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体验新版 GitCode,发现更多精彩内容 >>
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b6661d3a
编写于
3月 28, 2022
作者:
Y
Yang
提交者:
GitHub
3月 28, 2022
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差异文件
[phi] move infershape: flip/maxout/take_along_axis/put_along_axis (#40974)
上级
1431305e
变更
10
隐藏空白更改
内联
并排
Showing
10 changed file
with
206 addition
and
153 deletion
+206
-153
paddle/fluid/operators/flip_op.cc
paddle/fluid/operators/flip_op.cc
+7
-67
paddle/fluid/operators/maxout_op.cc
paddle/fluid/operators/maxout_op.cc
+8
-40
paddle/fluid/operators/put_along_axis_op.cc
paddle/fluid/operators/put_along_axis_op.cc
+7
-13
paddle/fluid/operators/take_along_axis_op.cc
paddle/fluid/operators/take_along_axis_op.cc
+7
-33
paddle/phi/infermeta/binary.cc
paddle/phi/infermeta/binary.cc
+25
-0
paddle/phi/infermeta/binary.h
paddle/phi/infermeta/binary.h
+5
-0
paddle/phi/infermeta/ternary.cc
paddle/phi/infermeta/ternary.cc
+10
-0
paddle/phi/infermeta/ternary.h
paddle/phi/infermeta/ternary.h
+7
-0
paddle/phi/infermeta/unary.cc
paddle/phi/infermeta/unary.cc
+121
-0
paddle/phi/infermeta/unary.h
paddle/phi/infermeta/unary.h
+9
-0
未找到文件。
paddle/fluid/operators/flip_op.cc
浏览文件 @
b6661d3a
...
...
@@ -16,8 +16,11 @@ limitations under the License. */
#include <unordered_map>
#include <vector>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/unary.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -29,72 +32,6 @@ class FlipOp : public framework::OperatorWithKernel {
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
// TODO move to phi kernel
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
platform
::
errors
::
NotFound
(
"Input(X) of FlipOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
platform
::
errors
::
NotFound
(
"Output(Out) of FlipOp should not be null."
));
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
flip_dims
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"axis"
);
size_t
flip_dims_size
=
flip_dims
.
size
();
if
(
flip_dims_size
>
0
)
{
// check if dims axis within range
auto
min_max_d
=
std
::
minmax_element
(
flip_dims
.
begin
(),
flip_dims
.
end
());
PADDLE_ENFORCE_LT
(
*
min_max_d
.
first
,
x_dims
.
size
(),
platform
::
errors
::
InvalidArgument
(
"min(axes) should be less than the input tensor X's "
"axes of FlipOp. But received min(axes) = %d, "
"X's axes = %d, X's shape = [%s]"
,
*
min_max_d
.
first
,
x_dims
.
size
(),
x_dims
));
PADDLE_ENFORCE_GE
(
*
min_max_d
.
first
,
x_dims
.
size
()
*
-
1
,
platform
::
errors
::
InvalidArgument
(
"min(axes) should be greater than or equal to the "
"input tensor X's "
"axes of FlipOp times -1. But received "
"min(axes) = %d, X's "
"axes = %d, X's shape = [%s]"
,
*
min_max_d
.
first
,
x_dims
.
size
()
*
-
1
,
x_dims
));
PADDLE_ENFORCE_LT
(
*
min_max_d
.
second
,
x_dims
.
size
(),
platform
::
errors
::
InvalidArgument
(
"max(axes) should be less than the input tensor X's "
"axes of FlipOp. But received max(axes) = %d, "
"X's axes = %d, X's shape = [%s]"
,
*
min_max_d
.
second
,
x_dims
.
size
(),
x_dims
));
PADDLE_ENFORCE_GE
(
*
min_max_d
.
second
,
x_dims
.
size
()
*
-
1
,
platform
::
errors
::
InvalidArgument
(
"max(axes) should be greater than or equal to the "
"input tensor X's "
"axes of FlipOp times -1. But received "
"max(axes) = %d, X's "
"axes = %d, X's shape = [%s]"
,
*
min_max_d
.
