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0f7fba66
编写于
2月 13, 2020
作者:
G
guru4elephant
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add general text infer and reader for debugging
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0a86cba1
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4 changed file
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425 addition
and
0 deletion
+425
-0
core/general-server/op/general_text_infer_op.cpp
core/general-server/op/general_text_infer_op.cpp
+152
-0
core/general-server/op/general_text_infer_op.h
core/general-server/op/general_text_infer_op.h
+45
-0
core/general-server/op/general_text_reader_op.cpp
core/general-server/op/general_text_reader_op.cpp
+166
-0
core/general-server/op/general_text_reader_op.h
core/general-server/op/general_text_reader_op.h
+62
-0
未找到文件。
core/general-server/op/general_text_infer_op.cpp
0 → 100644
浏览文件 @
0f7fba66
// Copyright (c) 2020 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.
#include <algorithm>
#include <iostream>
#include <memory>
#include <sstream>
#include "core/general-server/op/general_text_infer_op.h"
#include "core/general-server/op/general_infer_op.h"
#include "core/general-server/op/general_text_reader_op.h"
#include "core/general-server/op/general_reader_op.h"
#include "core/predictor/framework/infer.h"
#include "core/predictor/framework/memory.h"
#include "core/predictor/framework/resource.h"
#include "core/util/include/timer.h"
namespace
baidu
{
namespace
paddle_serving
{
namespace
serving
{
using
baidu
::
paddle_serving
::
serving
::
GENERAL_MODEL_NAME
;
using
baidu
::
paddle_serving
::
Timer
;
using
baidu
::
paddle_serving
::
predictor
::
MempoolWrapper
;
using
baidu
::
paddle_serving
::
predictor
::
general_model
::
Tensor
;
using
baidu
::
paddle_serving
::
predictor
::
general_model
::
Response
;
using
baidu
::
paddle_serving
::
predictor
::
general_model
::
Request
;
using
baidu
::
paddle_serving
::
predictor
::
general_model
::
FetchInst
;
using
baidu
::
paddle_serving
::
predictor
::
InferManager
;
using
baidu
::
paddle_serving
::
predictor
::
PaddleGeneralModelConfig
;
int
GeneralTextInferOp
::
inference
()
{
const
GeneralTextReaderOutput
*
reader_out
=
get_depend_argument
<
GeneralTextReaderOutput
>
(
"general_text_reader_op"
);
if
(
!
reader_out
)
{
LOG
(
ERROR
)
<<
"Failed mutable depended argument, op:"
<<
"general_text_reader_op"
;
return
-
1
;
}
int
reader_status
=
reader_out
->
reader_status
;
if
(
reader_status
!=
0
)
{
LOG
(
ERROR
)
<<
"Read request wrong."
;
return
-
1
;
}
const
TensorVector
*
in
=
&
reader_out
->
tensor_vector
;
TensorVector
*
out
=
butil
::
get_object
<
TensorVector
>
();
int
batch_size
=
(
*
in
)[
0
].
shape
[
0
];
// infer
Timer
timeline
;
double
infer_time
=
0.0
;
timeline
.
Start
();
if
(
InferManager
::
instance
().
infer
(
GENERAL_MODEL_NAME
,
in
,
out
,
batch_size
))
{
LOG
(
ERROR
)
<<
"Failed do infer in fluid model: "
<<
GENERAL_MODEL_NAME
;
return
-
1
;
}
timeline
.
Pause
();
infer_time
=
timeline
.
ElapsedUS
();
const
Request
*
req
=
dynamic_cast
<
const
Request
*>
(
get_request_message
());
VLOG
(
2
)
<<
"start to call load general model_conf op"
;
baidu
::
paddle_serving
::
predictor
::
Resource
&
resource
=
baidu
::
paddle_serving
::
predictor
::
Resource
::
instance
();
VLOG
(
2
)
<<
"get resource pointer done."
