hobbitgrad
hobbitgrad is a tiny educational autograd library written in pure Python. It includes a small NDArray, a Tensor type with backpropagation, a linear layer, SGD, and mean squared error loss.
Install
pip install hobbitgrad
Example
from hobbitgrad import Linear, SGD, Tensor, mse
x = Tensor([[0, 0], [0, 1], [1, 0], [1, 1]])
y = Tensor([[0], [0], [0], [1]])
model = Linear(2, 1)
optimizer = SGD(model.parameters(), lr=0.1)
for _ in range(100):
pred = model.forward(x)
loss = mse(pred, y)
loss.backward()
optimizer.step()
optimizer.zero_grad()
print(loss.data.data[0])
Current Scope
hobbitgrad currently supports a small set of tensor operations, broadcasting, matrix multiplication, scalar reductions, a linear layer, SGD, and MSE loss.
Metadata
Release files for hobbitgrad 0.0.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| hobbitgrad-0.0.2.tar.gz | 5.2 kB | With provenance | Details for hobbitgrad-0.0.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| hobbitgrad-0.0.2-py3-none-any.whl | Python 3 | none | any | Details for hobbitgrad-0.0.2-py3-none-any.whl |
Total release size: 11.7 kB
Release files / hobbitgrad-0.0.2.tar.gz
| Download URL | hobbitgrad-0.0.2.tar.gz |
|---|---|
| Size | 5.2 kB |
| Tags | Source |
|
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Transparency logRelease files / hobbitgrad-0.0.2-py3-none-any.whl
| Download URL | hobbitgrad-0.0.2-py3-none-any.whl |
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| Size | 6.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/6.1.0 CPython/3.13.12
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Signed by GitHub Actions, verified by PyPI on Jun 25, 2026.
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