Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
Paddle-Lite
提交
9d88feea
P
Paddle-Lite
项目概览
PaddlePaddle
/
Paddle-Lite
通知
331
Star
4
Fork
1
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
271
列表
看板
标记
里程碑
合并请求
78
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle-Lite
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
271
Issue
271
列表
看板
标记
里程碑
合并请求
78
合并请求
78
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
未验证
提交
9d88feea
编写于
2月 29, 2020
作者:
S
Santa An
提交者:
GitHub
2月 29, 2020
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
* [LITE][BM] support yolov3, test=develop (#3035)
上级
63e0f695
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
282 addition
and
48 deletion
+282
-48
lite/kernels/bm/bridges/CMakeLists.txt
lite/kernels/bm/bridges/CMakeLists.txt
+4
-0
lite/kernels/bm/bridges/act_op.cc
lite/kernels/bm/bridges/act_op.cc
+28
-9
lite/kernels/bm/bridges/elementwise_ops.cc
lite/kernels/bm/bridges/elementwise_ops.cc
+19
-30
lite/kernels/bm/bridges/interpolate_op.cc
lite/kernels/bm/bridges/interpolate_op.cc
+95
-0
lite/kernels/bm/bridges/paddle_use_bridges.h
lite/kernels/bm/bridges/paddle_use_bridges.h
+6
-0
lite/kernels/bm/bridges/yolo_box_op.cc
lite/kernels/bm/bridges/yolo_box_op.cc
+125
-0
lite/kernels/bm/subgraph_compute.cc
lite/kernels/bm/subgraph_compute.cc
+5
-8
lite/kernels/bm/subgraph_compute.h
lite/kernels/bm/subgraph_compute.h
+0
-1
未找到文件。
lite/kernels/bm/bridges/CMakeLists.txt
浏览文件 @
9d88feea
...
...
@@ -23,6 +23,8 @@ lite_cc_library(subgraph_bridge_norm_op_bm SRCS norm_op.cc DEPS ${bm_subgraph_br
lite_cc_library
(
subgraph_bridge_prior_box_op_bm SRCS prior_box_op.cc DEPS
${
bm_subgraph_bridge_deps
}
)
lite_cc_library
(
subgraph_bridge_box_coder_op_bm SRCS box_coder_op.cc DEPS
${
bm_subgraph_bridge_deps
}
)
lite_cc_library
(
subgraph_bridge_multiclass_nms_op_bm SRCS multiclass_nms_op.cc DEPS
${
bm_subgraph_bridge_deps
}
)
lite_cc_library
(
subgraph_bridge_interpolate_op_bm SRCS interpolate_op.cc DEPS
${
bm_subgraph_bridge_deps
}
)
lite_cc_library
(
subgraph_bridge_yolo_box_op_bm SRCS yolo_box_op.cc DEPS
${
bm_subgraph_bridge_deps
}
)
set
(
bm_subgraph_bridges
subgraph_bridge_registry
...
...
@@ -44,4 +46,6 @@ set(bm_subgraph_bridges
subgraph_bridge_prior_box_op_bm
subgraph_bridge_box_coder_op_bm
subgraph_bridge_multiclass_nms_op_bm
subgraph_bridge_interpolate_op_bm
subgraph_bridge_yolo_box_op_bm
CACHE INTERNAL
"bm_subgraph_bridges"
)
lite/kernels/bm/bridges/act_op.cc
浏览文件 @
9d88feea
...
...
@@ -13,6 +13,7 @@
// limitations under the License.
#include <bmcompiler_if.h>
#include <bmcompiler_op_code.h>
#include "lite/kernels/bm/bridges/graph.h"
#include "lite/kernels/npu/bridges/registry.h"
...
...
