mirror of https://github.com/zcash/halo2.git
329 lines
11 KiB
Rust
329 lines
11 KiB
Rust
use group::{
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ff::{BatchInvert, Field},
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Curve,
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};
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use halo2_middleware::ff::PrimeField;
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use rand_core::RngCore;
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use std::iter::{self, ExactSizeIterator};
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use super::super::{ChallengeBeta, ChallengeGamma, ChallengeX};
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use super::Argument;
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use crate::{
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arithmetic::{eval_polynomial, parallelize, CurveAffine},
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plonk::{self, permutation::ProvingKey, Error},
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poly::{
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commitment::{Blind, Params},
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Coeff, ExtendedLagrangeCoeff, LagrangeCoeff, Polynomial, ProverQuery,
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},
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transcript::{EncodedChallenge, TranscriptWrite},
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};
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use halo2_middleware::circuit::Any;
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use halo2_middleware::poly::Rotation;
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pub(crate) struct CommittedSet<C: CurveAffine> {
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pub(crate) permutation_product_poly: Polynomial<C::Scalar, Coeff>,
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pub(crate) permutation_product_coset: Polynomial<C::Scalar, ExtendedLagrangeCoeff>,
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permutation_product_blind: Blind<C::Scalar>,
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}
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pub(crate) struct Committed<C: CurveAffine> {
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pub(crate) sets: Vec<CommittedSet<C>>,
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}
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pub struct ConstructedSet<C: CurveAffine> {
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permutation_product_poly: Polynomial<C::Scalar, Coeff>,
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permutation_product_blind: Blind<C::Scalar>,
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}
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pub(crate) struct Constructed<C: CurveAffine> {
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sets: Vec<ConstructedSet<C>>,
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}
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pub(crate) struct Evaluated<C: CurveAffine> {
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constructed: Constructed<C>,
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}
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#[allow(clippy::too_many_arguments)]
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pub(in crate::plonk) fn permutation_commit<
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'params,
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C: CurveAffine,
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P: Params<'params, C>,
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E: EncodedChallenge<C>,
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R: RngCore,
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T: TranscriptWrite<C, E>,
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>(
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arg: &Argument,
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params: &P,
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pk: &plonk::ProvingKey<C>,
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pkey: &ProvingKey<C>,
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advice: &[Polynomial<C::Scalar, LagrangeCoeff>],
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fixed: &[Polynomial<C::Scalar, LagrangeCoeff>],
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instance: &[Polynomial<C::Scalar, LagrangeCoeff>],
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beta: ChallengeBeta<C>,
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gamma: ChallengeGamma<C>,
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mut rng: R,
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transcript: &mut T,
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) -> Result<Committed<C>, Error> {
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let domain = &pk.vk.domain;
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// How many columns can be included in a single permutation polynomial?
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// We need to multiply by z(X) and (1 - (l_last(X) + l_blind(X))). This
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// will never underflow because of the requirement of at least a degree
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// 3 circuit for the permutation argument.
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assert!(pk.vk.cs_degree >= 3);
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let chunk_len = pk.vk.cs_degree - 2;
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let blinding_factors = pk.vk.cs.blinding_factors();
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// Each column gets its own delta power.
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let mut deltaomega = C::Scalar::ONE;
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// Track the "last" value from the previous column set
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let mut last_z = C::Scalar::ONE;
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let mut sets = vec![];
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for (columns, permutations) in arg
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.columns
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.chunks(chunk_len)
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.zip(pkey.permutations.chunks(chunk_len))
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{
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// Goal is to compute the products of fractions
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//
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// (p_j(\omega^i) + \delta^j \omega^i \beta + \gamma) /
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// (p_j(\omega^i) + \beta s_j(\omega^i) + \gamma)
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//
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// where p_j(X) is the jth column in this permutation,
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// and i is the ith row of the column.
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let mut modified_values = vec![C::Scalar::ONE; params.n() as usize];
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// Iterate over each column of the permutation
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for (&column, permuted_column_values) in columns.iter().zip(permutations.iter()) {
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let values = match column.column_type() {
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Any::Advice(_) => advice,
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Any::Fixed => fixed,
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Any::Instance => instance,
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};
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parallelize(&mut modified_values, |modified_values, start| {
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for ((modified_values, value), permuted_value) in modified_values
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.iter_mut()
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.zip(values[column.index()][start..].iter())
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.zip(permuted_column_values[start..].iter())
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{
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*modified_values *= *beta * permuted_value + *gamma + value;
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}
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});
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}
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// Invert to obtain the denominator for the permutation product polynomial
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modified_values.batch_invert();
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// Iterate over each column again, this time finishing the computation
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// of the entire fraction by computing the numerators
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for &column in columns.iter() {
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let omega = domain.get_omega();
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let values = match column.column_type() {
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Any::Advice(_) => advice,
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Any::Fixed => fixed,
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Any::Instance => instance,
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};
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parallelize(&mut modified_values, |modified_values, start| {
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let mut deltaomega = deltaomega * omega.pow_vartime([start as u64, 0, 0, 0]);
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for (modified_values, value) in modified_values
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.iter_mut()
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.zip(values[column.index()][start..].iter())
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{
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// Multiply by p_j(\omega^i) + \delta^j \omega^i \beta
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*modified_values *= deltaomega * *beta + *gamma + value;
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deltaomega *= ω
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}
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});
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deltaomega *= &<C::Scalar as PrimeField>::DELTA;
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}
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// The modified_values vector is a vector of products of fractions
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// of the form
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//
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// (p_j(\omega^i) + \delta^j \omega^i \beta + \gamma) /
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// (p_j(\omega^i) + \beta s_j(\omega^i) + \gamma)
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//
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// where i is the index into modified_values, for the jth column in
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// the permutation
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// Compute the evaluations of the permutation product polynomial
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// over our domain, starting with z[0] = 1
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let mut z = vec![last_z];
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for row in 1..(params.n() as usize) {
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let mut tmp = z[row - 1];
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tmp *= &modified_values[row - 1];
