feat: dynamic lookups (#727)

BREAKING CHANGE: python and wasm felt utilities have new names

.github/workflows/rust.yml

@@ -500,7 +500,7 @@ jobs:
 
   prove-and-verify-aggr-tests:
     runs-on: large-self-hosted
-    needs: [build, library-tests, python-tests]
+    needs: [build, library-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
@@ -513,11 +513,11 @@ jobs:
           crate: cargo-nextest
           locked: true
       - name: KZG )tests
-        run: cargo nextest run --release --verbose tests_aggr::kzg_aggr_prove_and_verify_  --test-threads 8 -- --include-ignored
+        run: cargo nextest run --release --verbose tests_aggr::kzg_aggr_prove_and_verify_  --test-threads 4 -- --include-ignored
 
   prove-and-verify-aggr-evm-tests:
     runs-on: large-self-hosted
-    needs: [build, library-tests, python-tests]
+    needs: [build, library-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1

Cargo.lock

@@ -2263,7 +2263,7 @@ dependencies = [
 [[package]]
 name = "halo2_gadgets"
 version = "0.2.0"
-source = "git+https://github.com/zkonduit/halo2?branch=main#fe7522c85c8c434d7ceb9f663b0fb51909b9994f"
+source = "git+https://github.com/zkonduit/halo2?branch=main#4d7e6ddac661283e2b73c551b2e8f0011cedd50f"
 dependencies = [
  "arrayvec 0.7.4",
  "bitvec 1.0.1",
@@ -2280,7 +2280,7 @@ dependencies = [
 [[package]]
 name = "halo2_proofs"
 version = "0.3.0"
-source = "git+https://github.com/zkonduit/halo2?branch=main#fe7522c85c8c434d7ceb9f663b0fb51909b9994f"
+source = "git+https://github.com/zkonduit/halo2?branch=main#4d7e6ddac661283e2b73c551b2e8f0011cedd50f"
 dependencies = [
  "blake2b_simd",
  "env_logger",

examples/notebooks/data_attest_hashed.ipynb

@@ -309,7 +309,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "print(ezkl.string_to_felt(res['processed_outputs']['poseidon_hash'][0]))"
+                "print(ezkl.felt_to_big_endian(res['processed_outputs']['poseidon_hash'][0]))"
             ]
         },
         {
@@ -325,7 +325,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "from web3 import Web3, HTTPProvider, utils\n",
+                "from web3 import Web3, HTTPProvider\n",
                 "from solcx import compile_standard\n",
                 "from decimal import Decimal\n",
                 "import json\n",
@@ -338,7 +338,7 @@
                 "\n",
                 "def test_on_chain_data(res):\n",
                 "    # Step 0: Convert the tensor to a flat list\n",
-                "    data = [int(ezkl.string_to_felt(res['processed_outputs']['poseidon_hash'][0]), 0)]\n",
+                "    data = [int(ezkl.felt_to_big_endian(res['processed_outputs']['poseidon_hash'][0]), 0)]\n",
                 "\n",
                 "    # Step 1: Prepare the data\n",
                 "    # Step 2: Prepare and compile the contract.\n",
@@ -648,7 +648,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.13"
+            "version": "3.9.15"
         },
         "orig_nbformat": 4
     },

examples/notebooks/ezkl_demo.ipynb

@@ -695,7 +695,7 @@
         "formatted_output = \"[\"\n",
         "for i, value in enumerate(proof[\"instances\"]):\n",
         "    for j, field_element in enumerate(value):\n",
-        "        onchain_input_array.append(ezkl.string_to_felt(field_element))\n",
+        "        onchain_input_array.append(ezkl.felt_to_big_endian(field_element))\n",
         "        formatted_output += str(onchain_input_array[-1])\n",
         "        if j != len(value) - 1:\n",
         "            formatted_output += \", \"\n",
@@ -705,7 +705,7 @@
         "# copy them over to remix and see if they verify\n",
         "# What happens when you change a value?\n",
         "print(\"pubInputs: \", formatted_output)\n",
-        "print(\"proof: \", \"0x\" + proof[\"proof\"])"
+        "print(\"proof: \", proof[\"proof\"])"
       ]
     },
     {

examples/notebooks/set_membership.ipynb

@@ -122,8 +122,8 @@
         "# Loop through each element in the y tensor\n",
         "for e in y_input:\n",
         "    # Apply the custom function and append the result to the list\n",
-        "    print(ezkl.float_to_string(e,7))\n",
-        "    result.append(ezkl.poseidon_hash([ezkl.float_to_string(e, 7)])[0])\n",
+        "    print(ezkl.float_to_felt(e,7))\n",
+        "    result.append(ezkl.poseidon_hash([ezkl.float_to_felt(e, 7)])[0])\n",
         "\n",
         "y = y.unsqueeze(0)\n",
         "y = y.reshape(1, 9)\n",

examples/notebooks/solvency.ipynb

@@ -126,7 +126,7 @@
         "# Loop through each element in the y tensor\n",
         "for e in user_preimages:\n",
         "    # Apply the custom function and append the result to the list\n",
-        "    users.append(ezkl.poseidon_hash([ezkl.float_to_string(e, 0)])[0])\n",
+        "    users.append(ezkl.poseidon_hash([ezkl.float_to_felt(e, 0)])[0])\n",
         "\n",
         "users_t = torch.tensor(user_preimages)\n",
         "users_t = users_t.reshape(1, 6)\n",
@@ -303,7 +303,7 @@
         "# we force the output to be 1 this corresponds to the solvency test being true -- and we set this to a fixed vis output\n",
         "# this means that the output is fixed and the verifier can see it but that if the input is not in the set the output will not be 0 and the verifier will reject\n",
         "witness = json.load(open(witness_path, \"r\"))\n",
-        "witness[\"outputs\"][0] = [ezkl.float_to_string(1.0, 0)]\n",
+        "witness[\"outputs\"][0] = [ezkl.float_to_felt(1.0, 0)]\n",
         "json.dump(witness, open(witness_path, \"w\"))"
       ]
     },
@@ -417,7 +417,7 @@
         "# we force the output to be 1 this corresponds to the solvency test being true -- and we set this to a fixed vis output\n",
         "# this means that the output is fixed and the verifier can see it but that if the input is not in the set the output will not be 0 and the verifier will reject\n",
         "witness = json.load(open(witness_path, \"r\"))\n",
-        "witness[\"outputs\"][0] = [ezkl.float_to_string(1.0, 0)]\n",
+        "witness[\"outputs\"][0] = [ezkl.float_to_felt(1.0, 0)]\n",
         "json.dump(witness, open(witness_path, \"w\"))\n"
       ]
     },
@@ -510,7 +510,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.13"
+      "version": "3.9.15"
     }
   },
   "nbformat": 4,

examples/notebooks/tictactoe_autoencoder.ipynb

@@ -633,7 +633,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales = [4])"
+                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales = [11])"
             ]
         },
         {
@@ -664,7 +664,6 @@
                 "    compiled_model_path,\n",
                 "    vk_path,\n",
                 "    pk_path,\n",
-                "    \n",
                 ")"
             ]
         },

examples/notebooks/world_rotation.ipynb

@@ -503,11 +503,11 @@
     "pyplot.arrow(0, 0, 1, 0, width=0.02, alpha=0.5)\n",
     "pyplot.arrow(0, 0, 0, 1, width=0.02, alpha=0.5)\n",
     "\n",
-    "arrow_x = ezkl.string_to_float(witness['outputs'][0][0], out_scale)\n",
-    "arrow_y = ezkl.string_to_float(witness['outputs'][0][1], out_scale)\n",
+    "arrow_x = ezkl.felt_to_float(witness['outputs'][0][0], out_scale)\n",
+    "arrow_y = ezkl.felt_to_float(witness['outputs'][0][1], out_scale)\n",
     "pyplot.arrow(0, 0, arrow_x, arrow_y, width=0.02)\n",
-    "arrow_x = ezkl.string_to_float(witness['outputs'][0][2], out_scale)\n",
-    "arrow_y = ezkl.string_to_float(witness['outputs'][0][3], out_scale)\n",
+    "arrow_x = ezkl.felt_to_float(witness['outputs'][0][2], out_scale)\n",
+    "arrow_y = ezkl.felt_to_float(witness['outputs'][0][3], out_scale)\n",
     "pyplot.arrow(0, 0, arrow_x, arrow_y, width=0.02)"
    ]
   }

src/circuit/ops/chip.rs

@@ -19,8 +19,8 @@ use serde::{Deserialize, Serialize};
 use tosubcommand::ToFlags;
 