second
,
x_dims
.
size
()
*
-
1
,
x_dims
));
// check duplicates in dims
flip_dims
.
erase
(
std
::
unique
(
flip_dims
.
begin
(),
flip_dims
.
end
()),
flip_dims
.
end
());
PADDLE_ENFORCE_EQ
(
flip_dims
.
size
(),
flip_dims_size
,
platform
::
errors
::
InvalidArgument
(
"axes has duplicates, original flip axes size=%d, "
"but unique flip axes size=%d.)"
,
flip_dims_size
,
flip_dims
.
size
()));
}
VLOG
(
3
)
<<
"flip operator x.shape="
<<
x_dims
;
std
::
vector
<
int64_t
>
output_dims
(
x_dims
.
size
());
for
(
int
i
=
0
;
i
<
x_dims
.
size
();
++
i
)
{
output_dims
[
i
]
=
x_dims
[
i
];
}
ctx
->
SetOutputDim
(
"Out"
,
phi
::
make_ddim
(
output_dims
));
ctx
->
ShareLoD
(
"X"
,
"Out"
);
}
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
framework
::
LibraryType
library
=
framework
::
LibraryType
::
kPlain
;
...
...
@@ -148,9 +85,12 @@ class FlipOpGradMaker : public framework::SingleGradOpMaker<T> {
namespace
ops
=
paddle
::
operators
;
namespace
plat
=
paddle
::
platform
;
DECLARE_INFER_SHAPE_FUNCTOR
(
flip
,
FlipInferShapeFunctor
,
PD_INFER_META
(
phi
::
FlipInferMeta
));
REGISTER_OPERATOR
(
flip
,
ops
::
FlipOp
,
ops
::
FlipOpMaker
,
ops
::
FlipOpInferVarType
,
ops
::
FlipOpGradMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
FlipOpGradMaker
<
paddle
::
imperative
::
OpBase
>
);
ops
::
FlipOpGradMaker
<
paddle
::
imperative
::
OpBase
>
,
FlipInferShapeFunctor
);
/* ========================== register checkpoint ===========================*/
REGISTER_OP_VERSION
(
flip
)
...
...
paddle/fluid/operators/maxout_op.cc
浏览文件 @
b6661d3a
...
...
@@ -14,8 +14,11 @@
#include <vector>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/unary.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -71,50 +74,12 @@ Please refer to Paper:
class
MaxOutOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"maxout"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Out"
),
"Output"
,
"Out"
,
"maxout"
);
auto
in_x_dims
=
ctx
->
GetInputDim
(
"X"
);
int
groups
=
ctx
->
Attrs
().
Get
<
int
>
(
"groups"
);
int
axis
=
ctx
->
Attrs
().
Get
<
int
>
(
"axis"
);
// check groups > 1
PADDLE_ENFORCE_GT
(
groups
,
1
,
platform
::
errors
::
InvalidArgument
(
"Attr(groups) of Op(maxout) should be "
"larger than 1. But received %d."
,
groups
));
PADDLE_ENFORCE_EQ
(
axis
==
1
||
axis
==
-
1
||
axis
==
3
,
true
,
platform
::
errors
::
InvalidArgument
(
"axis only supported 1, -1 or 3, but recevied axis is: %d"
,
axis
));
PADDLE_ENFORCE_EQ
(
in_x_dims
.
size
(),
4
,
platform
::
errors
::
InvalidArgument
(
"x's dims should be 4, but received x's dims is: %d"
,
in_x_dims
.
size
()));
if
(
axis
<
0
)
{
axis
+=
in_x_dims
.
size
();
}
PADDLE_ENFORCE_EQ
(
in_x_dims
[
axis
]
%
groups
,
0
,
platform
::
errors
::
InvalidArgument
(
"The number of input channels for Op(maxout) "
"should be divisible by Attr(groups). But received: the "
"input's channels is [%d], the shape of input is [%s], "
"the Attr(groups) is [%d], the Attr(axis) is [%d]. The "
"error may come from wrong Attr(groups) or Attr(axis) setting."
