plonky2/src/plonk_challenger.rs
2021-04-22 22:21:24 +02:00

263 lines
9.1 KiB
Rust

use crate::circuit_builder::CircuitBuilder;
use crate::field::field::Field;
use crate::hash::{permute, SPONGE_RATE, SPONGE_WIDTH};
use crate::proof::{Hash, HashTarget};
use crate::target::Target;
/// Observes prover messages, and generates challenges by hashing the transcript.
#[derive(Clone)]
pub struct Challenger<F: Field> {
sponge_state: [F; SPONGE_WIDTH],
input_buffer: Vec<F>,
output_buffer: Vec<F>,
}
/// Observes prover messages, and generates verifier challenges based on the transcript.
///
/// The implementation is roughly based on a duplex sponge with a Rescue permutation. Note that in
/// each round, our sponge can absorb an arbitrary number of prover messages and generate an
/// arbitrary number of verifier challenges. This might appear to diverge from the duplex sponge
/// design, but it can be viewed as a duplex sponge whose inputs are sometimes zero (when we perform
/// multiple squeezes) and whose outputs are sometimes ignored (when we perform multiple
/// absorptions). Thus the security properties of a duplex sponge still apply to our design.
impl<F: Field> Challenger<F> {
pub fn new() -> Challenger<F> {
Challenger {
sponge_state: [F::ZERO; SPONGE_WIDTH],
input_buffer: Vec::new(),
output_buffer: Vec::new(),
}
}
pub fn observe_element(&mut self, element: F) {
// Any buffered outputs are now invalid, since they wouldn't reflect this input.
self.output_buffer.clear();
self.input_buffer.push(element);
}
pub fn observe_elements(&mut self, elements: &[F]) {
for &element in elements {
self.observe_element(element);
}
}
pub fn observe_hash(&mut self, hash: &Hash<F>) {
self.observe_elements(&hash.elements)
}
pub fn get_challenge(&mut self) -> F {
self.absorb_buffered_inputs();
if self.output_buffer.is_empty() {
// Evaluate the permutation to produce `r` new outputs.
self.sponge_state = permute(self.sponge_state);
self.output_buffer = self.sponge_state[0..SPONGE_RATE].to_vec();
}
self.output_buffer
.pop()
.expect("Output buffer should be non-empty")
}
pub fn get_2_challenges(&mut self) -> (F, F) {
(self.get_challenge(), self.get_challenge())
}
pub fn get_3_challenges(&mut self) -> (F, F, F) {
(
self.get_challenge(),
self.get_challenge(),
self.get_challenge(),
)
}
pub fn get_n_challenges(&mut self, n: usize) -> Vec<F> {
(0..n).map(|_| self.get_challenge()).collect()
}
pub fn get_hash(&mut self) -> Hash<F> {
Hash {
elements: [
self.get_challenge(),
self.get_challenge(),
self.get_challenge(),
self.get_challenge(),
],
}
}
/// Absorb any buffered inputs. After calling this, the input buffer will be empty.
fn absorb_buffered_inputs(&mut self) {
for input_chunk in self.input_buffer.chunks(SPONGE_RATE) {
// Overwrite the first r elements with the inputs. This differs from a standard sponge,
// where we would xor or add in the inputs. This is a well-known variant, though,
// sometimes called "overwrite mode".
for (i, &input) in input_chunk.iter().enumerate() {
self.sponge_state[i] = input;
}
// Apply the permutation.
self.sponge_state = permute(self.sponge_state);
}
self.output_buffer = self.sponge_state[0..SPONGE_RATE].to_vec();
self.input_buffer.clear();
}
}
/// A recursive version of `Challenger`.
pub(crate) struct RecursiveChallenger {
sponge_state: [Target; SPONGE_WIDTH],
input_buffer: Vec<Target>,
output_buffer: Vec<Target>,
}
impl RecursiveChallenger {
pub(crate) fn new<F: Field>(builder: &mut CircuitBuilder<F>) -> Self {
let zero = builder.zero();
RecursiveChallenger {
sponge_state: [zero; SPONGE_WIDTH],
input_buffer: Vec::new(),
output_buffer: Vec::new(),
}
}
pub(crate) fn observe_element(&mut self, target: Target) {
// Any buffered outputs are now invalid, since they wouldn't reflect this input.