 use crate::{
-    circuit::ops::base::BaseOp,
     circuit::{
+        ops::base::BaseOp,
         table::{Range, RangeCheck, Table},
         utils,
     },
@@ -198,6 +198,9 @@ pub struct BaseConfig<F: PrimeField + TensorType + PartialOrd> {
     pub lookup_input: VarTensor,
     /// the (currently singular) output of the accumulated operations.
     pub output: VarTensor,
+    /// The VarTensor reserved for dynamic lookup operations (could be an element of inputs or the same as output)
+    /// Note that you should be careful to ensure that the lookup_output is not simultaneously assigned to by other non-lookup operations eg. in the case of composite ops.
+    pub dynamic_lookup_tables: Vec<VarTensor>,
     /// the VarTensor reserved for lookup operations (could be an element of inputs or the same as output)
     /// Note that you should be careful to ensure that the lookup_output is not simultaneously assigned to by other non-lookup operations eg. in the case of composite ops.
     pub lookup_output: VarTensor,
@@ -207,6 +210,10 @@ pub struct BaseConfig<F: PrimeField + TensorType + PartialOrd> {
     pub selectors: BTreeMap<(BaseOp, usize, usize), Selector>,
     /// [Selector]s generated when configuring the layer. We use a [BTreeMap] as we expect to configure many lookup ops.
     pub lookup_selectors: BTreeMap<(LookupOp, usize, usize), Selector>,
+    /// [Selector]s generated when configuring the layer. We use a [BTreeMap] as we expect to configure many dynamic lookup ops.
+    pub dynamic_lookup_selectors: BTreeMap<(usize, usize), Vec<Selector>>,
+    ///
+    pub dynamic_table_selectors: Vec<Selector>,
     ///
     pub tables: BTreeMap<LookupOp, Table<F>>,
     ///
@@ -228,9 +235,12 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
             lookup_input: dummy_var.clone(),
             output: dummy_var.clone(),
             lookup_output: dummy_var.clone(),
+            dynamic_lookup_tables: vec![VarTensor::dummy(col_size, 2), dummy_var.clone()],
             lookup_index: dummy_var,
             selectors: BTreeMap::new(),
             lookup_selectors: BTreeMap::new(),
+            dynamic_lookup_selectors: BTreeMap::new(),
+            dynamic_table_selectors: vec![],
             range_check_selectors: BTreeMap::new(),
             tables: BTreeMap::new(),
             range_checks: BTreeMap::new(),
@@ -376,10 +386,13 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
             selectors,
             lookup_selectors: BTreeMap::new(),
             range_check_selectors: BTreeMap::new(),
+            dynamic_lookup_selectors: BTreeMap::new(),
             inputs: inputs.to_vec(),
             lookup_input: VarTensor::Empty,
             lookup_output: VarTensor::Empty,
             lookup_index: VarTensor::Empty,
+            dynamic_table_selectors: vec![],
+            dynamic_lookup_tables: vec![],
             tables: BTreeMap::new(),
             range_checks: BTreeMap::new(),
             output: output.clone(),
@@ -403,8 +416,6 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
     where
         F: Field,
     {
-        let mut selectors = BTreeMap::new();
-
         if !index.is_advice() {
             return Err("wrong input type for lookup index".into());
         }
@@ -514,10 +525,10 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
                         res
                     });
                 }
-                selectors.insert((nl.clone(), x, y), multi_col_selector);
+                self.lookup_selectors
+                    .insert((nl.clone(), x, y), multi_col_selector);
             }
         }
-        self.lookup_selectors.extend(selectors);
         // if we haven't previously initialized the input/output, do so now
         if let VarTensor::Empty = self.lookup_input {
             debug!("assigning lookup input");
@@ -536,17 +547,96 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
 
     /// Configures and creates lookup selectors
     #[allow(clippy::too_many_arguments)]
-    pub fn configure_range_check(
+    pub fn configure_dynamic_lookup(
         &mut self,
         cs: &mut ConstraintSystem<F>,
-        input: &VarTensor,
-        range: Range,
+        lookups: &[VarTensor; 2],
+        tables: &[VarTensor; 2],
     ) -> Result<(), Box<dyn Error>>
     where
         F: Field,
     {
-        let mut selectors = BTreeMap::new();
+        for l in lookups.iter() {
+            if !l.is_advice() {
+                return Err("wrong input type for dynamic lookup".into());
+            }
+        }
 
+        for t in tables.iter() {
+            if !t.is_advice() || t.num_blocks() > 1 || t.num_inner_cols() > 1 {
+                return Err("wrong table type for dynamic lookup".into());
+            }
+        }
+
+        let one = Expression::Constant(F::ONE);
+
+        let s_ltable = cs.complex_selector();
+
+        for x in 0..lookups[0].num_blocks() {
+            for y in 0..lookups[0].num_inner_cols() {
+                let s_lookup = cs.complex_selector();
+
+                cs.lookup_any("lookup", |cs| {
+                    let s_lookupq = cs.query_selector(s_lookup);
+                    let mut expression = vec![];
+                    let s_ltableq = cs.query_selector(s_ltable);
+                    let mut lookup_queries = vec![one.clone()];
+
+                    for lookup in lookups {
+                        lookup_queries.push(match lookup {
+                            VarTensor::Advice { inner: advices, .. } => {
+                                cs.query_advice(advices[x][y], Rotation(0))
+                            }
+                            _ => unreachable!(),
+                        });
+                    }
+
+                    let mut table_queries = vec![one.clone()];
+                    for table in tables {
+                        table_queries.push(match table {
+                            VarTensor::Advice { inner: advices, .. } => {
+                                cs.query_advice(advices[0][0], Rotation(0))
+                            }
+                            _ => unreachable!(),
+                        });
+                    }
+
+                    let lhs = lookup_queries.into_iter().map(|c| c * s_lookupq.clone());
+                    let rhs = table_queries.into_iter().map(|c| c * s_ltableq.clone());
+                    expression.extend(lhs.zip(rhs));
+
+                    expression
+                });
+                self.dynamic_lookup_selectors
+                    .entry((x, y))
+                    .or_default()
+                    .push(s_lookup);
+            }
+        }
+        self.dynamic_table_selectors.push(s_ltable);
+
+        // if we haven't previously initialized the input/output, do so now
+        if self.dynamic_lookup_tables.is_empty() {
+            debug!("assigning dynamic lookup table");
+            self.dynamic_lookup_tables = tables.to_vec();
+        }
+
+        Ok(())
+    }
+
+    /// Configures and creates lookup selectors
+    #[allow(clippy::too_many_arguments)]
+    pub fn configure_range_check(
+        &mut self,
+        cs: &mut ConstraintSystem<F>,
+        input: &VarTensor,
+        index: &VarTensor,
+        range: Range,
+        logrows: usize,
+    ) -> Result<(), Box<dyn Error>>
+    where
+        F: Field,
+    {
         if !input.is_advice() {
             return Err("wrong input type for lookup input".into());
         }
@@ -556,7 +646,7 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
         let range_check =
             if let std::collections::btree_map::Entry::Vacant(e) = self.range_checks.entry(range) {
                 // as all tables have the same input we see if there's another table who's input we can reuse
-                let range_check = RangeCheck::<F>::configure(cs, range);
+                let range_check = RangeCheck::<F>::configure(cs, range, logrows);
                 e.insert(range_check.clone());
                 range_check
             } else {
@@ -565,41 +655,74 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
 
         for x in 0..input.num_blocks() {
             for y in 0..input.num_inner_cols() {
-                let single_col_sel = cs.complex_selector();
+                let len = range_check.selector_constructor.degree;
+                let multi_col_selector = cs.complex_selector();
 
-                cs.lookup("", |cs| {
-                    let mut res = vec![];
-                    let sel = cs.query_selector(single_col_sel);
+                for (col_idx, input_col) in range_check.inputs.iter().enumerate() {
+                    cs.lookup("", |cs| {
+                        let mut res = vec![];
+                        let sel = cs.query_selector(multi_col_selector);
 
-                    let input_query = match &input {
-                        VarTensor::Advice { inner: advices, .. } => {
-                            cs.query_advice(advices[x][y], Rotation(0))
-                        }
-                        _ => unreachable!(),
-                    };
+                        let synthetic_sel = match len {
+                            1 => Expression::Constant(F::from(1)),
+                            _ => match index {
+                                VarTensor::Advice { inner: advices, .. } => {
+                                    cs.query_advice(advices[x][y], Rotation(0))
+                                }
+                                _ => unreachable!(),
+                            },
+                        };
 
-                    let default_x = range_check.get_first_element();
+                        let input_query = match &input {
+                            VarTensor::Advice { inner: advices, .. } => {
+                                cs.query_advice(advices[x][y], Rotation(0))
+                            }
+                            _ => unreachable!(),
+                        };
 
-                    let not_sel = Expression::Constant(F::ONE) - sel.clone();
+                        let default_x = range_check.get_first_element(col_idx);
 
-                    res.extend([(
-                        sel.clone() * input_query.clone()
-                            + not_sel.clone() * Expression::Constant(default_x),
-                        range_check.input,
-                    )]);
+                        let col_expr = sel.clone()
+                            * range_check
+                                .selector_constructor
+                                .get_expr_at_idx(col_idx, synthetic_sel);
 
-                    res
-                });
-                selectors.insert((range, x, y), single_col_sel);
+                        let multiplier = range_check
+                            .selector_constructor
+                            .get_selector_val_at_idx(col_idx);
+
+                        let not_expr = Expression::Constant(multiplier) - col_expr.clone();
+
+                        res.extend([(
+                            col_expr.clone() * input_query.clone()
+                                + not_expr.clone() * Expression::Constant(default_x),
+                            *input_col,
+                        )]);
+
+                        log::trace!("---------------- col {:?} ------------------", col_idx,);
+                        log::trace!("expr: {:?}", col_expr,);
+                        log::trace!("multiplier: {:?}", multiplier);
+                        log::trace!("not_expr: {:?}", not_expr);
+                        log::trace!("default x: {:?}", default_x);
+
+                        res
+                    });
+                }
+                self.range_check_selectors
+                    .insert((range, x, y), multi_col_selector);
             }
         }
-        self.range_check_selectors.extend(selectors);
         // if we haven't previously initialized the input/output, do so now
         if let VarTensor::Empty = self.lookup_input {
             debug!("assigning lookup input");
             self.lookup_input = input.clone();
         }
 