@@ -46,22 +47,38 @@ int ActConverter(void* ctx, OpLite* op, KernelBase* kernel) {
i_output_shape_data
[
i
]
=
static_cast
<
int
>
(
output_shape_data
[
i
]);
}
float
alpha
=
0.
f
;
int
active_type_id
=
0
;
if
(
op_type
==
"relu"
)
{
}
else
if
(
op_type
==
"leaky_relu"
)
{
alpha
=
op_info
->
GetAttr
<
float
>
(
"alpha"
);
}
else
if
(
op_type
==
"sqrt"
)
{
active_type_id
=
ACTIVE_SQRT
;
}
else
if
(
op_type
==
"square"
)
{
active_type_id
=
ACTIVE_SQUARE
;
}
else
{
LOG
(
FATAL
)
<<
"[BM] unsupport act type"
;
return
FAILED
;
}
add_relu_layer
(
graph
->
GetCompilerHandle
(),
const_cast
<
const
int
*>
(
&
i_x_shape_data
[
0
]),
x_dims
.
size
(),
static_cast
<
const
char
*>
(
x_var_name
.
c_str
()),
const_cast
<
const
int
*>
(
&
i_output_shape_data
[
0
]),
output_dims
.
size
(),
static_cast
<
const
char
*>
(
output_var_name
.
c_str
()),
alpha
,
-
1.
f
);
if
(
op_type
==
"relu"
||
op_type
==
"leaky_relu"
)
{
add_relu_layer
(
graph
->
GetCompilerHandle
(),
const_cast
<
const
int
*>
(
&
i_x_shape_data
[
0
]),
x_dims
.
size
(),
static_cast
<
const
char
*>
(
x_var_name
.
c_str
()),
const_cast
<
const
int
*>
(
&
i_output_shape_data
[
0
]),
output_dims
.
size
(),
static_cast
<
const
char
*>
(
output_var_name
.
c_str
()),
alpha
,
-
1.
f
);
}
else
{
add_active_layer
(
graph
->
GetCompilerHandle
(),
const_cast
<
const
int
*>
(
&
i_x_shape_data
[
0
]),
x_dims
.
size
(),
static_cast
<
const
char
*>
(
x_var_name
.
c_str
()),
const_cast
<
const
int
*>
(
&
i_output_shape_data
[
0
]),
output_dims
.
size
(),
static_cast
<
const
char
*>
(
output_var_name
.
c_str
()),
active_type_id
);
}
graph
->
AddNode
(
output_var_name
);
return
SUCCESS
;
}
...
...
@@ -75,3 +92,5 @@ REGISTER_SUBGRAPH_BRIDGE(relu, kBM, paddle::lite::subgraph::bm::ActConverter);
REGISTER_SUBGRAPH_BRIDGE
(
leaky_relu
,
kBM
,
paddle
::
lite
::
subgraph
::
bm
::
ActConverter
);
REGISTER_SUBGRAPH_BRIDGE
(
sqrt
,
kBM
,
paddle
::
lite
::
subgraph
::
bm
::
ActConverter
);
REGISTER_SUBGRAPH_BRIDGE
(
square
,
kBM
,
paddle
::
lite
::
subgraph
::
bm
::
ActConverter
);
lite/kernels/bm/bridges/elementwise_ops.cc
浏览文件 @
9d88feea
...
...
@@ -71,18 +71,14 @@ int ElementwiseConverter(void* ctx, OpLite* op, KernelBase* kernel) {
}
auto
axis
=
op_info
->
GetAttr
<
int
>
(
"axis"
);
int
op_code
{
-
1
};
int
eltwise_if_code
{
-
1
};
float
coeff
[
2
]
=
{
1.
f
,
1.
f
};
if
(
op_type
==
"elementwise_mul"
)
{
op_code
=
BINARY_MUL
;
eltwise_if_code
=
0
;
}
else
if
(
op_type
==
"elementwise_add"
)
{
op_code
=
BINARY_ADD
;
eltwise_if_code
=
1
;
}
else
if
(
op_type
==
"elementwise_sub"
)
{
op_code
=
BINARY_SUB
;
eltwise_if_code
=
1
;
coeff
[
1
]
=
-
1.
f
;
}
else
if
(
op_type
==
"elementwise_div"
)
{
op_code
=
BINARY_DIV
;
}
else
{
LOG
(
FATAL
)
<<
"UNSUPPORTED ELTWISE OPERATION: "
<<
op_type
;
}
...
...
