mirror of
https://github.com/arnaucube/mat-vec-prod-exp.git
synced 2026-01-12 08:51:28 +01:00
backup wip
This commit is contained in:
0
src/commitments_approach.rs
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src/commitments_approach.rs
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src/cyclefold_circuit.rs
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src/cyclefold_circuit.rs
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fn init(pp: &Self::ProverParam, F: FC, z_0: Vec<C1::ScalarField>) -> Result<Self, Error> {
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// prepare the circuit to obtain its R1CS
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let cs = ConstraintSystem::<C1::ScalarField>::new_ref();
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let cs2 = ConstraintSystem::<C1::BaseField>::new_ref();
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let augmented_F_circuit =
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AugmentedFCircuit::<C1, C2, GC2, FC>::empty(&pp.poseidon_config, F);
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let cf_circuit = CycleFoldCircuit::<C1, GC1>::empty();
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augmented_F_circuit.generate_constraints(cs.clone())?;
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cs.finalize();
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let cs = cs.into_inner().ok_or(Error::NoInnerConstraintSystem)?;
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let r1cs = extract_r1cs::<C1::ScalarField>(&cs);
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cf_circuit.generate_constraints(cs2.clone())?;
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cs2.finalize();
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let cs2 = cs2.into_inner().ok_or(Error::NoInnerConstraintSystem)?;
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let cf_r1cs = extract_r1cs::<C1::BaseField>(&cs2);
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}
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109
src/lib.rs
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src/lib.rs
@@ -2,112 +2,5 @@
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#![allow(unused_doc_comments)]
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#![allow(dead_code)]
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use ark_ff::PrimeField;
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use ark_r1cs_std::fields::nonnative::NonNativeFieldVar;
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use ark_r1cs_std::{alloc::AllocVar, eq::EqGadget, fields::FieldVar, R1CSVar};
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use ark_relations::r1cs::{ConstraintSynthesizer, ConstraintSystemRef, SynthesisError};
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use core::marker::PhantomData;
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use std::ops::Mul;
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mod sparse_approach;
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mod utils;
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use utils::*;
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/// - F stands for the field that we represent
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/// - CF stands for the ConstraintField over which we do the operations
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/// Implements the A * z matrix-vector-product by fixing the combinations of 'z'.
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fn handcrafted_A_by_z<F: PrimeField, CF: PrimeField>(
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cs: ConstraintSystemRef<CF>,
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z: Vec<NonNativeFieldVar<F, CF>>,
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) -> Result<Vec<NonNativeFieldVar<F, CF>>, SynthesisError> {
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let five = NonNativeFieldVar::<F, CF>::new_constant(cs.clone(), F::from(5u32))?;
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// directly hand-craft the output vector containing the operations in-place:
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Ok(vec![
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z[1].clone() + five.clone() * z[4].clone(),
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z[1].clone() + z[3].clone(),
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z[1].clone() + z[4].clone(),
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five * z[0].clone() + z[4].clone() + z[5].clone(),
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]
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.clone())
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}
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/// Implements the A * z matrix-vector-product by doing the sparse matrix by vector algorithm, and
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/// assuming that the elements of the matrix A are constants of the system.