+        if let VarTensor::Empty = self.lookup_index {
+            debug!("assigning lookup index");
+            self.lookup_index = index.clone();
+        }
+
         Ok(())
     }
 

src/circuit/ops/hybrid.rs

@@ -277,7 +277,7 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for HybridOp {
                 ..
             } => {
                 if denom.0.fract() == 0.0 && *use_range_check_for_int {
-                    layouts::div(
+                    layouts::loop_div(
                         config,
                         region,
                         values[..].try_into()?,

src/circuit/ops/layouts.rs

@@ -18,10 +18,7 @@ use super::{
     region::RegionCtx,
 };
 use crate::{
-    circuit::{
-        ops::base::BaseOp,
-        utils::{self},
-    },
+    circuit::{ops::base::BaseOp, utils},
     fieldutils::{felt_to_i128, i128_to_felt},
     tensor::{
         get_broadcasted_shape,
@@ -54,6 +51,41 @@ pub fn overflowed_len(starting_idx: usize, mut total_len: usize, column_len: usi
     total_len
 }
 
+/// Same as div but splits the division into N parts
+pub fn loop_div<F: PrimeField + TensorType + PartialOrd>(
+    config: &BaseConfig<F>,
+    region: &mut RegionCtx<F>,
+    value: &[ValTensor<F>; 1],
+    divisor: F,
+) -> Result<ValTensor<F>, Box<dyn Error>> {
+    if divisor == F::ONE {
+        return Ok(value[0].clone());
+    }
+
+    // if integer val is divisible by 2, we can use a faster method and div > F::S
+    let mut divisor = divisor;
+    let mut num_parts = 1;
+
+    while felt_to_i128(divisor) % 2 == 0 && felt_to_i128(divisor) > (2_i128.pow(F::S - 4)) {
+        divisor = i128_to_felt(felt_to_i128(divisor) / 2);
+        num_parts += 1;
+    }
+
+    let output = div(config, region, value, divisor)?;
+    if num_parts == 1 {
+        return Ok(output);
+    }
+
+    let divisor_int = 2_i128.pow(num_parts - 1);
+    let divisor_felt = i128_to_felt(divisor_int);
+    if divisor_int <= 2_i128.pow(F::S - 3) {
+        div(config, region, &[output], divisor_felt)
+    } else {
+        // keep splitting the divisor until it satisfies the condition
+        loop_div(config, region, &[output], divisor_felt)
+    }
+}
+
 /// Div accumulated layout
 pub fn div<F: PrimeField + TensorType + PartialOrd>(
     config: &BaseConfig<F>,
@@ -61,6 +93,10 @@ pub fn div<F: PrimeField + TensorType + PartialOrd>(
     value: &[ValTensor<F>; 1],
     div: F,
 ) -> Result<ValTensor<F>, Box<dyn Error>> {
+    if div == F::ONE {
+        return Ok(value[0].clone());
+    }
+
     let input = value[0].clone();
     let input_dims = input.dims();
 
@@ -88,6 +124,8 @@ pub fn div<F: PrimeField + TensorType + PartialOrd>(
         .into()
     };
     claimed_output.reshape(input_dims)?;
+    region.assign(&config.output, &claimed_output)?;
+    region.increment(claimed_output.len());
 
     let product = pairwise(
         config,
@@ -96,8 +134,6 @@ pub fn div<F: PrimeField + TensorType + PartialOrd>(
         BaseOp::Mult,
     )?;
 
-    log::debug!("product: {:?}", product.get_int_evals()?);
-
     let diff_with_input = pairwise(
         config,
         region,
@@ -115,6 +151,46 @@ pub fn div<F: PrimeField + TensorType + PartialOrd>(
     Ok(claimed_output)
 }
 
+fn recip_int<F: PrimeField + TensorType + PartialOrd>(
+    config: &BaseConfig<F>,
+    region: &mut RegionCtx<F>,
+    input: &[ValTensor<F>; 1],
+) -> Result<ValTensor<F>, Box<dyn Error>> {
+    // assert is boolean
+    let zero_inverse_val = tensor::ops::nonlinearities::zero_recip(1.0)[0];
+    // get values where input is 0
+    let zero_mask = equals_zero(config, region, input)?;
+
+    let one_minus_zero_mask = pairwise(
+        config,
+        region,
+        &[
+            zero_mask.clone(),
+            ValTensor::from(Tensor::from([ValType::Constant(F::ONE)].into_iter())),
+        ],
+        BaseOp::Sub,
+    )?;
+
+    let zero_inverse_val = pairwise(
+        config,
+        region,
+        &[
+            zero_mask,
+            ValTensor::from(Tensor::from(
+                [ValType::Constant(i128_to_felt(zero_inverse_val))].into_iter(),
+            )),
+        ],
+        BaseOp::Mult,
+    )?;
+
+    pairwise(
+        config,
+        region,
+        &[one_minus_zero_mask, zero_inverse_val],
+        BaseOp::Add,
+    )
+}
+
 /// recip accumulated layout
 pub fn recip<F: PrimeField + TensorType + PartialOrd>(
     config: &BaseConfig<F>,
@@ -123,10 +199,23 @@ pub fn recip<F: PrimeField + TensorType + PartialOrd>(
     input_scale: F,
     output_scale: F,
 ) -> Result<ValTensor<F>, Box<dyn Error>> {
+    if output_scale == F::ONE || output_scale == F::ZERO {
+        return recip_int(config, region, value);
+    }
+
     let input = value[0].clone();
     let input_dims = input.dims();
 
-    let range_check_bracket = felt_to_i128(output_scale * input_scale) / 2;
+    let integer_input_scale = felt_to_i128(input_scale);
+    let integer_output_scale = felt_to_i128(output_scale);
+
+    // range_check_bracket is min of input_scale * output_scale and 2^F::S - 3
+    let range_check_len = std::cmp::min(integer_output_scale, 2_i128.pow(F::S - 4));
+
+    let input_scale_ratio =
+        i128_to_felt(integer_input_scale * integer_output_scale / range_check_len);
+
+    let range_check_bracket = range_check_len / 2;
 
     let is_assigned = !input.any_unknowns()?;
 
@@ -149,6 +238,8 @@ pub fn recip<F: PrimeField + TensorType + PartialOrd>(
         .into()
     };
     claimed_output.reshape(input_dims)?;
+    let claimed_output = region.assign(&config.output, &claimed_output)?;
+    region.increment(claimed_output.len());
 
     // this is now of scale 2 * scale
     let product = pairwise(
@@ -158,15 +249,46 @@ pub fn recip<F: PrimeField + TensorType + PartialOrd>(
         BaseOp::Mult,
     )?;
 
-    log::debug!("product: {:?}", product.get_int_evals()?);
+    // divide by input_scale
+    let rebased_div = loop_div(config, region, &[product], input_scale_ratio)?;
 
-    log::debug!("range_check_bracket: {:?}", range_check_bracket);
+    let zero_inverse_val =
+        tensor::ops::nonlinearities::zero_recip(felt_to_i128(output_scale) as f64)[0];
+    let zero_inverse =
+        Tensor::from([ValType::Constant(i128_to_felt::<F>(zero_inverse_val))].into_iter());
+
+    let equal_zero_mask = equals_zero(config, region, &[input.clone()])?;
+
+    let equal_inverse_mask = equals(
+        config,
+        region,
+        &[claimed_output.clone(), zero_inverse.into()],
+    )?;
+
+    // assert the two masks are equal
+    enforce_equality(
+        config,
+        region,
+        &[equal_zero_mask.clone(), equal_inverse_mask],
+    )?;
+
+    let unit_scale = Tensor::from([ValType::Constant(i128_to_felt(range_check_len))].into_iter());
+
+    let unit_mask = pairwise(
+        config,
+        region,
+        &[equal_zero_mask, unit_scale.into()],
+        BaseOp::Mult,
+    )?;
+
+    // now add the unit mask to the rebased_div
+    let rebased_offset_div = pairwise(config, region, &[rebased_div, unit_mask], BaseOp::Add)?;
 
     // at most the error should be in the original unit scale's range
     range_check(
         config,
         region,
-        &[product],
+        &[rebased_offset_div],
         &(range_check_bracket, 3 * range_check_bracket),
     )?;
 
@@ -793,6 +915,78 @@ fn one_hot<F: PrimeField + TensorType + PartialOrd>(
     Ok(assigned_output)
 }
 
