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4dde9a00
编写于
12月 25, 2017
作者:
T
typhoonzero
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix send recv unit test
上级
e834eb87
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
66 addition
and
160 deletion
+66
-160
paddle/framework/operator.h
paddle/framework/operator.h
+3
-0
paddle/operators/detail/send_recv_impl.h
paddle/operators/detail/send_recv_impl.h
+2
-0
paddle/operators/recv_op.cc
paddle/operators/recv_op.cc
+30
-14
paddle/operators/send_op.cc
paddle/operators/send_op.cc
+11
-6
paddle/operators/send_recv_op_benchmark.cc
paddle/operators/send_recv_op_benchmark.cc
+0
-120
paddle/operators/send_recv_op_test.cc
paddle/operators/send_recv_op_test.cc
+17
-19
python/paddle/v2/fluid/distribute_transpiler.py
python/paddle/v2/fluid/distribute_transpiler.py
+3
-1
未找到文件。
paddle/framework/operator.h
浏览文件 @
4dde9a00
...
...
@@ -84,6 +84,9 @@ class OperatorBase {
/// Net will call this function to Run an op.
virtual
void
Run
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
=
0
;
// FIXME(typhoonzero): this is only used for recv_op to stop event_loop.
virtual
void
Stop
()
{}
virtual
bool
IsNetOp
()
const
{
return
false
;
}
virtual
bool
SupportGPU
()
const
{
return
false
;
}
...
...
paddle/operators/detail/send_recv_impl.h
浏览文件 @
4dde9a00
...
...
@@ -62,6 +62,8 @@ class SendRecvServerImpl final : public SendRecvService::Service {
const
TensorWithName
Get
()
{
return
this
->
var_recv_queue_
.
Pop
();
}
void
Push
(
const
TensorWithName
&
msg
)
{
this
->
var_recv_queue_
.
Push
(
msg
);
}
private:
// received variable from RPC, operators fetch variable from this queue.
SimpleBlockQueue
<
TensorWithName
>
var_recv_queue_
;
...
...
paddle/operators/recv_op.cc
浏览文件 @
4dde9a00
/* Copyright (c) 2016 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
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
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. */
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 <stdint.h>
#include <sys/stat.h>
...
...
@@ -28,6 +28,8 @@
#include "paddle/operators/detail/send_recv_impl.h"
#include "paddle/operators/detail/simple_block_queue.h"
#define LISTEN_TERMINATE_MESSAGE "TERMINATE@RECV"
namespace
paddle
{
namespace
operators
{
...
...
@@ -57,7 +59,12 @@ class RecvOp : public framework::OperatorBase {
}
}
virtual
~
RecvOp
()
{
void
Stop
()
override
{
detail
::
TensorWithName
term_msg
;
term_msg
.
first
=
LISTEN_TERMINATE_MESSAGE
;
LOG
(
ERROR
)
<<
"push term msg"
;
rpc_service_
->
Push
(
term_msg
);
LOG
(
ERROR
)
<<
"push term msg over"
;
rpc_server_
->
Shutdown
();
server_thread_
->
join
();
}
...
...
@@ -83,13 +90,19 @@ class RecvOp : public framework::OperatorBase {
size_t
param_count
=
param_list
.
size
();
rpc_service_
->
Reset
();
// TODO(typhoonzero): change this to a while_op for every cluster-batch.
while
(
true
)
{
bool
exit_flag
=
false
;
while
(
!
exit_flag
)
{
// Get from multiple trainers, we don't care about order in which
// the gradient arrives, just add suffix 0~n then average the gradient.
for
(
size_t
i
=
0
;
i
<
param_count
*
trainer_count
;
++
i
)
{
// blocking get one var from client.
const
detail
::
TensorWithName
&
v
=
rpc_service_
->
Get
();
auto
grad_var_name
=
v
.
first
;
LOG
(
ERROR
)
<<
"recved varname"
<<
grad_var_name
;
if
(
grad_var_name
==
LISTEN_TERMINATE_MESSAGE
)
{
exit_flag
=
true
;
break
;
}
auto
it
=
std
::
find
(
grad_list
.
begin
(),
grad_list
.
end
(),
grad_var_name
);
std
::
string
param_var_name
;
if
(
it
!=
grad_list
.
end
())
{
...
...
@@ -114,8 +127,11 @@ class RecvOp : public framework::OperatorBase {
auto
*
tensor
=
var
->
GetMutable
<
framework
::
LoDTensor
>
();
// FIXME(typhoonzero): do not copy
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Get
();
auto
&
dev_ctx
=
*
pool
.
Borrow
(
place
);
framework
::
CopyFrom
(
v
.
second
,
place
,
dev_ctx
,
tensor
);
auto
&
dev_ctx
=
*
pool
.
