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732f991e
编写于
9月 27, 2019
作者:
W
wangguibao
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
CTR prediction profiling
上级
671f3257
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
91 addition
and
77 deletion
+91
-77
demo-client/src/ctr_prediction.cpp
demo-client/src/ctr_prediction.cpp
+65
-47
demo-serving/op/ctr_prediction_op.cpp
demo-serving/op/ctr_prediction_op.cpp
+24
-24
predictor/src/pdserving.cpp
predictor/src/pdserving.cpp
+2
-6
未找到文件。
demo-client/src/ctr_prediction.cpp
浏览文件 @
732f991e
...
...
@@ -30,7 +30,6 @@ using baidu::paddle_serving::predictor::ctr_prediction::Response;
using
baidu
::
paddle_serving
::
predictor
::
ctr_prediction
::
CTRReqInstance
;
using
baidu
::
paddle_serving
::
predictor
::
ctr_prediction
::
CTRResInstance
;
int
batch_size
=
16
;
int
sparse_num
=
26
;
int
dense_num
=
13
;
int
hash_dim
=
1000001
;
...
...
@@ -157,67 +156,80 @@ void thread_worker(PredictorApi* api,
Request
req
;
Response
res
;
std
::
string
line
;
int
start_index
=
0
;
api
->
thrd_initialize
();
while
(
true
)
{
api
->
thrd_clear
()
;
for
(
int
i
=
0
;
i
<
FLAGS_repeat
;
++
i
)
{
int
start_index
=
0
;
Predictor
*
predictor
=
api
->
fetch_predictor
(
"ctr_prediction_service"
);
if
(
!
predictor
)
{
LOG
(
ERROR
)
<<
"Failed fetch predictor: ctr_prediction_service"
;
return
;
}
while
(
true
)
{
if
(
start_index
>=
data_list
.
size
())
{
break
;
}
req
.
Clear
();
res
.
Clear
();
api
->
thrd_clear
();
// wait for other thread
while
(
g_concurrency
.
load
()
>=
FLAGS_concurrency
)
{
}
g_concurrency
++
;
LOG
(
INFO
)
<<
"Current concurrency "
<<
g_concurrency
.
load
();
Predictor
*
predictor
=
api
->
fetch_predictor
(
"ctr_prediction_service"
);
if
(
!
predictor
)
{
LOG
(
ERROR
)
<<
"Failed fetch predictor: ctr_prediction_service"
;
return
;
}
if
(
create_req
(
&
req
,
data_list
,
start_index
,
FLAGS_batch_size
)
!=
0
)
{
return
;
}
start_index
+=
FLAGS_batch_size
;
req
.
Clear
();
res
.
Clear
();
// wait for other thread
while
(
g_concurrency
.
load
()
>=
FLAGS_concurrency
)
{
}
g_concurrency
++
;
LOG
(
INFO
)
<<
"Current concurrency "
<<
g_concurrency
.
load
();
timeval
start
;
gettimeofday
(
&
start
,
NULL
);
if
(
create_req
(
&
req
,
data_list
,
start_index
,
FLAGS_batch_size
)
!=
0
)
{
return
;
}
start_index
+=
FLAGS_batch_size
;
LOG
(
INFO
)
<<
"start_index = "
<<
start_index
;
if
(
predictor
->
inference
(
&
req
,
&
res
)
!=
0
)
{
LOG
(
ERROR
)
<<
"failed call predictor with req:"
<<
req
.
ShortDebugString
();
return
;
}
g_concurrency
--
;
timeval
start
;
gettimeofday
(
&
start
,
NULL
);
timeval
end
;
gettimeofday
(
&
end
,
NULL
);
uint64_t
elapse_ms
=
(
end
.
tv_sec
*
1000
+
end
.
tv_usec
/
1000
)
-
(
start
.
tv_sec
*
1000
+
start
.
tv_usec
/
1000
);
if
(
predictor
->
inference
(
&
req
,
&
res
)
!=
0
)
{
LOG
(
ERROR
)
<<
"failed call predictor with req:"
<<
req
.
ShortDebugString
();
return
;
}
g_concurrency
--
;
response_time
[
thread_id
].
push_back
(
elapse_ms
);
timeval
end
;
gettimeofday
(
&
end
,
NULL
);
uint64_t
elapse_ms
=
(
end
.
tv_sec
*
1000
+
end
.
tv_usec
/
1000
)
-
(
start
.
tv_sec
*
1000
+
start
.
tv_usec
/
1000
);
if
(
!
