ci: update version string in docs

docs/python/src/conf.py

@@ -1,7 +1,7 @@
 import ezkl
 
 project = 'ezkl'
-release = '0.0.0'
+release = '21.0.3'
 version = release
 
 

src/bindings/python.rs

@@ -1,34 +1,34 @@
-use crate::circuit::modules::polycommit::PolyCommitChip;
-use crate::circuit::modules::poseidon::{
-    spec::{PoseidonSpec, POSEIDON_RATE, POSEIDON_WIDTH},
-    PoseidonChip,
-};
-use crate::circuit::modules::Module;
+use crate::Commitments;
+use crate::RunArgs;
 use crate::circuit::CheckMode;
 use crate::circuit::InputType;
+use crate::circuit::modules::Module;
+use crate::circuit::modules::polycommit::PolyCommitChip;
+use crate::circuit::modules::poseidon::{
+    PoseidonChip,
+    spec::{POSEIDON_RATE, POSEIDON_WIDTH, PoseidonSpec},
+};
 use crate::commands::*;
-use crate::fieldutils::{felt_to_integer_rep, integer_rep_to_felt, IntegerRep};
+use crate::fieldutils::{IntegerRep, felt_to_integer_rep, integer_rep_to_felt};
 use crate::graph::TestDataSource;
 use crate::graph::{
-    quantize_float, scale_to_multiplier, GraphCircuit, GraphSettings, Model, Visibility,
+    GraphCircuit, GraphSettings, Model, Visibility, quantize_float, scale_to_multiplier,
 };
 use crate::pfsys::evm::aggregation_kzg::AggregationCircuit;
 use crate::pfsys::{
-    load_pk, load_vk, save_params, save_vk, srs::gen_srs as ezkl_gen_srs, srs::load_srs_prover,
-    ProofType, TranscriptType,
+    ProofType, TranscriptType, load_pk, load_vk, save_params, save_vk,
+    srs::gen_srs as ezkl_gen_srs, srs::load_srs_prover,
 };
-use crate::Commitments;
-use crate::RunArgs;
 use halo2_proofs::poly::ipa::commitment::IPACommitmentScheme;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2curves::bn256::{Bn256, Fq, Fr, G1Affine, G1};
+use halo2curves::bn256::{Bn256, Fq, Fr, G1, G1Affine};
 use pyo3::exceptions::{PyIOError, PyRuntimeError};
 use pyo3::prelude::*;
 use pyo3::wrap_pyfunction;
 use pyo3_log;
 use pyo3_stub_gen::{
-    define_stub_info_gatherer, derive::gen_stub_pyclass, derive::gen_stub_pyclass_enum,
-    derive::gen_stub_pyfunction, TypeInfo,
+    TypeInfo, define_stub_info_gatherer, derive::gen_stub_pyclass, derive::gen_stub_pyclass_enum,
+    derive::gen_stub_pyfunction,
 };
 use snark_verifier::util::arithmetic::PrimeField;
 use std::collections::HashSet;
@@ -962,6 +962,8 @@ fn gen_settings(
     output=PathBuf::from(DEFAULT_SETTINGS),
     variables=Vec::from([("batch_size".to_string(), 1)]),
     seed=DEFAULT_SEED.parse().unwrap(),
+    min=None, 
+    max=None
 ))]
 #[gen_stub_pyfunction]
 fn gen_random_data(
@@ -969,8 +971,10 @@ fn gen_random_data(
     output: PathBuf,
     variables: Vec<(String, usize)>,
     seed: u64,
+    min: Option<f32>,
+    max: Option<f32>,
 ) -> Result<bool, PyErr> {
-    crate::execute::gen_random_data(model, output, variables, seed).map_err(|e| {
+    crate::execute::gen_random_data(model, output, variables, seed, min, max).map_err(|e| {
         let err_str = format!("Failed to generate settings: {}", e);
         PyRuntimeError::new_err(err_str)
     })?;

