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e73e9a9a
编写于
8月 11, 2020
作者:
M
mindspore-ci-bot
提交者:
Gitee
8月 11, 2020
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差异文件
!4261 [MS][LITE] fix arm fp32 op bug: conv_depthwise_3x3, batchnorm, scale, etc.
Merge pull request !4261 from yangruoqi713/test_dw
上级
c2997845
c7ad8fca
变更
34
隐藏空白更改
内联
并排
Showing
34 changed file
with
453 addition
and
236 deletion
+453
-236
mindspore/lite/src/populate_parameter.cc
mindspore/lite/src/populate_parameter.cc
+5
-6
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_depthwise_fp16.cc
...src/runtime/kernel/arm/fp16/convolution_depthwise_fp16.cc
+24
-2
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_depthwise_fp16.h
.../src/runtime/kernel/arm/fp16/convolution_depthwise_fp16.h
+1
-6
mindspore/lite/src/runtime/kernel/arm/fp16/deconvolution_depthwise_fp16.cc
...c/runtime/kernel/arm/fp16/deconvolution_depthwise_fp16.cc
+24
-2
mindspore/lite/src/runtime/kernel/arm/fp16/deconvolution_depthwise_fp16.h
...rc/runtime/kernel/arm/fp16/deconvolution_depthwise_fp16.h
+1
-9
mindspore/lite/src/runtime/kernel/arm/fp32/batchnorm.cc
mindspore/lite/src/runtime/kernel/arm/fp32/batchnorm.cc
+51
-6
mindspore/lite/src/runtime/kernel/arm/fp32/batchnorm.h
mindspore/lite/src/runtime/kernel/arm/fp32/batchnorm.h
+2
-2
mindspore/lite/src/runtime/kernel/arm/fp32/convolution_depthwise.cc
...lite/src/runtime/kernel/arm/fp32/convolution_depthwise.cc
+31
-5
mindspore/lite/src/runtime/kernel/arm/fp32/convolution_depthwise.h
.../lite/src/runtime/kernel/arm/fp32/convolution_depthwise.h
+1
-8
mindspore/lite/src/runtime/kernel/arm/fp32/deconvolution_depthwise.cc
...te/src/runtime/kernel/arm/fp32/deconvolution_depthwise.cc
+26
-2
mindspore/lite/src/runtime/kernel/arm/fp32/deconvolution_depthwise.h
...ite/src/runtime/kernel/arm/fp32/deconvolution_depthwise.h
+1
-8
mindspore/lite/src/runtime/kernel/arm/fp32/flatten.cc
mindspore/lite/src/runtime/kernel/arm/fp32/flatten.cc
+6
-2
mindspore/lite/src/runtime/kernel/arm/fp32/fused_batchnorm.cc
...spore/lite/src/runtime/kernel/arm/fp32/fused_batchnorm.cc
+103
-15
mindspore/lite/src/runtime/kernel/arm/fp32/fused_batchnorm.h
mindspore/lite/src/runtime/kernel/arm/fp32/fused_batchnorm.h
+14
-5
mindspore/lite/src/runtime/kernel/arm/fp32/scale.cc
mindspore/lite/src/runtime/kernel/arm/fp32/scale.cc
+27
-24
mindspore/lite/src/runtime/kernel/arm/fp32/scale.h
mindspore/lite/src/runtime/kernel/arm/fp32/scale.h
+5
-3
mindspore/lite/src/runtime/kernel/arm/int8/convolution_depthwise_int8.cc
...src/runtime/kernel/arm/int8/convolution_depthwise_int8.cc
+27
-2
mindspore/lite/src/runtime/kernel/arm/int8/convolution_depthwise_int8.h
.../src/runtime/kernel/arm/int8/convolution_depthwise_int8.h
+1
-8
mindspore/lite/src/runtime/kernel/arm/int8/deconvolution_depthwise_int8.cc
...c/runtime/kernel/arm/int8/deconvolution_depthwise_int8.cc
+38
-5
mindspore/lite/src/runtime/kernel/arm/int8/deconvolution_depthwise_int8.h
...rc/runtime/kernel/arm/int8/deconvolution_depthwise_int8.h
+2
-9
mindspore/lite/src/runtime/kernel/arm/nnacl/flatten.h
mindspore/lite/src/runtime/kernel/arm/nnacl/flatten.h
+0
-1
mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/batchnorm.cc
...spore/lite/src/runtime/kernel/arm/nnacl/fp32/batchnorm.cc
+14
-3
mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/batchnorm.h
mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/batchnorm.h
+3
-0
mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/conv_depthwise.cc
.../lite/src/runtime/kernel/arm/nnacl/fp32/conv_depthwise.cc
+28
-0
mindspore/lite/src/runtime/kernel/arm/nnacl/fused_batchnorm.cc
...pore/lite/src/runtime/kernel/arm/nnacl/fused_batchnorm.cc
+0
-35
mindspore/lite/src/runtime/kernel/arm/nnacl/fused_batchnorm.h
...spore/lite/src/runtime/kernel/arm/nnacl/fused_batchnorm.h
+0
-32
mindspore/lite/src/runtime/kernel/arm/nnacl/scale.h
mindspore/lite/src/runtime/kernel/arm/nnacl/scale.h
+2
-3
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batchnorm_fp32_tests.cc
...st/ut/src/runtime/kernel/arm/fp32/batchnorm_fp32_tests.cc
+16
-29
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_0.bin
...kernel/arm/test_data/batchnorm/fusedBatchnorm_input_0.bin
+0
-0
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_1.bin
...kernel/arm/test_data/batchnorm/fusedBatchnorm_input_1.bin
+0
-1
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_2.bin
...kernel/arm/test_data/batchnorm/fusedBatchnorm_input_2.bin
+0
-1
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_3.bin
...kernel/arm/test_data/batchnorm/fusedBatchnorm_input_3.bin
+0
-1
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_4.bin
...kernel/arm/test_data/batchnorm/fusedBatchnorm_input_4.bin
+0
-1
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_out.bin
...ime/kernel/arm/test_data/batchnorm/fusedBatchnorm_out.bin
+0
-0
未找到文件。
mindspore/lite/src/populate_parameter.cc
浏览文件 @
e73e9a9a
...
@@ -40,7 +40,6 @@
...
@@ -40,7 +40,6 @@
#include "src/runtime/kernel/arm/nnacl/fp32/reduce.h"
#include "src/runtime/kernel/arm/nnacl/fp32/reduce.h"
#include "src/runtime/kernel/arm/nnacl/fp32/activation.h"
#include "src/runtime/kernel/arm/nnacl/fp32/activation.h"
#include "src/runtime/kernel/arm/nnacl/fp32/arithmetic.h"
#include "src/runtime/kernel/arm/nnacl/fp32/arithmetic.h"
#include "src/runtime/kernel/arm/nnacl/fused_batchnorm.h"
#include "src/runtime/kernel/arm/nnacl/fp32/batchnorm.h"
#include "src/runtime/kernel/arm/nnacl/fp32/batchnorm.h"
#include "src/runtime/kernel/arm/nnacl/power.h"
#include "src/runtime/kernel/arm/nnacl/power.h"
#include "src/runtime/kernel/arm/nnacl/fp32/range.h"
#include "src/runtime/kernel/arm/nnacl/fp32/range.h"
...
@@ -510,15 +509,15 @@ OpParameter *PopulateActivationParameter(const lite::Primitive *primitive) {
...
@@ -510,15 +509,15 @@ OpParameter *PopulateActivationParameter(const lite::Primitive *primitive) {
}
}
OpParameter
*
PopulateFusedBatchNorm
(
const
lite
::
Primitive
*
primitive
)
{
OpParameter
*
PopulateFusedBatchNorm
(
const
lite
::
Primitive
*
primitive
)
{
FusedBatchNormParameter
*
fuse_batch_norm_param
=
new
(
std
::
nothrow
)
Fused
BatchNormParameter
();
BatchNormParameter
*
batch_norm_param
=
new
(
std
::
nothrow
)
BatchNormParameter
();
if
(
fuse_
batch_norm_param
==
nullptr
)
{
if
(
batch_norm_param
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"new FusedBatchNormParameter failed."
;
MS_LOG
(
ERROR
)
<<
"new FusedBatchNormParameter failed."
;
return
nullptr
;
return
nullptr
;
}
}
fuse_
batch_norm_param
->
op_parameter_
.
type_
=
primitive
->
Type
();
batch_norm_param
->
op_parameter_
.
type_
=
primitive
->
Type
();
auto
param
=
primitive
->
Value
()
->
value_as_FusedBatchNorm
();
auto
param
=
primitive
->
Value
()
->
value_as_FusedBatchNorm
();
fuse_
batch_norm_param
->
epsilon_
=
param
->
epsilon
();
batch_norm_param
->
epsilon_
=
param
->
epsilon
();
return
reinterpret_cast
<
OpParameter
*>
(
fuse_
batch_norm_param
);
return
reinterpret_cast
<
OpParameter
*>
(
batch_norm_param
);
}
}
OpParameter
*
PopulateArithmetic
(
const
lite
::
Primitive
*
primitive
)
{
OpParameter
*
PopulateArithmetic
(
const
lite
::
Primitive
*
primitive
)
{
...
...
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_depthwise_fp16.cc
浏览文件 @
e73e9a9a
...
@@ -28,6 +28,22 @@ using mindspore::lite::RET_OK;
...
@@ -28,6 +28,22 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_DepthwiseConv2D
;
using
mindspore
::
schema
::
PrimitiveType_DepthwiseConv2D
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
ConvolutionDepthwiseFp16CPUKernel
::~
ConvolutionDepthwiseFp16CPUKernel
()
{
delete
sliding_
;
if
(
packed_weight_
!=
nullptr
)
{
delete
packed_weight_
;
packed_weight_
=
nullptr
;
}
if
(
packed_input_
!=
nullptr
)
{
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
int
ConvolutionDepthwiseFp16CPUKernel
::
InitBuffer
()
{
int
ConvolutionDepthwiseFp16CPUKernel
::
InitBuffer
()
{
// malloc pack input buffer
// malloc pack input buffer
int
C8
=
UP_DIV
(
conv_param_
->
input_channel_
,
C8NUM
);
int
C8
=
UP_DIV
(
conv_param_
->
input_channel_
,
C8NUM
);
...
@@ -113,8 +129,14 @@ int ConvolutionDepthwiseFp16CPUKernel::Init() {
...