,
in_x_dims
[
axis
],
in_x_dims
,
groups
,
axis
));
std
::
vector
<
int64_t
>
output_shape
(
{
in_x_dims
[
0
],
in_x_dims
[
1
],
in_x_dims
[
2
],
in_x_dims
[
3
]});
output_shape
[
axis
]
=
in_x_dims
[
axis
]
/
groups
;
ctx
->
SetOutputDim
(
"Out"
,
phi
::
make_ddim
(
output_shape
));
}
};
class
MaxOutOpGrad
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"maxout_grad"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"X"
)),
"Output"
,
"X@Grad"
,
"maxout_grad"
);
...
...
@@ -125,8 +90,11 @@ class MaxOutOpGrad : public framework::OperatorWithKernel {
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
DECLARE_INFER_SHAPE_FUNCTOR
(
maxout
,
MaxOutInferShapeFunctor
,
PD_INFER_META
(
phi
::
MaxOutInferMeta
));
REGISTER_OPERATOR
(
maxout
,
ops
::
MaxOutOp
,
ops
::
MaxOutOpMaker
,
paddle
::
framework
::
DefaultGradOpMaker
<
paddle
::
framework
::
OpDesc
,
true
>
,
paddle
::
framework
::
DefaultGradOpMaker
<
paddle
::
imperative
::
OpBase
,
true
>
);
paddle
::
framework
::
DefaultGradOpMaker
<
paddle
::
imperative
::
OpBase
,
true
>
,
MaxOutInferShapeFunctor
);
REGISTER_OPERATOR
(
maxout_grad
,
ops
::
MaxOutOpGrad
);
paddle/fluid/operators/put_along_axis_op.cc
浏览文件 @
b6661d3a
...
...
@@ -16,9 +16,12 @@ limitations under the License. */
#include <string>
#include <vector>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/phi/core/ddim.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/ternary.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -27,18 +30,6 @@ class PutAlongAxisOp : public framework::OperatorWithKernel {
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"Input"
),
"Input"
,
"Input"
,
"PutAlongAxis"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"Index"
),
"Input"
,
"Index"
,
"PutAlongAxis"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"Value"
),
"Input"
,
"Value"
,
"PutAlongAxis"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Result"
),
"Output"
,
"Result"
,
"PutAlongAxis"
);
auto
index_dim
=
ctx
->
GetInputDim
(
"Index"
);
ctx
->
SetOutputDim
(
"Result"
,
index_dim
);
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
...
...
@@ -118,9 +109,12 @@ DECLARE_INPLACE_OP_INFERER(PutAlongAxisInplaceInferer, {"Input", "Result"});
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
DECLARE_INFER_SHAPE_FUNCTOR
(
put_along_axis
,
PutAlongAxisInferShapeFunctor
,
PD_INFER_META
(
phi
::
PutAlongAxisInferMeta
));
REGISTER_OPERATOR
(
put_along_axis
,
ops
::
PutAlongAxisOp
,
ops
::
PutAlongAxisOpMaker
,
ops
::
PutAlongAxisGradOpMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
PutAlongAxisGradOpMaker
<
paddle
::
imperative
::
OpBase
>
,
paddle
::
operators
::
PutAlongAxisInplaceInferer
);
paddle
::
operators
::
PutAlongAxisInplaceInferer
,
PutAlongAxisInferShapeFunctor
);
REGISTER_OPERATOR
(
put_along_axis_grad
,
ops
::
PutAlongAxisGradOp
);
paddle/fluid/operators/take_along_axis_op.cc
浏览文件 @
b6661d3a
...
...