self.output_buffer.clear();
self.input_buffer.push(target);
}
pub(crate) fn observe_elements(&mut self, targets: &[Target]) {
for &target in targets {
self.observe_element(target);
}
}
pub fn observe_hash(&mut self, hash: &HashTarget) {
self.observe_elements(&hash.elements)
}
pub(crate) fn get_challenge<F: Field>(&mut self, builder: &mut CircuitBuilder<F>) -> Target {
self.absorb_buffered_inputs(builder);
if self.output_buffer.is_empty() {
// Evaluate the permutation to produce `r` new outputs.
self.sponge_state = builder.permute(self.sponge_state);
self.output_buffer = self.sponge_state[0..SPONGE_RATE].to_vec();
}
self.output_buffer
.pop()
.expect("Output buffer should be non-empty")
}
pub(crate) fn get_2_challenges<F: Field>(
&mut self,
builder: &mut CircuitBuilder<F>,
) -> (Target, Target) {
(self.get_challenge(builder), self.get_challenge(builder))
}
pub(crate) fn get_3_challenges<F: Field>(
&mut self,
builder: &mut CircuitBuilder<F>,
) -> (Target, Target, Target) {
(
self.get_challenge(builder),
self.get_challenge(builder),
self.get_challenge(builder),
)
}
pub(crate) fn get_n_challenges<F: Field>(
&mut self,
builder: &mut CircuitBuilder<F>,
n: usize,
) -> Vec<Target> {
(0..n).map(|_| self.get_challenge(builder)).collect()
}
/// Absorb any buffered inputs. After calling this, the input buffer will be empty.
fn absorb_buffered_inputs<F: Field>(&mut self, builder: &mut CircuitBuilder<F>) {
for input_chunk in self.input_buffer.chunks(SPONGE_RATE) {
// Overwrite the first r elements with the inputs. This differs from a standard sponge,
// where we would xor or add in the inputs. This is a well-known variant, though,
// sometimes called "overwrite mode".
for (i, &input) in input_chunk.iter().enumerate() {
self.sponge_state[i] = input;
}
// Apply the permutation.
self.sponge_state = builder.permute(self.sponge_state);
}
self.output_buffer = self.sponge_state[0..SPONGE_RATE].to_vec();
self.input_buffer.clear();
}
}
#[cfg(test)]
mod tests {
use crate::circuit_builder::CircuitBuilder;
use crate::circuit_data::CircuitConfig;
use crate::field::crandall_field::CrandallField;
use crate::field::field::Field;
use crate::generator::generate_partial_witness;
use crate::plonk_challenger::{Challenger, RecursiveChallenger};
use crate::target::Target;
use crate::witness::PartialWitness;
/// Tests for consistency between `Challenger` and `RecursiveChallenger`.
#[test]
fn test_consistency() {
type F = CrandallField;
// These are mostly arbitrary, but we want to test some rounds with enough inputs/outputs to
// trigger multiple absorptions/squeezes.
let num_inputs_per_round = vec![2, 5, 3];
let num_outputs_per_round = vec![1, 2, 4];
// Generate random input messages.
let inputs_per_round: Vec<Vec<F>> = num_inputs_per_round
.iter()
.map(|&n| (0..n).map(|_| F::rand()).collect::<Vec<_>>())
.collect();
let mut challenger = Challenger::new();
let mut outputs_per_round: Vec<Vec<F>> = Vec::new();
for (r, inputs) in inputs_per_round.iter().enumerate() {
challenger.observe_elements(inputs);
outputs_per_round.push(challenger.get_n_challenges(num_outputs_per_round[r]));
}
let config = CircuitConfig {
num_wires: 114,
num_routed_wires: 27,
..CircuitConfig::default()
};
let mut builder = CircuitBuilder::<F>::new(config);
let mut recursive_challenger = RecursiveChallenger::new(&mut builder);
let mut recursive_outputs_per_round: Vec<Vec<Target>> = Vec::new();
for (r, inputs) in inputs_per_round.iter().enumerate() {
recursive_challenger.observe_elements(&builder.constants(inputs));
recursive_outputs_per_round.push(
recursive_challenger.get_n_challenges(&mut builder, num_outputs_per_round[r]),
);
}
let circuit = builder.build();
let mut witness = PartialWitness::new();
generate_partial_witness(&mut witness, &circuit.prover_only.generators);
let recursive_output_values_per_round: Vec<Vec<F>> = recursive_outputs_per_round
.iter()
.map(|outputs| witness.get_targets(outputs))
.collect();
assert_eq!(outputs_per_round, recursive_output_values_per_round);
}
}