@@ -115,31 +111,21 @@ int ElementwiseConverter(void* ctx, OpLite* op, KernelBase* kernel) {
shape
[
1
]
=
&
i_expand_shape_data
[
0
];
y_data
=
nullptr
;
}
add_binary_layer_v2
(
graph
->
GetCompilerHandle
(),
name
[
0
],
shape
[
0
],
dim
[
0
],
0
,
static_cast
<
const
float
*>
(
x_data
),
name
[
1
],
shape
[
1
],
dim
[
1
],
0
,
static_cast
<
const
float
*>
(
y_data
),
static_cast
<
const
char
*>
(
output_var_name
.
c_str
()),
op_code
);
}
else
{
add_eltwise_layer
(
graph
->
GetCompilerHandle
(),
input_num
,
shape
,
dim
,
name
,
const_cast
<
const
int
*>
(
&
i_output_shape_data
[
0
]),
output_dims
.
size
(),
static_cast
<
const
char
*>
(
output_var_name
.
c_str
()),
eltwise_if_code
,
coeff
);
}
add_binary_layer_v2
(
graph
->
GetCompilerHandle
(),
name
[
0
],
shape
[
0
],
dim
[
0
],
0
,
static_cast
<
const
float
*>
(
x_data
),
name
[
1
],
shape
[
1
],
dim
[
1
],
0
,
static_cast
<
const
float
*>
(
y_data
),
static_cast
<
const
char
*>
(
output_var_name
.
c_str
()),
op_code
);
delete
[]
shape
;
delete
[]
name
;
delete
[]
dim
;
...
...
@@ -161,3 +147,6 @@ REGISTER_SUBGRAPH_BRIDGE(elementwise_mul,
REGISTER_SUBGRAPH_BRIDGE
(
elementwise_sub
,
kBM
,
paddle
::
lite
::
subgraph
::
bm
::
ElementwiseConverter
);
REGISTER_SUBGRAPH_BRIDGE
(
elementwise_div
,
kBM
,
paddle
::
lite
::
subgraph
::
bm
::
ElementwiseConverter
);
lite/kernels/bm/bridges/interpolate_op.cc
0 → 100644
浏览文件 @
9d88feea
// 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 <bmcompiler_if.h>
#include "lite/kernels/bm/bridges/graph.h"
#include "lite/kernels/npu/bridges/registry.h"
namespace
paddle
{
namespace
lite
{
namespace
subgraph
{
namespace
bm
{
int
InterpolateConverter
(
void
*
ctx
,
OpLite
*
op
,
KernelBase
*
kernel
)
{
CHECK
(
ctx
!=
nullptr
);
CHECK
(
op
!=
nullptr
);
auto
graph
=
static_cast
<
Graph
*>
(
ctx
);
auto
scope
=
op
->
scope
();
auto
op_info
=
op
->
op_info
();
auto
op_type
=
op_info
->
Type
();
auto
x_var_name
=
op_info
->
Input
(
"X"
).
front
();
auto
x
=
scope
->
FindVar
(
x_var_name
)
->
GetMutable
<
lite
::
Tensor
>
();
auto
x_dims
=
x
->
dims
();
std
::
vector
<
int32_t
>
i_x_shape_data
(
x_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
x_dims
.
size
();
i
++
)
{
i_x_shape_data
[
i
]
=
static_cast
<
int32_t
>
(
x_dims
[
i
]);
}
auto
output_var_name
=
op_info
->
Output
(
"Out"
).
front
();
auto
output
=
scope
->
FindVar
(
output_var_name
)
->
GetMutable
<
lite
::
Tensor
>
();
auto
output_dims
=
output
->
dims
();
std
::
vector
<
int32_t
>
i_output_shape_data
(
output_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
output_dims
.
size
();
i
++
)
{
i_output_shape_data
[
i
]
=
static_cast
<
int32_t
>
(
output_dims
[
i
]);
}
auto
scale
=
op_info
->
GetAttr
<
float
>
(
"scale"
);
int32_t
i_scale
=
static_cast
<
int32_t
>
(
scale
);
bool
is_int
=
false
;
if
((
scale
-
i_scale
)
<
0.000001
f
)
{
is_int
=
true
;
}
int32_t
type
=
0
;
if
(
op_type
==
"nearest_interp"
)
{
type
=
2
;
}
else
{
type
=
0
;
}
if
(
type
==
2
&&
is_int
)
{
add_upsample_layer
(
graph
->
GetCompilerHandle
(),
const_cast
<
const
int
*>
(
&
i_x_shape_data
[
0
]),
x_dims
.
size
(),
static_cast
<
const
char
*>
(
x_var_name
.
c_str
()),
const_cast
<
const
int
*>
(
&
i_output_shape_data
[
0
]),
output_dims
.