@@ -16,9 +16,12 @@ limitations under the License. */
#include <string>
#include <vector>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/phi/core/ddim.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/binary.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -27,38 +30,6 @@ class TakeAlongAxisOp : public framework::OperatorWithKernel {
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"Input"
),
true
,
platform
::
errors
::
InvalidArgument
(
"Input(Input) of TakeAlongAxisOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"Index"
),
true
,
platform
::
errors
::
InvalidArgument
(
"Input(Index) of TakeAlongAxisOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Result"
),
true
,
platform
::
errors
::
InvalidArgument
(
"Output(Result) of TakeAlongAxisOp should not be null."
));
auto
input_dim
=
ctx
->
GetInputDim
(
"Input"
);
auto
index_dim
=
ctx
->
GetInputDim
(
"Index"
);
PADDLE_ENFORCE_GT
(
input_dim
.
size
(),
0
,
platform
::
errors
::
InvalidArgument
(
"Dimension of the input(Input) of TakeAlongAxisOp "
"should be greater than 0."
,
input_dim
));
PADDLE_ENFORCE_GT
(
index_dim
.
size
(),
0
,
platform
::
errors
::
InvalidArgument
(
"Dimension of the input(Index) of TakeAlongAxisOp "
"should be greater than 0."
,
index_dim
));
ctx
->
SetOutputDim
(
"Result"
,
index_dim
);
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
...
...
@@ -134,9 +105,12 @@ class TakeAlongAxisGradOpMaker : public framework::SingleGradOpMaker<T> {
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
DECLARE_INFER_SHAPE_FUNCTOR
(
take_along_axis
,
TakeAlongAxisInferShapeFunctor
,
PD_INFER_META
(
phi
::
TakeAlongAxisInferMeta
));
REGISTER_OPERATOR
(
take_along_axis
,
ops
::
TakeAlongAxisOp
,
ops
::
TakeAlongAxisOpMaker
,
ops
::
TakeAlongAxisGradOpMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
TakeAlongAxisGradOpMaker
<
paddle
::
imperative
::
OpBase
>
);
ops
::
TakeAlongAxisGradOpMaker
<
paddle
::
imperative
::
OpBase
>
,
TakeAlongAxisInferShapeFunctor
);
REGISTER_OPERATOR
(
take_along_axis_grad
,
ops
::
TakeAlongAxisGradOp
);
paddle/phi/infermeta/binary.cc
浏览文件 @
b6661d3a
...
...
@@ -1583,6 +1583,31 @@ void SigmoidCrossEntropyWithLogitsInferMeta(const MetaTensor& x,
out
->
share_lod
(
x
);
}
void
TakeAlongAxisInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
index
,
int
axis
,
MetaTensor
*
out
)
{
auto
input_dim
=
x
.
dims
();
auto
index_dim
=
index
.
dims
();
PADDLE_ENFORCE_GT
(
input_dim
.
size
(),
0
,
phi
::
errors
::
InvalidArgument
(
"Dimension of the input(Input) of TakeAlongAxisOp "
"should be greater than 0."
,
input_dim
));
PADDLE_ENFORCE_GT
(
index_dim
.
size
(),
0
,
phi
::
errors
::
InvalidArgument
(
"Dimension of the input(Index) of TakeAlongAxisOp "
"should be greater than 0."
,
index_dim
));
out
->
set_dims
(
index_dim
);
out
->
set_dtype
(
x
.
dtype
());
}
void
TriangularSolveInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
y
,
bool
upper
,
...
...
paddle/phi/infermeta/binary.h
浏览文件 @
b6661d3a
...
...
@@ -221,6 +221,11 @@ void SigmoidCrossEntropyWithLogitsInferMeta(const MetaTensor& x,
MetaTensor
*
out
,
MetaConfig
config
=
MetaConfig
());
void
TakeAlongAxisInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
index
,
int
axis
,
MetaTensor
*
out
);
void
TriangularSolveInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
y
,
bool
upper
,
...
...
paddle/phi/infermeta/ternary.cc
浏览文件 @
b6661d3a
...
...
