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
2301_77200941
mindspore
提交
46a2d163
M
mindspore
项目概览
2301_77200941
/
mindspore
与 Fork 源项目一致
Fork自
MindSpore / mindspore
通知
1
Star
1
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
0
列表
看板
标记
里程碑
合并请求
0
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
M
mindspore
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
0
Issue
0
列表
看板
标记
里程碑
合并请求
0
合并请求
0
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
体验新版 GitCode,发现更多精彩内容 >>
提交
46a2d163
编写于
8月 20, 2020
作者:
L
liuzhongkai
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add biasadd in opencl
上级
6eb98f28
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
454 addition
and
0 deletion
+454
-0
mindspore/lite/src/runtime/kernel/opencl/cl/biasadd.cl
mindspore/lite/src/runtime/kernel/opencl/cl/biasadd.cl
+31
-0
mindspore/lite/src/runtime/kernel/opencl/kernel/biasadd.cc
mindspore/lite/src/runtime/kernel/opencl/kernel/biasadd.cc
+167
-0
mindspore/lite/src/runtime/kernel/opencl/kernel/biasadd.h
mindspore/lite/src/runtime/kernel/opencl/kernel/biasadd.h
+52
-0
mindspore/lite/test/CMakeLists.txt
mindspore/lite/test/CMakeLists.txt
+2
-0
mindspore/lite/test/ut/src/runtime/kernel/opencl/biasadd_tests.cc
...e/lite/test/ut/src/runtime/kernel/opencl/biasadd_tests.cc
+202
-0
未找到文件。
mindspore/lite/src/runtime/kernel/opencl/cl/biasadd.cl
0 → 100644
浏览文件 @
46a2d163
#
pragma
OPENCL
EXTENSION
cl_arm_printf
:
enable
#
define
SLICES
4
#
define
UP_DIV
(
x,
y
)
(((
x
)
+
(
y
)
-
(
1
))
/
(
y
))
#
define
FLT4
float4
#
define
READ_FLT4
read_imagef
#
define
WRITE_FLT4
write_imagef
__constant
sampler_t
smp_zero
=
CLK_NORMALIZED_COORDS_FALSE
| CLK_ADDRESS_CLAMP |
CLK_FILTER_NEAREST
;
__kernel
void
BiasAdd
(
__read_only
image2d_t
input,
__write_only
image2d_t
output,
const
int4
input_shape,
__global
float
*alpha,
const
int
dim
)
{
int
C
=
input_shape.w
; // channel size
int
Y
=
get_global_id
(
0
)
; // height id
int
X
=
get_global_id
(
1
)
; // weight id
for
(
int
num
=
0
; num < UP_DIV(C, SLICES); ++num) {
FLT4
in_c4
=
READ_FLT4
(
input,
smp_zero,
(
int2
)(
X
*
UP_DIV
(
C,
SLICES
)
+
num,
Y
))
; // NHWC4: H WC
FLT4
tmp
;
int
index
=
0
;
if
(
dim
==
2
)
{
index
=
X
*
4
;
}
else
{
index
=
num
*
4
;
}
tmp.x
=
in_c4.x
+
alpha[index]
;
tmp.y
=
in_c4.y
+
alpha[index
+
1]
;
tmp.z
=
in_c4.z
+
alpha[index
+
2]
;
tmp.w
=
in_c4.w
+
alpha[index
+
3]
;
WRITE_FLT4
(
output,
(
int2
)(
X
*
UP_DIV
(
C,
SLICES
)
+
num,
Y
)
,
tmp
)
; // NHWC4: H WC
}
}
mindspore/lite/src/runtime/kernel/opencl/kernel/biasadd.cc
0 → 100644
浏览文件 @
46a2d163
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* 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 <string>
#include <map>
#include <set>
#include <vector>
#include "src/kernel_registry.h"
