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https://github.com/shivendrra/micrograd.c
kaprathy's micrograd implemented in c & cpp
https://github.com/shivendrra/micrograd.c
Last synced: 20 days ago
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kaprathy's micrograd implemented in c & cpp
- Host: GitHub
- URL: https://github.com/shivendrra/micrograd.c
- Owner: shivendrra
- Created: 2024-08-07T14:06:15.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-08-12T14:40:14.000Z (3 months ago)
- Last Synced: 2024-08-12T16:30:23.965Z (3 months ago)
- Language: C
- Homepage:
- Size: 16.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Micrograd-C
**Micrograd-C** is a simple automatic differentiation library implemented in C, basically a 'C' version of Karpathy's [Micrograd](https://github.com/karpathy/micrograd). It provides a basic framework for creating and manipulating scalar values with gradient support, allowing for backpropagation through a computation graph.
## Features
- **Automatic Differentiation**: Compute gradients for scalar operations using backpropagation.
- **Scalar Operations**: Supports addition, multiplication, power, ReLU, sigmoid, and tanh functions.
- **Backward Pass**: Propagate gradients through a computation graph.
## Getting Started
To get started with Micrograd-C, clone this repository and compile the provided code.
### Prerequisites
- A C compiler (e.g., `gcc`)
- A C++ compiler (e.g. `g++`)
### Building the Project
1. Clone the repository:
```bash
git clone https://github.com/shivendrra/micrograd.c.git
cd micrograd-c
```
2. Compile the code:
- For c version
```bash
gcc csrc/scalar.c test.c -o test -lm
```
- For cpp version
```bash
g++ cppsrc/value.cpp cppsrc/module.cpp main.cpp -o main -lm
```
### Running the Example
After compiling, run the example:
- For c version
```bash
./test
```
- For cpp version
```bash
./main
```
### Example Output
Here is an example of what you can expect when running the program:
```
Scalar[data=(2), grad=0.0074]
Scalar[data=(3), grad=0.0049]
Scalar[data=(5), grad=0]
Scalar[data=(6), grad=0.0025]
Scalar[data=(6), grad=0]
Scalar[data=(1), grad=0]
Scalar[data=(0.9975), grad=1]
```
## Code Overview
### `scalar.h` / `value.h`
Header file defining the `Scalar` structure and function prototypes for scalar operations and backward propagation.
### `scalar.c` / `value.cpp`
C file containing all the necessary functions for `Scalar` value structure for ops & backprop.
### `nn.h` / `module.h`
Header file defining the `Neuron`, `Layer`, & `MLP` structures & function prototypes for creating a small MLP.
### `nn.c` / `module.cpp`
C file containing all the basic functions for building & implementing MLP in C using `Scalar` values.
### `test.c` / `cppsrc/main.cpp`
Demonstrates the usage of the Micrograd-C library by creating scalar values, performing operations, and computing gradients.
### Functions
- `initialize_scalars`: Initializes a scalar value with a given data value and its children.
- `add_val`, `mul_val`, `pow_val`, `relu`, `sigmoid`, `tan_h`, `sub_val`: Functions for scalar operations.
- `backward`: Computes gradients for all scalar values in the computation graph.
- `print`: Prints the scalar data and gradient values.
## Contributing
Feel free to contribute by submitting issues or pull requests. Your contributions are welcome!
## License
None!