Borrow
(
dev_place
);
framework
::
CopyFrom
(
v
.
second
,
dev_place
,
dev_ctx
,
tensor
);
}
if
(
exit_flag
)
{
break
;
}
rpc_service_
->
Reset
();
...
...
@@ -123,7 +139,7 @@ class RecvOp : public framework::OperatorBase {
framework
::
proto
::
ProgramDesc
program_desc
;
program_desc
.
ParseFromString
(
program_str
);
framework
::
ProgramDesc
program
(
program_desc
);
framework
::
Executor
executor
(
place
);
framework
::
Executor
executor
(
dev_
place
);
// Run sub graph to get optimized tensor
try
{
executor
.
Run
(
program
,
&
recv_scope
,
0
,
/*global_block*/
...
...
paddle/operators/send_op.cc
浏览文件 @
4dde9a00
...
...
@@ -43,8 +43,9 @@ class SendOp : public framework::OperatorBase {
}
void
Run
(
const
framework
::
Scope
&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
override
{
const
platform
::
Place
&
dev_place
)
const
override
{
auto
ins
=
Inputs
(
"X"
);
auto
outs
=
Outputs
(
"Out"
);
std
::
vector
<
std
::
string
>
epmap
=
Attr
<
std
::
vector
<
std
::
string
>>
(
"epmap"
);
// TODO(typhoonzero): use async calls to send multiple variable asyncly.
for
(
size_t
i
=
0
;
i
<
ins
.
size
();
++
i
)
{
...
...
@@ -55,10 +56,10 @@ class SendOp : public framework::OperatorBase {
}
// TODO(typhoonzero): support async optimization
client_map_
[
epmap
[
0
]]
->
Wait
();
for
(
size_t
i
=
0
;
i
<
in
s
.
size
();
++
i
)
{
bool
ret
=
client_map_
[
epmap
[
i
]]
->
GetVariable
(
scope
,
in
s
[
i
]);
for
(
size_t
i
=
0
;
i
<
out
s
.
size
();
++
i
)
{
bool
ret
=
client_map_
[
epmap
[
i
]]
->
GetVariable
(
scope
,
out
s
[
i
]);
if
(
!
ret
)
{
LOG
(
ERROR
)
<<
"GetVariable error: "
<<
in
s
[
i
];
LOG
(
ERROR
)
<<
"GetVariable error: "
<<
out
s
[
i
];
}
}
}
...
...
@@ -73,6 +74,8 @@ class SendOpMaker : public framework::OpProtoAndCheckerMaker {
SendOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"(Tensor) Input tensor to be send"
).
AsDuplicable
();
AddOutput
(
"Out"
,
"(Tensor) Output tensor to get from server"
)
.
AsDuplicable
();
AddComment
(
R"DOC(
Recv operator
...
...
@@ -80,11 +83,13 @@ This operator will recv tensor from send_op
)DOC"
);
AddAttr
<
std
::
vector
<
std
::
string
>>
(
"endpoints"
,
"(string vector, default 127.0.0.1:6164)"
"Server endpoints to send variables to."
);
"Server endpoints to send variables to."
)
.
SetDefault
({});
AddAttr
<
std
::
vector
<
std
::
string
>>
(
"epmap"
,
"(string vector, default 127.0.0.1:6164)"
"Server endpoints in the order of input "
"variables for mapping"
);
"variables for mapping"
)
.
SetDefault
({});
}
};
...
...
paddle/operators/send_recv_op_benchmark.cc
已删除
100644 → 0
浏览文件 @
e834eb87
/* Copyright (c) 2016 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. */
// TODO(typhoonzero): add python bindings for this test as
// a RemoteOptimizer.
#include <unistd.h>
#include <iostream>
#include <thread>
#include "gtest/gtest.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/program_desc.h"
USE_NO_KERNEL_OP
(
send
);
USE_NO_KERNEL_OP
(
recv
);
USE_OP
(
sum
);
// global for simplicity.
std
::
unique_ptr
<
paddle
::
framework
::
OperatorBase
>
recv_op
;
int
benchmark_count
=
1000
;
// FIXME(typhoonzero): protobuf message size limits the maximum tensor size
int
mat_size
=
512
;
void
InitTensorsInScope
(
paddle
::
framework
::
Scope
&
scope
,
paddle
::
platform
::
CPUPlace
&
place
)
{
paddle
::
platform
::
CPUDeviceContext
ctx
(
place
);
auto
var
=
scope
.
Var
(
"X"
);
auto
tensor
=
var
->
GetMutable
<
paddle
::
framework
::
LoDTensor
>
();
tensor
->
Resize
({
mat_size
,
mat_size
});
float
*
expect
=
tensor
->
mutable_data
<
float
>
(
place
);
for
(
int64_t
i
=
0
;
i
<
tensor
->
numel
();
++
i
)
{
expect
[
i
]
=
static_cast
<
float
>
(
i
)
/
1000.0
f
;
}
auto
out_var
=
scope
.