@@ -113,8 +129,14 @@ int ConvolutionDepthwiseFp16CPUKernel::Init() {
}
}
int
ConvolutionDepthwiseFp16CPUKernel
::
ReSize
()
{
int
ConvolutionDepthwiseFp16CPUKernel
::
ReSize
()
{
free
(
packed_input_
);
if
(
packed_input_
!=
nullptr
)
{
free
(
packed_output_
);
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
ConvolutionBaseCPUKernel
::
Init
();
ConvolutionBaseCPUKernel
::
Init
();
InitSlidingParam
(
sliding_
,
conv_param_
,
C8NUM
);
InitSlidingParam
(
sliding_
,
conv_param_
,
C8NUM
);
...
...
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_depthwise_fp16.h
浏览文件 @
e73e9a9a
...
@@ -29,12 +29,7 @@ class ConvolutionDepthwiseFp16CPUKernel : public ConvolutionBaseCPUKernel {
...
@@ -29,12 +29,7 @@ class ConvolutionDepthwiseFp16CPUKernel : public ConvolutionBaseCPUKernel {
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
~
ConvolutionDepthwiseFp16CPUKernel
()
override
{
~
ConvolutionDepthwiseFp16CPUKernel
()
override
;
delete
sliding_
;
free
(
packed_weight_
);
free
(
packed_input_
);
free
(
packed_output_
);
}
int
Init
()
override
;
int
Init
()
override
;
int
ReSize
()
override
;
int
ReSize
()
override
;
...
...
mindspore/lite/src/runtime/kernel/arm/fp16/deconvolution_depthwise_fp16.cc
浏览文件 @
e73e9a9a
...
@@ -28,6 +28,22 @@ using mindspore::lite::RET_OK;
...
@@ -28,6 +28,22 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_DeDepthwiseConv2D
;
using
mindspore
::
schema
::
PrimitiveType_DeDepthwiseConv2D
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
DeconvolutionDepthwiseFp16CPUKernel
::~
DeconvolutionDepthwiseFp16CPUKernel
()
{
delete
sliding_
;
if
(
packed_weight_
!=
nullptr
)
{
delete
packed_weight_
;
packed_weight_
=
nullptr
;
}
if
(
packed_input_
!=
nullptr
)
{
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
int
DeconvolutionDepthwiseFp16CPUKernel
::
InitSlideParam
()
{
int
DeconvolutionDepthwiseFp16CPUKernel
::
InitSlideParam
()
{
conv_param_
->
input_batch_
=
outputs_
.
front
()
->
shape
().
at
(
kNHWC_N
);
conv_param_
->
input_batch_
=
outputs_
.
front
()
->
shape
().
at
(
kNHWC_N
);
conv_param_
->
input_h_
=
outputs_
.
front
()
->
shape
().
at
(
kNHWC_H
);
conv_param_
->
input_h_
=
outputs_
.
front
()
->
shape
().
at
(
kNHWC_H
);
...
@@ -126,8 +142,14 @@ int DeconvolutionDepthwiseFp16CPUKernel::Init() {
...
@@ -126,8 +142,14 @@ int DeconvolutionDepthwiseFp16CPUKernel::Init() {
}
}
int
DeconvolutionDepthwiseFp16CPUKernel
::
ReSize
()
{
int
DeconvolutionDepthwiseFp16CPUKernel
::
ReSize
()
{
free
(
packed_input_
);
if
(
packed_input_
!=
nullptr
)
{
free
(
packed_output_
);
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
InitSlideParam
();
InitSlideParam
();
ConvolutionBaseCPUKernel
::
Init
();
ConvolutionBaseCPUKernel
::
Init
();
...
...
mindspore/lite/src/runtime/kernel/arm/fp16/deconvolution_depthwise_fp16.h
浏览文件 @
e73e9a9a
...
@@ -29,14 +29,7 @@ class DeconvolutionDepthwiseFp16CPUKernel : public ConvolutionBaseCPUKernel {
...
@@ -29,14 +29,7 @@ class DeconvolutionDepthwiseFp16CPUKernel : public ConvolutionBaseCPUKernel {
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
~
DeconvolutionDepthwiseFp16CPUKernel
()
override
{
~
DeconvolutionDepthwiseFp16CPUKernel
()
override
;
delete
sliding_
;
free
(
packed_weight_
);
if
(
need_align_
)
{
free
(
packed_input_
);
free
(
packed_output_
);
}
};
int
Init
()
override
;
int
Init
()
override
;
int
ReSize
()
override
;
int
ReSize
()
override
;
...
@@ -52,7 +45,6 @@ class DeconvolutionDepthwiseFp16CPUKernel : public ConvolutionBaseCPUKernel {
...
@@ -52,7 +45,6 @@ class DeconvolutionDepthwiseFp16CPUKernel : public ConvolutionBaseCPUKernel {
float16_t
*
packed_weight_
;
float16_t
*
packed_weight_
;
float16_t
*
packed_input_
;
float16_t
*
packed_input_
;
float16_t
*
packed_output_
;
float16_t
*
packed_output_
;
bool
need_align_
=
false
;
};
};
}
// namespace mindspore::kernel
}
// namespace mindspore::kernel
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/batchnorm.cc
浏览文件 @
e73e9a9a
...
@@ -15,7 +15,6 @@
...
@@ -15,7 +15,6 @@
*/
*/
#include "src/runtime/kernel/arm/fp32/batchnorm.h"
#include "src/runtime/kernel/arm/fp32/batchnorm.h"
#include <cmath>
#include "schema/model_generated.h"
#include "schema/model_generated.h"
#include "src/kernel_registry.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"
#include "include/errorcode.h"
...
@@ -28,7 +27,42 @@ using mindspore::lite::RET_OK;
...
@@ -28,7 +27,42 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_BatchNorm
;
using
mindspore
::
schema
::
PrimitiveType_BatchNorm
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
BatchnormCPUKernel
::~
BatchnormCPUKernel
()
{
if
(
mean_addr_
!=
nullptr
)
{
free
(
mean_addr_
);
mean_addr_
=
nullptr
;
}
if
(
var_addr_
!=
nullptr
)
{
free
(
var_addr_
);
var_addr_
=
nullptr
;
}
}
int
BatchnormCPUKernel
::
InitConstTensor
()
{
auto
mean
=
inputs_
[
1
];
mean_addr_
=
reinterpret_cast
<
float
*>
(
malloc
(
mean
->
ElementsNum
()
*
sizeof
(
float
)));
if
(
mean_addr_
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
return
RET_ERROR
;
}
memcpy
(
mean_addr_
,
mean
->
Data
(),
mean
->
ElementsNum
()
*
sizeof
(
float
));
auto
variance
=
inputs_
[
2
];
var_addr_
=
reinterpret_cast
<
float
*>
(
malloc
(
variance
->
ElementsNum
()
*
sizeof
(
float
)));
if
(
var_addr_
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
return
RET_ERROR
;
}
memcpy
(
var_addr_
,
variance
->
Data
(),
variance
->
ElementsNum
()
*
sizeof
(
float
));
return
RET_OK
;
}
int
BatchnormCPUKernel
::
Init
()
{
int
BatchnormCPUKernel
::
Init
()
{
if
(
context_
->
infer_shape_interrupt_
&&
!
context_
->
running_
)
{
SetNeedReInit
();
return
RET_OK
;
}
auto
input_shapes
=
inputs_
[
0
]
->
shape
();
auto
input_shapes
=
inputs_
[
0
]
->
shape
();
auto
n_dim
=
input_shapes
.
size
();
auto
n_dim
=
input_shapes
.
size
();
batchnorm_param_
->
channel_
=
input_shapes
[
n_dim
-
1
];
batchnorm_param_
->
channel_
=
input_shapes
[
n_dim
-
1
];
...
@@ -37,11 +71,24 @@ int BatchnormCPUKernel::Init() {
...
@@ -37,11 +71,24 @@ int BatchnormCPUKernel::Init() {
batchnorm_param_
->
unit_
*=
input_shapes
[
i
];
batchnorm_param_
->
unit_
*=
input_shapes
[
i
];
}
}
batchnorm_param_
->
op_parameter_
.
thread_num_
=
batchnorm_param_
->
op_parameter_
.
thread_num_
=
MSMIN
(
batchnorm_param_
->
op_parameter_
.
thread_num_
,
batchnorm_param_
->
unit_
);
MSMIN
(
batchnorm_param_
->
op_parameter_
.
thread_num_
,
batchnorm_param_
->
channel_
);
auto
ret
=
InitConstTensor
();
if
(
ret
!=
0
)
{
MS_LOG
(
ERROR
)
<<
"Batchnorm fp32 InitConstTensor failed."
;
return
RET_ERROR
;
}
return
RET_OK
;
return
RET_OK
;
}
}
int
BatchnormCPUKernel
::
ReSize
()
{
return
RET_OK
;
}
int
BatchnormCPUKernel
::
ReSize
()
{
auto
input_shapes
=
inputs_
[
0
]
->
shape
();
batchnorm_param_
->
unit_
=
1
;
for
(
int
i
=
0
;
i
<
input_shapes
.
size
()
-
1
;
i
++
)
{
batchnorm_param_
->
unit_
*=
input_shapes
[
i
];
}
return
RET_OK
;
}
int
BatchnormCPUKernel
::
DoExecute
(
int
task_id
)
{
int
BatchnormCPUKernel
::
DoExecute
(
int
task_id
)
{
BatchNorm
(
out_addr_
,
in_addr_
,
mean_addr_
,
var_addr_
,
task_id
,
batchnorm_param_
);
BatchNorm
(
out_addr_
,
in_addr_
,
mean_addr_
,
var_addr_
,
task_id
,
batchnorm_param_
);
...
@@ -61,12 +108,10 @@ int BatchNormRun(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
...
@@ -61,12 +108,10 @@ int BatchNormRun(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
int
BatchnormCPUKernel
::
Run
()
{
int
BatchnormCPUKernel
::
Run
()
{
auto
prepare_ret
=
Prepare
();
auto
prepare_ret
=
Prepare
();
if
(
prepare_ret
!=
RET_OK
)
{
if
(
prepare_ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"Prepare fail!
ret
: "
<<
prepare_ret
;
MS_LOG
(
ERROR
)
<<
"Prepare fail!
Ret error code
: "
<<
prepare_ret
;
return
prepare_ret
;
return
prepare_ret
;
}
}
in_addr_
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
0
)
->
Data
());
in_addr_
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
0
)
->
Data
());
mean_addr_
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
1
)
->
Data
());
var_addr_
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
2
)
->
Data
());
out_addr_
=
reinterpret_cast
<
float
*>
(
outputs_
.
at
(
0
)
->
Data
());
out_addr_
=
reinterpret_cast
<
float
*>
(
outputs_
.
at
(
0
)
->
Data
());
int
ret
=
LiteBackendParallelLaunch
(
BatchNormRun
,
this
,
batchnorm_param_
->
op_parameter_
.
thread_num_
);
int
ret
=
LiteBackendParallelLaunch
(
BatchNormRun
,
this
,
batchnorm_param_
->
op_parameter_
.
thread_num_
);
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/batchnorm.h
浏览文件 @
e73e9a9a
...