#include "include/errorcode.h"
#include "src/runtime/kernel/opencl/kernel/biasadd.h"
#include "src/runtime/opencl/opencl_runtime.h"
#include "src/runtime/kernel/opencl/cl/biasadd.cl.inc"
using
mindspore
::
kernel
::
KERNEL_ARCH
::
kGPU
;
using
mindspore
::
lite
::
KernelRegistrar
;
using
mindspore
::
lite
::
RET_ERROR
;
using
mindspore
::
lite
::
RET_OK
;
using
mindspore
::
schema
::
PrimitiveType_BiasAdd
;
namespace
mindspore
::
kernel
{
void
BiasAddOpenCLKernel
::
InitBuffer
()
{
int
C
=
in_tensors_
[
1
]
->
shape
()[
0
];
int
div_ci
=
UP_DIV
(
C
,
C4NUM
);
auto
allocator
=
lite
::
opencl
::
OpenCLRuntime
::
GetInstance
()
->
GetAllocator
();
BiasAdd_
=
reinterpret_cast
<
FLOAT_t
*>
(
allocator
->
Malloc
(
div_ci
*
C4NUM
*
sizeof
(
FLOAT_t
)));
BiasAdd_
=
reinterpret_cast
<
FLOAT_t
*>
(
allocator
->
MapBuffer
(
BiasAdd_
,
CL_MAP_WRITE
,
nullptr
,
true
));
memset
(
BiasAdd_
,
0x00
,
div_ci
*
C4NUM
*
sizeof
(
FLOAT_t
));
auto
origin_weight
=
reinterpret_cast
<
FLOAT_t
*>
(
in_tensors_
[
1
]
->
Data
());
for
(
int
i
=
0
;
i
<
in_tensors_
[
1
]
->
ElementsNum
();
++
i
)
{
BiasAdd_
[
i
]
=
origin_weight
[
i
];
}
allocator
->
UnmapBuffer
(
BiasAdd_
);
}
int
BiasAddOpenCLKernel
::
Init
()
{
in_size_
=
in_tensors_
[
0
]
->
shape
().
size
();
out_size_
=
out_tensors_
[
0
]
->
shape
().
size
();
if
(
in_size_
!=
4
&&
in_size_
!=
2
)
{
MS_LOG
(
ERROR
)
<<
"BiasAdd only support dim=4 or 2, but your dim="
<<
in_size_
;
return
RET_ERROR
;
}
int
C
=
in_tensors_
[
0
]
->
shape
()[
3
];
int
Bias_Size
=
in_tensors_
[
1
]
->
shape
()[
0
];
if
(
UP_DIV
(
Bias_Size
,
C4NUM
)
!=
UP_DIV
(
C
,
C4NUM
))
{
MS_LOG
(
ERROR
)
<<
"BiasAdd weight channel size:"
<<
Bias_Size
<<
" must be equal with in_teneors channel size:"
<<
C
;
return
RET_ERROR
;
}
InitBuffer
();
std
::
set
<
std
::
string
>
build_options
;
std
::
string
source
=
biasadd_source
;
std
::
string
program_name
=
"BiasAdd"
;
std
::
string
kernel_name
=
"BiasAdd"
;
auto
ocl_runtime
=
lite
::
opencl
::
OpenCLRuntime
::
GetInstance
();
ocl_runtime
->
LoadSource
(
program_name
,
source
);
ocl_runtime
->
BuildKernel
(
kernel_
,
program_name
,
kernel_name
,
build_options
);
in_ori_format_
=
in_tensors_
[
0
]
->
GetFormat
();
out_ori_format_
=
out_tensors_
[
0
]
->
GetFormat
();
std
::
map
<
int
,
schema
::
Format
>
format
{{
4
,
schema
::
Format_NHWC4
},
{
2
,
schema
::
Format_NC4
}};
if
(
format
.
count
(
out_size_
)
==
0
)
{
MS_LOG
(
ERROR
)
<<
"Not found output tensor format"
;
return
RET_ERROR
;
}
in_tensors_
[
0
]
->
SetFormat
(
format
[
in_size_
]);
out_tensors_
[
0
]
->
SetFormat
(
format
[
out_size_
]);
if
(
in_size_
==
2
)
{
in_ori_format_
=
format
[
in_size_
];
out_ori_format_
=
format
[
out_size_
];
}
MS_LOG
(
DEBUG
)
<<
program_name
<<
" Init Done!"
