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d3ca359e
编写于
12月 05, 2018
作者:
H
heqiaozhi
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
config init & adapt to interface
上级
45177aa2
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
85 addition
and
32 deletion
+85
-32
paddle/fluid/framework/async_executor.cc
paddle/fluid/framework/async_executor.cc
+49
-6
paddle/fluid/framework/async_executor.h
paddle/fluid/framework/async_executor.h
+2
-1
paddle/fluid/framework/executor_thread_worker.cc
paddle/fluid/framework/executor_thread_worker.cc
+24
-20
paddle/fluid/framework/executor_thread_worker.h
paddle/fluid/framework/executor_thread_worker.h
+10
-5
未找到文件。
paddle/fluid/framework/async_executor.cc
浏览文件 @
d3ca359e
...
...
@@ -67,21 +67,63 @@ void PrepareReaders(std::vector<std::shared_ptr<DataFeed>>& readers, // NOLINT
void
AsyncExecutor
::
ConfigPslib
(
const
std
::
string
&
dist_desc
,
std
::
vector
<
uint64_t
>&
host_sign_list
,
int
node_num
,
int
index
)
{
_pslib_ptr
=
std
::
shared_ptr
<
paddle
::
distributed
::
PSlib
>
(
new
paddle
::
distributed
::
PSlib
());
_pslib_ptr
->
init_and_config
(
dist_desc
,
host_sign_list
,
node_num
,
index
);
//TODO
_pslib_ptr
->
init_and_config
(
dist_desc
,
host_sign_list
,
node_num
,
index
);
//TODO
done
}
void
AsyncExecutor
::
StartServer
()
{
InitParamConfig
();
_pslib_ptr
->
run_server
();
}
void
AsyncExecutor
::
InitParamConfig
()
{
_param_config
.
fea_dim
=
_pslib_ptr
->
get_param
()
->
trainer_param
().
sparse_table
(
0
).
feature_dim
();
//TODO
_param_config
.
slot_dim
=
_param_config
.
fea_dim
-
2
;
//TODO
_param_config
.
tmp_push_dense_wait_times
=
(
int32_t
)(
_pslib_ptr
->
get_param
()
->
trainer_param
().
pull_dense_per_batch
());
_param_config
.
tmp_push_sparse_wait_times
=
(
int32_t
)(
_pslib_ptr
->
get_param
()
->
trainer_param
().
push_dense_per_batch
());
//sparse
for
(
auto
t
=
0u
;
t
<
_pslib_ptr
->
get_param
()
->
trainer_param
().
sparse_table_size
();
++
t
)
{
auto
&
table
=
_pslib_ptr
->
get_param
()
->
trainer_param
().
sparse_table
(
t
);
std
::
vector
<
std
::
string
>
tmp_sparse_variable_name
;
for
(
int
i
=
0u
;
i
<
table
.
slot_value_size
();
++
i
)
{
tmp_sparse_variable_name
.
push_back
(
table
.
slot_value
(
i
));
_param_config
.
slot_alias_to_table
[
table
.
slot_value
(
i
)]
=
table
.
table_id
();
}
std
::
vector
<
std
::
string
>
tmp_sparse_gradient_variable_name
;
for
(
auto
i
=
0u
;
i
<
table
.
slot_gradient_size
();
++
i
)
{
tmp_sparse_gradient_variable_name
.
push_back
(
table
.
slot_gradient
(
i
));
}
_param_config
.
slot_input_vec
[
table
.
table_id
()]
=
std
::
move
(
tmp_sparse_variable_name
);
_param_config
.
gradient_var
[
table
.
table_id
()]
=
std
::
move
(
tmp_sparse_gradient_variable_name
);
_param_config
.
sparse_table_id
.
push_back
(
table
.
table_id
());
}
//dense
for
(
auto
t
=
0u
;
t
<
_pslib_ptr
->
get_param
()
->
trainer_param
().
dense_table_size
();
++
t
)
{
auto
&
table
=
_pslib_ptr
->
get_param
()
->
trainer_param
().