FLAGS_enable_profiling
)
{
print_res
(
req
,
res
,
predictor
->
tag
(),
elapse_ms
);
}
response_time
[
thread_id
].
push_back
(
elapse_ms
);
LOG
(
INFO
)
<<
"Done. Current concurrency "
<<
g_concurrency
.
load
();
}
if
(
!
FLAGS_enable_profiling
)
{
print_res
(
req
,
res
,
predictor
->
tag
(),
elapse_ms
);
}
LOG
(
INFO
)
<<
"Done. Current concurrency "
<<
g_concurrency
.
load
();
}
// end while
}
// end for
api
->
thrd_finalize
();
}
void
calc_time
(
int
server_concurrency
,
int
batch_size
)
{
void
calc_time
()
{
std
::
vector
<
int
>
time_list
;
for
(
auto
a
:
response_time
)
{
time_list
.
insert
(
time_list
.
end
(),
a
.
begin
(),
a
.
end
());
}
LOG
(
INFO
)
<<
"Total request : "
<<
(
time_list
.
size
());
LOG
(
INFO
)
<<
"Batch size : "
<<
batch_size
;
LOG
(
INFO
)
<<
"Max concurrency : "
<<
server_concurrency
;
LOG
(
INFO
)
<<
"Batch size : "
<<
FLAGS_batch_size
;
LOG
(
INFO
)
<<
"Max concurrency : "
<<
FLAGS_concurrency
;
LOG
(
INFO
)
<<
"enable_profiling: "
<<
FLAGS_enable_profiling
;
LOG
(
INFO
)
<<
"repeat count: "
<<
FLAGS_repeat
;
float
total_time
=
0
;
float
max_time
=
0
;
float
min_time
=
1000000
;
...
...
@@ -226,21 +238,28 @@ void calc_time(int server_concurrency, int batch_size) {
if
(
time_list
[
i
]
>
max_time
)
max_time
=
time_list
[
i
];
if
(
time_list
[
i
]
<
min_time
)
min_time
=
time_list
[
i
];
}
float
mean_time
=
total_time
/
(
time_list
.
size
());
float
var_time
;
for
(
int
i
=
0
;
i
<
time_list
.
size
();
++
i
)
{
var_time
+=
(
time_list
[
i
]
-
mean_time
)
*
(
time_list
[
i
]
-
mean_time
);
}
var_time
=
var_time
/
time_list
.
size
();
LOG
(
INFO
)
<<
"Total time : "
<<
total_time
/
server_concurrency
<<
" Variance : "
<<
var_time
<<
" Max time : "
<<
max_time
<<
" Min time : "
<<
min_time
;
LOG
(
INFO
)
<<
"Total time : "
<<
total_time
/
FLAGS_concurrency
<<
"ms"
;
LOG
(
INFO
)
<<
"Variance : "
<<
var_time
<<
"ms"
;
LOG
(
INFO
)
<<
"Max time : "
<<
max_time
<<
"ms"
;
LOG
(
INFO
)
<<
"Min time : "
<<
min_time
<<
"ms"
;
float
qps
=
0.0
;
if
(
total_time
>
0
)
qps
=
(
time_list
.
size
()
*
1000
)
/
(
total_time
/
server_concurrency
);
if
(
total_time
>
0
)
{
qps
=
(
time_list
.
size
()
*
1000
)
/
(
total_time
/
FLAGS_concurrency
);
}
LOG
(
INFO
)
<<
"QPS: "
<<
qps
<<
"/s"
;
LOG
(
INFO
)
<<
"Latency statistics: "
;
sort
(
time_list
.
begin
(),
time_list
.
end
());
int
percent_pos_50
=
time_list
.
size
()
*
0.5
;
int
percent_pos_80
=
time_list
.
size
()
*
0.8
;
int
percent_pos_90
=
time_list
.
size
()
*
0.9
;
...
...
@@ -299,7 +318,6 @@ int main(int argc, char** argv) {
}
LOG
(
INFO
)
<<
"data sample file: "
<<
data_filename
;
LOG
(
INFO
)
<<
"enable_profiling: "
<<
FLAGS_enable_profiling
;
if
(
FLAGS_enable_profiling
)
{
LOG
(
INFO
)
<<
"In profiling mode, lot of normal output will be supressed. "
...
...
@@ -330,7 +348,7 @@ int main(int argc, char** argv) {
delete
thread_pool
[
i
];
}
calc_time
(
FLAGS_concurrency
,
batch_size
);
calc_time
();
api
.
destroy
();
return
0
;
...
