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aa18ae11
编写于
7月 06, 2022
作者:
J
joanna.wozna.intel
提交者:
GitHub
7月 06, 2022
浏览文件
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电子邮件补丁
差异文件
Set FC input data format to ANY (#44023)
* Fc add any to input format * Pre-commit changes
上级
3fd6f09f
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
4 addition
and
3 deletion
+4
-3
paddle/fluid/operators/mkldnn/fc_mkldnn_op.cc
paddle/fluid/operators/mkldnn/fc_mkldnn_op.cc
+4
-3
未找到文件。
paddle/fluid/operators/mkldnn/fc_mkldnn_op.cc
浏览文件 @
aa18ae11
...
@@ -209,7 +209,7 @@ class FCPrimitiveFactory {
...
@@ -209,7 +209,7 @@ class FCPrimitiveFactory {
const
Tensor
*
bias
,
const
Tensor
*
bias
,
LoDTensor
*
output
,
LoDTensor
*
output
,
const
ExecutionContext
&
ctx
)
{
const
ExecutionContext
&
ctx
)
{
auto
src_desc
=
CreateMemDescriptor
<
T_in
>
(
input
,
input
->
format
()
);
auto
src_desc
=
CreateMemDescriptor
<
T_in
>
(
input
,
MKLDNNMemoryFormat
::
any
);
auto
weight_dims
=
Get2DWeightDimsForDNNL
(
weights
);
auto
weight_dims
=
Get2DWeightDimsForDNNL
(
weights
);
auto
weights_desc
=
auto
weights_desc
=
CreateMemDescriptor
<
T_w
>
(
weight_dims
,
MKLDNNMemoryFormat
::
any
);
CreateMemDescriptor
<
T_w
>
(
weight_dims
,
MKLDNNMemoryFormat
::
any
);
...
@@ -236,7 +236,8 @@ class FCPrimitiveFactory {
...
@@ -236,7 +236,8 @@ class FCPrimitiveFactory {
auto
input_dims
=
phi
::
vectorize
(
input
->
dims
());
auto
input_dims
=
phi
::
vectorize
(
input
->
dims
());
std
::
vector
<
int64_t
>
new_input_dims
=
{
std
::
vector
<
int64_t
>
new_input_dims
=
{
input_dims
[
0
]
*
input_dims
[
1
],
input_dims
[
2
],
1
};
input_dims
[
0
]
*
input_dims
[
1
],
input_dims
[
2
],
1
};
auto
src_desc
=
CreateMemDescriptor
<
T_in
>
(
new_input_dims
,
input
->
format
());
auto
src_desc
=
CreateMemDescriptor
<
T_in
>
(
new_input_dims
,
MKLDNNMemoryFormat
::
any
);
auto
weight_dims
=
Get3DWeightDimsForDNNL
(
weights
);
auto
weight_dims
=
Get3DWeightDimsForDNNL
(
weights
);
auto
weights_desc
=
auto
weights_desc
=
...
@@ -267,7 +268,7 @@ class FCPrimitiveFactory {
...
@@ -267,7 +268,7 @@ class FCPrimitiveFactory {
const
Tensor
*
bias
,
const
Tensor
*
bias
,
LoDTensor
*
output
,
LoDTensor
*
output
,
const
ExecutionContext
&
ctx
)
{
const
ExecutionContext
&
ctx
)
{
auto
src_desc
=
CreateMemDescriptor
<
T_in
>
(
input
,
input
->
format
()
);
auto
src_desc
=
CreateMemDescriptor
<
T_in
>
(
input
,
MKLDNNMemoryFormat
::
any
);
// Since MKL-DNN doesn't support 4D column-major data formats in
// Since MKL-DNN doesn't support 4D column-major data formats in
// inner_product primitive, transpose the weights to be in
// inner_product primitive, transpose the weights to be in
// row-major format
// row-major format
...
...
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