dense_table
(
t
);
std
::
vector
<
std
::
string
>
tmp_dense_variable_name
;
for
(
int
i
=
0u
;
i
<
table
.
dense_variable_name_size
();
++
i
)
{
tmp_dense_variable_name
.
push_back
(
table
.
dense_variable_name
(
i
));
}
std
::
vector
<
std
::
string
>
tmp_dense_gradient_variable_name
;
for
(
auto
i
=
0u
;
i
<
table
.
dense_gradient_variable_name_size
();
++
i
)
{
tmp_dense_gradient_variable_name
.
push_back
(
table
.
dense_gradient_variable_name
(
i
));
}
_param_config
.
dense_variable_name
[
table
.
table_id
()]
=
std
::
move
(
tmp_dense_variable_name
);
_param_config
.
dense_gradient_variable_name
[
table
.
table_id
()]
=
std
::
move
(
tmp_dense_gradient_variable_name
);
_param_config
.
dense_table_id
.
push_back
(
table
.
table_id
());
_param_config
.
dense_table_size
.
push_back
(
table
.
fea_dim
());
//TODO
}
}
void
AsyncExecutor
::
InitModel
()
{
//TODO only rank = 0 do this
std
::
vector
<
int
>
all_dense_table_id
;
//TODO
all_dense_table_id
.
push_back
(
0
);
for
(
auto
table_id
:
all_
dense_table_id
)
{
//std::vector<int> all_dense_table_id; //TODO
//all_dense_table_id.push_back(0); //done
for
(
auto
table_id
:
_param_config
.
dense_table_id
)
{
std
::
vector
<
paddle
::
ps
::
Region
>
regions
;
std
::
vector
<
std
::
string
>
variables
;
//TODO
for
(
auto
&
t
:
variables
)
{
//
std::vector<std::string> variables; //TODO
for
(
auto
&
t
:
_param_config
.
dense_variable_name
[
table_id
]
)
{
Variable
*
var
=
root_scope_
->
FindVar
(
t
);
CHECK
(
var
!=
nullptr
)
<<
"var["
<<
t
<<
"] not found"
;
LoDTensor
*
tensor
=
var
->
GetMutable
<
LoDTensor
>
();
...
...
@@ -131,6 +173,7 @@ void AsyncExecutor::PrepareDenseThread() {
param
.
training_thread_num
=
actual_thread_num
;
param
.
root_scope
=
root_scope_
;
//param.dense_params = &GlobalConfig::instance().dense_variable_name; //TODO
param
.
dense_params
=
&
_param_config
.
dense_variable_name
;
_pull_dense_thread
=
std
::
shared_ptr
<
DensePullThread
>
(
new
DensePullThread
(
param
));
...
...
paddle/fluid/framework/async_executor.h
浏览文件 @
d3ca359e
...
...
@@ -68,7 +68,7 @@ class AsyncExecutor {
void
StartServer
();
void
InitModel
();
void
SaveModel
(
const
std
::
string
&
path
);
void
InitParamConfig
();
private:
void
CreateThreads
(
ExecutorThreadWorker
*
worker
,
const
ProgramDesc
&
main_program
,
...
...
@@ -86,6 +86,7 @@ class AsyncExecutor {
AsyncWorkerParamConfig
_param_config
;
private:
int
actual_thread_num
;
};
...
...
paddle/fluid/framework/executor_thread_worker.cc
浏览文件 @
d3ca359e
...
...