@@ -335,6 +335,16 @@ void NllLossRawInferMeta(const MetaTensor& input,
total_weight
->
set_dtype
(
input
.
dtype
());
}
void
PutAlongAxisInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
index
,
const
MetaTensor
&
value
,
int
axis
,
const
std
::
string
&
reduce
,
MetaTensor
*
out
)
{
out
->
set_dims
(
x
.
dims
());
out
->
set_dtype
(
x
.
dtype
());
}
void
RoiAlignInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
boxes
,
paddle
::
optional
<
const
MetaTensor
&>
boxes_num
,
...
...
paddle/phi/infermeta/ternary.h
浏览文件 @
b6661d3a
...
...
@@ -74,6 +74,13 @@ void NllLossRawInferMeta(const MetaTensor& input,
MetaTensor
*
total_weight
,
MetaConfig
config
=
MetaConfig
());
void
PutAlongAxisInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
index
,
const
MetaTensor
&
value
,
int
axis
,
const
std
::
string
&
reduce
,
MetaTensor
*
out
);
void
RoiAlignInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
boxes
,
paddle
::
optional
<
const
MetaTensor
&>
boxes_num
,
...
...
paddle/phi/infermeta/unary.cc
浏览文件 @
b6661d3a
...
...
@@ -467,6 +467,81 @@ void FlattenWithXShapeInferMeta(const MetaTensor& x,
xshape
->
share_lod
(
x
);
}
void
FlipInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
axis
,
MetaTensor
*
out
)
{
auto
x_dims
=
x
.
dims
();
auto
flip_dims
=
axis
;
size_t
flip_dims_size
=
axis
.
size
();
if
(
flip_dims_size
>
0
)
{
// check if dims axis within range
auto
min_max_d
=
std
::
minmax_element
(
flip_dims
.
begin
(),
flip_dims
.
end
());
PADDLE_ENFORCE_LT
(
*
min_max_d
.
first
,
x_dims
.
size
(),
phi
::
errors
::
InvalidArgument
(
"min(axes) should be less than the input tensor X's "
"axes of FlipOp. But received min(axes) = %d, "
"X's axes = %d, X's shape = [%s]"
,
*
min_max_d
.
first
,
x_dims
.
size
(),
x_dims
));
PADDLE_ENFORCE_GE
(
*
min_max_d
.
first
,
x_dims
.
size
()
*
-
1
,
phi
::
errors
::
InvalidArgument
(
"min(axes) should be greater than or equal to the "
"input tensor X's "
"axes of FlipOp times -1. But received "
"min(axes) = %d, X's "
"axes = %d, X's shape = [%s]"
,
*
min_max_d
.
first
,
x_dims
.
size
()
*
-
1
,
x_dims
));
PADDLE_ENFORCE_LT
(
*
min_max_d
.
second
,
x_dims
.
size
(),
phi
::
errors
::
InvalidArgument
(
"max(axes) should be less than the input tensor X's "
"axes of FlipOp. But received max(axes) = %d, "
"X's axes = %d, X's shape = [%s]"
,
*
min_max_d
.
second
,
x_dims
.
size
(),
x_dims
));
PADDLE_ENFORCE_GE
(
*
min_max_d
.
second
,
x_dims
.
size
()
*
-
1
,
phi
::
errors
::
InvalidArgument
(
"max(axes) should be greater than or equal to the "
"input tensor X's "
"axes of FlipOp times -1. But received "
"max(axes) = %d, X's "
"axes = %d, X's shape = [%s]"
,
*
min_max_d
.
second
,
x_dims
.
size
()
*
-
1
,
x_dims
));
// check duplicates in dims
flip_dims
.
erase
(
std
::
unique
(
flip_dims
.
begin
(),
flip_dims
.
end
()),
flip_dims
.
end
());
PADDLE_ENFORCE_EQ
(
flip_dims
.
size
(),
flip_dims_size
,
phi
::
errors
::
InvalidArgument
(
"axes has duplicates, original flip axes size=%d, "
"but unique flip axes size=%d.)"
