Method from_weights

src/fused_mm_sampling/core.py:670–677

(
        cls,
        weights: torch.Tensor,  # [V, D]
        epsilon: float = 0.2,
    )

    @classmethod
    def from_weights(
        cls,
        weights: torch.Tensor,  # [V, D]
        epsilon: float = 0.2,
    ) -> "JLSampler":
        k = optimal_k(n=weights.shape[0], epsilon=epsilon)
        print(f"JLSampler optimal k={k}")
        return cls(weights, k=k)

    def prepare(self) -> "JLSampler":
        D = self.weights.shape[1]  # noqa: N806