+/// Dynamic lookup
+pub fn dynamic_lookup<F: PrimeField + TensorType + PartialOrd>(
+    config: &BaseConfig<F>,
+    region: &mut RegionCtx<F>,
+    lookups: &[ValTensor<F>; 2],
+    tables: &[ValTensor<F>; 2],
+) -> Result<(ValTensor<F>, ValTensor<F>), Box<dyn Error>> {
+    // if not all lookups same length err
+    if lookups[0].len() != lookups[1].len() {
+        return Err("lookups must be same length".into());
+    }
+
+    // if not all inputs same length err
+    if tables[0].len() != tables[1].len() {
+        return Err("inputs must be same length".into());
+    }
+
+    // now assert the inputs of a smaller length than the lookups
+    if tables[0].len() > tables[0].len() {
+        return Err("inputs must be smaller length than dynamic lookups".into());
+    }
+
+    let (lookup_0, lookup_1) = (lookups[0].clone(), lookups[1].clone());
+    let (table_0, table_1) = (tables[0].clone(), tables[1].clone());
+
+    let table_0 = region.assign_dynamic_lookup(&config.dynamic_lookup_tables[0], &table_0)?;
+    let _table_1 = region.assign_dynamic_lookup(&config.dynamic_lookup_tables[1], &table_1)?;
+    let table_len = table_0.len();
+
+    let lookup_0 = region.assign(&config.inputs[0], &lookup_0)?;
+    let lookup_1 = region.assign(&config.inputs[1], &lookup_1)?;
+
+    let lookup_len = lookup_0.len();
+
+    if !region.is_dummy() {
+        (0..table_len)
+            .map(|i| {
+                let dynamic_lookup_index = region.dynamic_lookup_index();
+                let table_selector = config.dynamic_table_selectors[dynamic_lookup_index];
+                let (_, _, z) = config.dynamic_lookup_tables[0]
+                    .cartesian_coord(region.dynamic_lookup_col_coord() + i);
+                region.enable(Some(&table_selector), z)?;
+                Ok(())
+            })
+            .collect::<Result<Vec<_>, Box<dyn Error>>>()?;
+    }
+
+    if !region.is_dummy() {
+        // Enable the selectors
+        (0..lookup_len)
+            .map(|i| {
+                let (x, y, z) = config.inputs[0].cartesian_coord(region.linear_coord() + i);
+                let dynamic_lookup_index = region.dynamic_lookup_index();
+                let lookup_selector = config
+                    .dynamic_lookup_selectors
+                    .get(&(x, y))
+                    .ok_or("missing selectors")?[dynamic_lookup_index];
+
+                region.enable(Some(&lookup_selector), z)?;
+
+                Ok(())
+            })
+            .collect::<Result<Vec<_>, Box<dyn Error>>>()?;
+    }
+
+    region.increment_dynamic_lookup_col_coord(table_len);
+    region.increment_dynamic_lookup_index(1);
+    region.increment(lookup_len);
+
+    Ok((lookup_0, lookup_1))
+}
+
 /// One hot accumulated layout
 pub fn one_hot_axis<F: PrimeField + TensorType + PartialOrd>(
     config: &BaseConfig<F>,
@@ -1675,9 +1869,23 @@ pub fn equals<F: PrimeField + TensorType + PartialOrd>(
     values: &[ValTensor<F>; 2],
 ) -> Result<ValTensor<F>, Box<dyn Error>> {
     let diff = pairwise(config, region, values, BaseOp::Sub)?;
-    let diff_inverse = diff.inverse()?;
-    let product_diff_and_invert =
-        pairwise(config, region, &[diff.clone(), diff_inverse], BaseOp::Mult)?;
+    equals_zero(config, region, &[diff])
+}
+
+/// Equality boolean operation
+pub fn equals_zero<F: PrimeField + TensorType + PartialOrd>(
+    config: &BaseConfig<F>,
+    region: &mut RegionCtx<F>,
+    values: &[ValTensor<F>; 1],
+) -> Result<ValTensor<F>, Box<dyn Error>> {
+    let values = values[0].clone();
+    let values_inverse = values.inverse()?;
+    let product_values_and_invert = pairwise(
+        config,
+        region,
+        &[values.clone(), values_inverse],
+        BaseOp::Mult,
+    )?;
 
     // constant of 1
     let mut ones = Tensor::from(vec![ValType::Constant(F::from(1))].into_iter());
@@ -1687,12 +1895,12 @@ pub fn equals<F: PrimeField + TensorType + PartialOrd>(
     let output = pairwise(
         config,
         region,
-        &[ones.into(), product_diff_and_invert],
+        &[ones.into(), product_values_and_invert],
         BaseOp::Sub,
     )?;
 
     // take the product of diff and output
-    let prod_check = pairwise(config, region, &[diff, output.clone()], BaseOp::Mult)?;
+    let prod_check = pairwise(config, region, &[values, output.clone()], BaseOp::Mult)?;
 
     is_zero_identity(config, region, &[prod_check], false)?;
 
@@ -1858,7 +2066,7 @@ pub fn sumpool<F: PrimeField + TensorType + PartialOrd>(
     last_elem.reshape(&[&[batch_size, image_channels], shape].concat())?;
 
     if normalized {
-        last_elem = div(
+        last_elem = loop_div(
             config,
             region,
             &[last_elem],
@@ -2482,6 +2690,28 @@ pub fn range_check<F: PrimeField + TensorType + PartialOrd>(
 
     let is_dummy = region.is_dummy();
 
+    let table_index: ValTensor<F> = w
+        .get_inner_tensor()?
+        .par_enum_map(|_, e| {
+            Ok::<ValType<F>, TensorError>(if let Some(f) = e.get_felt_eval() {
+                let col_idx = if !is_dummy {
+                    let table = config
+                        .range_checks
+                        .get(range)
+                        .ok_or(TensorError::TableLookupError)?;
+                    table.get_col_index(f)
+                } else {
+                    F::ZERO
+                };
+                Value::known(col_idx).into()
+            } else {
+                Value::<F>::unknown().into()
+            })
+        })?
+        .into();
+
+    region.assign(&config.lookup_index, &table_index)?;
+
     if !is_dummy {
         (0..assigned_len)
             .map(|i| {
@@ -2495,6 +2725,17 @@ pub fn range_check<F: PrimeField + TensorType + PartialOrd>(
             .collect::<Result<Vec<_>, Box<dyn Error>>>()?;
     }
 
+    if region.throw_range_check_error() {
+        // assert is within range
+        let int_values = w.get_int_evals()?;
+        for v in int_values {
+            if v < range.0 || v > range.1 {
+                log::debug!("Value ({:?}) out of range: {:?}", v, range);
+                return Err(Box::new(TensorError::TableLookupError));
+            }
+        }
+    }
+
     region.increment(assigned_len);
 
     let elapsed = timer.elapsed();
@@ -2921,16 +3162,8 @@ pub fn softmax<F: PrimeField + TensorType + PartialOrd>(
     let denom = sum(config, region, &[ex.clone()])?;
     // get the inverse
 
-    let inv_denom = nonlinearity(
-        config,
-        region,
-        &[denom],
-        // we set to input scale + output_scale so the output scale is output)scale
-        &LookupOp::Recip {
-            input_scale: scale,
-            output_scale: scale,
-        },
-    )?;
+    let felt_scale = F::from(scale.0 as u64);
+    let inv_denom = recip(config, region, &[denom], felt_scale, felt_scale)?;
 
     // product of num * (1 / denom) = 2*output_scale
     let softmax = pairwise(config, region, &[ex, inv_denom], BaseOp::Mult)?;
@@ -2965,51 +3198,44 @@ pub fn range_check_percent<F: PrimeField + TensorType + PartialOrd>(
     // Calculate the difference between the expected output and actual output
     let diff = pairwise(config, region, &values, BaseOp::Sub)?;
 
-    // Calculate the reciprocal of the expected output tensor, scaling by double the scaling factor
-    let recip = nonlinearity(
+    // integer scale
+    let int_scale = scale.0 as i128;
+    // felt scale
+    let felt_scale = i128_to_felt(int_scale);
+    // range check len capped at 2^(S-3) and make it divisible 2
+    let range_check_bracket = std::cmp::min(
+        utils::F32(scale.0),
+        utils::F32(2_f32.powf((F::S - 5) as f32)),
+    )
+    .0;
+
+    let range_check_bracket_int = range_check_bracket as i128;
+
+    // input scale ratio we multiply by tol such that in the new scale range_check_len represents tol percent
+    let input_scale_ratio = ((scale.0.powf(2.0) / range_check_bracket) * tol) as i128 / 2 * 2;
+
+    let recip = recip(
         config,
         region,
         &[values[0].clone()],
-        &LookupOp::Recip {
-            input_scale: scale,
-            output_scale: scale,
-        },
+        felt_scale,
+        felt_scale * F::from(100),
     )?;
 
+    log::debug!("recip: {}", recip.show());
+
     // Multiply the difference by the recip
     let product = pairwise(config, region, &[diff, recip], BaseOp::Mult)?;
 
-    let scale_squared = scale.0 * scale.0;
+    log::debug!("product: {}", product.show());
+    let rebased_product = loop_div(config, region, &[product], i128_to_felt(input_scale_ratio))?;
+    log::debug!("rebased_product: {}", rebased_product.show());
 
-    // Use the greater than look up table to check if the percent error is within the tolerance for upper bound
-    let tol = tol / 100.0;
-    let upper_bound = nonlinearity(
+    // check that it is within the tolerance range
+    range_check(
         config,
         region,
-        &[product.clone()],
-        &LookupOp::GreaterThan {
-            a: utils::F32(tol * scale_squared),
-        },
-    )?;
-
-    // Negate the product
-    let neg_product = neg(config, region, &[product])?;
-
-    // Use the greater than look up table to check if the percent error is within the tolerance for lower bound
-    let lower_bound = nonlinearity(
-        config,
-        region,
-        &[neg_product],
-        &LookupOp::GreaterThan {
-            a: utils::F32(tol * scale_squared),
-        },
-    )?;
-
-    // Add the lower_bound and upper_bound
-    let sum = pairwise(config, region, &[lower_bound, upper_bound], BaseOp::Add)?;
-
-    // Constrain the sum to be all zeros
-    is_zero_identity(config, region, &[sum.clone()], false)?;
-
-    Ok(sum)
+        &[rebased_product],
+        &(-range_check_bracket_int, range_check_bracket_int),
+    )
 }

src/circuit/ops/region.rs

@@ -20,6 +20,33 @@ use portable_atomic::AtomicI128 as AtomicInt;
 
 use super::lookup::LookupOp;
 