size
(),
static_cast
<
const
char
*>
(
output_var_name
.
c_str
()),
i_scale
);
}
else
{
add_interp_layer_v2
(
graph
->
GetCompilerHandle
(),
const_cast
<
const
int
*>
(
&
i_x_shape_data
[
0
]),
x_dims
.
size
(),
static_cast
<
const
char
*>
(
x_var_name
.
c_str
()),
1
,
const_cast
<
const
int
*>
(
&
i_output_shape_data
[
0
]),
output_dims
.
size
(),
nullptr
,
static_cast
<
const
char
*>
(
output_var_name
.
c_str
()),
0
,
0
,
type
);
}
graph
->
AddNode
(
output_var_name
);
return
SUCCESS
;
}
}
// namespace bm
}
// namespace subgraph
}
// namespace lite
}
// namespace paddle
REGISTER_SUBGRAPH_BRIDGE
(
nearest_interp
,
kBM
,
paddle
::
lite
::
subgraph
::
bm
::
InterpolateConverter
);
REGISTER_SUBGRAPH_BRIDGE
(
bilinear_interp
,
kBM
,
paddle
::
lite
::
subgraph
::
bm
::
InterpolateConverter
);
lite/kernels/bm/bridges/paddle_use_bridges.h
浏览文件 @
9d88feea
...
...
@@ -21,6 +21,7 @@ USE_SUBGRAPH_BRIDGE(depthwise_conv2d, kBM);
USE_SUBGRAPH_BRIDGE
(
elementwise_add
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
elementwise_mul
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
elementwise_sub
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
elementwise_div
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
pool2d
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
softmax
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
mul
,
kBM
);
...
...
@@ -38,3 +39,8 @@ USE_SUBGRAPH_BRIDGE(norm, kBM);
USE_SUBGRAPH_BRIDGE
(
prior_box
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
box_coder
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
multiclass_nms
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
nearest_interp
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
bilinear_interp
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
yolo_box
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
sqrt
,
kBM
);
USE_SUBGRAPH_BRIDGE
(
square
,
kBM
);
lite/kernels/bm/bridges/yolo_box_op.cc
0 → 100644
浏览文件 @
9d88feea
// 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 <bmcompiler_if.h>
#include <user_bmcpu_common.h>
#include <iostream>
#include <string>
#include <vector>
#include "lite/kernels/bm/bridges/graph.h"
#include "lite/kernels/bm/bridges/utility.h"
#include "lite/kernels/npu/bridges/registry.h"
namespace
paddle
{
namespace
lite
{
namespace
subgraph
{
namespace
bm
{
int
YoloBoxConverter
(
void
*
ctx
,
OpLite
*
op
,
KernelBase
*
kernel
)
{
CHECK
(
ctx
!=
nullptr
);
CHECK
(
op
!=
nullptr
);
auto
graph
=
static_cast
<
Graph
*>
(
ctx
);
auto
scope
=
op
->
scope
();
auto
op_info
=
op
->
op_info
();
auto
op_type
=
op_info
->
Type
();
auto
x_var_name
=
op_info
->
Input
(
"X"
).
front
();
auto
x
=
scope
->
FindVar
(
x_var_name
)
->
GetMutable
<
lite
::
Tensor
>
();
auto
x_dims
=
x
->
dims
();
auto
img_size_var_name
=
op_info
->
Input
(
"ImgSize"
).
front
();
auto
img_size
=
scope
->
FindVar
(
img_size_var_name
)
->
GetMutable
<
lite
::
Tensor
>
();
auto
img_size_dims
=
img_size
->
dims
();
auto
boxes_var_name
=
op_info
->
Output
(
"Boxes"
).
front
();
auto
boxes
=
scope
->
FindVar
(
boxes_var_name
)
->
GetMutable
<
lite
::
Tensor
>
();
auto
boxes_dims
=
boxes
->
dims
();
auto
scores_var_name
=
op_info
->
Output
(
"Scores"
).
front
();
auto
scores
=
scope
->
FindVar
(
scores_var_name
)
->
GetMutable
<
lite
::
Tensor
>
();
auto
scores_dims
=
scores
->
dims
();
std
::
vector
<
int32_t
>
i_x_shape_data
(
x_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
x_dims
.