;
return
RET_OK
;
}
int
BiasAddOpenCLKernel
::
Run
()
{
cl_int4
input_shape
=
GetImg2dShape
();
MS_LOG
(
DEBUG
)
<<
op_parameter_
->
name_
<<
" Running!"
;
auto
ocl_runtime
=
lite
::
opencl
::
OpenCLRuntime
::
GetInstance
();
int
arg_idx
=
0
;
ocl_runtime
->
SetKernelArg
(
kernel_
,
arg_idx
++
,
in_tensors_
[
0
]
->
Data
());
ocl_runtime
->
SetKernelArg
(
kernel_
,
arg_idx
++
,
out_tensors_
[
0
]
->
Data
());
ocl_runtime
->
SetKernelArg
(
kernel_
,
arg_idx
++
,
input_shape
);
ocl_runtime
->
SetKernelArg
(
kernel_
,
arg_idx
++
,
BiasAdd_
);
ocl_runtime
->
SetKernelArg
(
kernel_
,
arg_idx
++
,
in_size_
);
std
::
vector
<
size_t
>
local
=
{
1
,
1
};
std
::
vector
<
size_t
>
global
=
{
static_cast
<
size_t
>
(
input_shape
.
s
[
1
]),
static_cast
<
size_t
>
(
input_shape
.
s
[
2
])};
auto
ret
=
ocl_runtime
->
RunKernel
(
kernel_
,
global
,
local
,
nullptr
);
if
(
ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"Run kernel "
<<
op_parameter_
->
name_
<<
" error."
;
return
RET_ERROR
;
}
return
RET_OK
;
}
cl_int4
BiasAddOpenCLKernel
::
GetImg2dShape
()
{
cl_int4
img2d_shape
=
{
0
,
0
,
0
,
0
};
for
(
int
i
=
0
;
i
<
in_size_
;
++
i
)
{
img2d_shape
.
s
[
i
+
4
-
in_size_
]
=
in_tensors_
[
0
]
->
shape
()[
i
];
}
if
(
in_size_
==
2
)
{
img2d_shape
.
s
[
1
]
=
img2d_shape
.
s
[
2
];
img2d_shape
.
s
[
2
]
=
UP_DIV
(
img2d_shape
.
s
[
3
],
C4NUM
);
img2d_shape
.
s
[
3
]
=
C4NUM
;
}
return
img2d_shape
;
}
int
BiasAddOpenCLKernel
::
GetImageSize
(
size_t
idx
,
std
::
vector
<
size_t
>
*
img_size
)
{
cl_int4
img_shape
=
GetImg2dShape
();
#ifdef ENABLE_FP16
size_t
img_dtype
=
CL_HALF_FLOAT
;
#else
size_t
img_dtype
=
CL_FLOAT
;
#endif
img_size
->
clear
();
img_size
->
push_back
(
img_shape
.
s
[
2
]
*
UP_DIV
(
img_shape
.
s
[
3
],
C4NUM
));
img_size
->
push_back
(
img_shape
.
s
[
1
]);
img_size
->
push_back
(
img_dtype
);
return
RET_OK
;
}
kernel
::
LiteKernel
*
OpenCLBiasAddKernelCreator
(
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
OpParameter
*
opParameter
,
const
lite
::
Context
*
ctx
,
const
kernel
::
KernelKey
&
desc
,
const
lite
::
PrimitiveC
*
primitive
)
{
if
(
inputs
.
size
()
==
0
)
{
MS_LOG
(
ERROR
)
<<
"Input data size must be greater than 0, but your size is "
<<
inputs
.
size
();
return
nullptr
;
}
if
(
inputs
[
0
]
->
shape
()[
0
]
>
1
)
{
MS_LOG
(
ERROR
)
<<
"Input data size unsupported multi-batch."
;
return
nullptr
;
}
auto
*
kernel
=
new
(
std
::
nothrow
)
BiasAddOpenCLKernel
(
reinterpret_cast
<
OpParameter
*>
(
opParameter
),
inputs
,
outputs
);
if
(
kernel
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Kernel "
<<
opParameter
->
name_
<<
"is nullptr."