@@ -31,14 +31,14 @@ class BatchnormCPUKernel : public LiteKernel {
...
@@ -31,14 +31,14 @@ class BatchnormCPUKernel : public LiteKernel {
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
LiteKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{
:
LiteKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{
opParameter
->
thread_num_
=
ctx
->
thread_num_
;
batchnorm_param_
=
reinterpret_cast
<
BatchNormParameter
*>
(
parameter
);
batchnorm_param_
=
reinterpret_cast
<
BatchNormParameter
*>
(
parameter
);
}
}
~
BatchnormCPUKernel
()
override
=
default
;
~
BatchnormCPUKernel
()
override
;
int
Init
()
override
;
int
Init
()
override
;
int
ReSize
()
override
;
int
ReSize
()
override
;
int
Run
()
override
;
int
Run
()
override
;
int
InitConstTensor
();
int
DoExecute
(
int
tid
);
int
DoExecute
(
int
tid
);
private:
private:
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/convolution_depthwise.cc
浏览文件 @
e73e9a9a
...
@@ -29,6 +29,24 @@ using mindspore::lite::RET_OK;
...
@@ -29,6 +29,24 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_DepthwiseConv2D
;
using
mindspore
::
schema
::
PrimitiveType_DepthwiseConv2D
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
ConvolutionDepthwiseCPUKernel
::~
ConvolutionDepthwiseCPUKernel
()
{
delete
sliding_
;
if
(
packed_weight_
!=
nullptr
)
{
delete
packed_weight_
;
packed_weight_
=
nullptr
;
}
if
(
need_align_
)
{
if
(
packed_input_
!=
nullptr
)
{
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
}
int
ConvolutionDepthwiseCPUKernel
::
InitWeightBias
()
{
int
ConvolutionDepthwiseCPUKernel
::
InitWeightBias
()
{
// init weight: o, h, w, i; o == group, i == 1
// init weight: o, h, w, i; o == group, i == 1
auto
weight_tensor
=
inputs_
[
kWeightIndex
];
auto
weight_tensor
=
inputs_
[
kWeightIndex
];
...
@@ -114,9 +132,16 @@ int ConvolutionDepthwiseCPUKernel::Init() {
...
@@ -114,9 +132,16 @@ int ConvolutionDepthwiseCPUKernel::Init() {
int
ConvolutionDepthwiseCPUKernel
::
ReSize
()
{
int
ConvolutionDepthwiseCPUKernel
::
ReSize
()
{
if
(
need_align_
)
{
if
(
need_align_
)
{
free
(
packed_input_
);
if
(
packed_input_
!=
nullptr
)
{
free
(
packed_output_
);
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
}
// conv base init
// conv base init
ConvolutionBaseCPUKernel
::
Init
();
ConvolutionBaseCPUKernel
::
Init
();
...
@@ -197,10 +222,11 @@ kernel::LiteKernel *CpuConvDwFp32KernelCreator(const std::vector<lite::tensor::T
...
@@ -197,10 +222,11 @@ kernel::LiteKernel *CpuConvDwFp32KernelCreator(const std::vector<lite::tensor::T
kernel
=
new
(
std
::
nothrow
)
kernel
::
ConvolutionDepthwiseCPUKernel
(
opParameter
,
inputs
,
outputs
,
ctx
,
primitive
);
kernel
=
new
(
std
::
nothrow
)
kernel
::
ConvolutionDepthwiseCPUKernel
(
opParameter
,
inputs
,
outputs
,
ctx
,
primitive
);
// auto param = reinterpret_cast<ConvParameter *>(opParameter);
// auto param = reinterpret_cast<ConvParameter *>(opParameter);
// if (param->kernel_h_ == 3 && param->kernel_w_ == 3 && param->stride_h_ == 1 && param->stride_w_ == 1 &&
// if (param->kernel_h_ == 3 && param->kernel_w_ == 3 && param->stride_h_ == 1 && param->stride_w_ == 1 &&
// param->dilation_h_ == 1 && param->dilation_w_ == 1) {
// param->dilation_h_ == 1 && param->dilation_w_ == 1) {
// kernel = new (std::nothrow) kernel::ConvolutionDepthwise3x3CPUKernel(opParameter, inputs, outputs, ctx);
// kernel = new (std::nothrow) kernel::ConvolutionDepthwise3x3CPUKernel(opParameter, inputs, outputs, ctx,
// primitive);
// } else {
// } else {
//
kernel = new (std::nothrow) kernel::ConvolutionDepthwiseCPUKernel(opParameter, inputs, outputs, ctx
);
//
kernel = new (std::nothrow) kernel::ConvolutionDepthwiseCPUKernel(opParameter, inputs, outputs, ctx, primitive
);
// }
// }
if
(
kernel
==
nullptr
)
{
if
(
kernel
==
nullptr
)
{
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/convolution_depthwise.h
浏览文件 @
e73e9a9a
...
@@ -29,14 +29,7 @@ class ConvolutionDepthwiseCPUKernel : public ConvolutionBaseCPUKernel {
...
@@ -29,14 +29,7 @@ class ConvolutionDepthwiseCPUKernel : public ConvolutionBaseCPUKernel {
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
lite
::
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
lite
::
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
~
ConvolutionDepthwiseCPUKernel
()
override
{
~
ConvolutionDepthwiseCPUKernel
()
override
;
delete
sliding_
;
free
(
packed_weight_
);
if
(
need_align_
)
{
free
(
packed_input_
);
free
(
packed_output_
);
}
};
int
Init
()
override
;
int
Init
()
override
;
int
ReSize
()
override
;
int
ReSize
()
override
;
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/deconvolution_depthwise.cc
浏览文件 @
e73e9a9a
...
@@ -27,6 +27,24 @@ using mindspore::lite::RET_OK;
...
@@ -27,6 +27,24 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_DeDepthwiseConv2D
;
using
mindspore
::
schema
::
PrimitiveType_DeDepthwiseConv2D
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
DeconvolutionDepthwiseCPUKernel
::~
DeconvolutionDepthwiseCPUKernel
()
{
delete
sliding_
;
if
(
packed_weight_
!=
nullptr
)
{
delete
packed_weight_
;
packed_weight_
=
nullptr
;
}
if
(
need_align_
)
{
if
(
packed_input_
!=
nullptr
)
{
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
}
int
DeconvolutionDepthwiseCPUKernel
::
InitSlideParam
()
{
int
DeconvolutionDepthwiseCPUKernel
::
InitSlideParam
()
{
conv_param_
->
input_batch_
=
outputs_
.
front
()
->
shape
().
at
(
kNHWC_N
);
conv_param_
->
input_batch_
=
outputs_
.
front
()
->
shape
().
at
(
kNHWC_N
);
conv_param_
->
input_h_
=
outputs_
.
front
()
->
shape
().
at
(
kNHWC_H
);
conv_param_
->
input_h_
=
outputs_
.
front
()
->
shape
().
at
(
kNHWC_H
);
...
@@ -126,8 +144,14 @@ int DeconvolutionDepthwiseCPUKernel::Init() {
...
@@ -126,8 +144,14 @@ int DeconvolutionDepthwiseCPUKernel::Init() {
int
DeconvolutionDepthwiseCPUKernel
::
ReSize
()
{
int
DeconvolutionDepthwiseCPUKernel
::
ReSize
()
{
if
(
need_align_
)
{
if
(
need_align_
)
{
free
(
packed_input_
);
if
(
packed_input_
!=
nullptr
)
{
free
(
packed_output_
);
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
}
InitSlideParam
();
InitSlideParam
();
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/deconvolution_depthwise.h
浏览文件 @
e73e9a9a
...
@@ -29,14 +29,7 @@ class DeconvolutionDepthwiseCPUKernel : public ConvolutionBaseCPUKernel {
...
@@ -29,14 +29,7 @@ class DeconvolutionDepthwiseCPUKernel : public ConvolutionBaseCPUKernel {
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
lite
::
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
lite
::
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
~
DeconvolutionDepthwiseCPUKernel
()
override
{
~
DeconvolutionDepthwiseCPUKernel
()
override
;
delete
sliding_
;
free
(
packed_weight_
);
if
(
need_align_
)
{
free
(
packed_input_
);
free
(
packed_output_
);
}
};
int
Init
()
override
;
int
Init
()
override
;
int
InitSlideParam
();
int
InitSlideParam
();
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/flatten.cc
浏览文件 @
e73e9a9a
...
@@ -32,6 +32,12 @@ int FlattenCPUKernel::Init() {
...
@@ -32,6 +32,12 @@ int FlattenCPUKernel::Init() {
SetNeedReInit
();
SetNeedReInit
();
return
RET_OK
;
return
RET_OK
;
}
}
ReSize
();
return
RET_OK
;
}
int
FlattenCPUKernel
::
ReSize
()
{
auto
output_shape
=
outputs_
[
0
]
->
shape
();
auto
output_shape
=
outputs_
[
0
]
->
shape
();
flatten_param_
->
size
=
sizeof
(
float
);
flatten_param_
->
size
=
sizeof
(
float
);
for
(
int
i
=
0
;
i
<
output_shape
.
size
();
i
++
)
{
for
(
int
i
=
0
;
i
<
output_shape
.
size
();
i
++
)
{
...
@@ -40,8 +46,6 @@ int FlattenCPUKernel::Init() {
...
@@ -40,8 +46,6 @@ int FlattenCPUKernel::Init() {
return
RET_OK
;
return
RET_OK
;
}
}
int
FlattenCPUKernel
::
ReSize
()
{
return
RET_OK
;
}
int
FlattenCPUKernel
::
Run
()
{
int
FlattenCPUKernel
::
Run
()
{
auto
prepare_ret
=
Prepare
();
auto
prepare_ret
=
Prepare
();
if
(
prepare_ret
!=
RET_OK
)
{
if
(
prepare_ret
!=
RET_OK
)
{
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/fused_batchnorm.cc
浏览文件 @
e73e9a9a
...
@@ -15,10 +15,10 @@
...