@@ -382,33 +382,38 @@ void AsyncExecutorThreadWorker::BindingSlotVariableMemory() {
}
*/
}
void
AsyncExecutorThreadWorker
::
SetParamConfig
(
AsyncWorkerParamConfig
*
pc
)
{
_param_config
=
pc
;
void
AsyncExecutorThreadWorker
::
SetParamConfig
(
AsyncWorkerParamConfig
*
param_config
)
{
_param_config
=
param_config
;
}
void
AsyncExecutorThreadWorker
::
PrepareParams
()
{
int
table_id
=
0
;
//TODO
PullSparse
(
table_id
);
for
(
auto
&
t
:
_pull_sparse_status
)
{
t
.
wait
();
auto
status
=
t
.
get
();
if
(
status
!=
0
)
{
LOG
(
ERROR
)
<<
"pull sparse failed, status["
<<
status
<<
"]"
;
exit
(
-
1
);
//int table_id = 0; //TODO
for
(
auto
table_id
:
_param_config
->
sparse_table_id
)
{
PullSparse
(
table_id
);
for
(
auto
&
t
:
_pull_sparse_status
)
{
t
.
wait
();
auto
status
=
t
.
get
();
if
(
status
!=
0
)
{
LOG
(
ERROR
)
<<
"pull sparse failed, status["
<<
status
<<
"]"
;
exit
(
-
1
);
}
}
}
_pull_sparse_status
.
resize
(
0
);
FillSparse
(
table_id
);
for
(
auto
table_id
:
_param_config
->
sparse_table_id
)
{
FillSparse
(
table_id
);
}
}
void
AsyncExecutorThreadWorker
::
UpdateParams
()
{
//for (auto i = 0u; i < GlobalConfig::instance().dense_table_id.size(); ++i
) {//TODO
for
(
int
i
=
0
;
i
<
1
;
++
i
)
{
for
(
auto
i
:
_param_config
->
sparse_table_id
)
{
//TODO
//
for (int i = 0; i < 1; ++i) {
PushSparse
(
i
);
}
//for (auto i = 0u; i < GlobalConfig::instance().dense_table_id.size(); ++i) {//TODO
for
(
int
i
=
1
;
i
<
2
;
++
i
)
{
for
(
auto
i
:
_param_config
->
dense_table_id
)
{
PushDense
(
i
);
}
int32_t
tmp_push_dense_wait_times
=
_param_config
->
tmp_push_dense_wait_times
;
//TODO
...
...
@@ -437,14 +442,13 @@ void AsyncExecutorThreadWorker::UpdateParams() {
}
//for (auto dense_table_id : GlobalConfig::instance().dense_table_id) {//TODO
int
dense_table_id
=
1
;
for
(
auto
dense_table_id
:
_param_config
->
dense_table_id
)
{
_pull_dense_thread
->
increase_thread_version
(
thread_id_
,
dense_table_id
);
}
//}
}
void
AsyncExecutorThreadWorker
::
PushDense
(
int
table_id
)
{
//auto table_id = GlobalConfig::instance().dense_table_id[table_id_index]; TODO
std
::
vector
<
paddle
::
ps
::
Region
>
regions
;
//auto& variables = GlobalConfig::instance().dense_gradient_variable_name[table_id];
std
::
vector
<
std
::
string
>
variables
;
...
...
@@ -529,7 +533,7 @@ void AsyncExecutorThreadWorker::FillSparse(int table_id) {
int64_t
*
ids
=
tensor
->
data
<
int64_t
>
();
int
len
=
tensor
->
numel
();
Variable
*
var_emb
=
thread_scope_
->
FindVar
(
_param_config
->
slot_input_vec
[
slot_idx
-
1
]);
Variable
*
var_emb
=
thread_scope_
->
FindVar
(
_param_config
->
slot_input_vec
[
table_id
][
slot_idx
-
1
]);
LoDTensor
*
tensor_emb
=
var_emb
->
GetMutable
<
LoDTensor
>
();
float
*
ptr
=
tensor_emb
->
data
<
float
>
();
...
...
