tiny_dnn  1.0.0
A header only, dependency-free deep learning framework in C++11
avx_deconv2d_kernel.h
1 /*
2  Copyright (c) 2016, Taiga Nomi, Edgar Riba
3  All rights reserved.
4 
5  Redistribution and use in source and binary forms, with or without
6  modification, are permitted provided that the following conditions are met:
7  * Redistributions of source code must retain the above copyright
8  notice, this list of conditions and the following disclaimer.
9  * Redistributions in binary form must reproduce the above copyright
10  notice, this list of conditions and the following disclaimer in the
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12  * Neither the name of the <organization> nor the
13  names of its contributors may be used to endorse or promote products
14  derived from this software without specific prior written permission.
15 
16  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY
17  EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
18  WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
19  DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
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26 */
27 #pragma once
28 
29 #include "tiny_dnn/core/params/deconv_params.h"
30 #include "tiny_dnn/core/kernels/tiny_deconv2d_kernel.h"
31 
32 namespace tiny_dnn {
33 namespace core {
34 namespace kernels {
35 
36 inline void avx_deconv2d_kernel(const deconv_params& params,
37  const tensor_t& in,
38  const vec_t& W,
39  const vec_t& bias,
40  tensor_t& a,
41  const bool layer_parallelize) {
42  // fallback to non-avx version
43  tiny_deconv2d_kernel(params, in, W, bias, a, layer_parallelize);
44 }
45 
46 } // namespace kernels
47 } // namespace core
48 } // namespace tiny_dnn