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feat: make max_rotations configurable (#82)

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This commit is contained in:
Genysys
2022-12-21 16:20:40 +04:00
committed by GitHub
parent f228d238f6
commit 4e0b7f08c2
12 changed files with 42 additions and 21 deletions
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8
benches/affine.rs
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@@ -33,10 +33,10 @@ impl<F: FieldExt + TensorType> Circuit<F> for MyCircuit<F> {
fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
let len = unsafe { LEN };
let input = VarTensor::new_advice(cs, K, len, vec![len], true);
let kernel = VarTensor::new_advice(cs, K, len * len, vec![len, len], true);
let bias = VarTensor::new_advice(cs, K, len, vec![len], true);
let output = VarTensor::new_advice(cs, K, len, vec![len], true);
let input = VarTensor::new_advice(cs, K, len, vec![len], true, 512);
let kernel = VarTensor::new_advice(cs, K, len * len, vec![len, len], true, 512);
let bias = VarTensor::new_advice(cs, K, len, vec![len], true, 512);
let output = VarTensor::new_advice(cs, K, len, vec![len], true, 512);
// tells the config layer to add an affine op to a circuit gate
let affine_node = FusedNode {
op: FusedOp::Affine,

5
benches/cnvrl.rs
View File

@@ -53,6 +53,7 @@ where
IN_CHANNELS * IMAGE_HEIGHT * IMAGE_WIDTH,
vec![IN_CHANNELS, IMAGE_HEIGHT, IMAGE_WIDTH],
true,
512,
);
let kernel = VarTensor::new_advice(
cs,
@@ -60,15 +61,17 @@ where
OUT_CHANNELS * IN_CHANNELS * KERNEL_HEIGHT * KERNEL_WIDTH,
vec![OUT_CHANNELS, IN_CHANNELS, KERNEL_HEIGHT, KERNEL_WIDTH],
true,
512
);
let bias = VarTensor::new_advice(cs, K, OUT_CHANNELS, vec![OUT_CHANNELS], true);
let bias = VarTensor::new_advice(cs, K, OUT_CHANNELS, vec![OUT_CHANNELS], true, 512);
let output = VarTensor::new_advice(
cs,
K,
OUT_CHANNELS * output_height * output_width,
vec![OUT_CHANNELS, output_height, output_width],
true,
512,
);
// tells the config layer to add a conv op to a circuit gate

2
benches/range.rs
View File

@@ -33,7 +33,7 @@ impl<F: FieldExt + TensorType> Circuit<F> for MyCircuit<F> {
fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
let len = unsafe { LEN };
let advices = (0..2)
.map(|_| VarTensor::new_advice(cs, K, len, vec![len], true))
.map(|_| VarTensor::new_advice(cs, K, len, vec![len], true, 512))
.collect_vec();
RangeCheckConfig::configure(cs, &advices[0], &advices[1], RANGE)

2
benches/relu.rs
View File

@@ -34,7 +34,7 @@ impl<F: FieldExt + TensorType, NL: 'static + Nonlinearity<F> + Clone> Circuit<F>
fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
unsafe {
let advices = (0..2)
.map(|_| VarTensor::new_advice(cs, K, LEN, vec![LEN], true))
.map(|_| VarTensor::new_advice(cs, K, LEN, vec![LEN], true, 512))
.collect::<Vec<_>>();
Self::Config::configure(cs, &advices[0], &advices[1], Some(&[BITS, 128]))

5
examples/conv2d_mnist/main.rs
View File

@@ -149,6 +149,7 @@ where
max(IN_CHANNELS * IMAGE_HEIGHT * IMAGE_WIDTH, LEN),
vec![IN_CHANNELS, IMAGE_HEIGHT, IMAGE_WIDTH],
true,
512,
);
let kernel = VarTensor::new_advice(
cs,
@@ -159,16 +160,18 @@ where
),
vec![OUT_CHANNELS, IN_CHANNELS, KERNEL_HEIGHT, KERNEL_WIDTH],
true,
512,
);
let bias =
VarTensor::new_advice(cs, K, max(OUT_CHANNELS, CLASSES), vec![OUT_CHANNELS], true);
VarTensor::new_advice(cs, K, max(OUT_CHANNELS, CLASSES), vec![OUT_CHANNELS], true, 512);
let output = VarTensor::new_advice(
cs,
K,
max(OUT_CHANNELS * output_height * output_width, LEN),
vec![OUT_CHANNELS, output_height, output_width],
true,
512,
);
// tells the config layer to add a conv op to a circuit gate