+/// Dynamic lookup index
+#[derive(Clone, Debug, Default)]
+pub struct DynamicLookupIndex {
+    lookup_index: usize,
+    col_coord: usize,
+}
+
+impl DynamicLookupIndex {
+    /// Create a new dynamic lookup index
+    pub fn new(lookup_index: usize, col_coord: usize) -> DynamicLookupIndex {
+        DynamicLookupIndex {
+            lookup_index,
+            col_coord,
+        }
+    }
+
+    /// Get the lookup index
+    pub fn lookup_index(&self) -> usize {
+        self.lookup_index
+    }
+
+    /// Get the column coord
+    pub fn col_coord(&self) -> usize {
+        self.col_coord
+    }
+}
+
 /// Region error
 #[derive(Debug, thiserror::Error)]
 pub enum RegionError {
@@ -66,10 +93,13 @@ pub struct RegionCtx<'a, F: PrimeField + TensorType + PartialOrd> {
     linear_coord: usize,
     num_inner_cols: usize,
     total_constants: usize,
+    dynamic_lookup_index: DynamicLookupIndex,
     used_lookups: HashSet<LookupOp>,
     used_range_checks: HashSet<Range>,
     max_lookup_inputs: i128,
     min_lookup_inputs: i128,
+    max_range_size: i128,
+    throw_range_check_error: bool,
 }
 
 impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
@@ -78,6 +108,21 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         self.total_constants += n;
     }
 
+    ///
+    pub fn increment_dynamic_lookup_index(&mut self, n: usize) {
+        self.dynamic_lookup_index.lookup_index += n;
+    }
+
+    ///
+    pub fn increment_dynamic_lookup_col_coord(&mut self, n: usize) {
+        self.dynamic_lookup_index.col_coord += n;
+    }
+
+    ///
+    pub fn throw_range_check_error(&self) -> bool {
+        self.throw_range_check_error
+    }
+
     /// Create a new region context
     pub fn new(region: Region<'a, F>, row: usize, num_inner_cols: usize) -> RegionCtx<'a, F> {
         let region = Some(RefCell::new(region));
@@ -89,10 +134,13 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             row,
             linear_coord,
             total_constants: 0,
+            dynamic_lookup_index: DynamicLookupIndex::default(),
             used_lookups: HashSet::new(),
             used_range_checks: HashSet::new(),
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
+            max_range_size: 0,
+            throw_range_check_error: false,
         }
     }
     /// Create a new region context from a wrapped region
@@ -100,6 +148,7 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         region: Option<RefCell<Region<'a, F>>>,
         row: usize,
         num_inner_cols: usize,
+        dynamic_lookup_index: DynamicLookupIndex,
     ) -> RegionCtx<'a, F> {
         let linear_coord = row * num_inner_cols;
         RegionCtx {
@@ -108,15 +157,22 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             linear_coord,
             row,
             total_constants: 0,
+            dynamic_lookup_index,
             used_lookups: HashSet::new(),
             used_range_checks: HashSet::new(),
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
+            max_range_size: 0,
+            throw_range_check_error: false,
         }
     }
 
     /// Create a new region context
-    pub fn new_dummy(row: usize, num_inner_cols: usize) -> RegionCtx<'a, F> {
+    pub fn new_dummy(
+        row: usize,
+        num_inner_cols: usize,
+        throw_range_check_error: bool,
+    ) -> RegionCtx<'a, F> {
         let region = None;
         let linear_coord = row * num_inner_cols;
 
@@ -126,10 +182,13 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             linear_coord,
             row,
             total_constants: 0,
+            dynamic_lookup_index: DynamicLookupIndex::default(),
             used_lookups: HashSet::new(),
             used_range_checks: HashSet::new(),
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
+            max_range_size: 0,
+            throw_range_check_error,
         }
     }
 
@@ -139,8 +198,10 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         linear_coord: usize,
         total_constants: usize,
         num_inner_cols: usize,
+        dynamic_lookup_index: DynamicLookupIndex,
         used_lookups: HashSet<LookupOp>,
         used_range_checks: HashSet<Range>,
+        throw_range_check_error: bool,
     ) -> RegionCtx<'a, F> {
         let region = None;
         RegionCtx {
@@ -149,10 +210,13 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             linear_coord,
             row,
             total_constants,
+            dynamic_lookup_index,
             used_lookups,
             used_range_checks,
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
+            max_range_size: 0,
+            throw_range_check_error,
         }
     }
 
@@ -207,6 +271,7 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         let min_lookup_inputs = AtomicInt::new(self.min_lookup_inputs());
         let lookups = Arc::new(Mutex::new(self.used_lookups.clone()));
         let range_checks = Arc::new(Mutex::new(self.used_range_checks.clone()));
+        let dynamic_lookup_index = Arc::new(Mutex::new(self.dynamic_lookup_index.clone()));
 
         *output = output
             .par_enum_map(|idx, _| {
@@ -222,8 +287,10 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
                     starting_linear_coord,
                     starting_constants,
                     self.num_inner_cols,
+                    DynamicLookupIndex::default(),
                     HashSet::new(),
                     HashSet::new(),
+                    self.throw_range_check_error,
                 );
                 let res = inner_loop_function(idx, &mut local_reg);
                 // we update the offset and constants
@@ -244,6 +311,10 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
                 lookups.extend(local_reg.used_lookups());
                 let mut range_checks = range_checks.lock().unwrap();
                 range_checks.extend(local_reg.used_range_checks());
+                let mut dynamic_lookup_index = dynamic_lookup_index.lock().unwrap();
+                dynamic_lookup_index.lookup_index += local_reg.dynamic_lookup_index.lookup_index;
+                dynamic_lookup_index.col_coord += local_reg.dynamic_lookup_index.col_coord;
+
                 res
             })
             .map_err(|e| {
@@ -272,6 +343,20 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             .map_err(|e| {
                 RegionError::from(format!("dummy_loop: failed to get range checks: {:?}", e))
             })?;
+        self.dynamic_lookup_index = Arc::try_unwrap(dynamic_lookup_index)
+            .map_err(|e| {
+                RegionError::from(format!(
+                    "dummy_loop: failed to get dynamic lookup index: {:?}",
+                    e
+                ))
+            })?
+            .into_inner()
+            .map_err(|e| {
+                RegionError::from(format!(
+                    "dummy_loop: failed to get dynamic lookup index: {:?}",
+                    e
+                ))
+            })?;
 
         Ok(())
     }
@@ -300,8 +385,9 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             return Err("update_max_min_lookup_range: invalid range".into());
         }
 
-        self.max_lookup_inputs = self.max_lookup_inputs.max(range.1);
-        self.min_lookup_inputs = self.min_lookup_inputs.min(range.0);
+        let range_size = (range.1 - range.0).abs();
+
+        self.max_range_size = self.max_range_size.max(range_size);
         Ok(())
     }
 
@@ -341,6 +427,16 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         self.total_constants
     }
 
+    /// Get the dynamic lookup index
+    pub fn dynamic_lookup_index(&self) -> usize {
+        self.dynamic_lookup_index.lookup_index
+    }
+
+    /// Get the dynamic lookup column coordinate
+    pub fn dynamic_lookup_col_coord(&self) -> usize {
+        self.dynamic_lookup_index.col_coord
+    }
+
     /// get used lookups
     pub fn used_lookups(&self) -> HashSet<LookupOp> {
         self.used_lookups.clone()
@@ -361,6 +457,11 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         self.min_lookup_inputs
     }
 
+    /// max range check
+    pub fn max_range_size(&self) -> i128 {
+        self.max_range_size
+    }
+
     /// Assign a constant value
     pub fn assign_constant(&mut self, var: &VarTensor, value: F) -> Result<ValType<F>, Error> {
         self.total_constants += 1;
@@ -385,6 +486,24 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         }
     }
 
+    /// Assign a valtensor to a vartensor
+    pub fn assign_dynamic_lookup(
+        &mut self,
+        var: &VarTensor,
+        values: &ValTensor<F>,
+    ) -> Result<ValTensor<F>, Error> {
+        self.total_constants += values.num_constants();
+        if let Some(region) = &self.region {
+            var.assign(
+                &mut region.borrow_mut(),
+                self.dynamic_lookup_col_coord(),
+                values,
+            )
+        } else {
+            Ok(values.clone())
+        }
+    }
+
     /// Assign a valtensor to a vartensor
     pub fn assign_with_omissions(
         &mut self,

src/circuit/table.rs

@@ -130,14 +130,12 @@ impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
     pub fn cal_bit_range(bits: usize, reserved_blinding_rows: usize) -> usize {
         2usize.pow(bits as u32) - reserved_blinding_rows
     }
+}
 
-    ///
-    pub fn num_cols_required(range: Range, col_size: usize) -> usize {
-        // double it to be safe
-        let range_len = range.1 - range.0;
-        // number of cols needed to store the range
-        (range_len / (col_size as i128)) as usize + 1
-    }
+///
+pub fn num_cols_required(range_len: i128, col_size: usize) -> usize {
+    // number of cols needed to store the range
+    (range_len / (col_size as i128)) as usize + 1
 }
 
 impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
@@ -152,7 +150,7 @@ impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
         let factors = cs.blinding_factors() + RESERVED_BLINDING_ROWS_PAD;
         let col_size = Self::cal_col_size(logrows, factors);
         // number of cols needed to store the range
-        let num_cols = Self::num_cols_required(range, col_size);
+        let num_cols = num_cols_required((range.1 - range.0).abs(), col_size);
 
         log::debug!("table range: {:?}", range);
 
@@ -265,7 +263,9 @@ impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
 #[derive(Clone, Debug)]
 pub struct RangeCheck<F: PrimeField> {
     /// Input to table.
-    pub input: TableColumn,
+    pub inputs: Vec<TableColumn>,
+    /// col size
+    pub col_size: usize,
     /// selector cn
     pub selector_constructor: SelectorConstructor<F>,
     /// Flags if table has been previously assigned to.
@@ -277,8 +277,10 @@ pub struct RangeCheck<F: PrimeField> {
 
 impl<F: PrimeField + TensorType + PartialOrd> RangeCheck<F> {
     /// get first_element of column
-    pub fn get_first_element(&self) -> F {
-        i128_to_felt(self.range.0)
+    pub fn get_first_element(&self, chunk: usize) -> F {
+        let chunk = chunk as i128;
+        // we index from 1 to prevent soundness issues
+        i128_to_felt(chunk * (self.col_size as i128) + self.range.0)
     }
 