src/commands.rs

@@ -443,6 +443,12 @@ pub enum Commands {
         /// random seed for reproducibility (optional)
         #[arg(long, value_hint = clap::ValueHint::Other, default_value = DEFAULT_SEED)]
         seed: u64,
+        /// min value for random data
+        #[arg(long, value_hint = clap::ValueHint::Other)]
+        min: Option<f32>,
+        /// max value for random data
+        #[arg(long, value_hint = clap::ValueHint::Other)]
+        max: Option<f32>,
     },
     /// Calibrates the proving scale, lookup bits and logrows from a circuit settings file.
     CalibrateSettings {

src/execute.rs

@@ -45,6 +45,7 @@ use halo2curves::serde::SerdeObject;
 use indicatif::{ProgressBar, ProgressStyle};
 use instant::Instant;
 use itertools::Itertools;
+use lazy_static::lazy_static;
 use log::debug;
 use log::{info, trace, warn};
 use serde::Serialize;
@@ -65,8 +66,6 @@ use thiserror::Error;
 use tract_onnx::prelude::IntoTensor;
 use tract_onnx::prelude::Tensor as TractTensor;
 
-use lazy_static::lazy_static;
-
 lazy_static! {
     #[derive(Debug)]
     /// The path to the ezkl related data.
@@ -138,11 +137,15 @@ pub async fn run(command: Commands) -> Result<String, EZKLError> {
             data,
             variables,
             seed,
+            min,
+            max,
         } => gen_random_data(
             model.unwrap_or(DEFAULT_MODEL.into()),
             data.unwrap_or(DEFAULT_DATA.into()),
             variables,
             seed,
+            min,
+            max,
         ),
         Commands::CalibrateSettings {
             model,
@@ -840,6 +843,8 @@ pub(crate) fn gen_random_data(
     data_path: PathBuf,
     variables: Vec<(String, usize)>,
     seed: u64,
+    min: Option<f32>,
+    max: Option<f32>,
 ) -> Result<String, EZKLError> {
     let mut file = std::fs::File::open(&model_path).map_err(|e| {
         crate::graph::errors::GraphError::ReadWriteFileError(
@@ -858,22 +863,32 @@ pub(crate) fn gen_random_data(
         .collect::<tract_onnx::prelude::TractResult<Vec<_>>>()
         .map_err(|e| EZKLError::from(e.to_string()))?;
 
+    let min = min.unwrap_or(0.0);
+    let max = max.unwrap_or(1.0);
+
     /// Generates a random tensor of a given size and type.
     fn random(
         sizes: &[usize],
         datum_type: tract_onnx::prelude::DatumType,
         seed: u64,
+        min: f32,
+        max: f32,
     ) -> TractTensor {
         use rand::{Rng, SeedableRng};
         let mut rng = rand::rngs::StdRng::seed_from_u64(seed);
 
         let mut tensor = TractTensor::zero::<f32>(sizes).unwrap();
         let slice = tensor.as_slice_mut::<f32>().unwrap();
-        slice.iter_mut().for_each(|x| *x = rng.r#gen());
+        slice.iter_mut().for_each(|x| *x = rng.gen_range(min..max));
         tensor.cast_to_dt(datum_type).unwrap().into_owned()
     }
 
-    fn tensor_for_fact(fact: &tract_onnx::prelude::TypedFact, seed: u64) -> TractTensor {
+    fn tensor_for_fact(
+        fact: &tract_onnx::prelude::TypedFact,
+        seed: u64,
+        min: f32,
+        max: f32,
+    ) -> TractTensor {
         if let Some(value) = &fact.konst {
             return value.clone().into_tensor();
         }
@@ -884,12 +899,14 @@ pub(crate) fn gen_random_data(
                 .expect("Expected concrete shape, found: {fact:?}"),
             fact.datum_type,
             seed,
+            min,
+            max,
         )
     }
 
     let generated = input_facts
         .iter()
-        .map(|v| tensor_for_fact(v, seed))
+        .map(|v| tensor_for_fact(v, seed, min, max))
         .collect_vec();
 
     let data = GraphData::from_tract_data(&generated)?;