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z.push(tmp);
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}
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let mut z = domain.lagrange_from_vec(z);
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// Set blinding factors
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for z in &mut z[params.n() as usize - blinding_factors..] {
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*z = C::Scalar::random(&mut rng);
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}
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// Set new last_z
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last_z = z[params.n() as usize - (blinding_factors + 1)];
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let blind = Blind(C::Scalar::random(&mut rng));
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let permutation_product_commitment_projective = params.commit_lagrange(&z, blind);
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let permutation_product_blind = blind;
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let z = domain.lagrange_to_coeff(z);
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let permutation_product_poly = z.clone();
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let permutation_product_coset = domain.coeff_to_extended(z.clone());
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let permutation_product_commitment = permutation_product_commitment_projective.to_affine();
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// Hash the permutation product commitment
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transcript.write_point(permutation_product_commitment)?;
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sets.push(CommittedSet {
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permutation_product_poly,
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permutation_product_coset,
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permutation_product_blind,
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});
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}
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Ok(Committed { sets })
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}
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impl<C: CurveAffine> Committed<C> {
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pub(in crate::plonk) fn construct(self) -> Constructed<C> {
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Constructed {
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sets: self
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.sets
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.iter()
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.map(|set| ConstructedSet {
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permutation_product_poly: set.permutation_product_poly.clone(),
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permutation_product_blind: set.permutation_product_blind,
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})
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.collect(),
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}
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}
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}
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impl<C: CurveAffine> super::ProvingKey<C> {
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pub(in crate::plonk) fn open(
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&self,
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x: ChallengeX<C>,
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) -> impl Iterator<Item = ProverQuery<'_, C>> + Clone {
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self.polys.iter().map(move |poly| ProverQuery {
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point: *x,
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poly,
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blind: Blind::default(),
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})
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}
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pub(in crate::plonk) fn evaluate<E: EncodedChallenge<C>, T: TranscriptWrite<C, E>>(
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&self,
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x: ChallengeX<C>,
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transcript: &mut T,
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) -> Result<(), Error> {
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// Hash permutation evals
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for eval in self.polys.iter().map(|poly| eval_polynomial(poly, *x)) {
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transcript.write_scalar(eval)?;
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}
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Ok(())
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}
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}
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impl<C: CurveAffine> Constructed<C> {
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pub(in crate::plonk) fn evaluate<E: EncodedChallenge<C>, T: TranscriptWrite<C, E>>(
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self,
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pk: &plonk::ProvingKey<C>,
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x: ChallengeX<C>,
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transcript: &mut T,
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) -> Result<Evaluated<C>, Error> {
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let domain = &pk.vk.domain;
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let blinding_factors = pk.vk.cs.blinding_factors();
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{
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let mut sets = self.sets.iter();
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while let Some(set) = sets.next() {
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let permutation_product_eval = eval_polynomial(&set.permutation_product_poly, *x);
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let permutation_product_next_eval = eval_polynomial(
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&set.permutation_product_poly,
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domain.rotate_omega(*x, Rotation::next()),
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);
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// Hash permutation product evals
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for eval in iter::empty()
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.chain(Some(&permutation_product_eval))
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.chain(Some(&permutation_product_next_eval))
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{
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transcript.write_scalar(*eval)?;
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}
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// If we have any remaining sets to process, evaluate this set at omega^u
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// so we can constrain the last value of its running product to equal the
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// first value of the next set's running product, chaining them together.
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if sets.len() > 0 {
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let permutation_product_last_eval = eval_polynomial(
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&set.permutation_product_poly,
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domain.rotate_omega(*x, Rotation(-((blinding_factors + 1) as i32))),
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);
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transcript.write_scalar(permutation_product_last_eval)?;
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}
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}
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}
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Ok(Evaluated { constructed: self })
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}
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}
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impl<C: CurveAffine> Evaluated<C> {
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pub(in crate::plonk) fn open<'a>(
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&'a self,
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pk: &'a plonk::ProvingKey<C>,
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x: ChallengeX<C>,
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) -> impl Iterator<Item = ProverQuery<'a, C>> + Clone {
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let blinding_factors = pk.vk.cs.blinding_factors();
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let x_next = pk.vk.domain.rotate_omega(*x, Rotation::next());
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let x_last = pk
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.vk
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.domain
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.rotate_omega(*x, Rotation(-((blinding_factors + 1) as i32)));
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iter::empty()
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.chain(self.constructed.sets.iter().flat_map(move |set| {
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iter::empty()
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// Open permutation product commitments at x and \omega x
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.chain(Some(ProverQuery {
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point: *x,
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poly: &set.permutation_product_poly,
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blind: set.permutation_product_blind,
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}))
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.chain(Some(ProverQuery {
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point: x_next,
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poly: &set.permutation_product_poly,
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blind: set.permutation_product_blind,
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}))
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}))
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// Open it at \omega^{last} x for all but the last set. This rotation is only
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// sensical for the first row, but we only use this rotation in a constraint
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// that is gated on l_0.
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.chain(
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self.constructed
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.sets
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.iter()
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.rev()
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.skip(1)
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.flat_map(move |set| {
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Some(ProverQuery {
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point: x_last,
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poly: &set.permutation_product_poly,
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blind: set.permutation_product_blind,
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})
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}),
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)
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}
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}
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