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tinysolve

torch.linalg.solve for tinygrad: solve A @ x = B for x.

from tinygrad import Tensor
from tinysolve import solve

A = Tensor.randn(2000, 16, 16) + 16 * Tensor.eye(16)
B = Tensor.randn(2000, 16, 4)

x = solve(A, B)  # (2000, 16, 4)

# differentiable (higher-order too)
gA, gB = solve(A, B).sum().gradient(A, B)

Install

uv add tinysolve  # or: pip install tinysolve

Development

uv run pytest                     # tests
uv run pytest tests/benchmark.py  # benchmarks
uv run ruff check . && uv run ty check

License

MIT

Metadata

Release files for tinysolve 0.2.1

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0.2.1 This release

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0.2.0

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0.1.0

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