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magicwindyyd
mindspore
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81c84737
M
mindspore
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81c84737
编写于
9月 09, 2020
作者:
M
mindspore-ci-bot
提交者:
Gitee
9月 09, 2020
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差异文件
!5936 fix CPU BatchNorm infer error
Merge pull request !5936 from zhaoting/mobilenet
上级
4cb190d4
a149784d
变更
1
显示空白变更内容
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并排
Showing
1 changed file
with
17 addition
and
8 deletion
+17
-8
mindspore/ccsrc/backend/kernel_compiler/cpu/mkldnn/fused_batch_norm_cpu_kernel.cc
...kernel_compiler/cpu/mkldnn/fused_batch_norm_cpu_kernel.cc
+17
-8
未找到文件。
mindspore/ccsrc/backend/kernel_compiler/cpu/mkldnn/fused_batch_norm_cpu_kernel.cc
浏览文件 @
81c84737
...
...
@@ -50,11 +50,13 @@ void FusedBatchNormCPUKernel::InitKernel(const CNodePtr &kernel_node) {
dnnl
::
memory
::
desc
scale_bias_desc
=
GetDefaultMemDesc
({
2
,
channel
});
auto
epsilon
=
AnfAlgo
::
GetNodeAttr
<
float
>
(
kernel_node
,
"epsilon"
);
auto
prop_kind
=
dnnl
::
prop_kind
::
forward_inference
;
auto
normalization_flags
=
dnnl
::
normalization_flags
::
use_scale_shift
|
dnnl
::
normalization_flags
::
use_global_stats
;
if
(
is_train
)
{
prop_kind
=
dnnl
::
prop_kind
::
forward_training
;
normalization_flags
=
dnnl
::
normalization_flags
::
use_scale_shift
;
}
dnnl
::
batch_normalization_forward
::
desc
desc
=
dnnl
::
batch_normalization_forward
::
desc
(
prop_kind
,
x_desc
,
epsilon
,
dnnl
::
normalization_flags
::
use_scale_shift
);
dnnl
::
batch_normalization_forward
::
desc
(
prop_kind
,
x_desc
,
epsilon
,
normalization_flags
);
auto
prim_desc
=
dnnl
::
batch_normalization_forward
::
primitive_desc
(
desc
,
MKLKernelEngine
::
Get
().
engine
());
primitive_
=
std
::
make_shared
<
dnnl
::
batch_normalization_forward
>
(
prim_desc
);
AddArgument
(
DNNL_ARG_SRC
,
x_desc
);
...
...
@@ -74,14 +76,14 @@ bool FusedBatchNormCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inpu
auto
wksp
=
reinterpret_cast
<
float
*>
(
workspace
[
0
]
->
addr
);
memcpy_s
(
wksp
,
workspace
[
0
]
->
size
,
inputs
[
1
]
->
addr
,
inputs
[
1
]
->
size
);
memcpy_s
(
wksp
+
(
inputs
[
1
]
->
size
/
sizeof
(
float
)),
inputs
[
2
]
->
size
,
inputs
[
2
]
->
addr
,
inputs
[
2
]
->
size
);
if
(
is_train
)
{
SetArgumentHandle
(
DNNL_ARG_SRC
,
inputs
[
0
]
->
addr
);
SetArgumentHandle
(
DNNL_ARG_MEAN
,
outputs
[
3
]
->
addr
);
SetArgumentHandle
(
DNNL_ARG_VARIANCE
,
outputs
[
4
]
->
addr
);
SetArgumentHandle
(
DNNL_ARG_SCALE_SHIFT
,
workspace
[
0
]
->
addr
);
SetArgumentHandle
(
DNNL_ARG_DST
,
outputs
[
0
]
->
addr
);
ExecutePrimitive
();
if
(
is_train
)
{
auto
moving_mean
=
reinterpret_cast
<
float
*>
(
inputs
[
3
]
->
addr
);
auto
moving_variance
=
reinterpret_cast
<
float
*>
(
inputs
[
4
]
->
addr
);
auto
mean
=
reinterpret_cast
<
float
*>
(
outputs
[
3
]
->
addr
);
...
...
@@ -90,6 +92,13 @@ bool FusedBatchNormCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inpu
moving_mean
[
i
]
=
moving_mean
[
i
]
*
(
1
-
momentum
)
+
mean
[
i
]
*
momentum
;
moving_variance
[
i
]
=
moving_variance
[
i
]
*
(
1
-
momentum
)
+
variance
[
i
]
*
momentum
;
}
}
else
{
SetArgumentHandle
(
DNNL_ARG_SRC
,
inputs
[
0
]
->
addr
);
SetArgumentHandle
(
DNNL_ARG_MEAN
,
inputs
[
3
]
->
addr
);
SetArgumentHandle
(
DNNL_ARG_VARIANCE
,
inputs
[
4
]
->
addr
);
SetArgumentHandle
(
DNNL_ARG_SCALE_SHIFT
,
workspace
[
0
]
->
addr
);
SetArgumentHandle
(
DNNL_ARG_DST
,
outputs
[
0
]
->
addr
);
ExecutePrimitive
();
}
return
true
;
}
...
...
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