;
std
::
shared_ptr
<
PaddleGeneralModelConfig
>
model_config
=
resource
.
get_general_model_config
();
std
::
vector
<
int
>
fetch_index
;
fetch_index
.
resize
(
req
->
fetch_var_names_size
());
for
(
int
i
=
0
;
i
<
req
->
fetch_var_names_size
();
++
i
)
{
fetch_index
[
i
]
=
model_config
->
_fetch_alias_name_to_index
[
req
->
fetch_var_names
(
i
)];
}
// response inst with only fetch_var_names
Response
*
res
=
mutable_data
<
Response
>
();
res
->
set_mean_infer_us
(
infer_time
);
for
(
int
i
=
0
;
i
<
batch_size
;
++
i
)
{
FetchInst
*
fetch_inst
=
res
->
add_insts
();
for
(
auto
&
idx
:
fetch_index
)
{
Tensor
*
tensor
=
fetch_inst
->
add_tensor_array
();
// currently only response float tensor or lod_tensor
tensor
->
set_elem_type
(
1
);
if
(
model_config
->
_is_lod_fetch
[
idx
])
{
VLOG
(
2
)
<<
"out["
<<
idx
<<
" is lod_tensor"
;
tensor
->
add_shape
(
-
1
);
}
else
{
VLOG
(
2
)
<<
"out["
<<
idx
<<
"] is tensor"
;
for
(
int
k
=
1
;
k
<
out
->
at
(
idx
).
shape
.
size
();
++
k
)
{
VLOG
(
2
)
<<
"shape["
<<
k
-
1
<<
"]: "
<<
out
->
at
(
idx
).
shape
[
k
];
tensor
->
add_shape
(
out
->
at
(
idx
).
shape
[
k
]);
}
}
}
}
int
var_idx
=
0
;
for
(
auto
&
idx
:
fetch_index
)
{
float
*
data_ptr
=
static_cast
<
float
*>
(
out
->
at
(
idx
).
data
.
data
());
int
cap
=
1
;
for
(
int
j
=
1
;
j
<
out
->
at
(
idx
).
shape
.
size
();
++
j
)
{
cap
*=
out
->
at
(
idx
).
shape
[
j
];
}
if
(
model_config
->
_is_lod_fetch
[
idx
])
{
for
(
int
j
=
0
;
j
<
batch_size
;
++
j
)
{
for
(
int
k
=
out
->
at
(
idx
).
lod
[
0
][
j
];
k
<
out
->
at
(
idx
).
lod
[
0
][
j
+
1
];
k
++
)
{
res
->
mutable_insts
(
j
)
->
mutable_tensor_array
(
var_idx
)
->
add_float_data
(
data_ptr
[
k
]);
/*
res->mutable_insts(j)->mutable_tensor_array(var_idx)->add_data(
reinterpret_cast<char *>(&(data_ptr[k])), sizeof(float));
*/
}
}
}
else
{
for
(
int
j
=
0
;
j
<
batch_size
;
++
j
)
{
for
(
int
k
=
j
*
cap
;
k
<
(
j
+
1
)
*
cap
;
++
k
)
{
res
->
mutable_insts
(
j
)
->
mutable_tensor_array
(
var_idx
)
->
add_float_data
(
data_ptr
[
k
]);
/*
res->mutable_insts(j)->mutable_tensor_array(var_idx)->add_float_data(
reinterpret_cast<char *>(&(data_ptr[k])), sizeof(float));
*/
}
}
}
var_idx
++
;
}
return
0
;
}
DEFINE_OP
(
GeneralTextInferOp
);
}
// namespace serving
}
// namespace paddle_serving
}
// namespace baidu
core/general-server/op/general_text_infer_op.h
0 → 100644
浏览文件 @
0f7fba66
// Copyright (c) 2019 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.
#pragma once
#include <vector>
#ifdef BCLOUD
#ifdef WITH_GPU
#include "paddle/paddle_inference_api.h"
#else
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#endif
#else
#include "paddle_inference_api.h" // NOLINT
#endif
#include "core/general-server/general_model_service.pb.h"
namespace
baidu
{
namespace
paddle_serving
{
namespace
serving
{
class
GeneralTextInferOp
:
public
baidu
::
paddle_serving
::
predictor
::
OpWithChannel
<
baidu
::
paddle_serving
::
predictor
::
general_model
::
Response
>
{
public:
typedef
std
::
vector
<
paddle
::
PaddleTensor
>
TensorVector
;
DECLARE_OP
(
GeneralTextInferOp
);
int
inference
();
};
}
// namespace serving
}
// namespace paddle_serving
}
// namespace baidu
core/general-server/op/general_text_reader_op.cpp
0 → 100644
浏览文件 @
0f7fba66
// Copyright (c) 2019 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.
