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aeaf69b3
编写于
3月 09, 2022
作者:
C
Chen Weihang
提交者:
GitHub
3月 09, 2022
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
remove determinant deps for svd helper (#40235)
上级
7ea9235c
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
49 addition
and
34 deletion
+49
-34
paddle/fluid/operators/determinant_op.h
paddle/fluid/operators/determinant_op.h
+37
-34
paddle/phi/kernels/full_kernel.h
paddle/phi/kernels/full_kernel.h
+12
-0
未找到文件。
paddle/fluid/operators/determinant_op.h
浏览文件 @
aeaf69b3
...
...
@@ -19,11 +19,17 @@
#include <cmath>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/svd_helper.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/for_range.h"
#include "paddle/phi/kernels/funcs/complex_functors.h"
#include "paddle/phi/kernels/complex_kernel.h"
#include "paddle/phi/kernels/full_kernel.h"
#include "paddle/phi/kernels/funcs/diag_functor.h"
#include "paddle/phi/kernels/funcs/math_function.h"
#include "paddle/phi/kernels/funcs/matrix_inverse.h"
#include "paddle/phi/kernels/funcs/unsqueeze.h"
#include "paddle/phi/kernels/math_kernel.h"
#include "paddle/phi/kernels/matmul_kernel.h"
#include "paddle/phi/kernels/transpose_kernel.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -172,7 +178,7 @@ template <typename DeviceContext, typename T>
class
DeterminantGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
&
dev_ctx
=
context
.
template
device_context
<
DeviceContext
>();
auto
&
orig_
dev_ctx
=
context
.
template
device_context
<
DeviceContext
>();
const
auto
*
input
=
context
.
Input
<
framework
::
Tensor
>
(
"Input"
);
const
auto
*
det
=
context
.
Input
<
framework
::
Tensor
>
(
"Out"
);
const
auto
*
grad
=
...
...
@@ -200,15 +206,18 @@ class DeterminantGradKernel : public framework::OpKernel<T> {
// checked in forward, pass
}
auto
&
dev_ctx
=
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
orig_dev_ctx
);
// Check Whether the matrix is invertible
// (matrix A not invertible) == (det(A)=0)
if
(
!
CheckMatrixInvertible
<
DeviceContext
,
T
>
(
context
,
det
))
{
// The matrix is not invertible
VLOG
(
3
)
<<
"The input matrix not invertible!"
;
ddet
->
Resize
(
input
->
dims
());
ddet
->
mutable_data
<
T
>
(
context
.
GetPlace
());
phi
::
funcs
::
SetConstant
<
DeviceContext
,
T
>
zero
;
zero
(
dev_ctx
,
ddet
,
static_cast
<
T
>
(
0.0
f
));
phi
::
Full
<
T
>
(
dev_ctx
,
phi
::
vectorize
(
input
->
dims
()),
static_cast
<
T
>
(
0.0
f
),
ddet
);
return
;
}
...
...
@@ -218,8 +227,6 @@ class DeterminantGradKernel : public framework::OpKernel<T> {
// we set d|A| = unsqueeze(dA * |A|, [-1, -2]) * inverse(A).transpose(-2,
// -1)
math
::
DeviceIndependenceTensorOperations
<
DeviceContext
,
T
>
helper
(
context
);
// First: inverse(A)
framework
::
Tensor
inverse_A
;
// A must be square matrices!
...
...
@@ -227,26 +234,28 @@ class DeterminantGradKernel : public framework::OpKernel<T> {
inverse_A
.
mutable_data
<
T
>
(
context
.
GetPlace
());
phi
::
funcs
::
MatrixInverseFunctor
<
DeviceContext
,
T
>
mat_inv
;
mat_inv
(
dev_ctx
,
*
input
,
&
inverse_A
);
mat_inv
(
orig_
dev_ctx
,
*
input
,
&
inverse_A
);
VLOG
(
3
)
<<
"inverse(A) dims: "
<<
inverse_A
.
dims
();
// Second: inverse(A).transpose(-2, -1)
framework
::
Tensor
transpose_inverse_A
=
helper
.