;
return
nullptr
;
}
auto
ret
=
kernel
->
Init
();
if
(
ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"Init BiasAdd kernel failed!"
;
delete
kernel
;
return
nullptr
;
}
return
kernel
;
}
REG_KERNEL
(
kGPU
,
kNumberTypeFloat32
,
PrimitiveType_BiasAdd
,
OpenCLBiasAddKernelCreator
)
}
// namespace mindspore::kernel
mindspore/lite/src/runtime/kernel/opencl/kernel/biasadd.h
0 → 100644
浏览文件 @
46a2d163
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* 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.
*/
#ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_OPENCL_KERNEL_BIASADD_H_
#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_OPENCL_KERNEL_BIASADD_H_
#include <vector>
#include <string>
#include "src/ir/tensor.h"
#include "src/runtime/kernel/opencl/opencl_kernel.h"
#include "schema/model_generated.h"
#include "src/runtime/opencl/opencl_runtime.h"
namespace
mindspore
::
kernel
{
class
BiasAddOpenCLKernel
:
public
OpenCLKernel
{
public:
explicit
BiasAddOpenCLKernel
(
OpParameter
*
parameter
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
)
:
OpenCLKernel
(
parameter
,
inputs
,
outputs
)
{}
~
BiasAddOpenCLKernel
()
override
{};
int
Init
()
override
;
int
Run
()
override
;
int
GetImageSize
(
size_t
idx
,
std
::
vector
<
size_t
>
*
img_size
)
override
;
void
InitBuffer
();
cl_int4
GetImg2dShape
();
private:
cl
::
Kernel
kernel_
;
FLOAT_t
*
BiasAdd_
;
int
in_size_
;
int
out_size_
;
};
}
// namespace mindspore::kernel
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_OPENCL_KERNEL_BIASADD_H_
mindspore/lite/test/CMakeLists.txt
浏览文件 @
46a2d163
...
...
@@ -158,6 +158,7 @@ if (SUPPORT_GPU)
${
LITE_DIR
}
/src/runtime/kernel/opencl/kernel/caffe_prelu.cc
${
LITE_DIR
}
/src/runtime/kernel/opencl/kernel/prelu.cc
${
LITE_DIR
}
/src/runtime/kernel/opencl/kernel/to_format.cc
${
LITE_DIR
}
/src/runtime/kernel/opencl/kernel/biasadd.cc
)
endif
()
### minddata lite
...
...
@@ -338,6 +339,7 @@ if (SUPPORT_GPU)
${
TEST_DIR
}
/ut/src/runtime/kernel/opencl/caffe_prelu_tests.cc
${
TEST_DIR
}
/ut/src/runtime/kernel/opencl/prelu_tests.cc
${
TEST_DIR
}
/ut/src/runtime/kernel/opencl/reshape_tests.cc
${
TEST_DIR
}
/ut/src/runtime/kernel/opencl/biasadd_tests.cc
)
endif
()
...
...
mindspore/lite/test/ut/src/runtime/kernel/opencl/biasadd_tests.cc
0 → 100644
浏览文件 @
46a2d163
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* 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 <iostream>
#include "utils/log_adapter.h"
#include "common/common_test.h"
#include "mindspore/lite/src/common/file_utils.h"
#include "mindspore/lite/src/runtime/opencl/opencl_runtime.h"
#include "mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.h"
#include "mindspore/lite/src/runtime/kernel/opencl/kernel/biasadd.h"
using
mindspore
::
kernel
::
BiasAddOpenCLKernel
;
using
mindspore
::
kernel
::
LiteKernel
;
using
mindspore
::
kernel
::
SubGraphOpenCLKernel
;
using
mindspore
::
lite
::
RET_ERROR
;
using
mindspore
::
lite
::
RET_OK
;
namespace
mindspore
{
class
TestBiasAddOpenCL
:
public
mindspore
::
CommonTest
{};
void
LoadDataBiasAdd
(
void
*
dst
,
size_t
dst_size
,
const
std
::
string
&
file_path
)
{
if
(
file_path
.
