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Anthony Barbier6ff3b192017-09-04 18:44:23 +01001/*
2 * Copyright (c) 2016, 2017 ARM Limited.
3 *
4 * SPDX-License-Identifier: MIT
5 *
6 * Permission is hereby granted, free of charge, to any person obtaining a copy
7 * of this software and associated documentation files (the "Software"), to
8 * deal in the Software without restriction, including without limitation the
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10 * sell copies of the Software, and to permit persons to whom the Software is
11 * furnished to do so, subject to the following conditions:
12 *
13 * The above copyright notice and this permission notice shall be included in all
14 * copies or substantial portions of the Software.
15 *
16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22 * SOFTWARE.
23 */
24#ifndef __ARM_COMPUTE_NEGEMMTRANSPOSE1xWKERNEL_H__
25#define __ARM_COMPUTE_NEGEMMTRANSPOSE1xWKERNEL_H__
26
27#include "arm_compute/core/NEON/INESimpleKernel.h"
28
29namespace arm_compute
30{
31class ITensor;
32
33/** NEON kernel which transposes the elements of a matrix in chunks of 1xW, where W is equal to (16 / element size of the tensor)
34 *
35 * Following an example of how the transposition1xW works when the input data is F32
36 *
37 * @f[
38 * \left( \begin{array}{cccc}
39 * a00 & a01 & a02 & a03 \\
40 * a10 & a11 & a12 & a13 \\
41 * a20 & a21 & a22 & a23 \\
42 * a30 & a31 & a32 & a33 \\
43 * \end{array} \right)
44 * \rightarrow
45 * \left( \begin{array}{ccccccccccccccccc}
46 * a00 & a01 & a02 & a03 & a10 & a11 & a12 & a13 & a20 & a21 & a22 & a23 & a30 & a31 & a32 & a33 \\
47 * \end{array} \right)
48 * @f]
49 *
50 * Following an example of how the transposition1xW works when the input data type is F16
51 *
52 * @f[
53 * \left( \begin{array}{cccccccc}
54 * a00 & a01 & a02 & a03 & a04 & a05 & a06 & a7 \\
55 * a10 & a11 & a12 & a13 & a14 & a15 & a16 & 17 \\
56 * a20 & a21 & a22 & a23 & a24 & a25 & a26 & 27 \\
57 * a30 & a31 & a32 & a33 & a34 & a35 & a36 & 37 \\
58 * \end{array} \right)
59 * \rightarrow
60 * \left( \begin{array}{cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc}
61 * a00 & a01 & a02 & a03 & a04 & a05 & a06 & a07 & a10 & a11 & a12 & a13 & a14 & a15 & a16 & a17 & a20 & a21 & a22 & a23 & a24 & a25 & a26 & a27 & a30 & a31 & a32 & a33 & a34 & a35 & a36 & a37\\
62 * \end{array} \right)
63 * @f]
64 *
65 * @note The output matrix will have the following shape: [ height * W, ceil(width / W) ], where W = (16 / element size of the tensor)
66 *
67 */
68class NEGEMMTranspose1xWKernel : public INESimpleKernel
69{
70public:
71 /** Initialise the kernel's input and output.
72 *
Gian Marco Iodicebdb6b0b2017-06-30 12:21:00 +010073 * @param[in] input Input tensor. Data types supported: U8/S8/QS8/U16/S16/QS16/F16/U32/S32/F32
Anthony Barbier6ff3b192017-09-04 18:44:23 +010074 * @param[out] output Output tensor. Data type supported: same as @p input.
75 */
76 void configure(const ITensor *input, ITensor *output);
77
78 // Inherited methods overridden:
Moritz Pflanzerc186b572017-09-07 09:48:04 +010079 void run(const Window &window, const ThreadInfo &info) override;
Anthony Barbier6ff3b192017-09-04 18:44:23 +010080};
81}
82#endif /*__ARM_COMPUTE_NEGEMMTRANSPOSE1xWKERNEL_H__ */