#include <algorithm>
#include <iostream>
#include <memory>
#include <sstream>
#include "core/general-server/op/general_text_reader_op.h"
#include "core/predictor/framework/infer.h"
#include "core/predictor/framework/memory.h"
namespace
baidu
{
namespace
paddle_serving
{
namespace
serving
{
using
baidu
::
paddle_serving
::
predictor
::
MempoolWrapper
;
using
baidu
::
paddle_serving
::
predictor
::
general_model
::
Tensor
;
using
baidu
::
paddle_serving
::
predictor
::
general_model
::
Request
;
using
baidu
::
paddle_serving
::
predictor
::
general_model
::
FeedInst
;
using
baidu
::
paddle_serving
::
predictor
::
PaddleGeneralModelConfig
;
int
GeneralTextReaderOp
::
inference
()
{
// reade request from client
const
Request
*
req
=
dynamic_cast
<
const
Request
*>
(
get_request_message
());
int
batch_size
=
req
->
insts_size
();
int
input_var_num
=
0
;
std
::
vector
<
int64_t
>
elem_type
;
std
::
vector
<
int64_t
>
elem_size
;
std
::
vector
<
int64_t
>
capacity
;
GeneralTextReaderOutput
*
res
=
mutable_data
<
GeneralTextReaderOutput
>
();
TensorVector
*
in
=
&
res
->
tensor_vector
;
if
(
!
res
)
{
LOG
(
ERROR
)
<<
"Failed get op tls reader object output"
;
}
if
(
batch_size
<=
0
)
{
res
->
reader_status
=
-
1
;
return
0
;
}
int
var_num
=
req
->
insts
(
0
).
tensor_array_size
();
VLOG
(
2
)
<<
"var num: "
<<
var_num
;
// read config
VLOG
(
2
)
<<
"start to call load general model_conf op"
;
baidu
::
paddle_serving
::
predictor
::
Resource
&
resource
=
baidu
::
paddle_serving
::
predictor
::
Resource
::
instance
();
VLOG
(
2
)
<<
"get resource pointer done."
;
std
::
shared_ptr
<
PaddleGeneralModelConfig
>
model_config
=
resource
.
get_general_model_config
();
VLOG
(
2
)
<<
"print general model config done."
;
elem_type
.
resize
(
var_num
);
elem_size
.
resize
(
var_num
);
capacity
.
resize
(
var_num
);
for
(
int
i
=
0
;
i
<
var_num
;
++
i
)
{
paddle
::
PaddleTensor
lod_tensor
;
elem_type
[
i
]
=
req
->
insts
(
0
).
tensor_array
(
i
).
elem_type
();
VLOG
(
2
)
<<
"var["
<<
i
<<
"] has elem type: "
<<
elem_type
[
i
];
if
(
elem_type
[
i
]
==
0
)
{
// int64
elem_size
[
i
]
=
sizeof
(
int64_t
);
lod_tensor
.
dtype
=
paddle
::
PaddleDType
::
INT64
;
}
else
{
elem_size
[
i
]
=
sizeof
(
float
);
lod_tensor
.
dtype
=
paddle
::
PaddleDType
::
FLOAT32
;
}
if
(
req
->
insts
(
0
).
tensor_array
(
i
).
shape
(
0
)
==
-
1
)
{
lod_tensor
.
lod
.
resize
(
1
);
lod_tensor
.
lod
[
0
].
push_back
(
0
);
VLOG
(
2
)
<<
"var["
<<
i
<<
"] is lod_tensor"
;
}
else
{
lod_tensor
.
shape
.
push_back
(
batch_size
);
capacity
[
i
]
=
1
;
for
(
int
k
=
0
;
k
<
req
->
insts
(
0
).
tensor_array
(
i
).
shape_size
();
++
k
)
{
int
dim
=
req
->
insts
(
0
).
tensor_array
(
i
).
shape
(
k
);
VLOG
(
2
)
<<
"shape for var["
<<
i
<<
"]: "
<<
dim
;
capacity
[
i
]
*=
dim
;
lod_tensor
.
shape
.
push_back
(
dim
);
}
VLOG
(
2
)
<<
"var["
<<
i
<<
"] is tensor, capacity: "
<<
capacity
[
i
];
}
lod_tensor
.
name
=
model_config
->
_feed_name
[
i
];
in
->
push_back
(
lod_tensor
);
}
for
(
int
i
=
0
;
i
<
var_num
;
++
i
)
{
if
(
in
->
at
(
i
).
lod
.
size
()
==
1
)
{
for
(
int
j
=
0
;
j
<
batch_size
;
++
j
)
{
const
Tensor
&
tensor
=
req
->
insts
(
j
).
tensor_array
(
i
);
int
data_len
=
tensor
.
int_data_size
();
int
cur_len
=
in
->
at
(
i
).
lod
[
0
].
back
();
in
->
at
(
i
).
lod
[
0
].
push_back
(
cur_len
+
data_len
);
}
in
->
at
(
i
).
data
.