,
flip_dims_size
,
flip_dims
.
size
()));
}
VLOG
(
3
)
<<
"flip operator x.shape="
<<
x_dims
;
std
::
vector
<
int64_t
>
output_dims
(
x_dims
.
size
());
for
(
int
i
=
0
;
i
<
x_dims
.
size
();
++
i
)
{
output_dims
[
i
]
=
x_dims
[
i
];
}
out
->
set_dims
(
phi
::
make_ddim
(
output_dims
));
out
->
set_dtype
(
x
.
dtype
());
out
->
share_lod
(
x
);
}
void
FullBatchSizeLikeInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
shape
,
const
Scalar
&
val
,
...
...
@@ -751,6 +826,52 @@ void MatrixPowerInferMeta(const MetaTensor& x, int n, MetaTensor* out) {
out
->
set_dtype
(
x
.
dtype
());
}
void
MaxOutInferMeta
(
const
MetaTensor
&
x
,
int
groups
,
int
axis
,
MetaTensor
*
out
)
{
auto
in_x_dims
=
x
.
dims
();
// check groups > 1
PADDLE_ENFORCE_GT
(
groups
,
1
,
phi
::
errors
::
InvalidArgument
(
"Attr(groups) of Op(maxout) should be "
"larger than 1. But received %d."
,
groups
));
PADDLE_ENFORCE_EQ
(
axis
==
1
||
axis
==
-
1
||
axis
==
3
,
true
,
phi
::
errors
::
InvalidArgument
(
"axis only supported 1, -1 or 3, but recevied axis is: %d"
,
axis
));
PADDLE_ENFORCE_EQ
(
in_x_dims
.
size
(),
4
,
phi
::
errors
::
InvalidArgument
(
"x's dims should be 4, but received x's dims is: %d"
,
in_x_dims
.
size
()));
if
(
axis
<
0
)
{
axis
+=
in_x_dims
.
size
();
}
PADDLE_ENFORCE_EQ
(
in_x_dims
[
axis
]
%
groups
,
0
,
phi
::
errors
::
InvalidArgument
(
"The number of input channels for Op(maxout) "
"should be divisible by Attr(groups). But received: the "
"input's channels is [%d], the shape of input is [%s], "
"the Attr(groups) is [%d], the Attr(axis) is [%d]. The "
"error may come from wrong Attr(groups) or Attr(axis) setting."
,
in_x_dims
[
axis
],
in_x_dims
,
groups
,
axis
));
std
::
vector
<
int64_t
>
output_shape
(
{
in_x_dims
[
0
],
in_x_dims
[
1
],
in_x_dims
[
2
],
in_x_dims
[
3
]});
output_shape
[
axis
]
=
in_x_dims
[
axis
]
/
groups
;
out
->
set_dims
(
phi
::
make_ddim
(
output_shape
));
out
->
set_dtype
(
x
.
dtype
());
}
void
MaxPoolWithIndexInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
kernel_size
,
const
std
::
vector
<
int
>&
strides
,
...
...
paddle/phi/infermeta/unary.h
浏览文件 @
b6661d3a
...
...
@@ -98,6 +98,10 @@ void FlattenWithXShapeInferMeta(const MetaTensor& x,
MetaTensor
*
out
,
MetaTensor
*
xshape
);
void
FlipInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
axis
,
MetaTensor
*
out
);
void
FullBatchSizeLikeInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
shape
,
const
Scalar
&
val
,
...
...
@@ -134,6 +138,11 @@ void KthvalueInferMeta(const MetaTensor& x,
void
MatrixPowerInferMeta
(
const
MetaTensor
&
x
,
int
n
,
MetaTensor
*
out
);
void
MaxOutInferMeta
(
const
MetaTensor
&
x
,
int
groups
,
int
axis
,
MetaTensor
*
out
);
void
MaxPoolWithIndexInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
kernel_size
,
const
std
::
vector
<
int
>&
strides
,
...
...
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