empty
())
{
memset
(
dst
,
0x00
,
dst_size
);
}
else
{
auto
src_data
=
reinterpret_cast
<
float
*>
(
mindspore
::
lite
::
ReadFile
(
file_path
.
c_str
(),
&
dst_size
));
memcpy
(
dst
,
src_data
,
dst_size
);
}
}
void
CompareOutBiasAdd
(
lite
::
tensor
::
Tensor
*
output_tensor
,
const
std
::
string
&
standard_answer_file
)
{
auto
*
output_data
=
reinterpret_cast
<
float
*>
(
output_tensor
->
Data
());
size_t
output_size
=
output_tensor
->
ElementsNum
();
auto
expect_data
=
reinterpret_cast
<
float
*>
(
mindspore
::
lite
::
ReadFile
(
standard_answer_file
.
c_str
(),
&
output_size
));
constexpr
float
atol
=
0.0002
;
for
(
int
i
=
0
;
i
<
output_tensor
->
ElementsNum
();
++
i
)
{
if
(
std
::
fabs
(
output_data
[
i
]
-
expect_data
[
i
])
>
atol
)
{
printf
(
"error at idx[%d] expect=%.3f output=%.3f
\n
"
,
i
,
expect_data
[
i
],
output_data
[
i
]);
printf
(
"error at idx[%d] expect=%.3f output=%.3f
\n
"
,
i
,
expect_data
[
i
],
output_data
[
i
]);
printf
(
"error at idx[%d] expect=%.3f output=%.3f
\n\n\n
"
,
i
,
expect_data
[
i
],
output_data
[
i
]);
return
;
}
}
printf
(
"compare success!
\n
"
);
printf
(
"compare success!
\n
"
);
printf
(
"compare success!
\n\n\n
"
);
}
void
printf_tensor_BiasAdd
(
mindspore
::
lite
::
tensor
::
Tensor
*
in_data
,
int
size
)
{
auto
input_data
=
reinterpret_cast
<
float
*>
(
in_data
->
Data
());
for
(
int
i
=
0
;
i
<
size
;
++
i
)
{
printf
(
"%f "
,
input_data
[
i
]);
}
printf
(
"
\n
"
);
MS_LOG
(
INFO
)
<<
"Print tensor done"
;
}
void
printf_float_BiasAdd
(
float
*
data
,
int
num
=
0
)
{
float
*
temp
=
data
;
for
(
int
i
=
0
;
i
<
num
;
++
i
)
{
std
::
cout
<<
*
temp
<<
" "
;
temp
++
;
}
std
::
cout
<<
std
::
endl
;
}
TEST_F
(
TestBiasAddOpenCL
,
BiasAddFp32_dim4
)
{
std
::
string
in_file
=
"/data/local/tmp/in_data.bin"
;
std
::
string
weight_file
=
"/data/local/tmp/weight_data.bin"
;
std
::
string
standard_answer_file
=
"/data/local/tmp/biasadd.bin"
;
MS_LOG
(
INFO
)
<<
"BiasAdd Begin test:"
;
auto
ocl_runtime
=
lite
::
opencl
::
OpenCLRuntime
::
GetInstance
();
ocl_runtime
->
Init
();
auto
allocator
=
ocl_runtime
->
GetAllocator
();
MS_LOG
(
INFO
)
<<
"BiasAdd init tensors."
;
std
::
vector
<
int
>
input_shape
=
{
1
,
9
};
std
::
vector
<
int
>
output_shape
=
{
1
,
9
};
auto
data_type
=
kNumberTypeFloat32
;
auto
tensor_type
=
schema
::
NodeType_ValueNode
;
auto
*
input_tensor
=
new
(
std
::
nothrow
)
lite
::
tensor
::
Tensor
(
data_type
,
input_shape
,
schema
::
Format_NC
,
tensor_type
);
if
(
input_tensor
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"new input tensor error!"
;
return
;
}
auto
*
output_tensor
=
new
(
std
::
nothrow
)
lite
::
tensor
::
Tensor
(
data_type
,
output_shape
,
schema
::
Format_NC
,
tensor_type
);
if
(
output_tensor
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"new output tensor error!"