@@ -15,10 +15,10 @@
*/
*/
#include "src/runtime/kernel/arm/fp32/fused_batchnorm.h"
#include "src/runtime/kernel/arm/fp32/fused_batchnorm.h"
#include <cmath>
#include "schema/model_generated.h"
#include "schema/model_generated.h"
#include "src/kernel_registry.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"
#include "include/errorcode.h"
#include "src/runtime/runtime_api.h"
using
mindspore
::
kernel
::
KERNEL_ARCH
::
kCPU
;
using
mindspore
::
kernel
::
KERNEL_ARCH
::
kCPU
;
using
mindspore
::
lite
::
KernelRegistrar
;
using
mindspore
::
lite
::
KernelRegistrar
;
...
@@ -27,33 +27,121 @@ using mindspore::lite::RET_OK;
...
@@ -27,33 +27,121 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_FusedBatchNorm
;
using
mindspore
::
schema
::
PrimitiveType_FusedBatchNorm
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
FusedBatchnormCPUKernel
::~
FusedBatchnormCPUKernel
()
{
if
(
scale_addr_
!=
nullptr
)
{
free
(
scale_addr_
);
scale_addr_
=
nullptr
;
}
if
(
offset_addr_
!=
nullptr
)
{
free
(
offset_addr_
);
offset_addr_
=
nullptr
;
}
if
(
mean_addr_
!=
nullptr
)
{
free
(
mean_addr_
);
mean_addr_
=
nullptr
;
}
if
(
var_addr_
!=
nullptr
)
{
free
(
var_addr_
);
var_addr_
=
nullptr
;
}
}
int
FusedBatchnormCPUKernel
::
InitConstTensor
()
{
auto
scale
=
inputs_
[
1
];
scale_addr_
=
reinterpret_cast
<
float
*>
(
malloc
(
scale
->
ElementsNum
()
*
sizeof
(
float
)));
if
(
scale_addr_
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
return
RET_ERROR
;
}
memcpy
(
scale_addr_
,
scale
->
Data
(),
scale
->
ElementsNum
()
*
sizeof
(
float
));
auto
offset
=
inputs_
[
2
];
offset_addr_
=
reinterpret_cast
<
float
*>
(
malloc
(
offset
->
ElementsNum
()
*
sizeof
(
float
)));
if
(
offset_addr_
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
return
RET_ERROR
;
}
memcpy
(
offset_addr_
,
offset
->
Data
(),
offset
->
ElementsNum
()
*
sizeof
(
float
));
auto
mean
=
inputs_
[
3
];
mean_addr_
=
reinterpret_cast
<
float
*>
(
malloc
(
mean
->
ElementsNum
()
*
sizeof
(
float
)));
if
(
mean_addr_
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
return
RET_ERROR
;
}
memcpy
(
mean_addr_
,
mean
->
Data
(),
mean
->
ElementsNum
()
*
sizeof
(
float
));
auto
variance
=
inputs_
[
4
];
var_addr_
=
reinterpret_cast
<
float
*>
(
malloc
(
variance
->
ElementsNum
()
*
sizeof
(
float
)));
if
(
var_addr_
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
return
RET_ERROR
;
}
memcpy
(
var_addr_
,
variance
->
Data
(),
variance
->
ElementsNum
()
*
sizeof
(
float
));
return
RET_OK
;
}
int
FusedBatchnormCPUKernel
::
Init
()
{
int
FusedBatchnormCPUKernel
::
Init
()
{
if
(
context_
->
infer_shape_interrupt_
&&
!
context_
->
running_
)
{
if
(
context_
->
infer_shape_interrupt_
&&
!
context_
->
running_
)
{
SetNeedReInit
();
SetNeedReInit
();
return
RET_OK
;
return
RET_OK
;
}
}
input_shape_
=
reinterpret_cast
<
int
*>
(
malloc
(
sizeof
(
int
)
*
inputs_
[
0
]
->
shape
().
size
()));
auto
input_shapes
=
inputs_
[
0
]
->
shape
();
memcpy
(
input_shape_
,
inputs_
[
0
]
->
shape
().
data
(),
inputs_
[
0
]
->
shape
().
size
()
*
sizeof
(
int
));
auto
n_dim
=
input_shapes
.
size
();
batchnorm_param_
->
channel_
=
input_shapes
[
n_dim
-
1
];
batchnorm_param_
->
unit_
=
1
;
for
(
int
i
=
0
;
i
<
n_dim
-
1
;
i
++
)
{
batchnorm_param_
->
unit_
*=
input_shapes
[
i
];
}
batchnorm_param_
->
op_parameter_
.
thread_num_
=
MSMIN
(
batchnorm_param_
->
op_parameter_
.
thread_num_
,
batchnorm_param_
->
channel_
);
auto
ret
=
InitConstTensor
();
if
(
ret
!=
0
)
{
MS_LOG
(
ERROR
)
<<
"FusedBatchnorm fp32 InitConstTensor failed."
;
return
RET_ERROR
;
}
return
RET_OK
;
}
int
FusedBatchnormCPUKernel
::
ReSize
()
{
auto
input_shapes
=
inputs_
[
0
]
->
shape
();
batchnorm_param_
->
unit_
=
1
;
for
(
int
i
=
0
;
i
<
input_shapes
.
size
()
-
1
;
i
++
)
{
batchnorm_param_
->
unit_
*=
input_shapes
[
i
];
}
return
RET_OK
;
}
int
FusedBatchnormCPUKernel
::
Execute
(
int
task_id
)
{
FusedBatchNorm
(
out_addr_
,
in_addr_
,
scale_addr_
,
offset_addr_
,
mean_addr_
,
var_addr_
,
task_id
,
batchnorm_param_
);
return
RET_OK
;
return
RET_OK
;
}
}
int
FusedBatchnormCPUKernel
::
ReSize
()
{
return
RET_OK
;
}
int
FusedBatchNormRun
(
int
task_id
,
LiteParallelGroupEnv
*
penv
,
void
*
cdata
)
{
auto
g_kernel
=
reinterpret_cast
<
FusedBatchnormCPUKernel
*>
(
cdata
);
auto
ret
=
g_kernel
->
Execute
(
task_id
);
if
(
ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"FusedBatchnormRun error task_id["
<<
task_id
<<
"] error_code["
<<
ret
<<
"]"
;
return
ret
;
}
return
RET_OK
;
}
int
FusedBatchnormCPUKernel
::
Run
()
{
int
FusedBatchnormCPUKernel
::
Run
()
{
auto
prepare_ret
=
Prepare
();
auto
prepare_ret
=
Prepare
();
if
(
prepare_ret
!=
RET_OK
)
{
if
(
prepare_ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"Prepare fail!
ret
: "
<<
prepare_ret
;
MS_LOG
(
ERROR
)
<<
"Prepare fail!
Ret error code
: "
<<
prepare_ret
;
return
prepare_ret
;
return
prepare_ret
;
}
}
auto
input_addr
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
0
)
->
Data
());
in_addr_
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
0
)
->
Data
());
auto
scale_addr
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
1
)
->
Data
());
out_addr_
=
reinterpret_cast
<
float
*>
(
outputs_
.
at
(
0
)
->
Data
());
auto
offest_addr
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
2
)
->
Data
());
auto
mean_addr
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
3
)
->
Data
());
auto
variance_addr
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
4
)
->
Data
());
auto
output_addr
=
reinterpret_cast
<
float
*>
(
outputs_
.
at
(
0
)
->
Data
());
FusedBatchNorm
(
input_addr
,
scale_addr
,
offest_addr
,
mean_addr
,
variance_addr
,
input_shape_
,
int
ret
=
LiteBackendParallelLaunch
(
FusedBatchNormRun
,
this
,
batchnorm_param_
->
op_parameter_
.
thread_num_
);
fused_batchnorm_param_
->
epsilon_
,
output_addr
);
if
(
ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"FusedBatchnormRun error error_code["
<<
ret
<<
"]"
;
return
ret
;
}
return
RET_OK
;
return
RET_OK
;
}
}
...
@@ -63,8 +151,8 @@ kernel::LiteKernel *CpuFusedBatchnormKernelCreator(const std::vector<lite::tenso
...
@@ -63,8 +151,8 @@ kernel::LiteKernel *CpuFusedBatchnormKernelCreator(const std::vector<lite::tenso
const
kernel
::
KernelKey
&
desc
,
const
lite
::
Primitive
*
primitive
)
{
const
kernel
::
KernelKey
&
desc
,
const
lite
::
Primitive
*
primitive
)
{
MS_ASSERT
(
opParameter
!=
nullptr
);
MS_ASSERT
(
opParameter
!=
nullptr
);
MS_ASSERT
(
desc
.
type
==
schema
::
PrimitiveType_FusedBatchNorm
);
MS_ASSERT
(
desc
.
type
==
schema
::
PrimitiveType_FusedBatchNorm
);
FusedBatchnormCPUKernel
*
kernel
=
new
(
std
::
nothrow
)
FusedBatchnormCPUKernel
(
opParameter
,
inputs
,
outputs
,
ctx
,
FusedBatchnormCPUKernel
*
kernel
=
primitive
);
new
(
std
::
nothrow
)
FusedBatchnormCPUKernel
(
opParameter
,
inputs
,
outputs
,
ctx
,
primitive
);
if
(
kernel
==
nullptr
)
{
if
(
kernel
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"new FusedBatchnormCPUKernel fail!"
;
MS_LOG
(
ERROR
)
<<
"new FusedBatchnormCPUKernel fail!"
;
return
nullptr
;
return
nullptr
;
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/fused_batchnorm.h
浏览文件 @
e73e9a9a
...
@@ -19,7 +19,7 @@
...
@@ -19,7 +19,7 @@
#include <vector>
#include <vector>
#include "src/lite_kernel.h"
#include "src/lite_kernel.h"
#include "src/runtime/kernel/arm/nnacl/f
used_
batchnorm.h"
#include "src/runtime/kernel/arm/nnacl/f
p32/
batchnorm.h"
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
class
FusedBatchnormCPUKernel
:
public
LiteKernel
{
class
FusedBatchnormCPUKernel
:
public
LiteKernel
{
...
@@ -28,17 +28,26 @@ class FusedBatchnormCPUKernel : public LiteKernel {
...
@@ -28,17 +28,26 @@ class FusedBatchnormCPUKernel : public LiteKernel {
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
lite
::
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
lite
::
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
LiteKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{
:
LiteKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{
fused_batchnorm_param_
=
reinterpret_cast
<
Fused
BatchNormParameter
*>
(
parameter
);
batchnorm_param_
=
reinterpret_cast
<
BatchNormParameter
*>
(
parameter
);
}
}
~
FusedBatchnormCPUKernel
()
override
{
delete
fused_batchnorm_param_
;
}
~
FusedBatchnormCPUKernel
()
override
;
int
Init
()
override
;
int
Init
()
override
;
int
ReSize
()
override
;
int
ReSize
()
override
;
int
Run
()
override
;
int
Run
()
override
;
int
InitConstTensor
();
int
Execute
(
int
task_id
);
private:
private:
int
*
input_shape_
{};
float
*
in_addr_
;
FusedBatchNormParameter
*
fused_batchnorm_param_
;
float
*
mean_addr_
;
float
*
var_addr_
;
float
*
scale_addr_
;
float
*
offset_addr_
;
float
*
out_addr_
;
BatchNormParameter
*
batchnorm_param_
;
};
};
}
// namespace mindspore::kernel
}
// namespace mindspore::kernel
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/scale.cc
浏览文件 @
e73e9a9a
...