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pub fn mat_vec_mul_sparse_gadget<F: PrimeField, CF: PrimeField>(
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m: SparseMatrixVar<F, CF>,
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v: Vec<NonNativeFieldVar<F, CF>>,
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) -> Vec<NonNativeFieldVar<F, CF>> {
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let mut res = vec![NonNativeFieldVar::<F, CF>::zero(); m.n_rows];
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for (row_i, row) in m.coeffs.iter().enumerate() {
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for (value, col_i) in row.iter() {
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if value.value().unwrap() == F::one() {
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res[row_i] += v[*col_i].clone(); // when value==1, no need to multiply by it
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continue;
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}
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res[row_i] += value.clone().mul(&v[*col_i].clone());
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}
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}
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res
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}
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/// Circuit that takes as constants the sparse matrix A, and as inputs the vectors z and y. It
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/// computes the matrix by vector product between A and z, and checks that is equal to y
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/// (ie. y == A*z)
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struct MatrixVectorCircuit<F: PrimeField, CF: PrimeField> {
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_cf: PhantomData<CF>,
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pub A: SparseMatrix<F>,
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pub z: Vec<F>,
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pub y: Vec<F>,
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}
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impl<F: PrimeField, CF: PrimeField> ConstraintSynthesizer<CF> for MatrixVectorCircuit<F, CF> {
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fn generate_constraints(self, cs: ConstraintSystemRef<CF>) -> Result<(), SynthesisError> {
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// set A as circuit constants
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let A = SparseMatrixVar::<F, CF>::new_constant(cs.clone(), self.A)?;
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// set z and y as witness (private inputs)
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let z: Vec<NonNativeFieldVar<F, CF>> = Vec::new_witness(cs.clone(), || Ok(self.z.clone()))?;
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let y: Vec<NonNativeFieldVar<F, CF>> = Vec::new_witness(cs.clone(), || Ok(self.y.clone()))?;
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/// The next two lines are the ones that can be swapped to see the number of constraints
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/// taken by the two approaches:
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let Az = mat_vec_mul_sparse_gadget(A, z);
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// let Az = handcrafted_A_by_z(cs, z)?;
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Az.enforce_equal(&y)?;
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Ok(())
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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use ark_pallas::{Fq, Fr};
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use ark_relations::r1cs::ConstraintSystem;
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#[test]
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fn test_relaxed_r1cs_nonnative_matrix_vector_product() {
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let A = to_F_matrix::<Fq>(vec![
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vec![0, 1, 0, 0, 5, 0],
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vec![0, 1, 0, 1, 0, 0],
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vec![0, 1, 0, 0, 1, 0],
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vec![5, 0, 0, 0, 1, 1],
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]);
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let z = to_F_vec(vec![1, 123, 35, 53, 80, 30]);
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let y = mat_vec_mul_sparse(&A, &z); // y = A*z
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println!("Matrix of size {} x {}", A.n_rows, A.n_cols);
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println!("Vector of size {}", z.len());
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println!(
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"Build the circuit that computes the matrix-vector-product over a non-native field"
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);
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let cs = ConstraintSystem::<Fr>::new_ref();
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let circuit = MatrixVectorCircuit::<Fq, Fr> {
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_cf: PhantomData,
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A,
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z,
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y,
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};
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circuit.generate_constraints(cs.clone()).unwrap();
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println!("Number of constraints: {}", cs.num_constraints());
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assert!(cs.is_satisfied().unwrap());
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}
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}
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113
src/sparse_approach.rs
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113
src/sparse_approach.rs
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/// Isolated test which gets the number of constraints for two 'naive' approaches for the
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/// matrix-vector-product:
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/// - handcrafted_A_by_z method
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/// - mat_vec_mul_sparse_gadget
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///
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use ark_ff::PrimeField;
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use ark_r1cs_std::fields::nonnative::NonNativeFieldVar;
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use ark_r1cs_std::{alloc::AllocVar, eq::EqGadget, fields::FieldVar, R1CSVar};
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use ark_relations::r1cs::{ConstraintSynthesizer, ConstraintSystemRef, SynthesisError};
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use core::marker::PhantomData;
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use std::ops::Mul;
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use crate::utils::*;
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/// - F stands for the field that we represent
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/// - CF stands for the ConstraintField over which we do the operations
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/// Implements the A * z matrix-vector-product by fixing the combinations of 'z'.
