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1b84553f
编写于
3月 08, 2020
作者:
M
MRXLT
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix batch predict
上级
16309001
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
47 addition
and
26 deletion
+47
-26
core/general-client/include/general_model.h
core/general-client/include/general_model.h
+3
-2
core/general-client/src/general_model.cpp
core/general-client/src/general_model.cpp
+34
-19
core/general-client/src/pybind_general_model.cpp
core/general-client/src/pybind_general_model.cpp
+4
-2
python/paddle_serving_client/__init__.py
python/paddle_serving_client/__init__.py
+6
-3
未找到文件。
core/general-client/include/general_model.h
浏览文件 @
1b84553f
...
@@ -91,12 +91,13 @@ class PredictorClient {
...
@@ -91,12 +91,13 @@ class PredictorClient {
const
std
::
vector
<
std
::
string
>&
int_feed_name
,
const
std
::
vector
<
std
::
string
>&
int_feed_name
,
const
std
::
vector
<
std
::
string
>&
fetch_name
);
const
std
::
vector
<
std
::
string
>&
fetch_name
);
std
::
vector
<
std
::
vector
<
std
::
vector
<
float
>>
>
batch_predict
(
std
::
vector
<
PredictorRes
>
batch_predict
(
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
float
>>>&
float_feed_batch
,
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
float
>>>&
float_feed_batch
,
const
std
::
vector
<
std
::
string
>&
float_feed_name
,
const
std
::
vector
<
std
::
string
>&
float_feed_name
,
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
int64_t
>>>&
int_feed_batch
,
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
int64_t
>>>&
int_feed_batch
,
const
std
::
vector
<
std
::
string
>&
int_feed_name
,
const
std
::
vector
<
std
::
string
>&
int_feed_name
,
const
std
::
vector
<
std
::
string
>&
fetch_name
);
const
std
::
vector
<
std
::
string
>&
fetch_name
,
const
int
&
pid
);
private:
private:
PredictorApi
_api
;
PredictorApi
_api
;
...
...
core/general-client/src/general_model.cpp
浏览文件 @
1b84553f
...
@@ -264,26 +264,23 @@ int PredictorClient::predict(const std::vector<std::vector<float>> &float_feed,
...
@@ -264,26 +264,23 @@ int PredictorClient::predict(const std::vector<std::vector<float>> &float_feed,
return
0
;
return
0
;
}
}
std
::
vector
<
std
::
vector
<
std
::
vector
<
float
>>
>
PredictorClient
::
batch_predict
(
std
::
vector
<
PredictorRes
>
PredictorClient
::
batch_predict
(
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
float
>>>
&
float_feed_batch
,
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
float
>>>
&
float_feed_batch
,
const
std
::
vector
<
std
::
string
>
&
float_feed_name
,
const
std
::
vector
<
std
::
string
>
&
float_feed_name
,
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
int64_t
>>>
&
int_feed_batch
,
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
int64_t
>>>
&
int_feed_batch
,
const
std
::
vector
<
std
::
string
>
&
int_feed_name
,
const
std
::
vector
<
std
::
string
>
&
int_feed_name
,
const
std
::
vector
<
std
::
string
>
&
fetch_name
)
{
const
std
::
vector
<
std
::
string
>
&
fetch_name
,
const
int
&
pid
)
{
int
batch_size
=
std
::
max
(
float_feed_batch
.
size
(),
int_feed_batch
.
size
());
int
batch_size
=
std
::
max
(
float_feed_batch
.
size
(),
int_feed_batch
.
size
());
std
::
vector
<
std
::
vector
<
std
::
vector
<
float
>>>
fetch_result_batch
;
std
::
vector
<
std
::
vector
<
std
::
vector
<
float
>>>
fetch_result_batch
;
if
(
fetch_name
.
size
()
==
0
)
{
return
fetch_result_batch
;
std
::
vector
<
PredictorRes
>
predict_res_batch
;
}
Timer
timeline
;
Timer
timeline
;
int64_t
preprocess_start
=
timeline
.