@@ -17,7 +17,6 @@
...
@@ -17,7 +17,6 @@
#include "src/runtime/kernel/arm/fp32/scale.h"
#include "src/runtime/kernel/arm/fp32/scale.h"
#include <string.h>
#include <string.h>
#include <vector>
#include <vector>
#include "src/runtime/kernel/arm/nnacl/scale.h"
#include "schema/model_generated.h"
#include "schema/model_generated.h"
#include "src/kernel_registry.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"
#include "include/errorcode.h"
...
@@ -29,23 +28,29 @@ using mindspore::lite::RET_OK;
...
@@ -29,23 +28,29 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_Scale
;
using
mindspore
::
schema
::
PrimitiveType_Scale
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
ScaleCPUKernel
::~
ScaleCPUKernel
()
{
FreeTmpBuffer
();
}
void
ScaleCPUKernel
::
FreeTmpBuffer
()
{
void
ScaleCPUKernel
::
FreeTmpBuffer
()
{
if
(
scale_
!=
nullptr
)
{
if
(
scale_param_
->
const_scale_
)
{
free
(
scale_
);
if
(
scale_
!=
nullptr
)
{
scale_
=
nullptr
;
free
(
scale_
);
scale_
=
nullptr
;
}
}
}
if
(
offset_
!=
nullptr
)
{
if
(
scale_param_
->
has_offset_
)
{
free
(
offset_
);
if
(
offset_
!=
nullptr
)
{
offset_
=
nullptr
;
free
(
offset_
);
offset_
=
nullptr
;
}
}
}
}
}
int
ScaleCPUKernel
::
InitScaleOffset
()
{
int
ScaleCPUKernel
::
InitScaleOffset
()
{
FreeTmpBuffer
();
FreeTmpBuffer
();
auto
param
=
reinterpret_cast
<
ScaleParameter
*>
(
opParameter
);
auto
scale_tensor
=
inputs_
.
at
(
1
);
auto
scale_tensor
=
inputs_
.
at
(
1
);
float
*
scale_ptr
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
1
)
->
Data
());
float
*
scale_ptr
=
reinterpret_cast
<
float
*>
(
inputs_
.
at
(
1
)
->
Data
());
if
(
scale_ptr
!=
nullptr
)
{
if
(
scale_ptr
!=
nullptr
)
{
scale_param_
->
const_scale_
=
true
;
scale_
=
reinterpret_cast
<
float
*>
(
malloc
(
scale_tensor
->
ElementsNum
()
*
sizeof
(
float
)));
scale_
=
reinterpret_cast
<
float
*>
(
malloc
(
scale_tensor
->
ElementsNum
()
*
sizeof
(
float
)));
if
(
scale_
==
nullptr
)
{
if
(
scale_
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
...
@@ -53,6 +58,7 @@ int ScaleCPUKernel::InitScaleOffset() {
...
@@ -53,6 +58,7 @@ int ScaleCPUKernel::InitScaleOffset() {
}
}
memcpy
(
scale_
,
scale_ptr
,
scale_tensor
->
ElementsNum
()
*
sizeof
(
float
));
memcpy
(
scale_
,
scale_ptr
,
scale_tensor
->
ElementsNum
()
*
sizeof
(
float
));
}
else
{
}
else
{
scale_param_
->
const_scale_
=
false
;
scale_
=
nullptr
;
scale_
=
nullptr
;
}
}
...
@@ -64,40 +70,39 @@ int ScaleCPUKernel::InitScaleOffset() {
...
@@ -64,40 +70,39 @@ int ScaleCPUKernel::InitScaleOffset() {
return
RET_ERROR
;
return
RET_ERROR
;
}
}
memcpy
(
offset_
,
offset_tensor
->
Data
(),
offset_tensor
->
ElementsNum
()
*
sizeof
(
float
));
memcpy
(
offset_
,
offset_tensor
->
Data
(),
offset_tensor
->
ElementsNum
()
*
sizeof
(
float
));
param
->
has_offset_
=
true
;
scale_param_
->
has_offset_
=
true
;
}
else
{
}
else
{
offset_
=
nullptr
;
offset_
=
nullptr
;
param
->
has_offset_
=
false
;
scale_param_
->
has_offset_
=
false
;
}
}
return
RET_OK
;
return
RET_OK
;
}
}
int
ScaleCPUKernel
::
InitParameter
()
{
int
ScaleCPUKernel
::
InitParameter
()
{
auto
param
=
reinterpret_cast
<
ScaleParameter
*>
(
opParameter
);
auto
in_tensor
=
inputs_
.
at
(
0
);
auto
in_tensor
=
inputs_
.
at
(
0
);
auto
in_shape
=
in_tensor
->
shape
();
auto
in_shape
=
in_tensor
->
shape
();
auto
scale_tensor
=
inputs_
.
at
(
1
);
auto
scale_tensor
=
inputs_
.
at
(
1
);
auto
scale_shape
=
scale_tensor
->
shape
();
auto
scale_shape
=
scale_tensor
->
shape
();
if
(
scale_shape
.
size
()
+
param
->
axis_
>
in_shape
.
size
())
{
if
(
scale_shape
.
size
()
+
scale_param_
->
axis_
>
in_shape
.
size
())
{
MS_LOG
(
ERROR
)
<<
"Scale tensor shape is incorrect."
;
MS_LOG
(
ERROR
)
<<
"Scale tensor shape is incorrect."
;
return
RET_ERROR
;
return
RET_ERROR
;
}
}
param
->
outer_size_
=
1
;
scale_param_
->
outer_size_
=
1
;
param
->
axis_size_
=
1
;
scale_param_
->
axis_size_
=
1
;
param
->
inner_size_
=
1
;
scale_param_
->
inner_size_
=
1
;
for
(
int
i
=
0
;
i
<
param
->
axis_
;
i
++
)
{
for
(
int
i
=
0
;
i
<
scale_param_
->
axis_
;
i
++
)
{
param
->
outer_size_
*=
in_shape
[
i
];
scale_param_
->
outer_size_
*=
in_shape
[
i
];
}
}
for
(
int
i
=
0
;
i
<
scale_shape
.
size
();
i
++
)
{
for
(
int
i
=
0
;
i
<
scale_shape
.
size
();
i
++
)
{
if
(
in_shape
[
i
+
param
->
axis_
]
!=
scale_shape
[
i
])
{
if
(
in_shape
[
i
+
scale_param_
->
axis_
]
!=
scale_shape
[
i
])
{
MS_LOG
(
ERROR
)
<<
"Scale tensor shape is incorrect."
;
MS_LOG
(
ERROR
)
<<
"Scale tensor shape is incorrect."
;
return
RET_ERROR
;
return
RET_ERROR
;
}
}
param
->
axis_size_
*=
in_shape
[
i
+
param
->
axis_
];
scale_param_
->
axis_size_
*=
in_shape
[
i
+
scale_param_
->
axis_
];
}
}
for
(
int
i
=
param
->
axis_
+
scale_shape
.
size
();
i
<
in_shape
.
size
();
i
++
)
{
for
(
int
i
=
scale_param_
->
axis_
+
scale_shape
.
size
();
i
<
in_shape
.
size
();
i
++
)
{
param
->
inner_size_
*=
in_shape
[
i
];
scale_param_
->
inner_size_
*=
in_shape
[
i
];
}
}
return
RET_OK
;
return
RET_OK
;
}
}
...
@@ -130,9 +135,7 @@ int ScaleCPUKernel::ReSize() {
...
@@ -130,9 +135,7 @@ int ScaleCPUKernel::ReSize() {
}
}
int
ScaleCPUKernel
::
Scale
(
int
task_id
)
{
int
ScaleCPUKernel
::
Scale
(
int
task_id
)
{
auto
ret
=
auto
ret
=
DoScale
(
input_ptr_
,
output_ptr_
,
scale_
,
offset_
,
task_id
,
scale_param_
);
DoScale
(
input_ptr_
,
output_ptr_
,
scale_
,
offset_
,
task_id
,
reinterpret_cast
<
ScaleParameter
*>
(
opParameter
));
if
(
ret
!=
RET_OK
)
{
if
(
ret
!=
RET_OK
)
{
MS_LOG
(
ERROR
)
<<
"Scale error task_id["
<<
task_id
<<
"] error_code["
<<
ret
<<
"]"
;
MS_LOG
(
ERROR
)
<<
"Scale error task_id["
<<
task_id
<<
"] error_code["
<<
ret
<<
"]"
;
return
RET_ERROR
;
return
RET_ERROR
;
...
...
mindspore/lite/src/runtime/kernel/arm/fp32/scale.h
浏览文件 @
e73e9a9a
...
@@ -19,6 +19,7 @@
...
@@ -19,6 +19,7 @@
#include <vector>
#include <vector>
#include "src/lite_kernel.h"
#include "src/lite_kernel.h"
#include "src/runtime/kernel/arm/nnacl/scale.h"
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
...
@@ -27,10 +28,10 @@ class ScaleCPUKernel : public LiteKernel {
...
@@ -27,10 +28,10 @@ class ScaleCPUKernel : public LiteKernel {
ScaleCPUKernel
(
OpParameter
*
parameter
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
inputs
,
ScaleCPUKernel
(
OpParameter
*
parameter
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
inputs
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
lite
::
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
lite
::
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
LiteKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
:
LiteKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{
~
ScaleCPUKernel
()
{
scale_param_
=
reinterpret_cast
<
ScaleParameter
*>
(
opParameter
);
FreeTmpBuffer
();
}
}
~
ScaleCPUKernel
()
override
;
int
Init
()
override
;
int
Init
()
override
;
int
ReSize
()
override
;
int
ReSize
()
override
;
...
@@ -45,6 +46,7 @@ class ScaleCPUKernel : public LiteKernel {
...
@@ -45,6 +46,7 @@ class ScaleCPUKernel : public LiteKernel {
float
*
scale_
;
float
*
scale_
;
float
*
offset_
;
float
*
offset_
;
float
*
output_ptr_
;
float
*
output_ptr_
;
ScaleParameter
*
scale_param_
;
};
};
}
// namespace mindspore::kernel
}
// namespace mindspore::kernel
...
