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curl -fsSL https://code-server.dev/install.sh | sh |
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#ifndef LIBTORCH_CIFAR10_H | |
#define LIBTORCH_CIFAR10_H | |
#include<torch/torch.h> | |
namespace { | |
constexpr uint32_t kTrainSize = 50000; | |
constexpr uint32_t kTestSize = 10000; | |
const std::vector<std::string> kTrainImagesFilename = { "data_batch_1.bin","data_batch_2.bin","data_batch_3.bin","data_batch_4.bin","data_batch_5.bin" }; | |
const std::vector<std::string> kTestImagesFilename = {"test_batch.bin"}; | |
constexpr uint32_t kImageRows = 32; | |
constexpr uint32_t kImageColumns = 32; |
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/* | |
* ts3psr.h | |
* We wish you a merry DL training | |
* | |
* Created by kimbomm on 2019. 2. 27... | |
* Copyright 2019 VIRNECT. All rights reserved. | |
* | |
*/ | |
#if !defined(WE_WISH_YOU_A_MERRY_DL_TRAINING_7E3_2_1B_TS3PSR_H_INCLUDED) |
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#pragma once | |
#include<Windows.h> | |
LRESULT CALLBACK WndProc(HWND, UINT, WPARAM, LPARAM); | |
__declspec(selectany) float* __host_block; | |
__declspec(selectany) size_t __host_block_size; | |
void CudaMemBlockShow(float* device_block, size_t size) { | |
__host_block = (float*)malloc(size*sizeof(float)); | |
__host_block_size = size; | |
cudaMemcpy(__host_block, device_block, size*sizeof(float), cudaMemcpyDeviceToHost); | |
static TCHAR* title = TEXT("CudaMemoryBlock"); |
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# Project | |
* text eol=crlf | |
# Language Diffs | |
*.cs diff=csharp | |
*.css diff=css |
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. |
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. |
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#include<iostream> | |
#include<opencv2/opencv.hpp> | |
std::vector<std::string> GetTrainFiles(std::string filename) { | |
std::vector<std::string> ret; | |
std::fstream fin(filename, std::ios::in); | |
if (fin.is_open() == false) { | |
std::cout << "Incorrect file path" << std::endl; | |
exit(1); | |
} | |
while (fin.eof() == false) { |
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#if defined(_MSC_VER) | |
const char* compiler = "msvc"; | |
#elif defined(__GNUC__) | |
const char* compiler = "gcc"; | |
#elif defined(__clang__) | |
const char* compiler = "clang"; | |
#endif | |
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