size
();
i
++
)
{
i_x_shape_data
[
i
]
=
static_cast
<
int32_t
>
(
x_dims
[
i
]);
}
std
::
vector
<
int32_t
>
i_img_size_shape_data
(
img_size_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
img_size_dims
.
size
();
i
++
)
{
i_img_size_shape_data
[
i
]
=
static_cast
<
int32_t
>
(
img_size_dims
[
i
]);
}
std
::
vector
<
int32_t
>
i_boxes_shape_data
(
boxes_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
boxes_dims
.
size
();
i
++
)
{
i_boxes_shape_data
[
i
]
=
static_cast
<
int32_t
>
(
boxes_dims
[
i
]);
}
std
::
vector
<
int32_t
>
i_scores_shape_data
(
scores_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
scores_dims
.
size
();
i
++
)
{
i_scores_shape_data
[
i
]
=
static_cast
<
int32_t
>
(
scores_dims
[
i
]);
}
auto
class_num
=
op_info
->
GetAttr
<
int
>
(
"class_num"
);
auto
downsample_ratio
=
op_info
->
GetAttr
<
int
>
(
"downsample_ratio"
);
auto
conf_thresh
=
op_info
->
GetAttr
<
float
>
(
"conf_thresh"
);
auto
anchors
=
op_info
->
GetAttr
<
std
::
vector
<
int
>>
(
"anchors"
);
int
*
anchors_buffer
=
static_cast
<
int
*>
(
malloc
(
sizeof
(
int
)
*
anchors
.
size
()));
CHECK
(
anchors_buffer
!=
nullptr
);
memcpy
(
anchors_buffer
,
&
anchors
[
0
],
sizeof
(
int
)
*
anchors
.
size
());
user_cpu_param_t
bm_param
;
bm_param
.
op_type
=
USER_PADDLE_YOLO_BOX
;
bm_param
.
u
.
yolo_box_param
.
class_num
=
class_num
;
bm_param
.
u
.
yolo_box_param
.
downsample_ratio
=
downsample_ratio
;
bm_param
.
u
.
yolo_box_param
.
conf_thresh
=
conf_thresh
;
bm_param
.
u
.
yolo_box_param
.
anchors
=
anchors_buffer
;
bm_param
.
u
.
yolo_box_param
.
anchors_size
=
anchors
.
size
();
memcpy
(
anchors_buffer
,
&
anchors
[
0
],
sizeof
(
int
)
*
anchors
.
size
());
int32_t
input_num
=
2
;
int32_t
output_num
=
2
;
int32_t
*
in_shape
[
2
];
int32_t
in_dim
[
2
];
const
char
*
in_name
[
2
];
in_shape
[
0
]
=
&
i_x_shape_data
[
0
];
in_shape
[
1
]
=
&
i_img_size_shape_data
[
0
];
in_dim
[
0
]
=
x_dims
.
size
();
in_dim
[
1
]
=
img_size_dims
.
size
();
in_name
[
0
]
=
static_cast
<
const
char
*>
(
x_var_name
.
c_str
());
in_name
[
1
]
=
static_cast
<
const
char
*>
(
img_size_var_name
.
c_str
());
int32_t
*
out_shape
[
2
];
int32_t
out_dim
[
2
];
const
char
*
out_name
[
2
];
out_shape
[
0
]
=
&
i_boxes_shape_data
[
0
];
out_shape
[
1
]
=
&
i_scores_shape_data
[
0
];
out_dim
[
0
]
=
boxes_dims
.
size
();
out_dim
[
1
]
=
scores_dims
.
size
();
out_name
[
0
]
=
static_cast
<
const
char
*>
(
boxes_var_name
.
c_str
());
out_name
[
1
]
=
static_cast
<
const
char
*>
(
scores_var_name
.
c_str
());
add_user_cpu_layer
(
graph
->
GetCompilerHandle
(),
input_num
,
in_shape
,
in_dim
,
in_name
,
output_num
,
out_shape
,
out_dim
,
out_name
,
&
bm_param
,
static_cast
<
int
>
(
sizeof
(
bm_param
)));
graph
->
AddNode
(
boxes_var_name
);
graph
->
AddNode
(
scores_var_name
);
return
SUCCESS
;
}
}
// namespace bm
}
// namespace subgraph
}
// namespace lite
}
// namespace paddle
REGISTER_SUBGRAPH_BRIDGE
(
yolo_box
,
kBM
,
paddle
::
lite
::
subgraph
::
bm
::
YoloBoxConverter
);
lite/kernels/bm/subgraph_compute.cc
浏览文件 @
9d88feea
...
