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82 lines (65 loc) · 3.01 KB
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/*
This file is part of Leela Zero.
Copyright (C) 2018-2019 Junhee Yoo and contributors
Leela Zero is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Leela Zero is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with Leela Zero. If not, see <http://www.gnu.org/licenses/>.
Additional permission under GNU GPL version 3 section 7
If you modify this Program, or any covered work, by linking or
combining it with NVIDIA Corporation's libraries from the
NVIDIA CUDA Toolkit and/or the NVIDIA CUDA Deep Neural
Network library and/or the NVIDIA TensorRT inference library
(or a modified version of those libraries), containing parts covered
by the terms of the respective license agreement, the licensors of
this Program grant you additional permission to convey the resulting
work.
*/
#ifndef CPUPIPE_H_INCLUDED
#define CPUPIPE_H_INCLUDED
#include "config.h"
#include <vector>
#include <cassert>
#include "ForwardPipe.h"
class CPUPipe : public ForwardPipe {
public:
virtual void initialize(const int channels);
virtual void forward(const std::vector<float>& input,
std::vector<float>& output_pol,
std::vector<float>& output_val);
virtual void push_weights(unsigned int filter_size,
unsigned int channels,
unsigned int outputs,
std::shared_ptr<const ForwardPipeWeights> weights);
private:
void winograd_transform_in(const std::vector<float>& in,
std::vector<float>& V,
const int C);
void winograd_sgemm(const std::vector<float>& U,
const std::vector<float>& V,
std::vector<float>& M,
const int C, const int K);
void winograd_transform_out(const std::vector<float>& M,
std::vector<float>& Y,
const int K);
void winograd_convolve3(const int outputs,
const std::vector<float>& input,
const std::vector<float>& U,
std::vector<float>& V,
std::vector<float>& M,
std::vector<float>& output);
int m_input_channels;
// Input + residual block tower
std::shared_ptr<const ForwardPipeWeights> m_weights;
std::vector<float> m_conv_pol_w;
std::vector<float> m_conv_val_w;
std::vector<float> m_conv_pol_b;
std::vector<float> m_conv_val_b;
};
#endif