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PolyBake

純粋関数によって構成されるプログラムを、訓練なしに 意味論を保存または制御された誤差内で近似するニューラル回路へ決定的に変換するコンパイラ。

from polybake import Baker, TensorSpec

baker = Baker()

@baker.collect()
def f(x):
    return max(2 * x + 1, 0)

compiled = baker.bake(inputs=[TensorSpec(shape=(4,), dtype="float32")])
compiled(x)                    # Neural IR を NumPy で実行
compiled.verify()              # 元の Python 関数との差分検査 (note.md §20)
compiled.export_onnx("f.onnx") # ONNX 書き出し

近似が要る関数も 入力領域を明示すれば誤差証明書付きで 変換できる。

from math import exp

@baker.collect()
def gaussian(x):
    return exp(-(x * x))

compiled = baker.bake(inputs=[...], domain=[(-2.0, 2.0)], error=1e-2)
compiled.error_certificate   # -> interval bound<=0.00889 domain=[-2, 2]

Metadata

Release files for polybake 0.1.0

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Source distribution for polybake 0.1.0
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Table of built distributions (wheels) for polybake 0.1.0
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polybake-0.1.0-py3-none-any.whl Python 3 none any Details for polybake-0.1.0-py3-none-any.whl

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Release files / polybake-0.1.0.tar.gz

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Size 385.7 kB
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Release files / polybake-0.1.0-py3-none-any.whl

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Size 467.6 kB
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