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Merge pull request #19 from fszewczyk/image
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Image class
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fszewczyk authored Nov 10, 2023
2 parents ef545a1 + fc8c0ec commit 98e7f86
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Showing 15 changed files with 8,615 additions and 8 deletions.
2 changes: 1 addition & 1 deletion .github/workflows/linux.yml
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Expand Up @@ -32,5 +32,5 @@ jobs:
run: |
g++ examples/scalars.cpp -O3 --std=c++17
./a.out
g++ examples/xor_regression.cpp -O3 --std=c++17
g++ examples/xor.cpp -O3 --std=c++17
./a.out
2 changes: 1 addition & 1 deletion .github/workflows/macos.yml
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Expand Up @@ -32,5 +32,5 @@ jobs:
run: |
g++ examples/scalars.cpp -O3 --std=c++17
./a.out
g++ examples/xor_regression.cpp -O3 --std=c++17
g++ examples/xor.cpp -O3 --std=c++17
./a.out
2 changes: 1 addition & 1 deletion .github/workflows/windows.yml
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Expand Up @@ -30,4 +30,4 @@ jobs:
CXX: ${{matrix.conf.compiler}}
run: |
g++ -o out examples/scalars.cpp -O3 --std=c++17
g++ -o out examples/xor_regression.cpp -O3 --std=c++17
g++ -o out examples/xor.cpp -O3 --std=c++17
1 change: 1 addition & 0 deletions .gitignore
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@@ -1,4 +1,5 @@
build/
datasets/

docs/html
docs/latex
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2 changes: 1 addition & 1 deletion docs/tutorials/GetStarted.md
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Expand Up @@ -233,7 +233,7 @@ for (size_t sample = 0; sample < xs.size(); ++sample) { // Go through ea
}
```

In case you got lost along the way, check out the `examples/xor_regression.cpp` file. It contains the exact same code and is ready to run :)
In case you got lost along the way, check out the `examples/xor.cpp` file. It contains the exact same code and is ready to run :)

### Results

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2 changes: 1 addition & 1 deletion examples/README.md
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Expand Up @@ -3,7 +3,7 @@
To compile an example, simply run the following command:

```
g++ --std=c++17 xor_nn.cpp
g++ --std=c++17 xor.cpp
```

Remember to replace the file name with the appropriate name :)
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79 changes: 79 additions & 0 deletions examples/mnist.cpp
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@@ -0,0 +1,79 @@
#include <filesystem>
#include <iostream>

#include "../include/ShkyeraGrad.hpp"

namespace fs = std::filesystem;
using namespace shkyera;

Dataset<Vec32, Vec32> load(std::string directory) {
Dataset<Vec32, Vec32> dataset;

std::cerr << "Loading [" << std::flush;
for (size_t digit = 0; digit < 10; ++digit) {
std::cerr << "" << std::flush;
int added = 0;
for (const auto &entry : fs::directory_iterator(directory + std::to_string(digit))) {
Image image(entry.path().string());
auto target = Vec32::oneHotEncode(digit, 10);

dataset.addSample(image.flatten<Type::float32>() / 255.0f, target);
}
}
std::cerr << "]" << std::endl;

return dataset;
}

int main() {
Dataset<Vec32, Vec32> trainData = load("datasets/mnist/train/");
std::cerr << "Loaded training data." << std::endl;

DataLoader trainLoader(trainData, 16, true);

// clang-format off
auto mlp = SequentialBuilder32::begin()
.add(Linear32::create(784, 100))
.add(ReLU32::create())
.add(Linear32::create(100, 50))
.add(Sigmoid32::create())
.add(Linear32::create(50, 10))
.add(Softmax32::create())
.build();
// clang-format on

auto optimizer = Adam32(mlp->parameters(), 0.01, 0.99);
auto lossFunction = Loss::CrossEntropy<Type::float32>;

for (size_t epoch = 0; epoch < 50; epoch++) {
float epochLoss = 0;
double epochAccuracy = 0;

for (const auto [x, y] : trainLoader) {
optimizer.reset();

auto pred = mlp->forward(x);

double accuracy = 0;
for (size_t i = 0; i < pred.size(); ++i) {
size_t predictedDigit = pred[i].argMax();
size_t trueDigit = y[i].argMax();

if (predictedDigit == trueDigit)
accuracy += 1;
}

accuracy /= pred.size();
epochAccuracy += accuracy;

auto loss = Loss::compute(lossFunction, pred, y);
epochLoss = epochLoss + loss->getValue();

optimizer.step();

std::cerr << "Loss: " << loss->getValue() << " Accuracy: " << accuracy << std::endl;
}
std::cerr << "Epoch: " << epoch + 1 << " Loss: " << epochLoss / trainLoader.getTotalBatches()
<< " Accuracy: " << epochAccuracy / trainLoader.getTotalBatches() << std::endl;
}
}
File renamed without changes.