Resize
(
in
->
at
(
i
).
lod
[
0
].
back
()
*
elem_size
[
i
]);
in
->
at
(
i
).
shape
=
{
in
->
at
(
i
).
lod
[
0
].
back
(),
1
};
VLOG
(
2
)
<<
"var["
<<
i
<<
"] is lod_tensor and len="
<<
in
->
at
(
i
).
lod
[
0
].
back
();
}
else
{
in
->
at
(
i
).
data
.
Resize
(
batch_size
*
capacity
[
i
]
*
elem_size
[
i
]);
VLOG
(
2
)
<<
"var["
<<
i
<<
"] is tensor and capacity="
<<
batch_size
*
capacity
[
i
];
}
}
for
(
int
i
=
0
;
i
<
var_num
;
++
i
)
{
if
(
elem_type
[
i
]
==
0
)
{
int64_t
*
dst_ptr
=
static_cast
<
int64_t
*>
(
in
->
at
(
i
).
data
.
data
());
int
offset
=
0
;
for
(
int
j
=
0
;
j
<
batch_size
;
++
j
)
{
for
(
int
k
=
0
;
k
<
req
->
insts
(
j
).
tensor_array
(
i
).
int_data_size
();
++
k
)
{
dst_ptr
[
offset
+
k
]
=
req
->
insts
(
j
).
tensor_array
(
i
).
int_data
(
k
);
}
if
(
in
->
at
(
i
).
lod
.
size
()
==
1
)
{
offset
=
in
->
at
(
i
).
lod
[
0
][
j
+
1
];
}
else
{
offset
+=
capacity
[
i
];
}
}
}
else
{
float
*
dst_ptr
=
static_cast
<
float
*>
(
in
->
at
(
i
).
data
.
data
());
int
offset
=
0
;
for
(
int
j
=
0
;
j
<
batch_size
;
++
j
)
{
for
(
int
k
=
0
;
k
<
req
->
insts
(
j
).
tensor_array
(
i
).
int_data_size
();
++
k
)
{
dst_ptr
[
offset
+
k
]
=
req
->
insts
(
j
).
tensor_array
(
i
).
int_data
(
k
);
}
if
(
in
->
at
(
i
).
lod
.
size
()
==
1
)
{
offset
=
in
->
at
(
i
).
lod
[
0
][
j
+
1
];
}
else
{
offset
+=
capacity
[
i
];
}
}
}
}
VLOG
(
2
)
<<
"read data from client success"
;
return
0
;
}
DEFINE_OP
(
GeneralTextReaderOp
);
}
// namespace serving
}
// namespace paddle_serving
}
// namespace baidu
core/general-server/op/general_text_reader_op.h
0 → 100644
浏览文件 @
0f7fba66
// Copyright (c) 2019 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.
#pragma once
#include <vector>
#ifdef BCLOUD
#ifdef WITH_GPU
#include "paddle/paddle_inference_api.h"
#else
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#endif
#else
#include "paddle_inference_api.h" // NOLINT
#endif
#include <string>
#include "core/predictor/framework/resource.h"
#include "core/general-server/general_model_service.pb.h"
#include "core/general-server/load_general_model_service.pb.h"
namespace
baidu
{
namespace
paddle_serving
{
namespace
serving
{
struct
GeneralTextReaderOutput
{
std
::
vector
<
paddle
::
PaddleTensor
>
tensor_vector
;
int
reader_status
=
0
;
void
Clear
()
{
size_t
tensor_count
=
tensor_vector
.
size
();
for
(
size_t
ti
=
0
;
ti
<
tensor_count
;
++
ti
)
{
tensor_vector
[
ti
].
shape
.
clear
();
}
tensor_vector
.
clear
();
}
std
::
string
ShortDebugString
()
const
{
return
"Not implemented!"
;
}
};
class
GeneralTextReaderOp
:
public
baidu
::
paddle_serving
::
predictor
::
OpWithChannel
<
GeneralTextReaderOutput
>
{
public:
typedef
std
::
vector
<
paddle
::
PaddleTensor
>
TensorVector
;
DECLARE_OP
(
GeneralTextReaderOp
);
int
inference
();
};
}
// namespace serving
}
// namespace paddle_serving
}
// namespace baidu
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