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37fddd5c
编写于
8月 23, 2021
作者:
B
bjjwwang
浏览文件
操作
浏览文件
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差异文件
fix dist kv infer for MSN team
上级
d0c66c8c
4eb91d52
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
31 addition
and
6 deletion
+31
-6
core/general-server/op/general_dist_kv_infer_op.cpp
core/general-server/op/general_dist_kv_infer_op.cpp
+31
-6
未找到文件。
core/general-server/op/general_dist_kv_infer_op.cpp
浏览文件 @
37fddd5c
...
@@ -69,10 +69,13 @@ int GeneralDistKVInferOp::inference() {
...
@@ -69,10 +69,13 @@ int GeneralDistKVInferOp::inference() {
<<
") Failed mutable depended argument, op:"
<<
pre_name
;
<<
") Failed mutable depended argument, op:"
<<
pre_name
;
return
-
1
;
return
-
1
;
}
}
Timer
timeline
;
timeline
.
Start
();
const
TensorVector
*
in
=
&
input_blob
->
tensor_vector
;
const
TensorVector
*
in
=
&
input_blob
->
tensor_vector
;
TensorVector
*
out
=
&
output_blob
->
tensor_vector
;
TensorVector
*
out
=
&
output_blob
->
tensor_vector
;
std
::
vector
<
uint64_t
>
keys
;
std
::
vector
<
uint64_t
>
keys
;
std
::
vector
<
uint64_t
>
rm_dup_keys
;
std
::
unordered_map
<
uint64_t
,
rec
::
mcube
::
CubeValue
*>
key_map
;
std
::
vector
<
rec
::
mcube
::
CubeValue
>
values
;
std
::
vector
<
rec
::
mcube
::
CubeValue
>
values
;
int
sparse_count
=
0
;
int
sparse_count
=
0
;
int
dense_count
=
0
;
int
dense_count
=
0
;
...
@@ -93,7 +96,7 @@ int GeneralDistKVInferOp::inference() {
...
@@ -93,7 +96,7 @@ int GeneralDistKVInferOp::inference() {
dataptr_size_pairs
.
push_back
(
std
::
make_pair
(
data_ptr
,
elem_num
));
dataptr_size_pairs
.
push_back
(
std
::
make_pair
(
data_ptr
,
elem_num
));
}
}
keys
.
resize
(
key_len
);
keys
.
resize
(
key_len
);
VLOG
(
2
)
<<
"(logid="
<<
log_id
<<
") cube number of keys to look up: "
<<
key_len
;
rm_dup_keys
.
resize
(
key_len
)
;
int
key_idx
=
0
;
int
key_idx
=
0
;
for
(
size_t
i
=
0
;
i
<
dataptr_size_pairs
.
size
();
++
i
)
{
for
(
size_t
i
=
0
;
i
<
dataptr_size_pairs
.
size
();
++
i
)
{
std
::
copy
(
dataptr_size_pairs
[
i
].
first
,
std
::
copy
(
dataptr_size_pairs
[
i
].
first
,
...
@@ -102,14 +105,31 @@ int GeneralDistKVInferOp::inference() {
...
@@ -102,14 +105,31 @@ int GeneralDistKVInferOp::inference() {
key_idx
+=
dataptr_size_pairs
[
i
].
second
;
key_idx
+=
dataptr_size_pairs
[
i
].
second
;
}
}
int
rm_dup_keys_count
=
0
;
for
(
size_t
i
=
0
;
i
<
keys
.
size
();
++
i
)
{
if
(
key_map
.
find
(
keys
[
i
])
==
key_map
.
end
())
{
key_map
[
keys
[
i
]]
=
nullptr
;
rm_dup_keys
[
rm_dup_keys_count
++
]
=
keys
[
i
];
}
}
rm_dup_keys
.
resize
(
rm_dup_keys_count
);
VLOG
(
2
)
<<
"(logid="
<<
log_id
<<
") cube number of keys to look up: "
<<
key_len
<<
" after rm dup keys: "
<<
rm_dup_keys_count
;
rec
::
mcube
::
CubeAPI
*
cube
=
rec
::
mcube
::
CubeAPI
::
instance
();
rec
::
mcube
::
CubeAPI
*
cube
=
rec
::
mcube
::
CubeAPI
::
instance
();
std
::
vector
<
std
::
string
>
table_names
=
cube
->
get_table_names
();
std
::
vector
<
std
::
string
>
table_names
=
cube
->
get_table_names
();
if
(
table_names
.
size
()
==
0
)
{
if
(
table_names
.
size
()
==
0
)
{
LOG
(
ERROR
)
<<
"cube init error or cube config not given."
;
LOG
(
ERROR
)
<<
"cube init error or cube config not given."
;
return
-
1
;
return
-
1
;
}
}
int
ret
=
cube
->
seek
(
table_names
[
0
],
keys
,
&
values
);
int64_t
seek_start
=
timeline
.
TimeStampUS
();
VLOG
(
2
)
<<
"(logid="
<<
log_id
<<
") cube seek status: "
<<
ret
;
int
ret
=
cube
->
seek
(
table_names
[
0
],
rm_dup_keys
,
&
values
);
int64_t
seek_end
=
timeline
.