Var
(
"Out"
);
auto
out_tensor
=
out_var
->
GetMutable
<
paddle
::
framework
::
LoDTensor
>
();
out_tensor
->
Resize
({
mat_size
,
mat_size
});
out_tensor
->
mutable_data
<
float
>
(
place
);
// allocate
}
void
AddOp
(
const
std
::
string
&
type
,
const
paddle
::
framework
::
VariableNameMap
&
inputs
,
const
paddle
::
framework
::
VariableNameMap
&
outputs
,
paddle
::
framework
::
AttributeMap
attrs
,
paddle
::
framework
::
BlockDescBind
*
block
)
{
// insert output
for
(
auto
kv
:
outputs
)
{
for
(
auto
v
:
kv
.
second
)
{
auto
var
=
block
->
Var
(
v
);
var
->
SetDataType
(
paddle
::
framework
::
DataType
::
FP32
);
}
}
// insert op
auto
op
=
block
->
AppendOp
();
op
->
SetType
(
type
);
for
(
auto
&
kv
:
inputs
)
{
op
->
SetInput
(
kv
.
first
,
kv
.
second
);
}
for
(
auto
&
kv
:
outputs
)
{
op
->
SetOutput
(
kv
.
first
,
kv
.
second
);
}
op
->
SetAttrMap
(
attrs
);
}
void
StartServerNet
()
{
paddle
::
framework
::
Scope
scope
;
paddle
::
platform
::
CPUPlace
place
;
InitTensorsInScope
(
scope
,
place
);
// sub program run in recv_op, for simple test we use sum
paddle
::
framework
::
ProgramDescBind
program
;
paddle
::
framework
::
BlockDescBind
*
block
=
program
.
MutableBlock
(
0
);
// X for server side tensors, RX for received tensers, must be of same shape.
AddOp
(
"sum"
,
{{
"X"
,
{
"X"
,
"RX"
}}},
{{
"Out"
,
{
"Out"
}}},
{},
block
);
paddle
::
framework
::
AttributeMap
attrs
;
attrs
.
insert
({
"endpoint"
,
std
::
string
(
"127.0.0.1:6174"
)});
attrs
.
insert
({
"OptimizeBlock"
,
block
});
recv_op
=
paddle
::
framework
::
OpRegistry
::
CreateOp
(
"recv"
,
{{
"RX"
,
{
"RX"
}}},
{{
"Out"
,
{
"Out"
}}},
attrs
);
paddle
::
platform
::
CPUDeviceContext
ctx
(
place
);
recv_op
->
Run
(
scope
,
ctx
);
}
TEST
(
SendRecvBenchmark
,
CPU
)
{
std
::
thread
server_thread
(
StartServerNet
);
sleep
(
5
);
// wait server to start
// local net
paddle
::
framework
::
Scope
scope
;
paddle
::
platform
::
CPUPlace
place
;
InitTensorsInScope
(
scope
,
place
);
paddle
::
framework
::
AttributeMap
attrs
;
attrs
.
insert
({
"endpoint"
,
std
::
string
(
"127.0.0.1:6174"
)});
auto
send_op
=
paddle
::
framework
::
OpRegistry
::
CreateOp
(
"send"
,
{{
"X"
,
{
"X"
}}},
{{
"Out"
,
{
"Out"
}}},
attrs
);
paddle
::
platform
::
CPUDeviceContext
ctx
(
place
);
for
(
int
i
=
0
;
i
<
benchmark_count
;
++
i
)
{
send_op
->
Run
(
scope
,
ctx
);
}
recv_op
.
reset
();
// dtor can shutdown and join server thread.
server_thread
.
join
();
}
paddle/operators/send_recv_op_test.cc
浏览文件 @
4dde9a00
...
...
@@ -13,6 +13,7 @@
limitations under the License. */
#include <unistd.h>
#include <iostream>
#include <string>
#include <thread>
...
...
@@ -83,22 +84,19 @@ void StartServerNet() {
paddle
::
framework
::
ProgramDesc
program
;
paddle
::
framework
::
BlockDesc
*
block
=
program
.
MutableBlock
(
0
);
// X for server side tensors, RX for received tensers, must be of same shape.