...
mindspore/lite/src/runtime/kernel/arm/int8/convolution_depthwise_int8.cc
浏览文件 @
e73e9a9a
...
@@ -28,6 +28,24 @@ using mindspore::lite::RET_OK;
...
@@ -28,6 +28,24 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_DepthwiseConv2D
;
using
mindspore
::
schema
::
PrimitiveType_DepthwiseConv2D
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
ConvolutionDepthwiseInt8CPUKernel
::~
ConvolutionDepthwiseInt8CPUKernel
()
{
delete
sliding
;
if
(
packed_weight_
!=
nullptr
)
{
delete
packed_weight_
;
packed_weight_
=
nullptr
;
}
if
(
packed_input_
!=
nullptr
)
{
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
need_align_
)
{
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
}
int
ConvolutionDepthwiseInt8CPUKernel
::
InitWeightBias
()
{
int
ConvolutionDepthwiseInt8CPUKernel
::
InitWeightBias
()
{
// init weight, int8 -> int16
// init weight, int8 -> int16
// o, h, w, i -> o/8, h, w, i, 8; o == group, i == 1
// o, h, w, i -> o/8, h, w, i, 8; o == group, i == 1
...
@@ -111,10 +129,17 @@ int ConvolutionDepthwiseInt8CPUKernel::Init() {
...
@@ -111,10 +129,17 @@ int ConvolutionDepthwiseInt8CPUKernel::Init() {
}
}
int
ConvolutionDepthwiseInt8CPUKernel
::
ReSize
()
{
int
ConvolutionDepthwiseInt8CPUKernel
::
ReSize
()
{
free
(
packed_input_
);
if
(
packed_input_
!=
nullptr
)
{
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
need_align_
)
{
if
(
need_align_
)
{
free
(
packed_output_
);
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
}
// conv base init
// conv base init
ConvolutionBaseCPUKernel
::
Init
();
ConvolutionBaseCPUKernel
::
Init
();
...
...
mindspore/lite/src/runtime/kernel/arm/int8/convolution_depthwise_int8.h
浏览文件 @
e73e9a9a
...
@@ -29,14 +29,7 @@ class ConvolutionDepthwiseInt8CPUKernel : public ConvolutionBaseCPUKernel {
...
@@ -29,14 +29,7 @@ class ConvolutionDepthwiseInt8CPUKernel : public ConvolutionBaseCPUKernel {
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
~
ConvolutionDepthwiseInt8CPUKernel
()
override
{
~
ConvolutionDepthwiseInt8CPUKernel
()
override
;
delete
sliding
;
free
(
packed_weight_
);
free
(
packed_input_
);
if
(
need_align_
)
{
free
(
packed_output_
);
}
};
int
Init
()
override
;
int
Init
()
override
;
int
ReSize
()
override
;
int
ReSize
()
override
;
...
...
mindspore/lite/src/runtime/kernel/arm/int8/deconvolution_depthwise_int8.cc
浏览文件 @
e73e9a9a
...
@@ -28,6 +28,28 @@ using mindspore::lite::RET_OK;
...
@@ -28,6 +28,28 @@ using mindspore::lite::RET_OK;
using
mindspore
::
schema
::
PrimitiveType_DeDepthwiseConv2D
;
using
mindspore
::
schema
::
PrimitiveType_DeDepthwiseConv2D
;
namespace
mindspore
::
kernel
{
namespace
mindspore
::
kernel
{
DeconvolutionDepthwiseInt8CPUKernel
::~
DeconvolutionDepthwiseInt8CPUKernel
()
{
delete
sliding
;
if
(
packed_weight_
!=
nullptr
)
{
delete
packed_weight_
;
packed_weight_
=
nullptr
;
}
if
(
packed_input_
!=
nullptr
)
{
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
need_align_
)
{
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
if
(
output_buffer_
!=
nullptr
)
{
delete
output_buffer_
;
output_buffer_
=
nullptr
;
}
}
int
DeconvolutionDepthwiseInt8CPUKernel
::
InitWeightBias
()
{
int
DeconvolutionDepthwiseInt8CPUKernel
::
InitWeightBias
()
{
// init weight: int8 -> int16
// init weight: int8 -> int16
// o, h, w, i -> o/8, h, w, i, 8; o == group, i == 1
// o, h, w, i -> o/8, h, w, i, 8; o == group, i == 1
...
@@ -101,9 +123,9 @@ int DeconvolutionDepthwiseInt8CPUKernel::InitBuffer() {
...
@@ -101,9 +123,9 @@ int DeconvolutionDepthwiseInt8CPUKernel::InitBuffer() {
}
}
// malloc tmp buffer for int32 output
// malloc tmp buffer for int32 output
output_buffer
=
output_buffer
_
=
reinterpret_cast
<
int32_t
*>
(
malloc
(
conv_param_
->
output_h_
*
conv_param_
->
output_w_
*
C4NUM
*
sizeof
(
int32_t
)));
reinterpret_cast
<
int32_t
*>
(
malloc
(
conv_param_
->
output_h_
*
conv_param_
->
output_w_
*
C4NUM
*
sizeof
(
int32_t
)));
if
(
output_buffer
==
nullptr
)
{
if
(
output_buffer
_
==
nullptr
)
{
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
MS_LOG
(
ERROR
)
<<
"Malloc buffer failed."
;
return
RET_ERROR
;
return
RET_ERROR
;
}
}
...
@@ -144,10 +166,21 @@ int DeconvolutionDepthwiseInt8CPUKernel::Init() {
...
@@ -144,10 +166,21 @@ int DeconvolutionDepthwiseInt8CPUKernel::Init() {
}
}
int
DeconvolutionDepthwiseInt8CPUKernel
::
ReSize
()
{
int
DeconvolutionDepthwiseInt8CPUKernel
::
ReSize
()
{
free
(
packed_input_
);
if
(
packed_input_
!=
nullptr
)
{
delete
packed_input_
;
packed_input_
=
nullptr
;
}
if
(
need_align_
)
{
if
(
need_align_
)
{
free
(
packed_output_
);
if
(
packed_output_
!=
nullptr
)
{
delete
packed_output_
;
packed_output_
=
nullptr
;
}
}
if
(
output_buffer_
!=
nullptr
)
{
delete
output_buffer_
;
output_buffer_
=
nullptr
;
}
}
InitSlideParam
();
InitSlideParam
();
// conv base init
// conv base init
...
@@ -162,7 +195,7 @@ int DeconvolutionDepthwiseInt8CPUKernel::ReSize() {
...
@@ -162,7 +195,7 @@ int DeconvolutionDepthwiseInt8CPUKernel::ReSize() {
}
}
int
DeconvolutionDepthwiseInt8CPUKernel
::
Execute
(
int
task_id
)
{
int
DeconvolutionDepthwiseInt8CPUKernel
::
Execute
(
int
task_id
)
{
DeconvDwInt8
(
packed_output_
,
output_buffer
,
packed_input_
,
packed_weight_
,
reinterpret_cast
<
int32_t
*>
(
bias_data_
),
DeconvDwInt8
(
packed_output_
,
output_buffer
_
,
packed_input_
,
packed_weight_
,
reinterpret_cast
<
int32_t
*>
(
bias_data_
),
conv_param_
,
sliding
,
task_id
);
conv_param_
,
sliding
,
task_id
);
return
RET_OK
;
return
RET_OK
;
}
}
...
...
mindspore/lite/src/runtime/kernel/arm/int8/deconvolution_depthwise_int8.h
浏览文件 @
e73e9a9a
...
@@ -29,14 +29,7 @@ class DeconvolutionDepthwiseInt8CPUKernel : public ConvolutionBaseCPUKernel {
...
@@ -29,14 +29,7 @@ class DeconvolutionDepthwiseInt8CPUKernel : public ConvolutionBaseCPUKernel {
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
std
::
vector
<
lite
::
tensor
::
Tensor
*>
&
outputs
,
const
Context
*
ctx
,
const
lite
::
Primitive
*
primitive
)
const
lite
::
Primitive
*
primitive
)
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
:
ConvolutionBaseCPUKernel
(
parameter
,
inputs
,
outputs
,
ctx
,
primitive
)
{}
~
DeconvolutionDepthwiseInt8CPUKernel
()
override
{
~
DeconvolutionDepthwiseInt8CPUKernel
()
override
;
delete
sliding
;
free
(
packed_weight_
);
free
(
packed_input_
);
if
(
need_align_
)
{
free
(
packed_output_
);
}
};
int
Init
()
override
;
int
Init
()
override
;
int
ReSize
()
override
;
int
ReSize
()
override
;
...
@@ -52,7 +45,7 @@ class DeconvolutionDepthwiseInt8CPUKernel : public ConvolutionBaseCPUKernel {
...
@@ -52,7 +45,7 @@ class DeconvolutionDepthwiseInt8CPUKernel : public ConvolutionBaseCPUKernel {
int16_t
*
packed_weight_
;
int16_t
*
packed_weight_
;
int16_t
*
packed_input_
;
int16_t
*
packed_input_
;
int8_t
*
packed_output_
;
int8_t
*
packed_output_
;
int32_t
*
output_buffer
;
int32_t
*
output_buffer
_
;
bool
need_align_
=
false
;
bool
need_align_
=
false
;
};
};
}
// namespace mindspore::kernel
}
// namespace mindspore::kernel
...
...
mindspore/lite/src/runtime/kernel/arm/nnacl/flatten.h
浏览文件 @
e73e9a9a
...
@@ -24,4 +24,3 @@ typedef struct FlattenParameter {
...
@@ -24,4 +24,3 @@ typedef struct FlattenParameter {
void
Flatten
(
const
void
*
input
,
void
*
output
,
FlattenParameter
*
flatten_param
);
void
Flatten
(
const
void
*
input
,
void
*
output
,
FlattenParameter
*
flatten_param
);
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FLATTEN_H_
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FLATTEN_H_
mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/batchnorm.cc
浏览文件 @
e73e9a9a
...
@@ -19,10 +19,21 @@
...
