tiny_dnn
1.0.0
A header only, dependency-free deep learning framework in C++11
tiny_dnn
core
kernels
nnp_deconv2d_kernel.h
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/*
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Copyright (c) 2016, Taiga Nomi, Edgar Riba
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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* Neither the name of the <organization> nor the
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names of its contributors may be used to endorse or promote products
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derived from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY
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EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
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DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#pragma once
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#include "tiny_dnn/core/params/deconv_params.h"
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#ifdef CNN_USE_NNPACK
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#include "nnpack.h"
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namespace
tiny_dnn {
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namespace
core {
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namespace
kernels {
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inline
void
nnp_deconv2d_kernel(
const
conv_params& params,
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const
std::vector<const vec_t*>& in,
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const
vec_t& W,
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const
vec_t& bias,
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tensor_t& a) {
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}
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}
// namespace kernels
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}
// namespace core
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}
// namespace tiny_dnn
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#endif
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