@@ -575,10 +579,10 @@ void AsyncExecutorThreadWorker::PushSparse(int table_id) {
// slot_idx = 0 is label TODO
for
(
auto
slot_idx
=
1u
;
slot_idx
<
feed_vec
.
size
();
++
slot_idx
)
{
if
(
_slot_alias_to_table
[
feed_vec
[
slot_idx
]]
!=
table_id
)
{
if
(
_
param_config
->
slot_alias_to_table
[
feed_vec
[
slot_idx
]]
!=
table_id
)
{
continue
;
}
Variable
*
g_var
=
thread_scope_
->
FindVar
(
_param_config
->
gradient_var
[
slot_idx
-
1
]);
Variable
*
g_var
=
thread_scope_
->
FindVar
(
_param_config
->
gradient_var
[
table_id
][
slot_idx
-
1
]);
LoDTensor
*
g_tensor
=
g_var
->
GetMutable
<
LoDTensor
>
();
//int count = g_tensor->numel();
float
*
g
=
g_tensor
->
data
<
float
>
();
...
...
paddle/fluid/framework/executor_thread_worker.h
浏览文件 @
d3ca359e
...
...
@@ -40,8 +40,14 @@ struct AsyncWorkerParamConfig {
int32_t
tmp_push_dense_wait_times
;
int32_t
tmp_push_sparse_wait_times
;
std
::
vector
<
std
::
string
>
slot_input_vec
;
//6048slot 6050slot //name
std
::
vector
<
std
::
string
>
gradient_var
;
//6048slot_embed
std
::
map
<
uint64_t
,
std
::
vector
<
std
::
string
>>
dense_variable_name
;
std
::
map
<
uint64_t
,
std
::
vector
<
std
::
string
>>
dense_gradient_variable_name
;
std
::
vector
<
int
>
dense_table_id
;
std
::
vector
<
uint32_t
>
dense_table_size
;
// fea_dim for each dense table
std
::
vector
<
int
>
sparse_table_id
;
std
::
map
<
uint64_t
,
std
::
vector
<
std
::
string
>>
slot_input_vec
;
//6048slot 6050slot //name
std
::
map
<
uint64_t
,
std
::
vector
<
std
::
string
>>
gradient_var
;
//6048slot_embed
std
::
unordered_map
<
std
::
string
,
uint64_t
>
slot_alias_to_table
;
//TODO done
};
struct
DensePullThreadParam
{
...
...
@@ -148,7 +154,7 @@ class ExecutorThreadWorker {
virtual
void
SetPSlibPtr
(
std
::
shared_ptr
<
paddle
::
distributed
::
PSlib
>
pslib_ptr
);
virtual
void
SetPullDenseThread
(
std
::
shared_ptr
<
DensePullThread
>
dpt
)
{};
virtual
void
BindingSlotVariableMemory
()
{};
virtual
void
SetParamConfig
(
AsyncWorkerParamConfig
*
p
c
)
{};
virtual
void
SetParamConfig
(
AsyncWorkerParamConfig
*
p
aram_config
)
{};
private:
void
CreateThreadScope
(
const
framework
::
ProgramDesc
&
program
);
void
CreateThreadOperators
(
const
framework
::
ProgramDesc
&
program
);
...
...
@@ -184,7 +190,7 @@ public:
void
SetPSlibPtr
(
std
::
shared_ptr
<
paddle
::
distributed
::
PSlib
>
pslib_ptr
);
void
SetPullDenseThread
(
std
::
shared_ptr
<
DensePullThread
>
dpt
);
void
BindingSlotVariableMemory
();
void
SetParamConfig
(
AsyncWorkerParamConfig
*
p
c
);
void
SetParamConfig
(
AsyncWorkerParamConfig
*
p
aram_config
);
void
TrainFiles
();
void
TrainOneNetwork
();
void
PrepareParams
();
...
...
@@ -209,7 +215,6 @@ private:
std
::
map
<
uint64_t
,
std
::
vector
<
std
::
vector
<
float
>>>
_feature_value
;
std
::
map
<
uint64_t
,
std
::
vector
<
std
::
vector
<
float
>>>
_feature_push_value
;
std
::
unordered_map
<
std
::
string
,
uint64_t
>
_slot_alias_to_table
;
//TODO
std
::
shared_ptr
<
paddle
::
distributed
::
PSlib
>
_pslib_ptr
;
...
...
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