@@ -19,10 +19,21 @@
void
BatchNorm
(
float
*
output_ptr
,
const
float
*
input_ptr
,
const
float
*
mean_ptr
,
const
float
*
variance_ptr
,
int
task_id
,
void
BatchNorm
(
float
*
output_ptr
,
const
float
*
input_ptr
,
const
float
*
mean_ptr
,
const
float
*
variance_ptr
,
int
task_id
,
BatchNormParameter
*
param
)
{
BatchNormParameter
*
param
)
{
for
(
int
u
=
task_id
;
u
<
param
->
unit_
;
u
+=
param
->
op_parameter_
.
thread_num_
)
{
for
(
int
c
=
task_id
;
c
<
param
->
channel_
;
c
+=
param
->
op_parameter_
.
thread_num_
)
{
for
(
int
c
=
0
;
c
<
param
->
channel_
;
c
++
)
{
auto
variance_sqrt
=
sqrt
(
variance_ptr
[
c
]
+
param
->
epsilon_
);
auto
variance_sqrt
=
sqrt
(
variance_ptr
[
c
]
+
param
->
epsilon_
);
for
(
int
u
=
0
;
u
<
param
->
unit_
;
u
++
)
{
output_ptr
[
u
*
param
->
channel_
+
c
]
=
(
input_ptr
[
u
*
param
->
channel_
+
c
]
-
mean_ptr
[
c
])
/
variance_sqrt
;
output_ptr
[
u
*
param
->
channel_
+
c
]
=
(
input_ptr
[
u
*
param
->
channel_
+
c
]
-
mean_ptr
[
c
])
/
variance_sqrt
;
}
}
}
}
}
}
void
FusedBatchNorm
(
float
*
output_ptr
,
const
float
*
input_ptr
,
const
float
*
scale_ptr
,
const
float
*
offest_ptr
,
const
float
*
mean_ptr
,
const
float
*
variance_ptr
,
int
task_id
,
BatchNormParameter
*
param
)
{
for
(
int
c
=
task_id
;
c
<
param
->
channel_
;
c
+=
param
->
op_parameter_
.
thread_num_
)
{
auto
variance_sqrt
=
sqrt
(
variance_ptr
[
c
]
+
param
->
epsilon_
);
for
(
int
u
=
0
;
u
<
param
->
unit_
;
u
++
)
{
output_ptr
[
u
*
param
->
channel_
+
c
]
=
(
input_ptr
[
u
*
param
->
channel_
+
c
]
-
mean_ptr
[
c
])
/
variance_sqrt
*
scale_ptr
[
c
]
+
offest_ptr
[
c
];
}
}
}
mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/batchnorm.h
浏览文件 @
e73e9a9a
...
@@ -29,4 +29,7 @@ typedef struct BatchNormParameter {
...
@@ -29,4 +29,7 @@ typedef struct BatchNormParameter {
void
BatchNorm
(
float
*
output_ptr
,
const
float
*
input_ptr
,
const
float
*
mean_ptr
,
const
float
*
variance_ptr
,
int
task_id
,
void
BatchNorm
(
float
*
output_ptr
,
const
float
*
input_ptr
,
const
float
*
mean_ptr
,
const
float
*
variance_ptr
,
int
task_id
,
BatchNormParameter
*
param
);
BatchNormParameter
*
param
);
void
FusedBatchNorm
(
float
*
output_ptr
,
const
float
*
input_ptr
,
const
float
*
scale_ptr
,
const
float
*
offest_ptr
,
const
float
*
mean_ptr
,
const
float
*
variance_ptr
,
int
task_id
,
BatchNormParameter
*
param
);
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FUSED_BATCHNORM_H_
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FUSED_BATCHNORM_H_
mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/conv_depthwise.cc
浏览文件 @
e73e9a9a
...
@@ -486,6 +486,21 @@ void ConvDw3x3Fp32OutputUnit(float *src_buf, float *dst_output, const float *bia
...
@@ -486,6 +486,21 @@ void ConvDw3x3Fp32OutputUnit(float *src_buf, float *dst_output, const float *bia
float32x4_t
d10
=
vaddq_f32
(
vaddq_f32
(
vaddq_f32
(
t10
,
t11
),
t12
),
bias_ptr
);
float32x4_t
d10
=
vaddq_f32
(
vaddq_f32
(
vaddq_f32
(
t10
,
t11
),
t12
),
bias_ptr
);
float32x4_t
d11
=
vaddq_f32
(
vsubq_f32
(
vsubq_f32
(
t11
,
t12
),
t13
),
bias_ptr
);
float32x4_t
d11
=
vaddq_f32
(
vsubq_f32
(
vsubq_f32
(
t11
,
t12
),
t13
),
bias_ptr
);
float32x4_t
zeros
=
{
0
,
0
,
0
,
0
};
float32x4_t
bounds
=
{
6
,
6
,
6
,
6
};
if
(
is_relu
)
{
d00
=
vmaxq_f32
(
d00
,
zeros
);
d01
=
vmaxq_f32
(
d01
,
zeros
);
d10
=
vmaxq_f32
(
d10
,
zeros
);
d11
=
vmaxq_f32
(
d11
,
zeros
);
}
if
(
is_relu6
)
{
d00
=
vminq_f32
(
vmaxq_f32
(
d00
,
zeros
),
bounds
);
d01
=
vminq_f32
(
vmaxq_f32
(
d01
,
zeros
),
bounds
);
d10
=
vminq_f32
(
vmaxq_f32
(
d10
,
zeros
),
bounds
);
d11
=
vminq_f32
(
vmaxq_f32
(
d11
,
zeros
),
bounds
);
}
vst1q_f32
(
dst_output
,
d00
);
vst1q_f32
(
dst_output
,
d00
);
if
(
w_in_range
)
{
if
(
w_in_range
)
{
vst1q_f32
(
dst_output
+
channel
,
d01
);
vst1q_f32
(
dst_output
+
channel
,
d01
);
...
@@ -536,6 +551,19 @@ void ConvDw3x3Fp32OutputUnit(float *src_buf, float *dst_output, const float *bia
...
@@ -536,6 +551,19 @@ void ConvDw3x3Fp32OutputUnit(float *src_buf, float *dst_output, const float *bia
float
d10
=
t10
+
t11
+
t12
+
bias_ptr
[
0
];
float
d10
=
t10
+
t11
+
t12
+
bias_ptr
[
0
];
float
d11
=
t11
-
t12
-
t13
+
bias_ptr
[
0
];
float
d11
=
t11
-
t12
-
t13
+
bias_ptr
[
0
];
if
(
is_relu
)
{
d00
=
MSMAX
(
d00
,
0
);
d01
=
MSMAX
(
d01
,
0
);
d10
=
MSMAX
(
d10
,
0
);
d11
=
MSMAX
(
d11
,
0
);
}
if
(
is_relu6
)
{
d00
=
MSMIN
(
MSMAX
(
d00
,
0
),
6
);
d01
=
MSMIN
(
MSMAX
(
d01
,
0
),
6
);
d10
=
MSMIN
(
MSMAX
(
d10
,
0
),
6
);
d11
=
MSMIN
(
MSMAX
(
d11
,
0
),
6
);
}
(
dst_output
+
i
)[
0
]
=
d00
;
(
dst_output
+
i
)[
0
]
=
d00
;
if
(
w_in_range
)
{
if
(
w_in_range
)
{
(
dst_output
+
i
+
channel
)[
0
]
=
d01
;
(
dst_output
+
i
+
channel
)[
0
]
=
d01
;
...
...
mindspore/lite/src/runtime/kernel/arm/nnacl/fused_batchnorm.cc
已删除
100644 → 0
浏览文件 @
c2997845
/**
* 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 "nnacl/fused_batchnorm.h"
#include <math.h>
void
FusedBatchNorm
(
const
float
*
input_ptr
,
const
float
*
scale_ptr
,
const
float
*
offest_ptr
,
const
float
*
mean_ptr
,
const
float
*
variance_ptr
,
int
*
input_shapes
,
float
epsilon
,
float
*
output_ptr
)
{
int
channel
=
input_shapes
[
3
];
int
units
=
1
;
for
(
int
i
=
0
;
i
<
3
;
i
++
)
{
units
*=
input_shapes
[
i
];
}
for
(
int
c
=
0
;
c
<
input_shapes
[
3
];
c
++
)
{
auto
variance_sqrt
=
sqrt
(
variance_ptr
[
c
]
+
epsilon
);
for
(
int
u
=
0
;
u
<
units
;
u
++
)
{
output_ptr
[
u
*
channel
+
c
]
=
(
input_ptr
[
u
*
channel
+
c
]
-
mean_ptr
[
c
])
/
variance_sqrt
*
scale_ptr
[
c
]
+
offest_ptr
[
c
];
}
}
}
mindspore/lite/src/runtime/kernel/arm/nnacl/fused_batchnorm.h
已删除
100644 → 0
浏览文件 @
c2997845
/**
* 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_ARM_NNACL_FUSED_BATCHNORM_H_
#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FUSED_BATCHNORM_H_
#include "nnacl/op_base.h"
typedef
struct
FusedBatchNormParameter
{
OpParameter
op_parameter_
;
float
epsilon_
;
}
FusedBatchNormParameter
;
void
FusedBatchNorm
(
const
float
*
input_ptr
,
const
float
*
scale_ptr
,
const
float
*
offest_ptr
,
const
float
*
mean_ptr
,
const
float
*
variance_ptr
,
int
*
input_shapes
,
float
epsilon
,
float
*
output_ptr
);
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FUSED_BATCHNORM_H_
mindspore/lite/src/runtime/kernel/arm/nnacl/scale.h
浏览文件 @
e73e9a9a
...
@@ -25,10 +25,9 @@ typedef struct ScaleParameter {
...
@@ -25,10 +25,9 @@ typedef struct ScaleParameter {
int
axis_size_
;
int
axis_size_
;
int
inner_size_
;
int
inner_size_
;
int
axis_
;
int
axis_
;
bool
has_offset_
;
bool
const_scale_
=
false
;
// todo yangruoqi: axis
bool
has_offset_
=
false
;
}
ScaleParameter
;
}
ScaleParameter
;
int
DoScale
(
float
*
in_data
,
float
*
out_data
,
float
*
scale
,
float
*
offset
,
int
task_id
,
ScaleParameter
*
scale_param
);
int
DoScale
(
float
*
in_data
,
float
*
out_data
,
float
*
scale
,
float
*
offset
,
int
task_id
,
ScaleParameter
*
scale_param
);
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_SCALE_H_
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_SCALE_H_
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batchnorm_fp32_tests.cc
浏览文件 @
e73e9a9a
...
@@ -17,33 +17,20 @@
...