1 change: 1 addition & 0 deletions include/ShkyeraGrad.hpp
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Expand Up @@ -7,6 +7,7 @@

#pragma once

#include "core/Image.hpp"
#include "core/Type.hpp"
#include "core/Utils.hpp"
#include "core/Value.hpp"
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61 changes: 61 additions & 0 deletions include/core/Image.hpp
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@@ -0,0 +1,61 @@
/**
* Copyright © 2023 Franciszek Szewczyk. None of the rights reserved.
* This code is released under the Beerware License. If you find this code useful or you appreciate the work, you are
* encouraged to buy the author a beer in return.
* Contact the author at [email protected] for inquiries and support.
*/

#pragma once

#include <string>
#include <vector>

#define STB_IMAGE_IMPLEMENTATION
#include "../external/stb_image.h"

#include "Vector.hpp"

namespace shkyera {

class Image {
private:
std::vector<uint8_t> _data;

public:
Image() = default;
Image(std::string filename, bool grayscale = true);

template <typename T> Vector<T> flatten(size_t takeEvery = 1) const;
};

Image::Image(std::string filename, bool grayscale) {
int width, height, channels;
uint8_t *imageData = nullptr;

if (grayscale)
imageData = stbi_load(filename.c_str(), &width, &height, &channels, 1);
else
imageData = stbi_load(filename.c_str(), &width, &height, &channels, 3);

if (!imageData) {
std::cerr << "Error loading image: " << filename << std::endl;
return;
}

if (grayscale)
_data.assign(imageData, imageData + (width * height));
else
_data.assign(imageData, imageData + (width * height * 3));

stbi_image_free(imageData);
}

template <typename T> Vector<T> Image::flatten(size_t takeEvery) const {
std::vector<T> converted;
converted.reserve(_data.size());
for (size_t i = 0; i < _data.size(); i += takeEvery)
converted.push_back(static_cast<T>(_data[i]));
return Vector<T>::of(converted);
}

} // namespace shkyera
5 changes: 5 additions & 0 deletions include/core/Value.hpp
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Expand Up @@ -238,6 +238,11 @@ template <typename T> void Value<T>::backward() {
for (auto val = sorted.rbegin(); val != sorted.rend(); val++) {
(*val)->_backward();
}

for (auto s : sorted) {
s->_children = {};
s->_backward = []() {};
}
}

template <typename T> std::ostream &operator<<(std::ostream &os, const ValuePtr<T> &value) {
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28 changes: 28 additions & 0 deletions include/core/Vector.hpp
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Expand Up @@ -8,6 +8,7 @@
#pragma once

#include <exception>
#include <numeric>

#include "Type.hpp"
#include "Value.hpp"
Expand All @@ -30,10 +31,12 @@ template <typename T> class Vector {

static Vector<T> of(const std::vector<T> &values);
template <typename... Args> static Vector<T> of(const Args &...args);
static Vector<T> oneHotEncode(size_t index, size_t size);

ValuePtr<T> dot(const Vector<T> &other) const;
ValuePtr<T> sum() const;
size_t size() const;
size_t argMax() const;

template <typename U> friend std::ostream &operator<<(std::ostream &os, const Vector<U> &vector);

Expand Down Expand Up @@ -85,8 +88,33 @@ template <typename T> template <typename... Args> Vector<T> Vector<T>::of(const
return Vector<T>(valuePtrs);
}

template <typename T> Vector<T> Vector<T>::oneHotEncode(size_t index, size_t size) {
std::vector<ValuePtr<T>> valuePtrs(size);

for (size_t i = 0; i < size; ++i) {
if (i == index)
valuePtrs[i] = Value<T>::create(1);
else
valuePtrs[i] = Value<T>::create(0);
}

return valuePtrs;
}

template <typename T> size_t Vector<T>::size() const { return _values.size(); }

template <typename T> size_t Vector<T>::argMax() const {
T largest = std::numeric_limits<T>::lowest();
size_t largestIndex = 0;
for (size_t i = 0; i < _values.size(); ++i) {
if (_values[i]->getValue() > largest) {
largest = _values[i]->getValue();
largestIndex = i;
}
}
return largestIndex;
}

template <typename T> ValuePtr<T> Vector<T>::dot(const Vector<T> &other) const {
if (other.size() != size()) {
throw std::invalid_argument("Vectors need to be of the same size to compute the dot product. Sizes are " +
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