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28fffef6
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28fffef6
编写于
9月 17, 2021
作者:
0
0x45f
提交者:
GitHub
9月 17, 2021
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电子邮件补丁
差异文件
refine matrix_rank op code and doc (#35722)
上级
5548061b
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
34 addition
and
35 deletion
+34
-35
paddle/fluid/operators/matrix_rank_op.cc
paddle/fluid/operators/matrix_rank_op.cc
+6
-10
python/paddle/fluid/tests/unittests/test_matrix_rank_op.py
python/paddle/fluid/tests/unittests/test_matrix_rank_op.py
+18
-13
python/paddle/tensor/linalg.py
python/paddle/tensor/linalg.py
+10
-12
未找到文件。
paddle/fluid/operators/matrix_rank_op.cc
浏览文件 @
28fffef6
...
...
@@ -27,7 +27,7 @@ namespace operators {
using
DDim
=
framework
::
DDim
;
namespace
detail
{
static
DDim
GetInputBatch
Dim
(
const
DDim
&
dim_x
)
{
static
DDim
CheckAndGetOutput
Dim
(
const
DDim
&
dim_x
)
{
auto
x_vec
=
framework
::
vectorize
(
dim_x
);
if
(
x_vec
.
size
()
==
2
)
{
return
framework
::
make_ddim
({
1
});
...
...
@@ -58,11 +58,8 @@ class MatrixRankeOp : public framework::OperatorWithKernel {
"if hermitian == true, matrix should be n*n"
));
}
DDim
dim_x_batch
=
detail
::
GetInputBatchDim
(
dim_x
);
if
(
ctx
->
Attrs
().
Get
<
bool
>
(
"use_default_tol"
))
{
// user not input TolTensor and tol
ctx
->
SetOutputDim
(
"Out"
,
dim_x_batch
);
}
else
if
(
ctx
->
HasInput
(
"TolTensor"
))
{
DDim
dim_x_batch
=
detail
::
CheckAndGetOutputDim
(
dim_x
);
if
(
ctx
->
HasInput
(
"TolTensor"
))
{
auto
dim_tol
=
ctx
->
GetInputDim
(
"TolTensor"
);
if
(
dim_x_batch
==
dim_tol
)
{
ctx
->
SetOutputDim
(
"Out"
,
dim_x_batch
);
...
...
@@ -75,9 +72,6 @@ class MatrixRankeOp : public framework::OperatorWithKernel {
GetBroadcastDimsArrays
(
dim_x_batch
,
dim_tol
,
x_batch_dims_array
.
data
(),
tol_dims_array
.
data
(),
out_dims_array
.
data
(),
max_dim
,
axis
);
for
(
auto
&
it
:
out_dims_array
)
{
VLOG
(
3
)
<<
"out dims: "
<<
it
;
}
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
out_dims_array
));
}
}
else
{
...
...
@@ -100,7 +94,9 @@ class MatrixRankeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(Tensor), The input tensor of matrix_rank op."
);
AddInput
(
"TolTensor"
,
"(optional) Tol tensor, shape is same as X batch."
)
AddInput
(
"TolTensor"
,
"(optional) Tol tensor, shape is same as X batch or can broadcast "
"with X batch."
)
.
AsDispensable
();
AddOutput
(
"Out"
,
"(Tensor), The output tensor of matrix_rank op."
);
AddAttr
<
float
>
(
"tol"
,
"(float, optional). tol"
).
SetDefault
(
0.0
f
);
...
...
python/paddle/fluid/tests/unittests/test_matrix_rank_op.py
浏览文件 @
28fffef6
...
...
@@ -36,8 +36,8 @@ class TestMatrixRankOP(OpTest):
self
.
init_data
()
self
.
inputs
=
{
'X'
:
self
.
x
}
self
.
attrs
=
{
'hermitian'
:
self
.
hermitian
}
if
self
.
tol
T
ensor
is
not
None
:
self
.
inputs
[
"TolTensor"
]
=
self
.
tol
T
ensor
if
self
.
tol
_t
ensor
is
not
None
:
self
.
inputs
[
"TolTensor"
]
=
self
.
tol
_t
ensor
if
self
.
tol
is
not
None
:
self
.
attrs
[
"tol"
]
=
self
.
tol
self
.
attrs
[
"use_default_tol"
]
=
self
.
use_default_tol
...
...
@@ -48,7 +48,7 @@ class TestMatrixRankOP(OpTest):
def
init_data
(
self
):
self
.
x
=
np
.
eye
(
3
,
dtype
=
np
.
float32
)
self
.
tol
T
ensor
=
None
self
.
tol
_t
ensor
=
None
self
.
tol
=
0.1
self
.
use_default_tol
=
False
self
.
hermitian
=
True
...
...