Transpose
(
inverse_A
);
framework
::
Tensor
transpose_inverse_A
=
phi
::
TransposeLast2Dim
<
T
>
(
dev_ctx
,
inverse_A
);
VLOG
(
3
)
<<
"(dA * |A|).transpose(-2, -1) dims: "
<<
transpose_inverse_A
.
dims
();
// Third: dA * |A|
auto
mul_dA_detA
=
helper
.
Mul
(
*
grad
,
*
det
);
auto
mul_dA_detA
=
phi
::
Multiply
<
T
>
(
dev_ctx
,
*
grad
,
*
det
);
VLOG
(
3
)
<<
"dA * |A| dims: "
<<
mul_dA_detA
.
dims
();
// Fourth: unsqueeze(dA * |A|, [-1, -2])
auto
unsqueeze1
=
helper
.
Unsqueeze
(
mul_dA_detA
,
-
1
);
auto
unsqueeze2
=
helper
.
Unsqueeze
(
unsqueeze1
,
-
2
);
auto
unsqueeze1
=
phi
::
funcs
::
Unsqueeze
(
mul_dA_detA
,
-
1
);
auto
unsqueeze2
=
phi
::
funcs
::
Unsqueeze
(
unsqueeze1
,
-
2
);
VLOG
(
3
)
<<
"unsqueezed(dA * |A|) dims: "
<<
unsqueeze2
.
dims
();
// Finally: unsqueeze(dA * |A|) * inverse(A)
auto
res
=
helper
.
Mul
(
unsqueeze2
,
transpose_inverse_A
);
auto
res
=
phi
::
Multiply
<
T
>
(
dev_ctx
,
unsqueeze2
,
transpose_inverse_A
);
VLOG
(
3
)
<<
"unsqueeze(dA * |A|) * inverse(A) dims: "
<<
res
.
dims
();
...
...
@@ -331,7 +340,7 @@ template <typename DeviceContext, typename T>
class
SlogDeterminantGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
&
dev_ctx
=
context
.
template
device_context
<
DeviceContext
>();
auto
&
orig_
dev_ctx
=
context
.
template
device_context
<
DeviceContext
>();
const
auto
*
input
=
context
.
Input
<
framework
::
Tensor
>
(
"Input"
);
const
auto
*
slogdet
=
context
.
Input
<
framework
::
Tensor
>
(
"Out"
);
const
auto
*
grad
=
...
...
@@ -353,6 +362,10 @@ class SlogDeterminantGradKernel : public framework::OpKernel<T> {
input
->
dims
().
size
()
-
grad
->
dims
().
size
()));
}
auto
&
dev_ctx
=
static_cast
<
const
typename
framework
::
ConvertToPhiContext
<
DeviceContext
>::
TYPE
&>
(
orig_dev_ctx
);
// Check Whether the matrix is invertible
// (matrix A not invertible) == (absslogdet(A)=0)
auto
slogdet_vec
=
slogdet
->
Split
(
1
,
0
);
...
...
@@ -361,9 +374,8 @@ class SlogDeterminantGradKernel : public framework::OpKernel<T> {
// The matrix is not invertible
VLOG
(
3
)
<<
"The input matrix not invertible!"
;
dslogdet
->
Resize
(
input
->
dims
());
dslogdet
->
mutable_data
<
T
>
(
context
.
GetPlace
());
phi
::
funcs
::
SetConstant
<
DeviceContext
,
T
>
zero
;
zero
(
dev_ctx
,
dslogdet
,
std
::
numeric_limits
<
T
>::
quiet_NaN
());
phi
::
Full
<
T
>
(
dev_ctx
,
phi
::
vectorize
(
input
->
dims
()),
std
::
numeric_limits
<
T
>::
quiet_NaN
(),
dslogdet
);
return
;
}
...
...
@@ -373,8 +385,6 @@ class SlogDeterminantGradKernel : public framework::OpKernel<T> {
// we set dsl|A| = unsqueeze(dslA, [-1, -2]) *
// inverse(A).conj().transpose(-2, -1)
math
::
DeviceIndependenceTensorOperations
<
DeviceContext
,
T
>
helper
(
context
);
// First: inverse(A)
framework
::
Tensor
inverse_A
;
// A must be square matrices!
...
...
