Browse Source

backup wip

wip
arnaucube 2 months ago
parent
commit
3c91628ea5
4 changed files with 136 additions and 108 deletions
  1. +0
    -0
      src/commitments_approach.rs
  2. +22
    -0
      src/cyclefold_circuit.rs
  3. +1
    -108
      src/lib.rs
  4. +113
    -0
      src/sparse_approach.rs

+ 0
- 0
src/commitments_approach.rs


+ 22
- 0
src/cyclefold_circuit.rs

@ -0,0 +1,22 @@
fn init(pp: &Self::ProverParam, F: FC, z_0: Vec<C1::ScalarField>) -> Result<Self, Error> {
// prepare the circuit to obtain its R1CS
let cs = ConstraintSystem::<C1::ScalarField>::new_ref();
let cs2 = ConstraintSystem::<C1::BaseField>::new_ref();
let augmented_F_circuit =
AugmentedFCircuit::<C1, C2, GC2, FC>::empty(&pp.poseidon_config, F);
let cf_circuit = CycleFoldCircuit::<C1, GC1>::empty();
augmented_F_circuit.generate_constraints(cs.clone())?;
cs.finalize();
let cs = cs.into_inner().ok_or(Error::NoInnerConstraintSystem)?;
let r1cs = extract_r1cs::<C1::ScalarField>(&cs);
cf_circuit.generate_constraints(cs2.clone())?;
cs2.finalize();
let cs2 = cs2.into_inner().ok_or(Error::NoInnerConstraintSystem)?;
let cf_r1cs = extract_r1cs::<C1::BaseField>(&cs2);
}