TimeStampUS
();
VLOG
(
2
)
<<
"(logid="
<<
log_id
<<
") cube seek status: "
<<
ret
<<
" seek_time: "
<<
seek_end
-
seek_start
;
for
(
size_t
i
=
0
;
i
<
rm_dup_keys
.
size
();
++
i
)
{
key_map
[
rm_dup_keys
[
i
]]
=
&
values
[
i
];
}
if
(
values
.
size
()
!=
keys
.
size
()
||
values
[
0
].
buff
.
size
()
==
0
)
{
LOG
(
ERROR
)
<<
"cube value return null"
;
}
//size_t EMBEDDING_SIZE = values[0].buff.size() / sizeof(float);
//size_t EMBEDDING_SIZE = values[0].buff.size() / sizeof(float);
size_t
EMBEDDING_SIZE
=
9
;
size_t
EMBEDDING_SIZE
=
9
;
TensorVector
sparse_out
;
TensorVector
sparse_out
;
...
@@ -147,7 +167,9 @@ int GeneralDistKVInferOp::inference() {
...
@@ -147,7 +167,9 @@ int GeneralDistKVInferOp::inference() {
float
*
dst_ptr
=
static_cast
<
float
*>
(
sparse_out
[
sparse_idx
].
data
.
data
());
float
*
dst_ptr
=
static_cast
<
float
*>
(
sparse_out
[
sparse_idx
].
data
.
data
());
for
(
int
x
=
0
;
x
<
sparse_out
[
sparse_idx
].
lod
[
0
].
back
();
++
x
)
{
for
(
int
x
=
0
;
x
<
sparse_out
[
sparse_idx
].
lod
[
0
].
back
();
++
x
)
{
float
*
data_ptr
=
dst_ptr
+
x
*
EMBEDDING_SIZE
;
float
*
data_ptr
=
dst_ptr
+
x
*
EMBEDDING_SIZE
;
if
(
values
[
cube_val_idx
].
buff
.
size
()
==
0
)
{
uint64_t
cur_key
=
keys
[
cube_val_idx
];
rec
::
mcube
::
CubeValue
*
cur_val
=
key_map
[
cur_key
];
if
(
cur_val
->
buff
.
size
()
==
0
)
{
memset
(
data_ptr
,
(
float
)
0.0
,
sizeof
(
float
)
*
EMBEDDING_SIZE
);
memset
(
data_ptr
,
(
float
)
0.0
,
sizeof
(
float
)
*
EMBEDDING_SIZE
);
VLOG
(
3
)
<<
"(logid="
<<
log_id
<<
") cube key not found: "
<<
keys
[
cube_val_idx
];
VLOG
(
3
)
<<
"(logid="
<<
log_id
<<
") cube key not found: "
<<
keys
[
cube_val_idx
];
++
cube_key_miss
;
++
cube_key_miss
;
...
@@ -170,12 +192,13 @@ int GeneralDistKVInferOp::inference() {
...
@@ -170,12 +192,13 @@ int GeneralDistKVInferOp::inference() {
}
}
VLOG
(
2
)
<<
"(logid="
<<
log_id
<<
") cube key found: "
<<
cube_key_found
<<
" , cube key miss: "
<<
cube_key_miss
;
VLOG
(
2
)
<<
"(logid="
<<
log_id
<<
") cube key found: "
<<
cube_key_found
<<
" , cube key miss: "
<<
cube_key_miss
;
VLOG
(
2
)
<<
"(logid="
<<
log_id
<<
") sparse tensor load success."
;
VLOG
(
2
)
<<
"(logid="
<<
log_id
<<
") sparse tensor load success."
;
timeline
.
Pause
();
VLOG
(
2
)
<<
"dist kv, cube and datacopy time: "
<<
timeline
.
ElapsedUS
();
TensorVector
infer_in
;
TensorVector
infer_in
;
infer_in
.
insert
(
infer_in
.
end
(),
dense_out
.
begin
(),
dense_out
.
end
());
infer_in
.
insert
(
infer_in
.
end
(),
dense_out
.
begin
(),
dense_out
.
end
());
infer_in
.
insert
(
infer_in
.
end
(),
sparse_out
.
begin
(),
sparse_out
.
end
());
infer_in
.
insert
(
infer_in
.
end
(),
sparse_out
.
begin
(),
sparse_out
.
end
());
int
batch_size
=
input_blob
->
_batch_size
;
int
batch_size
=
input_blob
->
_batch_size
;
output_blob
->
_batch_size
=
batch_size
;
output_blob
->
_batch_size
=
batch_size
;
Timer
timeline
;
int64_t
start
=
timeline
.
TimeStampUS
();
int64_t
start
=
timeline
.
TimeStampUS
();
timeline
.
Start
();
timeline
.
Start
();
...
@@ -189,6 +212,8 @@ int GeneralDistKVInferOp::inference() {
...
@@ -189,6 +212,8 @@ int GeneralDistKVInferOp::inference() {
float
*
out_ptr
=
static_cast
<
float
*>
(
out
->
at
(
0
).
data
.
data
());
float
*
out_ptr
=
static_cast
<
float
*>
(
out
->
at
(
0
).
data
.
data
());
out_ptr
[
0
]
=
0.0
;
out_ptr
[
0
]
=
0.0
;
}
}
timeline
.
Pause
();
VLOG
(
2
)
<<
"dist kv, pure paddle infer time: "
<<
timeline
.
ElapsedUS
();
CopyBlobInfo
(
input_blob
,
output_blob
);
CopyBlobInfo
(
input_blob
,
output_blob
);
AddBlobInfo
(
output_blob
,
start
);
AddBlobInfo
(
output_blob
,
start
);
AddBlobInfo
(
output_blob
,
end
);
AddBlobInfo
(
output_blob
,
end
);
...
...
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