@@ -382,25 +392,18 @@ class SlogDeterminantGradKernel : public framework::OpKernel<T> {
inverse_A
.
mutable_data
<
T
>
(
context
.
GetPlace
());
phi
::
funcs
::
MatrixInverseFunctor
<
DeviceContext
,
T
>
mat_inv
;
mat_inv
(
dev_ctx
,
*
input
,
&
inverse_A
);
mat_inv
(
orig_
dev_ctx
,
*
input
,
&
inverse_A
);
VLOG
(
3
)
<<
"inverse(A) dims: "
<<
inverse_A
.
dims
();
// Second: inverse(A).conj()
framework
::
Tensor
conj_inverse_A
;
conj_inverse_A
.
Resize
(
inverse_A
.
dims
());
auto
numel
=
input
->
numel
();
auto
*
conj_data
=
conj_inverse_A
.
mutable_data
<
T
>
(
context
.
GetPlace
(),
size_t
(
numel
*
sizeof
(
T
)));
platform
::
ForRange
<
DeviceContext
>
for_range
(
dev_ctx
,
numel
);
phi
::
funcs
::
ConjFunctor
<
T
>
functor
(
inverse_A
.
data
<
T
>
(),
numel
,
conj_data
);
for_range
(
functor
);
auto
conj_inverse_A
=
phi
::
Conj
<
T
>
(
dev_ctx
,
inverse_A
);
VLOG
(
3
)
<<
"inverse(A).conj() dims: "
<<
conj_inverse_A
.
dims
();
// Third: inverse(A).conj().transpose(-2, -1)
framework
::
Tensor
transpose_inverse_A
=
helper
.
Transpose
(
conj_inverse_A
);
framework
::
Tensor
transpose_inverse_A
=
phi
::
TransposeLast2Dim
<
T
>
(
dev_ctx
,
conj_inverse_A
);
VLOG
(
3
)
<<
"inverse(A).conj().transpose(-2, -1) dims: "
<<
transpose_inverse_A
.
dims
();
...
...
@@ -417,12 +420,12 @@ class SlogDeterminantGradKernel : public framework::OpKernel<T> {
det_grad
.
Resize
(
det_grad
.
dims
().
reshape
(
det_grad_vec
));
// Fifth: unsqueeze(dslA, [-1, -2])
auto
unsqueeze1
=
helper
.
Unsqueeze
(
det_grad
,
-
1
);
auto
unsqueeze2
=
helper
.
Unsqueeze
(
unsqueeze1
,
-
2
);
auto
unsqueeze1
=
phi
::
funcs
::
Unsqueeze
(
det_grad
,
-
1
);
auto
unsqueeze2
=
phi
::
funcs
::
Unsqueeze
(
unsqueeze1
,
-
2
);
VLOG
(
3
)
<<
"unsqueezed(dslA, [-1, -2]) dims: "
<<
unsqueeze2
.
dims
();
// Finally: unsqueeze(dslA) * inverse(A)
auto
res
=
helper
.
Mul
(
unsqueeze2
,
transpose_inverse_A
);
auto
res
=
phi
::
Multiply
<
T
>
(
dev_ctx
,
unsqueeze2
,
transpose_inverse_A
);
VLOG
(
3
)
<<
"unsqueeze(dslA) * inverse(A) dims: "
<<
res
.
dims
();
framework
::
TensorCopy
(
res
,
context
.
GetPlace
(),
dslogdet
);
...
...
paddle/phi/kernels/full_kernel.h
浏览文件 @
aeaf69b3
...
...
@@ -37,6 +37,18 @@ void FullLikeKernel(const Context& dev_ctx,
DataType
dtype
,
DenseTensor
*
out
);
template
<
typename
T
,
typename
Context
>
void
Full
(
const
Context
&
dev_ctx
,
const
ScalarArray
&
shape
,
const
Scalar
&
val
,
DenseTensor
*
out
)
{
FullKernel
<
T
,
Context
>
(
dev_ctx
,
shape
,
val
,
paddle
::
experimental
::
CppTypeToDataType
<
T
>::
Type
(),
out
);
}
template
<
typename
T
,
typename
Context
>
DenseTensor
Full
(
const
Context
&
dev_ctx
,
const
ScalarArray
&
shape
,
...
...
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