+ 1
- 108
src/lib.rs

@ -2,112 +2,5 @@
#![allow(unused_doc_comments)] #![allow(unused_doc_comments)]
#![allow(dead_code)] #![allow(dead_code)]
use ark_ff::PrimeField;
use ark_r1cs_std::fields::nonnative::NonNativeFieldVar;
use ark_r1cs_std::{alloc::AllocVar, eq::EqGadget, fields::FieldVar, R1CSVar};
use ark_relations::r1cs::{ConstraintSynthesizer, ConstraintSystemRef, SynthesisError};
use core::marker::PhantomData;
use std::ops::Mul;
mod sparse_approach;
mod utils; mod utils;
use utils::*;
/// - F stands for the field that we represent
/// - CF stands for the ConstraintField over which we do the operations
/// Implements the A * z matrix-vector-product by fixing the combinations of 'z'.
fn handcrafted_A_by_z<F: PrimeField, CF: PrimeField>(
cs: ConstraintSystemRef<CF>,
z: Vec<NonNativeFieldVar<F, CF>>,
) -> Result<Vec<NonNativeFieldVar<F, CF>>, SynthesisError> {
let five = NonNativeFieldVar::<F, CF>::new_constant(cs.clone(), F::from(5u32))?;
// directly hand-craft the output vector containing the operations in-place:
Ok(vec![
z[1].clone() + five.clone() * z[4].clone(),
z[1].clone() + z[3].clone(),
z[1].clone() + z[4].clone(),
five * z[0].clone() + z[4].clone() + z[5].clone(),
]
.clone())
}
/// Implements the A * z matrix-vector-product by doing the sparse matrix by vector algorithm, and
/// assuming that the elements of the matrix A are constants of the system.
pub fn mat_vec_mul_sparse_gadget<F: PrimeField, CF: PrimeField>(
m: SparseMatrixVar<F, CF>,
v: Vec<NonNativeFieldVar<F, CF>>,
) -> Vec<NonNativeFieldVar<F, CF>> {
let mut res = vec![NonNativeFieldVar::<F, CF>::zero(); m.n_rows];
for (row_i, row) in m.coeffs.iter().enumerate() {
for (value, col_i) in row.iter() {
if value.value().unwrap() == F::one() {
res[row_i] += v[*col_i].clone(); // when value==1, no need to multiply by it
continue;
}
res[row_i] += value.clone().mul(&v[*col_i].clone());
}
}
res
}
/// Circuit that takes as constants the sparse matrix A, and as inputs the vectors z and y. It
/// computes the matrix by vector product between A and z, and checks that is equal to y
/// (ie. y == A*z)
struct MatrixVectorCircuit<F: PrimeField, CF: PrimeField> {
_cf: PhantomData<CF>,
pub A: SparseMatrix<F>,
pub z: Vec<F>,
pub y: Vec<F>,
}
impl<F: PrimeField, CF: PrimeField> ConstraintSynthesizer<CF> for MatrixVectorCircuit<F, CF> {
fn generate_constraints(self, cs: ConstraintSystemRef<CF>) -> Result<(), SynthesisError> {
// set A as circuit constants
let A = SparseMatrixVar::<F, CF>::new_constant(cs.clone(), self.A)?;
// set z and y as witness (private inputs)
let z: Vec<NonNativeFieldVar<F, CF>> = Vec::new_witness(cs.clone(), || Ok(self.z.clone()))?;
let y: Vec<NonNativeFieldVar<F, CF>> = Vec::new_witness(cs.clone(), || Ok(self.y.clone()))?;
/// The next two lines are the ones that can be swapped to see the number of constraints
/// taken by the two approaches:
let Az = mat_vec_mul_sparse_gadget(A, z);
// let Az = handcrafted_A_by_z(cs, z)?;
Az.enforce_equal(&y)?;
Ok(())
}
}
#[cfg(test)]
mod tests {
use super::*;
use ark_pallas::{Fq, Fr};
use ark_relations::r1cs::ConstraintSystem;
#[test]
fn test_relaxed_r1cs_nonnative_matrix_vector_product() {
let A = to_F_matrix::<Fq>(vec![
vec![0, 1, 0, 0, 5, 0],
vec![0, 1, 0, 1, 0, 0],
vec![0, 1, 0, 0, 1, 0],
vec![5, 0, 0, 0, 1, 1],
]);
let z = to_F_vec(vec![1, 123, 35, 53, 80, 30]);
let y = mat_vec_mul_sparse(&A, &z); // y = A*z
println!("Matrix of size {} x {}", A.n_rows, A.n_cols);
println!("Vector of size {}", z.len());
println!(
"Build the circuit that computes the matrix-vector-product over a non-native field"
);
let cs = ConstraintSystem::<Fr>::new_ref();
let circuit = MatrixVectorCircuit::<Fq, Fr> {
_cf: PhantomData,
A,
z,
y,
};
circuit.generate_constraints(cs.clone()).unwrap();
println!("Number of constraints: {}", cs.num_constraints());
assert!(cs.is_satisfied().unwrap());
}
}