     ///
@@ -290,24 +292,58 @@ impl<F: PrimeField + TensorType + PartialOrd> RangeCheck<F> {
     pub fn cal_bit_range(bits: usize, reserved_blinding_rows: usize) -> usize {
         2usize.pow(bits as u32) - reserved_blinding_rows
     }
+
+    /// get column index given input
+    pub fn get_col_index(&self, input: F) -> F {
+        //    range is split up into chunks of size col_size, find the chunk that input is in
+        let chunk =
+            (crate::fieldutils::felt_to_i128(input) - self.range.0).abs() / (self.col_size as i128);
+
+        i128_to_felt(chunk)
+    }
 }
 
 impl<F: PrimeField + TensorType + PartialOrd> RangeCheck<F> {
     /// Configures the table.
-    pub fn configure(cs: &mut ConstraintSystem<F>, range: Range) -> RangeCheck<F> {
+    pub fn configure(cs: &mut ConstraintSystem<F>, range: Range, logrows: usize) -> RangeCheck<F> {
         log::debug!("range check range: {:?}", range);
 
-        let inputs = cs.lookup_table_column();
+        let factors = cs.blinding_factors() + RESERVED_BLINDING_ROWS_PAD;
+        let col_size = Self::cal_col_size(logrows, factors);
+        // number of cols needed to store the range
+        let num_cols = num_cols_required((range.1 - range.0).abs(), col_size);
+
+        let inputs = {
+            let mut cols = vec![];
+            for _ in 0..num_cols {
+                cols.push(cs.lookup_table_column());
+            }
+            cols
+        };
+
+        let num_cols = inputs.len();
+
+        if num_cols > 1 {
+            warn!("Using {} columns for range-check.", num_cols);
+        }
 
         RangeCheck {
-            input: inputs,
+            inputs,
+            col_size,
             is_assigned: false,
-            selector_constructor: SelectorConstructor::new(2),
+            selector_constructor: SelectorConstructor::new(num_cols),
             range,
             _marker: PhantomData,
         }
     }
 
+    /// Take a linear coordinate and output the (column, row) position in the storage block.
+    pub fn cartesian_coord(&self, linear_coord: usize) -> (usize, usize) {
+        let x = linear_coord / self.col_size;
+        let y = linear_coord % self.col_size;
+        (x, y)
+    }
+
     /// Assigns values to the constraints generated when calling `configure`.
     pub fn layout(&mut self, layouter: &mut impl Layouter<F>) -> Result<(), Box<dyn Error>> {
         if self.is_assigned {
@@ -318,28 +354,43 @@ impl<F: PrimeField + TensorType + PartialOrd> RangeCheck<F> {
         let largest = self.range.1;
 
         let inputs: Tensor<F> = Tensor::from(smallest..=largest).map(|x| i128_to_felt(x));
+        let chunked_inputs = inputs.chunks(self.col_size);
 
         self.is_assigned = true;
 
-        layouter.assign_table(
-            || "range check table",
-            |mut table| {
-                let _ = inputs
-                    .iter()
-                    .enumerate()
-                    .map(|(row_offset, input)| {
-                        table.assign_cell(
-                            || format!("rc_i_col row {}", row_offset),
-                            self.input,
-                            row_offset,
-                            || Value::known(*input),
-                        )?;
+        let col_multipliers: Vec<F> = (0..chunked_inputs.len())
+            .map(|x| self.selector_constructor.get_selector_val_at_idx(x))
+            .collect();
+
+        let _ = chunked_inputs
+            .enumerate()
+            .map(|(chunk_idx, inputs)| {
+                layouter.assign_table(
+                    || "range check table",
+                    |mut table| {
+                        let _ = inputs
+                            .iter()
+                            .enumerate()
+                            .map(|(mut row_offset, input)| {
+                                let col_multiplier = col_multipliers[chunk_idx];
+
+                                row_offset += chunk_idx * self.col_size;
+                                let (x, y) = self.cartesian_coord(row_offset);
+                                table.assign_cell(
+                                    || format!("rc_i_col row {}", row_offset),
+                                    self.inputs[x],
+                                    y,
+                                    || Value::known(*input * col_multiplier),
+                                )?;
+
+                                Ok(())
+                            })
+                            .collect::<Result<Vec<()>, halo2_proofs::plonk::Error>>()?;
                         Ok(())
-                    })
-                    .collect::<Result<Vec<()>, halo2_proofs::plonk::Error>>()?;
-                Ok(())
-            },
-        )?;
+                    },
+                )
+            })
+            .collect::<Result<Vec<()>, halo2_proofs::plonk::Error>>()?;
         Ok(())
     }
 }

src/circuit/tests.rs

@@ -1,4 +1,3 @@
-use crate::circuit::ops::hybrid::HybridOp;
 use crate::circuit::ops::poly::PolyOp;
 use crate::circuit::*;
 use crate::tensor::{Tensor, TensorType, ValTensor, VarTensor};
@@ -1575,6 +1574,142 @@ mod add {
     }
 }
 
+#[cfg(test)]
+mod dynamic_lookup {
+    use super::*;
+
+    const K: usize = 6;
+    const LEN: usize = 4;
+    const NUM_LOOP: usize = 5;
+
+    #[derive(Clone)]
+    struct MyCircuit<F: PrimeField + TensorType + PartialOrd> {
+        tables: [[ValTensor<F>; 2]; NUM_LOOP],
+        lookups: [[ValTensor<F>; 2]; NUM_LOOP],
+        _marker: PhantomData<F>,
+    }
+
+    impl Circuit<F> for MyCircuit<F> {
+        type Config = BaseConfig<F>;
+        type FloorPlanner = SimpleFloorPlanner;
+        type Params = TestParams;
+
+        fn without_witnesses(&self) -> Self {
+            self.clone()
+        }
+
+        fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
+            let a = VarTensor::new_advice(cs, K, 2, LEN);
+            let b = VarTensor::new_advice(cs, K, 2, LEN);
+            let c: VarTensor = VarTensor::new_advice(cs, K, 2, LEN);
+
+            let d = VarTensor::new_advice(cs, K, 1, LEN);
+            let e = VarTensor::new_advice(cs, K, 1, LEN);
+
+            let mut config =
+                Self::Config::configure(cs, &[a.clone(), b.clone()], &c, CheckMode::SAFE);
+            for _ in 0..NUM_LOOP {
+                config
+                    .configure_dynamic_lookup(cs, &[a.clone(), b.clone()], &[d.clone(), e.clone()])
+                    .unwrap();
+            }
+
+            config
+        }
+
+        fn synthesize(
+            &self,
+            config: Self::Config,
+            mut layouter: impl Layouter<F>,
+        ) -> Result<(), Error> {
+            layouter
+                .assign_region(
+                    || "",
+                    |region| {
+                        let mut region = RegionCtx::new(region, 0, 1);
+                        for i in 0..NUM_LOOP {
+                            layouts::dynamic_lookup(
+                                &config,
+                                &mut region,
+                                &self.lookups[i],
+                                &self.tables[i],
+                            )
+                            .map_err(|_| Error::Synthesis)?;
+                        }
+                        assert_eq!(
+                            region.dynamic_lookup_col_coord(),
+                            NUM_LOOP * self.tables[0][0].len()
+                        );
+                        assert_eq!(region.dynamic_lookup_index(), NUM_LOOP);
+
+                        Ok(())
+                    },
+                )
+                .unwrap();
+            Ok(())
+        }
+    }
+
+    #[test]
+    fn dynamiclookupcircuit() {
+        // parameters
+        let tables = (0..NUM_LOOP)
+            .map(|loop_idx| {
+                [
+                    ValTensor::from(Tensor::from(
+                        (0..LEN).map(|i| Value::known(F::from((i * loop_idx) as u64 + 1))),
+                    )),
+                    ValTensor::from(Tensor::from(
+                        (0..LEN).map(|i| Value::known(F::from((loop_idx * i * i) as u64 + 1))),
+                    )),
+                ]
+            })
+            .collect::<Vec<_>>();
+
+        let lookups = (0..NUM_LOOP)
+            .map(|loop_idx| {
+                [
+                    ValTensor::from(Tensor::from(
+                        (0..3).map(|i| Value::known(F::from((i * loop_idx) as u64 + 1))),
+                    )),
+                    ValTensor::from(Tensor::from(
+                        (0..3).map(|i| Value::known(F::from((loop_idx * i * i) as u64 + 1))),
+                    )),
+                ]
+            })
+            .collect::<Vec<_>>();
+
+        let circuit = MyCircuit::<F> {
+            tables: tables.clone().try_into().unwrap(),
+            lookups: lookups.try_into().unwrap(),
+            _marker: PhantomData,
+        };
+
+        let prover = MockProver::run(K as u32, &circuit, vec![]).unwrap();
+        prover.assert_satisfied();
+
+        let lookups = (0..NUM_LOOP)
+            .map(|loop_idx| {
+                [
+                    ValTensor::from(Tensor::from(
+                        (0..2).map(|i| Value::known(F::from((i * loop_idx) as u64 + 1))),
+                    )),
+                    ValTensor::from(Tensor::from((0..2).map(|_| Value::known(F::from(10000))))),
+                ]
+            })
+            .collect::<Vec<_>>();
+
+        let circuit = MyCircuit::<F> {
+            tables: tables.try_into().unwrap(),
+            lookups: lookups.try_into().unwrap(),
+            _marker: PhantomData,
+        };
+
+        let prover = MockProver::run(K as u32, &circuit, vec![]).unwrap();
+        assert!(prover.verify().is_err());
+    }
+}
+
 #[cfg(test)]
 mod add_with_overflow {
     use super::*;
@@ -2140,148 +2275,6 @@ mod matmul_relu {
     }
 }
 