@@ -17,33 +17,20 @@
#include "mindspore/core/utils/log_adapter.h"
#include "mindspore/core/utils/log_adapter.h"
#include "common/common_test.h"
#include "common/common_test.h"
#include "mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/batchnorm.h"
#include "mindspore/lite/src/runtime/kernel/arm/nnacl/fp32/batchnorm.h"
#include "mindspore/lite/src/runtime/kernel/arm/nnacl/fused_batchnorm.h"
#include "mindspore/lite/src/kernel_registry.h"
#include "mindspore/lite/src/kernel_registry.h"
#include "mindspore/lite/src/lite_kernel.h"
#include "mindspore/lite/src/lite_kernel.h"
#include "mindspore/lite/src/common/file_utils.h"
namespace
mindspore
{
namespace
mindspore
{
class
TestBatchnormFp32
:
public
mindspore
::
Common
{
class
TestBatchnormFp32
:
public
mindspore
::
Common
{
public:
public:
TestBatchnormFp32
()
{}
TestBatchnormFp32
()
{}
};
};
TEST_F
(
TestBatchnormFp32
,
BNTest
)
{
TEST_F
(
TestBatchnormFp32
,
BNTest
)
{
std
::
vector
<
float
>
in_data
=
{
0.0669681
,
0.959215
,
0.252686
,
0.613594
,
0.811776
,
0.139469
,
0.322848
,
0.118354
,
std
::
vector
<
float
>
in_data
=
{
-
11.18675
,
11.433986
,
11.386012
,
11.245945
,
-
2.7614849
,
14.692399
,
0.082978
,
0.399467
,
0.961267
,
0.0247456
,
0.0714259
,
0.0791484
,
0.0648625
,
0.561612
,
-
1.1983503
,
-
6.6790967
,
6.383416
,
-
13.3213005
,
-
8.693595
,
9.476344
};
0.412069
,
0.311492
,
0.46109
,
0.377125
,
0.369283
,
0.0332446
,
0.696142
,
0.715973
,
std
::
vector
<
float
>
in_data1
=
{
12.352293
,
5.122387
,
14.249514
};
0.525524
,
0.477265
,
0.0336351
,
0.751577
,
0.377548
,
0.964603
,
0.0196834
,
0.174865
};
std
::
vector
<
float
>
in_data2
=
{
14.632595
,
0.70900035
,
11.179003
};
std
::
vector
<
float
>
in_data1
=
{
0.855446
,
0.821765
,
0.281008
,
0.0798653
,
0.22294
,
0.793782
,
0.963222
,
0.17851
,
0.667549
,
0.274381
,
0.592842
,
0.216552
,
0.190274
,
0.237873
,
0.610063
,
0.307559
,
0.830007
,
0.760957
,
0.583265
,
0.763793
,
0.456372
,
0.391378
,
0.547915
,
0.862198
,
0.510794
,
0.826776
,
0.515894
,
0.30071
,
0.404987
,
0.184773
};
std
::
vector
<
float
>
in_data2
=
{
0.712438
,
0.4927
,
0.078419
,
0.310429
,
0.546871
,
0.0667141
,
0.874321
,
0.0265647
,
0.685165
,
0.732586
,
0.952889
,
0.506402
,
0.540784
,
0.131119
,
0.357713
,
0.678992
,
0.960839
,
0.340706
,
0.697678
,
0.398146
,
0.313321
,
0.6485
,
0.739153
,
0.00190134
,
0.536842
,
0.996873
,
0.445276
,
0.371212
,
0.420397
,
0.0930115
};
std
::
vector
<
float
>
in_data3
(
32
,
1
);
std
::
vector
<
float
>
in_data4
(
32
,
0
);
std
::
vector
<
lite
::
tensor
::
Tensor
*>
inputs_tensor
;
std
::
vector
<
lite
::
tensor
::
Tensor
*>
inputs_tensor
;
std
::
vector
<
lite
::
tensor
::
Tensor
*>
outputs_tensor
;
std
::
vector
<
lite
::
tensor
::
Tensor
*>
outputs_tensor
;
...
@@ -51,8 +38,7 @@ TEST_F(TestBatchnormFp32, BNTest) {
...
@@ -51,8 +38,7 @@ TEST_F(TestBatchnormFp32, BNTest) {
op_param
.
op_parameter_
.
type_
=
schema
::
PrimitiveType_BatchNorm
;
op_param
.
op_parameter_
.
type_
=
schema
::
PrimitiveType_BatchNorm
;
op_param
.
epsilon_
=
0.001
f
;
op_param
.
epsilon_
=
0.001
f
;
std
::
vector
<
int
>
in_shape
=
{
1
,
2
,
4
,
4
};
std
::
vector
<
int
>
shape
=
{
1
,
2
,
2
,
3
};
lite
::
tensor
::
Tensor
input0_tensor
;
lite
::
tensor
::
Tensor
input0_tensor
;
lite
::
tensor
::
Tensor
input1_tensor
;
lite
::
tensor
::
Tensor
input1_tensor
;
lite
::
tensor
::
Tensor
input2_tensor
;
lite
::
tensor
::
Tensor
input2_tensor
;
...
@@ -62,39 +48,40 @@ TEST_F(TestBatchnormFp32, BNTest) {
...
@@ -62,39 +48,40 @@ TEST_F(TestBatchnormFp32, BNTest) {
input0_tensor
.
SetData
(
in_data
.
data
());
input0_tensor
.
SetData
(
in_data
.
data
());
input1_tensor
.
SetData
(
in_data1
.
data
());
input1_tensor
.
SetData
(
in_data1
.
data
());
input2_tensor
.
SetData
(
in_data2
.
data
());
input2_tensor
.
SetData
(
in_data2
.
data
());
input0_tensor
.
set_shape
(
in_shape
);
input0_tensor
.
set_shape
(
shape
);
input1_tensor
.
set_shape
({
3
});
input2_tensor
.
set_shape
({
3
});
std
::
vector
<
float
>
output
(
3
2
);
std
::
vector
<
float
>
output
(
1
2
);
std
::
vector
<
float
>
corr_out
(
32
);
std
::
vector
<
float
>
corr_out
=
{
-
6.1533737
,
7.4904885
,
-
0.8563998
,
-
0.289212
,
-
9.356432
,
0.13245535
,
std
::
vector
<
int
>
output_shape
=
{
1
,
2
,
4
,
4
};
-
3.5422924
,
-
14.005781
,
-
2.3525476
,
-
6.7113695
,
-
16.396551
,
-
1.427532
4
};
lite
::
tensor
::
Tensor
output0_tensor
;
lite
::
tensor
::
Tensor
output0_tensor
;
outputs_tensor
.
push_back
(
&
output0_tensor
);
outputs_tensor
.
push_back
(
&
output0_tensor
);
output0_tensor
.
SetData
(
output
.
data
());
output0_tensor
.
SetData
(
output
.
data
());
output0_tensor
.
set_shape
(
shape
);
kernel
::
KernelKey
desc
=
{
kernel
::
KERNEL_ARCH
::
kCPU
,
kNumberTypeFloat32
,
schema
::
PrimitiveType_BatchNorm
};
kernel
::
KernelKey
desc
=
{
kernel
::
KERNEL_ARCH
::
kCPU
,
kNumberTypeFloat32
,
schema
::
PrimitiveType_BatchNorm
};
auto
creator
=
lite
::
KernelRegistry
::
GetInstance
()
->
GetCreator
(
desc
);
auto
creator
=
lite
::
KernelRegistry
::
GetInstance
()
->
GetCreator
(
desc
);
ASSERT_NE
(
creator
,
nullptr
);
ASSERT_NE
(
creator
,
nullptr
);
lite
::
Context
ctx
;
lite
::
Context
ctx
;
ctx
.
thread_num_
=
7
;
ctx
.
thread_num_
=
1
;
kernel
::
LiteKernel
*
kernel
=
kernel
::
LiteKernel
*
kernel
=
creator
(
inputs_tensor
,
outputs_tensor
,
reinterpret_cast
<
OpParameter
*>
(
&
op_param
),
&
ctx
,
desc
,
nullptr
);
creator
(
inputs_tensor
,
outputs_tensor
,
reinterpret_cast
<
OpParameter
*>
(
&
op_param
),
&
ctx
,
desc
,
nullptr
);
ASSERT_NE
(
kernel
,
nullptr
);
ASSERT_NE
(
kernel
,
nullptr
);
auto
output_tensor_shape
=
output0_tensor
.
shape
();
auto
output_tensor_shape
=
output0_tensor
.
shape
();
kernel
->
Run
();
kernel
->
Run
();
FusedBatchNorm
(
in_data
.
data
(),
in_data3
.
data
(),
in_data4
.
data
(),
in_data1
.
data
(),
in_data2
.
data
(),
in_shape
.
data
(),
0.001
f
,
corr_out
.
data
());
printf
(
"==================output data=================
\n
"
);
printf
(
"==================output data=================
\n
"
);
for
(
int
i
=
0
;
i
<
1
*
28
;
i
++
)
{
for
(
int
i
=
0
;
i
<
output0_tensor
.
ElementsNum
()
;
i
++
)
{
std
::
cout
<<
output
[
i
]
<<
" ,"
;
std
::
cout
<<
output
[
i
]
<<
" ,"
;
}
}
std
::
cout
<<
std
::
endl
;
std
::
cout
<<
std
::
endl
;
CompareOutputData
(
output
.
data
(),
corr_out
.
data
(),
32
,
0.00
001
);
CompareOutputData
(
output
.
data
(),
corr_out
.
data
(),
output0_tensor
.
ElementsNum
(),
0.
001
);
input0_tensor
.
SetData
(
nullptr
);
input0_tensor
.
SetData
(
nullptr
);
input1_tensor
.
SetData
(
nullptr
);
input1_tensor
.
SetData
(
nullptr
);
input2_tensor
.
SetData
(
nullptr
);
input2_tensor
.
SetData
(
nullptr
);
output0_tensor
.
SetData
(
nullptr
);
output0_tensor
.
SetData
(
nullptr
);
MS_LOG
(
INFO
)
<<
"TestBathNormFp32 accuracy passed"
;
}
}
}
// namespace mindspore
}
// namespace mindspore
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_0.bin
已删除
100644 → 0
浏览文件 @
c2997845
文件已删除
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_1.bin
已删除
100644 → 0
浏览文件 @
c2997845
L[?-"R>q>{B>?yx?_>JSD>G0?
\ No newline at end of file
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_2.bin
已删除
100644 → 0
浏览文件 @
c2997845
J[q?P?>g?A?>oo?7G?x<"?
\ No newline at end of file
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_3.bin
已删除
100644 → 0
浏览文件 @
c2997845
WU>X8?*?!v>F>0?.<C?d?
\ No newline at end of file
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_input_4.bin
已删除
100644 → 0
浏览文件 @
c2997845
R?]?>c~?um?z1->??'?U?
\ No newline at end of file
mindspore/lite/test/ut/src/runtime/kernel/arm/test_data/batchnorm/fusedBatchnorm_out.bin
已删除
100644 → 0
浏览文件 @
c2997845
文件已删除
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