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fn handcrafted_A_by_z<F: PrimeField, CF: PrimeField>(
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cs: ConstraintSystemRef<CF>,
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z: Vec<NonNativeFieldVar<F, CF>>,
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) -> Result<Vec<NonNativeFieldVar<F, CF>>, SynthesisError> {
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let five = NonNativeFieldVar::<F, CF>::new_constant(cs.clone(), F::from(5u32))?;
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// directly hand-craft the output vector containing the operations in-place:
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Ok(vec![
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z[1].clone() + five.clone() * z[4].clone(),
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z[1].clone() + z[3].clone(),
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z[1].clone() + z[4].clone(),
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five * z[0].clone() + z[4].clone() + z[5].clone(),
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]
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.clone())
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}
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/// Implements the A * z matrix-vector-product by doing the sparse matrix by vector algorithm, and
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/// assuming that the elements of the matrix A are constants of the system.
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pub fn mat_vec_mul_sparse_gadget<F: PrimeField, CF: PrimeField>(
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m: SparseMatrixVar<F, CF>,
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v: Vec<NonNativeFieldVar<F, CF>>,
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) -> Vec<NonNativeFieldVar<F, CF>> {
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let mut res = vec![NonNativeFieldVar::<F, CF>::zero(); m.n_rows];
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for (row_i, row) in m.coeffs.iter().enumerate() {
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for (value, col_i) in row.iter() {
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if value.value().unwrap() == F::one() {
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res[row_i] += v[*col_i].clone(); // when value==1, no need to multiply by it
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continue;
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}
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res[row_i] += value.clone().mul(&v[*col_i].clone());
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}
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}
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res
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}
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/// Circuit that takes as constants the sparse matrix A, and as inputs the vectors z and y. It
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/// computes the matrix by vector product between A and z, and checks that is equal to y
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/// (ie. y == A*z)
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struct MatrixVectorCircuit<F: PrimeField, CF: PrimeField> {
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_cf: PhantomData<CF>,
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pub A: SparseMatrix<F>,
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pub z: Vec<F>,
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pub y: Vec<F>,
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}
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impl<F: PrimeField, CF: PrimeField> ConstraintSynthesizer<CF> for MatrixVectorCircuit<F, CF> {
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fn generate_constraints(self, cs: ConstraintSystemRef<CF>) -> Result<(), SynthesisError> {
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// set A as circuit constants
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let A = SparseMatrixVar::<F, CF>::new_constant(cs.clone(), self.A)?;
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// set z and y as witness (private inputs)
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let z: Vec<NonNativeFieldVar<F, CF>> = Vec::new_witness(cs.clone(), || Ok(self.z.clone()))?;
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let y: Vec<NonNativeFieldVar<F, CF>> = Vec::new_witness(cs.clone(), || Ok(self.y.clone()))?;
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/// The next two lines are the ones that can be swapped to see the number of constraints
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/// taken by the two approaches:
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let Az = mat_vec_mul_sparse_gadget(A, z);
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// let Az = handcrafted_A_by_z(cs, z)?;
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Az.enforce_equal(&y)?;
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Ok(())
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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use ark_pallas::{Fq, Fr};
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use ark_relations::r1cs::ConstraintSystem;
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#[test]
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fn test_relaxed_r1cs_nonnative_matrix_vector_product() {
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let A = to_F_matrix::<Fq>(vec![
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vec![0, 1, 0, 0, 5, 0],
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vec![0, 1, 0, 1, 0, 0],
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vec![0, 1, 0, 0, 1, 0],
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vec![5, 0, 0, 0, 1, 1],
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]);
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let z = to_F_vec(vec![1, 123, 35, 53, 80, 30]);
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let y = mat_vec_mul_sparse(&A, &z); // y = A*z
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println!("Matrix of size {} x {}", A.n_rows, A.n_cols);
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println!("Vector of size {}", z.len());
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println!(
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"Build the circuit that computes the matrix-vector-product over a non-native field"
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);
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let cs = ConstraintSystem::<Fr>::new_ref();
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let circuit = MatrixVectorCircuit::<Fq, Fr> {
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_cf: PhantomData,
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A,
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z,
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y,
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};
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circuit.generate_constraints(cs.clone()).unwrap();
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println!("Number of constraints: {}", cs.num_constraints());
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assert!(cs.is_satisfied().unwrap());
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}
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}
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