AddOp
(
"sum"
,
{{
"X"
,
{
"x0"
,
"x1"
}}},
{{
"Out"
,
{
"
Out
"
}}},
{},
block
);
AddOp
(
"sum"
,
{{
"X"
,
{
"x0"
,
"x1"
}}},
{{
"Out"
,
{
"
x0
"
}}},
{},
block
);
paddle
::
framework
::
AttributeMap
attrs
;
attrs
.
insert
({
"endpoint"
,
std
::
string
(
"127.0.0.1:6174"
)});
attrs
.
insert
({
"ParamList"
,
std
::
vector
<
std
::
string
>
({
"x0"
})});
attrs
.
insert
({
"GradList"
,
std
::
vector
<
std
::
string
>
({
"x1"
})});
std
::
string
program_proto
;
PADDLE_ENFORCE
(
program
.
Proto
()
->
SerializeToString
(
&
program_proto
));
attrs
.
insert
({
"OptimizeProgram"
,
program_proto
});
recv_op
=
paddle
::
framework
::
OpRegistry
::
CreateOp
(
"recv"
,
{{
"RX"
,
{
"x0"
,
"x1"
}}},
{{
"Out"
,
{
"Out"
}}},
attrs
);
paddle
::
platform
::
CPUDeviceContext
ctx
(
place
);
while
(
1
)
{
recv_op
->
Run
(
scope
,
ctx
);
// run once
break
;
}
recv_op
=
paddle
::
framework
::
OpRegistry
::
CreateOp
(
"recv"
,
{{
"RX"
,
{
"x1"
}}},
{},
attrs
);
recv_op
->
Run
(
scope
,
place
);
}
TEST
(
SendRecvOp
,
CPU
)
{
...
...
@@ -110,25 +108,25 @@ TEST(SendRecvOp, CPU) {
InitTensorsInScope
(
scope
,
place
);
paddle
::
framework
::
AttributeMap
attrs
;
attrs
.
insert
({
"endpoint
"
,
std
::
string
(
"127.0.0.1:6174"
)});
attrs
.
insert
({
"endpoint
s"
,
std
::
vector
<
std
::
string
>
({
"127.0.0.1:6174"
}
)});
attrs
.
insert
({
"epmap"
,
std
::
vector
<
std
::
string
>
({
"127.0.0.1:6174"
})});
auto
send_op
=
paddle
::
framework
::
OpRegistry
::
CreateOp
(
"send"
,
{{
"X"
,
{
"x0"
,
"x1"
}}},
{{
"Out"
,
{
"Out"
}}},
attrs
);
paddle
::
platform
::
CPUDeviceContext
ctx
(
place
);
send_op
->
Run
(
scope
,
ctx
);
"send"
,
{{
"X"
,
{
"x1"
}}},
{{
"Out"
,
{
"x0"
}}},
attrs
);
send_op
->
Run
(
scope
,
place
);
auto
in_var
=
scope
.
Var
(
"x
0
"
);
auto
in_var
=
scope
.
Var
(
"x
1
"
);
auto
tensor
=
in_var
->
GetMutable
<
paddle
::
framework
::
LoDTensor
>
();
float
*
expected
=
tensor
->
data
<
float
>
();
auto
out_var
=
scope
.
Var
(
"Out"
);
auto
out_var
=
scope
.
Var
(
"x0"
);
auto
target
=
out_var
->
GetMutable
<
paddle
::
framework
::
LoDTensor
>
();
//
send fail cause output is none.
//
x1 * 2 == x0
EXPECT_NE
(
target
->
memory_size
(),
size_t
(
0
));
float
*
actual
=
target
->
data
<
float
>
();
for
(
int64_t
i
=
0
;
i
<
target
->
numel
();
++
i
)
{
EXPECT_EQ
(
expected
[
i
]
*
2
,
actual
[
i
]);
}
recv_op
.
reset
();
// dtor can shutdown and join server thread.
recv_op
->
Stop
();
server_thread
.
join
();
// recv_op.reset();
}
python/paddle/v2/fluid/distribute_transpiler.py
浏览文件 @
4dde9a00
...
...
@@ -141,16 +141,18 @@ class DistributeTranspiler:
self
.
param_grad_map
=
split_method
(
params_and_grads
,
pserver_endpoints
)
send_op_ordered_inputs
=
[]
send_op_ordered_outputs
=
[]
epmap
=
[]
for
ep
,
v
in
self
.
param_grad_map
.
iteritems
():
send_op_ordered_inputs
.
extend
(
v
[
"grads"
])
send_op_ordered_outputs
.
extend
(
v
[
"params"
])
for
i
in
v
[
"grads"
]:
epmap
.
append
(
ep
)
send_op
=
program
.
global_block
().
append_op
(
type
=
"send"
,
inputs
=
{
"X"
:
send_op_ordered_inputs
},
# inputs is a list of tensors to be send
outputs
=
{},
outputs
=
{
"Out"
:
send_op_ordered_outputs
},
attrs
=
{
"endpoints"
:
pserver_endpoints
,
"epmap"
:
epmap
})
...
...
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