-#[cfg(test)]
-mod rangecheckpercent {
-    use crate::circuit::Tolerance;
-    use crate::{circuit, tensor::Tensor};
-    use halo2_proofs::{
-        circuit::{Layouter, SimpleFloorPlanner, Value},
-        dev::MockProver,
-        plonk::{Circuit, ConstraintSystem, Error},
-    };
-
-    const RANGE: f32 = 1.0; // 1 percent error tolerance
-    const K: usize = 18;
-    const LEN: usize = 1;
-    const SCALE: usize = i128::pow(2, 7) as usize;
-
-    use super::*;
-
-    #[derive(Clone)]
-    struct MyCircuit<F: PrimeField + TensorType + PartialOrd> {
-        input: ValTensor<F>,
-        output: ValTensor<F>,
-        _marker: PhantomData<F>,
-    }
-
-    impl Circuit<F> for MyCircuit<F> {
-        type Config = BaseConfig<F>;
-        type FloorPlanner = SimpleFloorPlanner;
-        type Params = TestParams;
-
-        fn without_witnesses(&self) -> Self {
-            self.clone()
-        }
-
-        fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
-            let scale = utils::F32(SCALE as f32);
-            let a = VarTensor::new_advice(cs, K, 1, LEN);
-            let b = VarTensor::new_advice(cs, K, 1, LEN);
-            let output = VarTensor::new_advice(cs, K, 1, LEN);
-            let mut config =
-                Self::Config::configure(cs, &[a.clone(), b.clone()], &output, CheckMode::SAFE);
-            // set up a new GreaterThan and Recip tables
-            let nl = &LookupOp::GreaterThan {
-                a: circuit::utils::F32((RANGE * SCALE.pow(2) as f32) / 100.0),
-            };
-            config
-                .configure_lookup(cs, &b, &output, &a, (-32768, 32768), K, nl)
-                .unwrap();
-
-            config
-                .configure_lookup(
-                    cs,
-                    &b,
-                    &output,
-                    &a,
-                    (-32768, 32768),
-                    K,
-                    &LookupOp::Recip {
-                        input_scale: scale,
-                        output_scale: scale,
-                    },
-                )
-                .unwrap();
-            config
-        }
-
-        fn synthesize(
-            &self,
-            mut config: Self::Config,
-            mut layouter: impl Layouter<F>,
-        ) -> Result<(), Error> {
-            config.layout_tables(&mut layouter).unwrap();
-            layouter
-                .assign_region(
-                    || "",
-                    |region| {
-                        let mut region = RegionCtx::new(region, 0, 1);
-                        config
-                            .layout(
-                                &mut region,
-                                &[self.output.clone(), self.input.clone()],
-                                Box::new(HybridOp::RangeCheck(Tolerance {
-                                    val: RANGE,
-                                    scale: SCALE.into(),
-                                })),
-                            )
-                            .map_err(|_| Error::Synthesis)
-                    },
-                )
-                .unwrap();
-            Ok(())
-        }
-    }
-
-    #[test]
-    #[allow(clippy::assertions_on_constants)]
-    fn test_range_check_percent() {
-        // Successful cases
-        {
-            let inp = Tensor::new(Some(&[Value::<F>::known(F::from(100_u64))]), &[1]).unwrap();
-            let out = Tensor::new(Some(&[Value::<F>::known(F::from(101_u64))]), &[1]).unwrap();
-            let circuit = MyCircuit::<F> {
-                input: ValTensor::from(inp),
-                output: ValTensor::from(out),
-                _marker: PhantomData,
-            };
-            let prover = MockProver::run(K as u32, &circuit, vec![]).unwrap();
-            prover.assert_satisfied();
-        }
-        {
-            let inp = Tensor::new(Some(&[Value::<F>::known(F::from(200_u64))]), &[1]).unwrap();
-            let out = Tensor::new(Some(&[Value::<F>::known(F::from(199_u64))]), &[1]).unwrap();
-            let circuit = MyCircuit::<F> {
-                input: ValTensor::from(inp),
-                output: ValTensor::from(out),
-                _marker: PhantomData,
-            };
-            let prover = MockProver::run(K as u32, &circuit, vec![]).unwrap();
-            prover.assert_satisfied();
-        }
-
-        // Unsuccessful case
-        {
-            let inp = Tensor::new(Some(&[Value::<F>::known(F::from(100_u64))]), &[1]).unwrap();
-            let out = Tensor::new(Some(&[Value::<F>::known(F::from(102_u64))]), &[1]).unwrap();
-            let circuit = MyCircuit::<F> {
-                input: ValTensor::from(inp),
-                output: ValTensor::from(out),
-                _marker: PhantomData,
-            };
-            let prover = MockProver::run(K as u32, &circuit, vec![]).unwrap();
-            match prover.verify() {
-                Ok(_) => {
-                    assert!(false)
-                }
-                Err(_) => {
-                    assert!(true)
-                }
-            }
-        }
-    }
-}
-
 #[cfg(test)]
 mod relu {
     use super::*;
@@ -2480,113 +2473,3 @@ mod lookup_ultra_overflow {
         println!("done.");
     }
 }
-
-#[cfg(test)]
-mod softmax {
-
-    use super::*;
-    use halo2_proofs::{
-        circuit::{Layouter, SimpleFloorPlanner, Value},
-        dev::MockProver,
-        plonk::{Circuit, ConstraintSystem, Error},
-    };
-
-    const K: usize = 18;
-    const LEN: usize = 3;
-    const SCALE: f32 = 128.0;
-
-    #[derive(Clone)]
-    struct SoftmaxCircuit<F: PrimeField + TensorType + PartialOrd> {
-        pub input: ValTensor<F>,
-        _marker: PhantomData<F>,
-    }
-
-    impl Circuit<F> for SoftmaxCircuit<F> {
-        type Config = BaseConfig<F>;
-        type FloorPlanner = SimpleFloorPlanner;
-        type Params = TestParams;
-
-        fn without_witnesses(&self) -> Self {
-            self.clone()
-        }
-        fn configure(cs: &mut ConstraintSystem<F>) -> Self::Config {
-            let a = VarTensor::new_advice(cs, K, 1, LEN);
-            let b = VarTensor::new_advice(cs, K, 1, LEN);
-            let output = VarTensor::new_advice(cs, K, 1, LEN);
-            let mut config = Self::Config::configure(cs, &[a, b], &output, CheckMode::SAFE);
-            let advices = (0..3)
-                .map(|_| VarTensor::new_advice(cs, K, 1, LEN))
-                .collect::<Vec<_>>();
-
-            config
-                .configure_lookup(
-                    cs,
-                    &advices[0],
-                    &advices[1],
-                    &advices[2],
-                    (-32768, 32768),
-                    K,
-                    &LookupOp::Exp {
-                        scale: SCALE.into(),
-                    },
-                )
-                .unwrap();
-            config
-                .configure_lookup(
-                    cs,
-                    &advices[0],
-                    &advices[1],
-                    &advices[2],
-                    (-32768, 32768),
-                    K,
-                    &LookupOp::Recip {
-                        input_scale: SCALE.into(),
-                        output_scale: SCALE.into(),
-                    },
-                )
-                .unwrap();
-            config
-        }
-
-        fn synthesize(
-            &self,
-            mut config: Self::Config,
-            mut layouter: impl Layouter<F>,
-        ) -> Result<(), Error> {
-            config.layout_tables(&mut layouter).unwrap();
-            layouter
-                .assign_region(
-                    || "",
-                    |region| {
-                        let mut region = RegionCtx::new(region, 0, 1);
-                        let _output = config
-                            .layout(
-                                &mut region,
-                                &[self.input.clone()],
-                                Box::new(HybridOp::Softmax {
-                                    scale: SCALE.into(),
-                                    axes: vec![0],
-                                }),
-                            )
-                            .unwrap();
-                        Ok(())
-                    },
-                )
-                .unwrap();
-
-            Ok(())
-        }
-    }
-
-    #[test]
-    fn softmax_circuit() {
-        let input = Tensor::from((0..LEN).map(|i| Value::known(F::from(i as u64 + 1))));
-
-        let circuit = SoftmaxCircuit::<F> {
-            input: ValTensor::from(input),
-            _marker: PhantomData,
-        };
-        let prover = MockProver::run(K as u32, &circuit, vec![]).unwrap();
-        prover.assert_satisfied();
-    }
-}

src/commands.rs

@@ -471,7 +471,7 @@ pub enum Commands {
             long,
             require_equals = true,
             num_args = 0..=1,
-            default_value_t = TranscriptType::EVM,
+            default_value_t = TranscriptType::default(),
             value_enum
         )]
         transcript: TranscriptType,
@@ -526,13 +526,13 @@ pub enum Commands {
         #[arg(short = 'W', long, default_value = DEFAULT_WITNESS)]
         witness: PathBuf,
         /// The path to the compiled model file (generated using the compile-circuit command)
-        #[arg(short = 'M', long, default_value = DEFAULT_COMPILED_CIRCUIT)]
+        #[arg(short = 'M', long)]
         compiled_circuit: PathBuf,
         #[arg(
             long,
             require_equals = true,
             num_args = 0..=1,
-            default_value_t = TranscriptType::EVM,
+            default_value_t = TranscriptType::default(),
             value_enum
         )]
         transcript: TranscriptType,

src/execute.rs

@@ -488,8 +488,14 @@ async fn fetch_srs(uri: &str) -> Result<Vec<u8>, Box<dyn Error>> {
 
