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体验新版 GitCode,发现更多精彩内容 >>
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ae60105d
编写于
3月 02, 2023
作者:
Y
Yuanle Liu
提交者:
GitHub
3月 02, 2023
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电子邮件补丁
差异文件
process multiple conv2d_fusion shares weight (#51068)
上级
4652bee4
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
32 addition
and
25 deletion
+32
-25
paddle/fluid/framework/ir/conv2d_fusion_layout_transfer_pass.cc
.../fluid/framework/ir/conv2d_fusion_layout_transfer_pass.cc
+29
-21
paddle/fluid/inference/api/paddle_pass_builder.cc
paddle/fluid/inference/api/paddle_pass_builder.cc
+3
-4
未找到文件。
paddle/fluid/framework/ir/conv2d_fusion_layout_transfer_pass.cc
浏览文件 @
ae60105d
...
...
@@ -142,6 +142,10 @@ void Conv2dFusionLayoutTransferPass::ApplyImpl(ir::Graph *graph) const {
auto
iter
=
op_nodes
.
cbegin
();
auto
*
block_desc
=
(
*
iter
)
->
Op
()
->
Block
();
// Process multiple conv2d_fusion shares weight.
std
::
unordered_set
<
std
::
string
>
weights_shape_nhwc
;
// Used to control the insertion of transfer_layout op.
std
::
unordered_set
<
ir
::
Node
*>
vars_shape_nhwc
;
// Only support conv2d_fusion now.
...
...
@@ -157,6 +161,9 @@ void Conv2dFusionLayoutTransferPass::ApplyImpl(ir::Graph *graph) const {
constexpr
int
NHWC_ALIGNMENT
=
8
;
// If filter's channel is not multiple of 8, conv2d_fusion not run at nhwc.
for
(
const
auto
&
filter_name
:
filter_names
)
{
if
(
weights_shape_nhwc
.
count
(
filter_name
))
{
continue
;
}
auto
*
filter_var
=
scope
->
FindLocalVar
(
filter_name
);
const
auto
&
filter_tensor
=
filter_var
->
Get
<
phi
::
DenseTensor
>
();
CHECK_EQ
(
filter_tensor
.
dims
().
size
()
==
4UL
,
true
);
...
...
@@ -206,27 +213,28 @@ void Conv2dFusionLayoutTransferPass::ApplyImpl(ir::Graph *graph) const {
// transfer weights
auto
filter_names
=
op_desc
->
Input
(
"Filter"
);
for
(
const
auto
&
filter_name
:
filter_names
)
{
auto
*
filter_var
=
scope
->
FindLocalVar
(
filter_name
);
auto
*
filter_tensor
=
filter_var
->
GetMutable
<
phi
::
DenseTensor
>
();
phi
::
DenseTensor
temp_tensor
=
*
filter_tensor
;
filter_tensor
->
clear
();
framework
::
TransDataLayout
(
phi
::
DataLayout
::
kNCHW
,
phi
::
DataLayout
::
kNHWC
,
phi
::
CPUPlace
{},
temp_tensor
,
filter_tensor
);
}
auto
op_inputs
=
op_node
->
inputs
;
for
(
auto
*
in_var_node
:
op_inputs
)
{
CHECK_EQ
(
in_var_node
->
IsVar
(),
true
);
if
(
in_var_node
->
Var
()
->
Persistable
())
{
if
(
std
::
find
(
filter_names
.
cbegin
(),
filter_names
.
cend
(),
in_var_node
->
Var
()
->
Name
())
!=
filter_names
.
cend
())
{
auto
from_shape
=
in_var_node
->
Var
()
->
GetShape
();
in_var_node
->
Var
()
->
SetShape
(
{
from_shape
[
0
],
from_shape
[
2
],
from_shape
[
3
],
from_shape
[
1
]});
if
(
weights_shape_nhwc
.
count
(
filter_name
)
==
0
)
{
weights_shape_nhwc
.
insert
(
filter_name
);
auto
*
filter_var
=
scope
->
FindLocalVar
(
filter_name
);
auto
*
filter_tensor
=
filter_var
->
GetMutable
<
phi
::
DenseTensor
>
();
phi
::
DenseTensor
temp_tensor
;
framework
::
TransDataLayout
(
phi
::
DataLayout
::
kNCHW
,
phi
::
DataLayout
::
kNHWC
,
phi
::
CPUPlace
{},
*
filter_tensor
,
&
temp_tensor
);
*
filter_tensor
=
temp_tensor
;
auto
op_inputs
=
op_node
->
inputs
;
for
(
auto
*
in_var_node
:
op_inputs
)
{
CHECK_EQ
(
in_var_node
->
IsVar
(),
true
);
if
(
in_var_node
->
Var
()
->
Persistable
()
&&
in_var_node
->
Var
()
->
Name
()
==
filter_name
)
{
auto
from_shape
=
in_var_node
->
Var
()
->
GetShape
();
in_var_node
->
Var
()
->
SetShape
(
{
from_shape
[
0
],
from_shape
[
2
],
from_shape
[
3
],
from_shape
[
1
]});
}
}
}
}
...
...
paddle/fluid/inference/api/paddle_pass_builder.cc
浏览文件 @
ae60105d
...
...
@@ -270,10 +270,9 @@ GpuPassStrategy::GpuPassStrategy() : PassStrategy({}) {
"conv_elementwise_add_fuse_pass"
,
//
#endif //
"transpose_flatten_concat_fuse_pass"
,
//
// TODO(liuyuanle): rewrite this pass with new logic
// "conv2d_fusion_layout_transfer_pass", //
"auto_mixed_precision_pass"
,
//
"inplace_op_var_pass"
,
// should be the last pass.
"conv2d_fusion_layout_transfer_pass"
,
//
"auto_mixed_precision_pass"
,
//
"inplace_op_var_pass"
,
// should be the last pass.
});
use_gpu_
=
true
;
...
...
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