8
examples/mlp_4d.rs
View File

@@ -50,10 +50,10 @@ impl<F: FieldExt + TensorType, const LEN: usize, const BITS: usize> Circuit<F>
// Here we wire together the layers by using the output advice in each layer as input advice in the next (not with copying / equality).
// This can be automated but we will sometimes want skip connections, etc. so we need the flexibility.
fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
let input = VarTensor::new_advice(cs, K, LEN, vec![LEN], true);
let kernel = VarTensor::new_advice(cs, K, LEN * LEN, vec![LEN, LEN], true);
let bias = VarTensor::new_advice(cs, K, LEN, vec![LEN], true);
let output = VarTensor::new_advice(cs, K, LEN, vec![LEN], true);
let input = VarTensor::new_advice(cs, K, LEN, vec![LEN], true, 512);
let kernel = VarTensor::new_advice(cs, K, LEN * LEN, vec![LEN, LEN], true, 512);
let bias = VarTensor::new_advice(cs, K, LEN, vec![LEN], true, 512);
let output = VarTensor::new_advice(cs, K, LEN, vec![LEN], true, 512);
// tells the config layer to add an affine op to the circuit gate
let affine_node = FusedNode {
op: FusedOp::Affine,

2
src/circuit/eltwise.rs
View File

@@ -336,7 +336,7 @@ mod tests {
fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
let advices = (0..2)
.map(|_| VarTensor::new_advice(cs, 4, 1, vec![1], true))
.map(|_| VarTensor::new_advice(cs, 4, 1, vec![1], true, 512))
.collect::<Vec<_>>();
Self::Config::configure(cs, &advices[0], &advices[1], Some(&[2, 1]))

8
src/circuit/fused.rs
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@@ -335,10 +335,10 @@ mod tests {
}
fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
let input = VarTensor::new_advice(cs, K, LEN, vec![LEN], true);
let kernel = VarTensor::new_advice(cs, K, LEN * LEN, vec![LEN, LEN], true);
let bias = VarTensor::new_advice(cs, K, LEN, vec![LEN], true);
let output = VarTensor::new_advice(cs, K, LEN, vec![LEN], true);
let input = VarTensor::new_advice(cs, K, LEN, vec![LEN], true, 512);
let kernel = VarTensor::new_advice(cs, K, LEN * LEN, vec![LEN, LEN], true, 512);
let bias = VarTensor::new_advice(cs, K, LEN, vec![LEN], true, 512);
let output = VarTensor::new_advice(cs, K, LEN, vec![LEN], true, 512);
// tells the config layer to add an affine op to a circuit gate
let affine_node = FusedNode {
op: FusedOp::Affine,

2
src/circuit/range.rs
View File

@@ -156,7 +156,7 @@ mod tests {
fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
let advices = (0..2)
.map(|_| VarTensor::new_advice(cs, 4, 1, vec![1], true))
.map(|_| VarTensor::new_advice(cs, 4, 1, vec![1], true, 512))
.collect_vec();
let input = &advices[0];
let expected = &advices[1];

3
src/commands.rs
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@@ -30,6 +30,9 @@ pub struct Cli {
/// Flags whether params are public
#[arg(long, default_value = "false")]
pub public_params: bool,
/// Flags to set maximum rotations
#[arg(short = 'M', long, default_value = "512")]
pub max_rotations: usize,
}
#[derive(ValueEnum, Copy, Clone, Debug, PartialEq, Eq)]

12
src/graph/vars.rs
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@@ -122,6 +122,8 @@ impl<F: FieldExt + TensorType> ModelVars<F> {
fixed_dims: (usize, usize),
instance_dims: (usize, Vec<Vec<usize>>),
) -> Self {
let tensor_max = Cli::parse().max_rotations;
let advices = (0..advice_dims.0)
.map(|_| {
VarTensor::new_advice(
@@ -130,12 +132,20 @@ impl<F: FieldExt + TensorType> ModelVars<F> {
advice_dims.1,
vec![advice_dims.1],
true,
tensor_max,
)
})
.collect_vec();
let fixed = (0..fixed_dims.0)
.map(|_| {
VarTensor::new_fixed(cs, logrows as usize, fixed_dims.1, vec![fixed_dims.1], true)
VarTensor::new_fixed(
cs,
logrows as usize,
fixed_dims.1,
vec![fixed_dims.1],
true,
tensor_max,
)
})
.collect_vec();
let instances = (0..instance_dims.0)

6
src/tensor/var.rs
View File

@@ -33,9 +33,10 @@ impl VarTensor {
capacity: usize,
dims: Vec<usize>,
equality: bool,
v1: usize,
) -> Self {
let base = 2u32;
let max_rows = min(512, base.pow(k as u32) as usize - cs.blinding_factors() - 1);
let max_rows = min(v1, base.pow(k as u32) as usize - cs.blinding_factors() - 1);
let modulo = (capacity / max_rows) + 1;
let mut advices = vec![];
for _ in 0..modulo {
@@ -60,9 +61,10 @@ impl VarTensor {
capacity: usize,
dims: Vec<usize>,
equality: bool,
v1: usize,
) -> Self {
let base = 2u32;
let max_rows = min(512, base.pow(k as u32) as usize - cs.blinding_factors() - 1);
let max_rows = min(v1, base.pow(k as u32) as usize - cs.blinding_factors() - 1);
let modulo = (capacity / max_rows) + 1;
let mut fixed = vec![];
for _ in 0..modulo {