+ 113
- 0
src/sparse_approach.rs

@ -0,0 +1,113 @@
/// Isolated test which gets the number of constraints for two 'naive' approaches for the
/// matrix-vector-product:
/// - handcrafted_A_by_z method
/// - mat_vec_mul_sparse_gadget
///
use ark_ff::PrimeField;
use ark_r1cs_std::fields::nonnative::NonNativeFieldVar;
use ark_r1cs_std::{alloc::AllocVar, eq::EqGadget, fields::FieldVar, R1CSVar};
use ark_relations::r1cs::{ConstraintSynthesizer, ConstraintSystemRef, SynthesisError};
use core::marker::PhantomData;
use std::ops::Mul;
use crate::utils::*;
/// - F stands for the field that we represent
/// - CF stands for the ConstraintField over which we do the operations
/// Implements the A * z matrix-vector-product by fixing the combinations of 'z'.
fn handcrafted_A_by_z<F: PrimeField, CF: PrimeField>(
cs: ConstraintSystemRef<CF>,
z: Vec<NonNativeFieldVar<F, CF>>,
) -> Result<Vec<NonNativeFieldVar<F, CF>>, SynthesisError> {
let five = NonNativeFieldVar::<F, CF>::new_constant(cs.clone(), F::from(5u32))?;
// directly hand-craft the output vector containing the operations in-place:
Ok(vec![
z[1].clone() + five.clone() * z[4].clone(),
z[1].clone() + z[3].clone(),
z[1].clone() + z[4].clone(),
five * z[0].clone() + z[4].clone() + z[5].clone(),
]
.clone())
}
/// Implements the A * z matrix-vector-product by doing the sparse matrix by vector algorithm, and
/// assuming that the elements of the matrix A are constants of the system.
pub fn mat_vec_mul_sparse_gadget<F: PrimeField, CF: PrimeField>(
m: SparseMatrixVar<F, CF>,
v: Vec<NonNativeFieldVar<F, CF>>,
) -> Vec<NonNativeFieldVar<F, CF>> {
let mut res = vec![NonNativeFieldVar::<F, CF>::zero(); m.n_rows];
for (row_i, row) in m.coeffs.iter().enumerate() {
for (value, col_i) in row.iter() {
if value.value().unwrap() == F::one() {
res[row_i] += v[*col_i].clone(); // when value==1, no need to multiply by it
continue;
}
res[row_i] += value.clone().mul(&v[*col_i].clone());
}
}
res
}
/// Circuit that takes as constants the sparse matrix A, and as inputs the vectors z and y. It
/// computes the matrix by vector product between A and z, and checks that is equal to y
/// (ie. y == A*z)
struct MatrixVectorCircuit<F: PrimeField, CF: PrimeField> {
_cf: PhantomData<CF>,
pub A: SparseMatrix<F>,
pub z: Vec<F>,
pub y: Vec<F>,
}
impl<F: PrimeField, CF: PrimeField> ConstraintSynthesizer<CF> for MatrixVectorCircuit<F, CF> {
fn generate_constraints(self, cs: ConstraintSystemRef<CF>) -> Result<(), SynthesisError> {
// set A as circuit constants
let A = SparseMatrixVar::<F, CF>::new_constant(cs.clone(), self.A)?;
// set z and y as witness (private inputs)
let z: Vec<NonNativeFieldVar<F, CF>> = Vec::new_witness(cs.clone(), || Ok(self.z.clone()))?;
let y: Vec<NonNativeFieldVar<F, CF>> = Vec::new_witness(cs.clone(), || Ok(self.y.clone()))?;
/// The next two lines are the ones that can be swapped to see the number of constraints
/// taken by the two approaches:
let Az = mat_vec_mul_sparse_gadget(A, z);
// let Az = handcrafted_A_by_z(cs, z)?;
Az.enforce_equal(&y)?;
Ok(())
}
}
#[cfg(test)]
mod tests {
use super::*;
use ark_pallas::{Fq, Fr};
use ark_relations::r1cs::ConstraintSystem;
#[test]
fn test_relaxed_r1cs_nonnative_matrix_vector_product() {
let A = to_F_matrix::<Fq>(vec![
vec![0, 1, 0, 0, 5, 0],
vec![0, 1, 0, 1, 0, 0],
vec![0, 1, 0, 0, 1, 0],
vec![5, 0, 0, 0, 1, 1],
]);
let z = to_F_vec(vec![1, 123, 35, 53, 80, 30]);
let y = mat_vec_mul_sparse(&A, &z); // y = A*z
println!("Matrix of size {} x {}", A.n_rows, A.n_cols);
println!("Vector of size {}", z.len());
println!(
"Build the circuit that computes the matrix-vector-product over a non-native field"
);
let cs = ConstraintSystem::<Fr>::new_ref();
let circuit = MatrixVectorCircuit::<Fq, Fr> {
_cf: PhantomData,
A,
z,
y,
};
circuit.generate_constraints(cs.clone()).unwrap();
println!("Number of constraints: {}", cs.num_constraints());
assert!(cs.is_satisfied().unwrap());
}
}

Loading…
Cancel
Save