TimeStampUS
();
int64_t
preprocess_start
=
timeline
.
TimeStampUS
();
fetch_result
_batch
.
resize
(
batch_size
);
predict_res
_batch
.
resize
(
batch_size
);
int
fetch_name_num
=
fetch_name
.
size
();
int
fetch_name_num
=
fetch_name
.
size
();
for
(
int
bi
=
0
;
bi
<
batch_size
;
bi
++
)
{
fetch_result_batch
[
bi
].
resize
(
fetch_name_num
);
}
_api
.
thrd_clear
();
_api
.
thrd_clear
();
_predictor
=
_api
.
fetch_predictor
(
"general_model"
);
_predictor
=
_api
.
fetch_predictor
(
"general_model"
);
...
@@ -373,18 +370,36 @@ std::vector<std::vector<std::vector<float>>> PredictorClient::batch_predict(
...
@@ -373,18 +370,36 @@ std::vector<std::vector<std::vector<float>>> PredictorClient::batch_predict(
postprocess_start
=
client_infer_end
;
postprocess_start
=
client_infer_end
;
for
(
int
bi
=
0
;
bi
<
batch_size
;
bi
++
)
{
for
(
int
bi
=
0
;
bi
<
batch_size
;
bi
++
)
{
predict_res_batch
[
bi
].
_int64_map
.
clear
();
predict_res_batch
[
bi
].
_float_map
.
clear
();
for
(
auto
&
name
:
fetch_name
)
{
for
(
auto
&
name
:
fetch_name
)
{
int
idx
=
_fetch_name_to_idx
[
name
];
int
idx
=
_fetch_name_to_idx
[
name
];
int
len
=
res
.
insts
(
bi
).
tensor_array
(
idx
).
data_size
();
int
len
=
res
.
insts
(
bi
).
tensor_array
(
idx
).
data_size
();
VLOG
(
2
)
<<
"fetch name: "
<<
name
;
if
(
_fetch_name_to_type
[
name
]
==
0
)
{
VLOG
(
2
)
<<
"tensor data size: "
<<
len
;
int
len
=
res
.
insts
(
bi
).
tensor_array
(
idx
).
int64_data_size
();
fetch_result_batch
[
bi
][
idx
].
resize
(
len
);
VLOG
(
2
)
<<
"fetch tensor : "
<<
name
<<
" type: int64 len : "
<<
len
;
VLOG
(
2
)
predict_res_batch
[
bi
].
_int64_map
[
name
].
resize
(
1
);
<<
"fetch name "
<<
name
<<
" index "
<<
idx
<<
" first data "
predict_res_batch
[
bi
].
_int64_map
[
name
][
0
].
resize
(
len
);
<<
*
(
const
float
*
)
res
.
insts
(
bi
).
tensor_array
(
idx
).
data
(
0
).
c_str
();
VLOG
(
2
)
<<
"fetch name "
<<
name
<<
" index "
<<
idx
<<
" first data "
/*
<<
res
.
insts
(
bi
).
tensor_array
(
idx
).
int64_data
(
0
);
TBA
for
(
int
i
=
0
;
i
<
len
;
++
i
)
{
*/
predict_res_batch
[
bi
].
_int64_map
[
name
][
0
][
i
]
=
res
.
insts
(
bi
).
tensor_array
(
idx
).
int64_data
(
i
);
}
}
else
if
(
_fetch_name_to_type
[
name
]
==
1
)
{
int
len
=
res
.
insts
(
bi
).
tensor_array
(
idx
).
float_data_size
();
VLOG
(
2
)
<<
"fetch tensor : "
<<
name
<<
" type: float32 len : "
<<
len
;
predict_res_batch
[
bi
].
_float_map
[
name
].
resize
(
1
);
predict_res_batch
[
bi
].