@@ -58,51 +58,56 @@ class TestMatrixRankOP(OpTest):
class
TestMatrixRankOP1
(
TestMatrixRankOP
):
def
init_data
(
self
):
self
.
x
=
np
.
eye
(
3
,
k
=
1
,
dtype
=
np
.
float64
)
self
.
tol
T
ensor
=
None
self
.
tol
_t
ensor
=
None
self
.
tol
=
None
self
.
use_default_tol
=
True
self
.
hermitian
=
False
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tolTensor
,
self
.
hermitian
)
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tol_tensor
,
self
.
hermitian
)
class
TestMatrixRankOP2
(
TestMatrixRankOP
):
def
init_data
(
self
):
self
.
x
=
np
.
random
.
rand
(
3
,
4
,
5
,
6
).
astype
(
np
.
float32
)
self
.
tol
T
ensor
=
np
.
random
.
random
([
3
,
4
]).
astype
(
self
.
x
.
dtype
)
self
.
tol
_t
ensor
=
np
.
random
.
random
([
3
,
4
]).
astype
(
self
.
x
.
dtype
)
self
.
tol
=
None
self
.
use_default_tol
=
False
self
.
hermitian
=
False
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tolTensor
,
self
.
hermitian
)
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tol_tensor
,
self
.
hermitian
)
class
TestMatrixRankOP3
(
TestMatrixRankOP
):
def
init_data
(
self
):
self
.
x
=
np
.
eye
(
200
,
dtype
=
np
.
float64
)
self
.
tol
T
ensor
=
None
self
.
tol
_t
ensor
=
None
self
.
tol
=
None
self
.
use_default_tol
=
True
self
.
hermitian
=
True
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tolTensor
,
self
.
hermitian
)
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tol_tensor
,
self
.
hermitian
)
class
TestMatrixRankOP4
(
TestMatrixRankOP
):
def
init_data
(
self
):
self
.
x
=
np
.
random
.
rand
(
1
,
10
).
astype
(
np
.
float32
)
self
.
tol
T
ensor
=
None
self
.
tol
_t
ensor
=
None
self
.
tol
=
None
self
.
use_default_tol
=
True
self
.
hermitian
=
False
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tolTensor
,
self
.
hermitian
)
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tol_tensor
,
self
.
hermitian
)
class
TestMatrixRankOP5
(
TestMatrixRankOP
):
def
init_data
(
self
):
self
.
x
=
np
.
random
.
rand
(
5
,
1
).
astype
(
np
.
float64
)
self
.
tol
T
ensor
=
np
.
random
.
random
([
1
,
4
]).
astype
(
self
.
x
.
dtype
)
self
.
tol
_t
ensor
=
np
.
random
.
random
([
1
,
4
]).
astype
(
self
.
x
.
dtype
)
self
.
tol
=
None
self
.
use_default_tol
=
False
self
.
hermitian
=
False
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tolTensor
,
self
.
hermitian
)
self
.
out
=
np
.
linalg
.
matrix_rank
(
self
.
x
,
self
.
tol_tensor
,
self
.
hermitian
)
class
TestMatrixRankAPI
(
unittest
.
TestCase
):
...
...
python/paddle/tensor/linalg.py
浏览文件 @
28fffef6
...
...
@@ -1106,20 +1106,18 @@ def matrix_rank(x, tol=None, hermitian=False, name=None):
r
"""
Computes the rank of a matrix.
The rank of a matrix is the number of singular values that are greater than the specified
tol threshold when hermitian=False,
or the number of eigenvalues in absolute value that are greater than the specified
tol
threshold when hermitian=True.
The rank of a matrix is the number of singular values that are greater than the specified
`tol` threshold when hermitian=False,
or the number of eigenvalues in absolute value that are greater than the specified
`tol`
threshold when hermitian=True.
Args:
x (Tensor): The input tensor.
Its shape should be [..., m, n], where ... is zero or more batch dimensions. If x is a batch of matrices then the output
has the same batch dimensions. The data type of x should be float32 or float64.
tol (float,Tensor,optional): the tolerance value. Default: None.
If tol is not specified, and sigma is the largest singular value (or eigenvalue in absolute value), and eps is the
epsilon value for the dtype of x, then tol is computed with formula tol=sigma * max(m,n) * eps. Note that if x is
a batch of matrices, tol is computed this way for every batch.
hermitian (bool,optional): indicates whether x is Hermitian. Default: False.
When hermitian=True, x is assumed to be Hermitian, but x is not checked inside the function. Instead, We just use the
lower triangular of the matrix to compute.
x (Tensor): The input tensor. Its shape should be `[..., m, n]`, where `...` is zero or more batch dimensions. If `x` is a batch
of matrices then the output has the same batch dimensions. The data type of `x` should be float32 or float64.
tol (float,Tensor,optional): the tolerance value. Default: None. If `tol` is not specified, and `sigma` is the largest
singular value (or eigenvalues in absolute value), and `eps` is the epsilon value for the dtype of `x`, then `tol` is computed
with formula `tol=sigma * max(m,n) * eps`. Note that if `x` is a batch of matrices, `tol` is computed this way for every batch.
hermitian (bool,optional): indicates whether `x` is Hermitian. Default: False. When hermitian=True, `x` is assumed to be Hermitian,
enabling a more efficient method for finding eigenvalues, but `x` is not checked inside the function. Instead, We just use
the lower triangular of the matrix to compute.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
...
...
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