https://github.com/goktug97/minigrad
Autograd Engine for Python Written in Python C-API for Speed
https://github.com/goktug97/minigrad
autograd neural-network python python-c-api
Last synced: about 1 year ago
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Autograd Engine for Python Written in Python C-API for Speed
- Host: GitHub
- URL: https://github.com/goktug97/minigrad
- Owner: goktug97
- License: mit
- Created: 2020-04-20T14:24:24.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2023-05-06T10:56:54.000Z (about 3 years ago)
- Last Synced: 2025-04-19T17:18:54.131Z (about 1 year ago)
- Topics: autograd, neural-network, python, python-c-api
- Language: C
- Homepage:
- Size: 51.8 KB
- Stars: 20
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
Minigrad
==========
An autograd engine inspired by Karpathy's
[micrograd](https://github.com/karpathy/micrograd) library. It is a
Drop-In Replacement but it requires you to cast Python numerical types
to the Value type.
It is called minigrad because it is a little bit bigger and more complex in terms of readability than micrograd. Engine is implemented in Python C API so it runs faster.
Currently, minigrad.nn and micrograd.nn are the same.
## Installation
``` bash
pip install minigrad
```
## Example usage
``` python
a = Value(-4.0)
b = Value(2.0)
c = a + b
d = a * b + b**3.0 # The power exponent must be Python double not Value.
c += c + Value(1.0)
c += Value(1.0) + c + -a
d += d * Value(2.0) + (b + a).relu()
d += Value(3.0) * d + (b - a).relu()
e = c - d
f = e**2.0
g = f / Value(2.0)
g += Value(10.0) / f
print(f'{g.data:.4f}') # prints 24.7041, the outcome of this forward pass
g.backward()
print(f'{a.grad:.4f}') # prints 138.8338, i.e. the numerical value of dg/da
print(f'{b.grad:.4f}') # prints 645.5773, i.e. the numerical value of dg/db
```
## Training a neural net
Refer to
[demo.ipynb](https://github.com/goktug97/minigrad/tree/master/examples/demo.ipynb)
example. It differs from the original implementation in terms of types
as the library only allows Value to Value operations. For example
`Value(2.0) * 2.0` is not allowed, so it should be `Value(2.0) * Value(2.0)`.
## Running tests
Should be run under test directory because It will try to import local
minigrad and fail because of the C extension. Also it requires PyTorch.
``` bash
cd test
python -m pytest
```
## License
Minigrad is licensed under the MIT License.