[
i
];
auto
&
endpoint
=
epmap
[
i
];
if
(
NeedSend
(
*
local_scope
,
send_var_name
))
{
VLOG
(
3
)
<<
"sending "
<<
send_var_name
<<
" to "
<<
endpoint
;
rets
.
push_back
(
rpc_client
->
AsyncSendVar
(
endpoint
,
cpu_ctx
,
*
local_scope
,
send_var_name
));
}
else
{
VLOG
(
3
)
<<
"don't send non-initialized variable: "
<<
send_varnames
[
i
];
}
}
if
(
sync
)
{
for
(
size_t
i
=
0
;
i
<
rets
.
size
();
i
++
)
{
PADDLE_ENFORCE
(
rets
[
i
]
->
Wait
(),
"internal error in RPCClient"
);
}
}
delete
local_scope
;
}
};
// namespace distributed
};
// namespace operators
};
// namespace paddle
paddle/fluid/operators/distributed/parameter_send.h
0 → 100644
浏览文件 @
ca5d96bb
// 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 <string>
#include <vector>
#include "paddle/fluid/framework/operator.h"
namespace
paddle
{
namespace
operators
{
namespace
distributed
{
void
send
(
const
std
::
string
&
var_name
,
const
std
::
vector
<
std
::
string
>&
send_varnames
,
const
std
::
vector
<
std
::
string
>&
epmap
,
const
std
::
vector
<
int
>&
height_sections
,
const
framework
::
ExecutionContext
&
context
,
const
framework
::
Scope
&
scope
,
bool
sync
);
};
// namespace distributed
};
// namespace operators
};
// namespace paddle
paddle/fluid/operators/distributed_ops/send_op.cc
浏览文件 @
ca5d96bb
...
...
@@ -88,6 +88,21 @@ This operator will send variables to listen_and_serve op at the parameter server
"Server endpoints in the order of input "
"variables for mapping"
)
.
SetDefault
({
"127.0.0.1:6164"
});
AddAttr
<
std
::
vector
<
int
>>
(
"sections"
,
"(vector<int>) "
"the length of each output along the "
"specified axis."
)
.
SetDefault
(
std
::
vector
<
int
>
{});
AddAttr
<
std
::
vector
<
std
::
string
>>
(
"send_varnames"
,
"(vector<string>) "
"the splited output varnames to send to pserver"
)
.
SetDefault
(
std
::
vector
<
std
::
string
>
{});
AddAttr
<
int
>
(
"num"
,
"(int, default 0)"
"Number of sub-tensors. This must evenly divide "
"Input.dims()[axis]"
)
.
SetDefault
(
0
);
}
};
...
...
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