_float_map
[
name
][
0
].
resize
(
len
);
VLOG
(
2
)
<<
"fetch name "
<<
name
<<
" index "
<<
idx
<<
" first data "
<<
res
.
insts
(
bi
).
tensor_array
(
idx
).
float_data
(
0
);
for
(
int
i
=
0
;
i
<
len
;
++
i
)
{
predict_res_batch
[
bi
].
_float_map
[
name
][
0
][
i
]
=
res
.
insts
(
bi
).
tensor_array
(
idx
).
float_data
(
i
);
}
}
}
}
}
}
postprocess_end
=
timeline
.
TimeStampUS
();
postprocess_end
=
timeline
.
TimeStampUS
();
...
@@ -411,7 +426,7 @@ std::vector<std::vector<std::vector<float>>> PredictorClient::batch_predict(
...
@@ -411,7 +426,7 @@ std::vector<std::vector<std::vector<float>>> PredictorClient::batch_predict(
fprintf
(
stderr
,
"%s
\n
"
,
oss
.
str
().
c_str
());
fprintf
(
stderr
,
"%s
\n
"
,
oss
.
str
().
c_str
());
}
}
return
fetch_result
_batch
;
return
predict_res
_batch
;
}
}
}
// namespace general_model
}
// namespace general_model
...
...
core/general-client/src/pybind_general_model.cpp
浏览文件 @
1b84553f
...
@@ -90,12 +90,14 @@ PYBIND11_MODULE(serving_client, m) {
...
@@ -90,12 +90,14 @@ PYBIND11_MODULE(serving_client, m) {
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
int64_t
>>>
const
std
::
vector
<
std
::
vector
<
std
::
vector
<
int64_t
>>>
&
int_feed_batch
,
&
int_feed_batch
,
const
std
::
vector
<
std
::
string
>
&
int_feed_name
,
const
std
::
vector
<
std
::
string
>
&
int_feed_name
,
const
std
::
vector
<
std
::
string
>
&
fetch_name
)
{
const
std
::
vector
<
std
::
string
>
&
fetch_name
,
const
int
&
pid
)
{
return
self
.
batch_predict
(
float_feed_batch
,
return
self
.
batch_predict
(
float_feed_batch
,
float_feed_name
,
float_feed_name
,
int_feed_batch
,
int_feed_batch
,
int_feed_name
,
int_feed_name
,
fetch_name
);
fetch_name
,
pid
);
});
});
}
}
...
...
python/paddle_serving_client/__init__.py
浏览文件 @
1b84553f
...
@@ -204,14 +204,17 @@ class Client(object):
...
@@ -204,14 +204,17 @@ class Client(object):
result_batch
=
self
.
client_handle_
.
batch_predict
(
result_batch
=
self
.
client_handle_
.
batch_predict
(
float_slot_batch
,
float_feed_names
,
int_slot_batch
,
int_feed_names
,
float_slot_batch
,
float_feed_names
,
int_slot_batch
,
int_feed_names
,
fetch_names
)
fetch_names
,
self
.
pid
)
result_map_batch
=
[]
result_map_batch
=
[]
for
result
in
result_batch
:
for
result
in
result_batch
:
result_map
=
{}
result_map
=
{}
for
i
,
name
in
enumerate
(
fetch_names
):
for
i
,
name
in
enumerate
(
fetch_names
):
result_map
[
name
]
=
result
[
i
]
if
self
.
fetch_names_to_type_
[
name
]
==
int_type
:
result_map_batch
.
append
(
result_map
)
result_map
[
name
]
=
result
.
get_int64_by_name
(
name
)[
0
]
elif
self
.
fetch_names_to_type_
[
name
]
==
float_type
:
result_map
[
name
]
=
result
.
get_float_by_name
(
name
)[
0
]
result_map_batch
.
appenf
(
result_map
)
return
result_map_batch
return
result_map_batch
...
...
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