...
demo-serving/op/ctr_prediction_op.cpp
浏览文件 @
732f991e
...
...
@@ -148,31 +148,31 @@ int CTRPredictionOp::inference() {
int
ret
;
if
(
FLAGS_enable_ctr_profiling
)
{
gettimeofday
(
&
start
,
NULL
);
ret
=
cube
->
seek
(
table_name
,
keys
,
&
values
);
gettimeofday
(
&
end
,
NULL
);
uint64_t
usec
=
end
.
tv_sec
*
1e6
+
end
.
tv_usec
-
start
.
tv_sec
*
1e6
-
start
.
tv_usec
;
// Statistics
mutex_
.
lock
();
cube_time_us_
+=
usec
;
++
cube_req_num_
;
cube_req_key_num_
+=
keys
.
size
();
if
(
cube_req_num_
>=
1000
)
{
LOG
(
INFO
)
<<
"Cube request count: "
<<
cube_req_num_
;
LOG
(
INFO
)
<<
"Cube request key count: "
<<
cube_req_key_num_
;
LOG
(
INFO
)
<<
"Cube request total time: "
<<
cube_time_us_
<<
"us"
;
LOG
(
INFO
)
<<
"Average "
<<
cube_time_us_
/
cube_req_num_
<<
"us/req"
;
LOG
(
INFO
)
<<
"Average "
<<
cube_time_us_
/
cube_req_key_num_
<<
"us/key"
;
}
mutex_
.
unlock
();
}
else
{
ret
=
cube
->
seek
(
table_name
,
keys
,
&
values
);
gettimeofday
(
&
start
,
NULL
);
ret
=
cube
->
seek
(
table_name
,
keys
,
&
values
);
gettimeofday
(
&
end
,
NULL
);
uint64_t
usec
=
end
.
tv_sec
*
1e6
+
end
.
tv_usec
-
start
.
tv_sec
*
1e6
-
start
.
tv_usec
;
// Statistics
mutex_
.
lock
();
cube_time_us_
+=
usec
;
++
cube_req_num_
;
cube_req_key_num_
+=
keys
.
size
();
if
(
cube_req_num_
>=
1000
)
{
LOG
(
INFO
)
<<
"Cube request count: "
<<
cube_req_num_
;
LOG
(
INFO
)
<<
"Cube request key count: "
<<
cube_req_key_num_
;
LOG
(
INFO
)
<<
"Cube request total time: "
<<
cube_time_us_
<<
"us"
;
LOG
(
INFO
)
<<
"Average "
<<
cube_time_us_
/
cube_req_num_
<<
"us/req"
;
LOG
(
INFO
)
<<
"Average "
<<
cube_time_us_
/
cube_req_key_num_
<<
"us/key"
;
cube_time_us_
=
0
;
cube_req_num_
=
0
;
cube_req_key_num_
=
0
;
}
mutex_
.
unlock
();
// Statistics end
if
(
ret
!=
0
)
{
fill_response_with_message
(
res
,
-
1
,
"Query cube for embeddings error"
);
...
...
predictor/src/pdserving.cpp
浏览文件 @
732f991e
...
...
@@ -51,8 +51,6 @@ using baidu::paddle_serving::predictor::FLAGS_port;
using
baidu
::
paddle_serving
::
configure
::
InferServiceConf
;
using
baidu
::
paddle_serving
::
configure
::
read_proto_conf
;
DECLARE_bool
(
logtostderr
);
void
print_revision
(
std
::
ostream
&
os
,
void
*
)
{
#if defined(PDSERVING_VERSION)
os
<<
PDSERVING_VERSION
;
...
...
@@ -69,9 +67,6 @@ static bvar::PassiveStatus<std::string> s_predictor_revision(
DEFINE_bool
(
V
,
false
,
"print version, bool"
);
DEFINE_bool
(
g
,
false
,
"user defined gflag path"
);
DEFINE_bool
(
enable_ctr_profiling
,
false
,
"Enable profiling in CTR prediction demo"
);
DECLARE_string
(
flagfile
);
namespace
bthread
{
...
...
@@ -220,7 +215,8 @@ int main(int argc, char** argv) {
}
LOG
(
INFO
)
<<
"Succ initialize cube"
;
FLAGS_logtostderr
=
false
;
// FATAL messages are output to stderr
FLAGS_stderrthreshold
=
3
;
if
(
ServerManager
::
instance
().
start_and_wait
()
!=
0
)
{
LOG
(
ERROR
)
<<
"Failed start server and wait!"
;
...
...
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