Initial commit

Author: prabhuomkar

.gitignore

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+# Prerequisites
+*.d
+
+# Compiled Object files
+*.slo
+*.lo
+*.o
+*.obj
+
+# Precompiled Headers
+*.gch
+*.pch
+
+# Compiled Dynamic libraries
+*.so
+*.dylib
+*.dll
+
+# Fortran module files
+*.mod
+*.smod
+
+# Compiled Static libraries
+*.lai
+*.la
+*.a
+*.lib
+
+# Executables
+*.exe
+*.out
+*.app
+
+# PyTorch
+libtorch/
+build/
+
+# Other
+.DS_Store
+.idea/

CMakeLists.txt

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+cmake_minimum_required(VERSION 3.0 FATAL_ERROR)
+project(pytorch-cpp)
+
+
+find_package(Torch REQUIRED)
+
+add_executable(pytorch-cpp main.cpp)
+target_link_libraries(pytorch-cpp "${TORCH_LIBRARIES}")
+
+add_executable(pytorch_basics tutorials/basics/pytorch_basics/main.cpp)
+target_link_libraries(pytorch_basics "${TORCH_LIBRARIES}")
+add_executable(linear_regression tutorials/basics/linear_regression/main.cpp)
+target_link_libraries(linear_regression "${TORCH_LIBRARIES}")
+add_executable(logistic_regression tutorials/basics/logistic_regression/main.cpp)
+target_link_libraries(logistic_regression "${TORCH_LIBRARIES}")
+add_executable(feedforward_neural_network tutorials/basics/feedforward_neural_network/main.cpp)
+target_link_libraries(feedforward_neural_network "${TORCH_LIBRARIES}")
+
+set_property(TARGET pytorch-cpp PROPERTY CXX_STANDARD 11)

LICENSE

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+MIT License
+
+Copyright (c) 2019 Omkar Prabhu
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+<p align="center"><img width="50%" src="images/pytorch_log.svg" /></p>
+
+--------------------------------------------------------------------------------
+
+This repository provides tutorial code in C++ for deep learning researchers to learn PyTorch.
+
+## How to Build
+- Install
+```
+wget https://download.pytorch.org/libtorch/nightly/cpu/libtorch-shared-with-deps-latest.zip
+unzip libtorch-shared-with-deps-latest.zip
+```
+- Build
+```
+mkdir build
+cd build
+cmake -DCMAKE_PREFIX_PATH=/absolute/path/to/libtorch ..
+make
+```
+
+## Table of Contents
+
+#### 1. Basics
+* [PyTorch Basics](https://github.com/prabhuomkar/pytorch-cpp/tree/master/tutorials/basics/pytorch_basics.cpp)
+* [Linear Regression](https://github.com/prabhuomkar/pytorch-cpp/tree/master/tutorials/basics/linear_regression.cpp)
+* [Logistic Regression](https://github.com/prabhuomkar/pytorch-cpp/tree/master/tutorials/basics/logistic_regression.cpp)
+* [Feedforward Neural Network](https://github.com/prabhuomkar/pytorch-cpp/tree/master/tutorials/basics/feedforward_neural_network.cpp)

images/pytorch_logo.svg

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+#include <torch/torch.h>
+#include <iostream>
+
+int main() {
+  std::cout << "Welcome to PyTorch Tutorial in C++ for Deep Learning Researchers" << std::endl;
+}

main.cpp

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+#include <torch/torch.h>
+#include <iostream>
+
+int main() {
+  std::cout << "FeedForward Neural Network" << std::endl;
+}

tutorials/basics/feedforward_neural_network/main.cpp

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+#include <torch/torch.h>
+#include <iostream>
+
+int main() {
+  std::cout << "Linear Regression" << std::endl;
+}

tutorials/basics/linear_regression/main.cpp

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+#include <torch/torch.h>
+#include <iostream>
+
+int main() {
+  std::cout << "Logistic Regression" << std::endl;
+}

tutorials/basics/logistic_regression/main.cpp

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+#include <torch/torch.h>
+#include <iostream>
+
+int main() {
+  std::cout << "PyTorch Basics" << std::endl;
+}