;
delete
input_tensor
;
return
;
}
auto
*
weight_tensor
=
new
(
std
::
nothrow
)
lite
::
tensor
::
Tensor
(
data_type
,
std
::
vector
<
int
>
{
input_shape
[
1
]},
schema
::
Format_NHWC
,
tensor_type
);
if
(
weight_tensor
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"new weight tensor error!"
;
delete
output_tensor
;
delete
input_tensor
;
return
;
}
std
::
vector
<
lite
::
tensor
::
Tensor
*>
inputs
{
input_tensor
,
weight_tensor
};
std
::
vector
<
lite
::
tensor
::
Tensor
*>
outputs
{
output_tensor
};
inputs
[
0
]
->
MallocData
(
allocator
);
inputs
[
1
]
->
MallocData
(
allocator
);
LoadDataBiasAdd
(
input_tensor
->
Data
(),
input_tensor
->
Size
(),
in_file
);
MS_LOG
(
INFO
)
<<
"BiasAdd==================input data================"
;
printf_tensor_BiasAdd
(
inputs
[
0
],
input_tensor
->
ElementsNum
());
LoadDataBiasAdd
(
weight_tensor
->
Data
(),
weight_tensor
->
Size
(),
weight_file
);
MS_LOG
(
INFO
)
<<
"BiasAdd==================weight data================"
;
printf_tensor_BiasAdd
(
inputs
[
1
],
weight_tensor
->
ElementsNum
());
auto
*
param
=
new
(
std
::
nothrow
)
OpParameter
();
if
(
param
==
nullptr
)
{
delete
input_tensor
;
delete
output_tensor
;
delete
weight_tensor
;
MS_LOG
(
ERROR
)
<<
"new OpParameter error!"
;
return
;
}
auto
*
biasadd_kernel
=
new
(
std
::
nothrow
)
kernel
::
BiasAddOpenCLKernel
(
reinterpret_cast
<
OpParameter
*>
(
param
),
inputs
,
outputs
);
if
(
biasadd_kernel
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Create biasadd kernel error."
;
delete
input_tensor
;
delete
output_tensor
;
delete
weight_tensor
;
delete
param
;
return
;
}
auto
ret
=
biasadd_kernel
->
Init
();
if
(
ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"biasadd kernel init error."
;
delete
input_tensor
;
delete
output_tensor
;
delete
weight_tensor
;
delete
param
;
delete
biasadd_kernel
;
return
;
}
MS_LOG
(
INFO
)
<<
"initialize sub_graph"
;
std
::
vector
<
kernel
::
LiteKernel
*>
kernels
{
biasadd_kernel
};
auto
*
sub_graph
=
new
(
std
::
nothrow
)
kernel
::
SubGraphOpenCLKernel
({
input_tensor
},
outputs
,
kernels
,
kernels
,
kernels
);
if
(
sub_graph
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Create sub_graph kernel error."
;
delete
input_tensor
;
delete
output_tensor
;
delete
weight_tensor
;
delete
param
;
delete
biasadd_kernel
;
return
;
}
ret
=
sub_graph
->
Init
();
if
(
ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"sub_graph init error."
;
delete
input_tensor
;
delete
output_tensor
;
delete
weight_tensor
;
delete
sub_graph
;
delete
param
;
delete
biasadd_kernel
;
return
;
}
MS_LOG
(
INFO
)
<<
"Sub graph begin running!"
;
ret
=
sub_graph
->
Run
();
if
(
ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"sub_graph run error."
;
delete
input_tensor
;
delete
output_tensor
;
delete
weight_tensor
;
delete
sub_graph
;
delete
param
;
delete
biasadd_kernel
;
return
;
}
MS_LOG
(
INFO
)
<<
"BiasAdd==================output data================"
;
printf_tensor_BiasAdd
(
outputs
[
0
],
output_tensor
->
ElementsNum
());
CompareOutBiasAdd
(
output_tensor
,
standard_answer_file
);
delete
input_tensor
;
delete
weight_tensor
;
delete
output_tensor
;
delete
sub_graph
;
delete
param
;
delete
biasadd_kernel
;
}
}
// namespace mindspore
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