...
@@ -34,6 +34,7 @@ int SubgraphEngine::BuildDeviceProgram() {
const
auto
&
bridges
=
subgraph
::
Registry
::
Instance
();
graph
.
CreateCompilerHandle
();
auto
&
ctx
=
this
->
ctx_
->
template
As
<
BMContext
>();
int
kk
=
0
;
for
(
auto
&
inst
:
origin_program_
)
{
auto
op
=
inst
.
op
();
CHECK
(
op
);
...
...
@@ -52,7 +53,7 @@ int SubgraphEngine::BuildDeviceProgram() {
return
subgraph
::
FAILED
;
}
}
std
::
string
net_name
=
"
paddle_bitmain
"
;
std
::
string
net_name
=
"
bmnetc_f32umodel
"
;
__bmcompile_opt
(
graph
.
GetCompilerHandle
(),
const_cast
<
char
*>
(
net_name
.
c_str
()),
1
);
void
*
bmodel_data
=
nullptr
;
...
...
@@ -71,7 +72,7 @@ int SubgraphEngine::BuildDeviceProgram() {
origin_itensors_
.
resize
(
input_names_
.
size
());
device_inputs_
.
resize
(
input_names_
.
size
());
for
(
size_t
i
=
0
;
i
<
input_names_
.
size
();
i
++
)
{
origin_itensors_
[
i
]
=
scope_
->
FindMutableTensor
(
input_names_
[
i
]);
origin_itensors_
[
i
]
=
scope_
->
FindMutableTensor
(
net_info_
->
input_names
[
i
]);
CHECK
(
origin_itensors_
[
i
]);
origin_idims_
[
i
]
=
origin_itensors_
[
i
]
->
dims
();
bm_device_mem_t
*
p_mem
=
...
...
@@ -90,19 +91,15 @@ int SubgraphEngine::BuildDeviceProgram() {
origin_otensors_
.
resize
(
output_names_
.
size
());
device_outputs_
.
resize
(
output_names_
.
size
());
for
(
size_t
i
=
0
;
i
<
output_names_
.
size
();
i
++
)
{
origin_otensors_
[
i
]
=
scope_
->
FindMutableTensor
(
output_names_
[
i
]);
origin_otensors_
[
i
]
=
scope_
->
FindMutableTensor
(
net_info_
->
output_names
[
i
]);
CHECK
(
origin_otensors_
[
i
]);
origin_odims_
[
i
]
=
origin_otensors_
[
i
]
->
dims
();
output_map_
.
insert
(
std
::
pair
<
std
::
string
,
int
>
(
output_names_
[
i
],
i
));
origin_otensors_
[
i
]
->
mutable_data
<
float
>
();
}
for
(
size_t
i
=
0
;
i
<
output_names_
.
size
();
i
++
)
{
int
mapping_index
=
output_map_
.
at
(
net_info_
->
output_names
[
i
]);
bm_device_mem_t
*
p_mem
=
static_cast
<
bm_device_mem_t
*>
(
malloc
(
sizeof
(
bm_device_mem_t
)));
CHECK
(
p_mem
!=
nullptr
);
CHECK_EQ
(
bm_malloc_device_byte
(
bm_hd_
,
p_mem
,
origin_otensors_
[
mapping_index
]
->
memory_size
()),
bm_hd_
,
p_mem
,
origin_otensors_
[
i
]
->
memory_size
()),
BM_SUCCESS
);
bmrt_tensor_with_device
(
&
device_outputs_
[
i
],
*
p_mem
,
...
...
lite/kernels/bm/subgraph_compute.h
浏览文件 @
9d88feea
...
...
@@ -51,7 +51,6 @@ class SubgraphEngine : public subgraph::Engine {
void
*
bmrt_hd_
;
std
::
vector
<
bm_tensor_t
>
device_inputs_
;
std
::
vector
<
bm_tensor_t
>
device_outputs_
;
std
::
map
<
std
::
string
,
int
>
output_map_
;
const
char
**
net_names_
;
const
bm_net_info_t
*
net_info_
;
bm_handle_t
bm_hd_
;
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录