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NiuTrans.Tensor
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NiuTrans
NiuTrans.Tensor
Commits
12036ec0
Commit
12036ec0
authored
Jul 04, 2018
by
xiaotong
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select a range of data in a tensor
parent
cdbe99d8
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source/core/Select.cpp
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source/core/Select.cpp
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12036ec0
/* NiuTrans.Tensor - an open-source tensor library
* Copyright (C) 2018, Natural Language Processing Lab, Northestern University.
* All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*
* $Created by: XIAO Tong (email: xiaotong@mail.neu.edu.cn) 2018-07-04
*/
#include "Select.h"
#include "../XUtility.h"
namespace
nts
{
// namespace nts(NiuTrans.Tensor)
/*
generate a tensor with seleccted data in range[low,high] along the given dimension
c = select(a)
>> a - input tensor
>> dim - the dimension along with which we do the job
>> low - lower bound
>> high - higher bound.
Note that range [1,3] means that we select 1 and 2.
>> c - result tensor
*/
void
SelectRange
(
XTensor
*
a
,
int
dim
,
int
low
,
int
high
,
XTensor
*
c
)
{
CheckNTErrors
(
a
!=
NULL
&&
c
!=
NULL
,
"empty tensors!"
);
CheckNTErrors
(
a
->
order
==
c
->
order
,
"The input and output tensors must in the same order!"
);
CheckNTErrors
(
dim
>=
0
&&
dim
<
a
->
order
,
"The input dimension is out of bounds!"
);
CheckNTErrors
(
a
->
dataType
==
c
->
dataType
,
"The tensor must be of the same data type!"
);
if
(
low
>=
high
)
return
;
for
(
int
i
=
0
;
i
<
a
->
order
;
i
++
){
if
(
i
==
dim
){
CheckNTErrors
(
low
>
0
&&
low
<
a
->
dimSize
[
dim
],
"Illegal range specified!"
);
CheckNTErrors
(
high
>
0
&&
high
<
a
->
dimSize
[
dim
],
"Illegal range specified!"
);
}
else
{
CheckNTErrors
(
a
->
dimSize
[
i
]
==
c
->
dimSize
[
i
],
"The size of the dimensions should be same!"
);
}
}
int
stride
=
1
;
for
(
int
i
=
0
;
i
<
a
->
order
;
i
++
)
stride
*=
a
->
dimSizeRDI
[
i
];
int
blockSize
=
stride
*
(
high
-
low
)
*
a
->
unitSize
;
int
stepSizeS
=
stride
*
a
->
dimSize
[
dim
]
*
a
->
unitSize
;
int
stepSizeT
=
stride
*
c
->
dimSize
[
dim
]
*
a
->
unitSize
;
char
*
s
=
(
char
*
)
a
->
data
+
stride
*
low
*
a
->
unitSize
;
char
*
t
=
(
char
*
)
c
->
data
;
for
(
int
i
=
0
;
i
<
high
-
low
;
i
++
){
XMemCopy
(
t
,
c
->
devID
,
s
,
a
->
devID
,
blockSize
);
s
+=
stepSizeS
;
t
+=
stepSizeT
;
}
}
}
// namespace nts(NiuTrans.Tensor)
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