 #[cfg(not(target_arch = "wasm32"))]
 fn check_srs_hash(logrows: u32, srs_path: Option<PathBuf>) -> Result<String, Box<dyn Error>> {
+    use std::io::Read;
+
     let path = get_srs_path(logrows, srs_path);
-    let hash = sha256::digest(std::fs::read(path.clone())?);
+    let file = std::fs::File::open(path.clone())?;
+    let mut buffer = vec![];
+    let bytes_read = std::io::BufReader::new(file).read_to_end(&mut buffer)?;
+    debug!("read {} bytes from SRS file", bytes_read);
+    let hash = sha256::digest(buffer);
     info!("SRS hash: {}", hash);
 
     let predefined_hash = match { crate::srs_sha::PUBLIC_SRS_SHA256_HASHES.get(&logrows) } {
@@ -612,7 +618,7 @@ pub(crate) async fn gen_witness(
 
     let start_time = Instant::now();
 
-    let witness = circuit.forward(&mut input, vk.as_ref(), srs.as_ref())?;
+    let witness = circuit.forward(&mut input, vk.as_ref(), srs.as_ref(), false)?;
 
     // print each variable tuple (symbol, value) as symbol=value
     trace!(
@@ -802,16 +808,7 @@ pub(crate) fn calibrate(
     // we load the model to get the input and output shapes
     // check if gag already exists
 
-    #[cfg(unix)]
-    let _r = match Gag::stdout() {
-        Ok(r) => Some(r),
-        Err(_) => None,
-    };
-
     let model = Model::from_run_args(&settings.run_args, &model_path)?;
-    // drop the gag
-    #[cfg(unix)]
-    std::mem::drop(_r);
 
     let chunks = data.split_into_batches(model.graph.input_shapes()?)?;
     info!("num of calibration batches: {}", chunks.len());
@@ -827,7 +824,7 @@ pub(crate) fn calibrate(
     let range = if let Some(scales) = scales {
         scales
     } else {
-        (10..14).collect::<Vec<crate::Scale>>()
+        (11..14).collect::<Vec<crate::Scale>>()
     };
 
     let div_rebasing = if only_range_check_rebase {
@@ -890,16 +887,6 @@ pub(crate) fn calibrate(
             input_scale, param_scale, scale_rebase_multiplier, div_rebasing
         ));
 
-        #[cfg(unix)]
-        let _r = match Gag::stdout() {
-            Ok(r) => Some(r),
-            Err(_) => None,
-        };
-        #[cfg(unix)]
-        let _q = match Gag::stderr() {
-            Ok(r) => Some(r),
-            Err(_) => None,
-        };
         let key = (input_scale, param_scale, scale_rebase_multiplier);
         forward_pass_res.insert(key, vec![]);
 
@@ -914,17 +901,12 @@ pub(crate) fn calibrate(
         let mut circuit = match GraphCircuit::from_run_args(&local_run_args, &model_path) {
             Ok(c) => c,
             Err(e) => {
-                // drop the gag
-                #[cfg(unix)]
-                std::mem::drop(_r);
-                #[cfg(unix)]
-                std::mem::drop(_q);
                 debug!("circuit creation from run args failed: {:?}", e);
                 continue;
             }
         };
 
-        chunks
+        let forward_res = chunks
             .iter()
             .map(|chunk| {
                 let chunk = chunk.clone();
@@ -934,7 +916,7 @@ pub(crate) fn calibrate(
                     .map_err(|e| format!("failed to load circuit inputs: {}", e))?;
 
                 let forward_res = circuit
-                    .forward(&mut data.clone(), None, None)
+                    .forward(&mut data.clone(), None, None, true)
                     .map_err(|e| format!("failed to forward: {}", e))?;
 
                 // push result to the hashmap
@@ -945,7 +927,16 @@ pub(crate) fn calibrate(
 
                 Ok(()) as Result<(), String>
             })
-            .collect::<Result<Vec<()>, String>>()?;
+            .collect::<Result<Vec<()>, String>>();
+
+        match forward_res {
+            Ok(_) => (),
+            // typically errors will be due to the circuit overflowing the i128 limit
+            Err(e) => {
+                debug!("forward pass failed: {:?}", e);
+                continue;
+            }
+        }
 
         let min_lookup_range = forward_pass_res
             .get(&key)
@@ -963,19 +954,21 @@ pub(crate) fn calibrate(
             .max()
             .unwrap_or(0);
 
-        let res = circuit.calibrate_from_min_max(
-            min_lookup_range,
-            max_lookup_range,
+        let max_range_size = forward_pass_res
+            .get(&key)
+            .unwrap()
+            .iter()
+            .map(|x| x.max_range_size)
+            .max()
+            .unwrap_or(0);
+
+        let res = circuit.calc_min_logrows(
+            (min_lookup_range, max_lookup_range),
+            max_range_size,
             max_logrows,
             lookup_safety_margin,
         );
 
-        // drop the gag
-        #[cfg(unix)]
-        std::mem::drop(_r);
-        #[cfg(unix)]
-        std::mem::drop(_q);
-
         if res.is_ok() {
             let new_settings = circuit.settings().clone();
 

src/graph/input.rs

@@ -624,13 +624,13 @@ impl ToPyObject for DataSource {
 }
 
 #[cfg(feature = "python-bindings")]
-use crate::pfsys::field_to_string_montgomery;
+use crate::pfsys::field_to_string;
 
 #[cfg(feature = "python-bindings")]
 impl ToPyObject for FileSourceInner {
     fn to_object(&self, py: Python) -> PyObject {
         match self {
-            FileSourceInner::Field(data) => field_to_string_montgomery(data).to_object(py),
+            FileSourceInner::Field(data) => field_to_string(data).to_object(py),
             FileSourceInner::Bool(data) => data.to_object(py),
             FileSourceInner::Float(data) => data.to_object(py),
         }

src/graph/mod.rs

@@ -24,7 +24,7 @@ use self::input::{FileSource, GraphData};
 use self::modules::{GraphModules, ModuleConfigs, ModuleForwardResult, ModuleSizes};
 use crate::circuit::lookup::LookupOp;
 use crate::circuit::modules::ModulePlanner;
-use crate::circuit::table::{Range, Table, RESERVED_BLINDING_ROWS_PAD};
+use crate::circuit::table::{num_cols_required, Range, Table, RESERVED_BLINDING_ROWS_PAD};
 use crate::circuit::{CheckMode, InputType};
 use crate::fieldutils::felt_to_f64;
 use crate::pfsys::PrettyElements;
@@ -56,13 +56,16 @@ pub use utilities::*;
 pub use vars::*;
 
 #[cfg(feature = "python-bindings")]
-use crate::pfsys::field_to_string_montgomery;
+use crate::pfsys::field_to_string;
 
 /// The safety factor for the range of the lookup table.
 pub const RANGE_MULTIPLIER: i128 = 2;
 
+/// The maximum number of columns in a lookup table.
+pub const MAX_NUM_LOOKUP_COLS: usize = 12;
+
 /// Max representation of a lookup table input
-pub const MAX_LOOKUP_ABS: i128 = 8 * 2_i128.pow(MAX_PUBLIC_SRS);
+pub const MAX_LOOKUP_ABS: i128 = (MAX_NUM_LOOKUP_COLS as i128) * 2_i128.pow(MAX_PUBLIC_SRS);
 
 #[cfg(not(target_arch = "wasm32"))]
 lazy_static! {
@@ -134,15 +137,16 @@ pub enum GraphError {
     MissingResults,
 }
 
-const ASSUMED_BLINDING_FACTORS: usize = 5;
+///
+pub const ASSUMED_BLINDING_FACTORS: usize = 5;
 /// The minimum number of rows in the grid
 pub const MIN_LOGROWS: u32 = 6;
 
 /// 26
 pub const MAX_PUBLIC_SRS: u32 = bn256::Fr::S - 2;
 
-/// Lookup deg
-pub const LOOKUP_DEG: usize = 5;
+///
+pub const RESERVED_BLINDING_ROWS: usize = ASSUMED_BLINDING_FACTORS + RESERVED_BLINDING_ROWS_PAD;
 
 use std::cell::RefCell;
 
@@ -171,6 +175,8 @@ pub struct GraphWitness {
     pub max_lookup_inputs: i128,
     /// max lookup input
     pub min_lookup_inputs: i128,
+    /// max range check size
+    pub max_range_size: i128,
 }
 
 impl GraphWitness {
@@ -198,6 +204,7 @@ impl GraphWitness {
             processed_outputs: None,
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
+            max_range_size: 0,
         }
     }
 
@@ -355,19 +362,23 @@ impl ToPyObject for GraphWitness {
         let inputs: Vec<Vec<String>> = self
             .inputs
             .iter()
-            .map(|x| x.iter().map(field_to_string_montgomery).collect())
+            .map(|x| x.iter().map(field_to_string).collect())
             .collect();
 
         let outputs: Vec<Vec<String>> = self
             .outputs
             .iter()
-            .map(|x| x.iter().map(field_to_string_montgomery).collect())
+            .map(|x| x.iter().map(field_to_string).collect())
             .collect();
 
         dict.set_item("inputs", inputs).unwrap();
         dict.set_item("outputs", outputs).unwrap();
         dict.set_item("max_lookup_inputs", self.max_lookup_inputs)
             .unwrap();
+        dict.set_item("min_lookup_inputs", self.min_lookup_inputs)
+            .unwrap();
+        dict.set_item("max_range_size", self.max_range_size)
+            .unwrap();
 
         if let Some(processed_inputs) = &self.processed_inputs {
             //poseidon_hash
@@ -409,10 +420,7 @@ impl ToPyObject for GraphWitness {
 
 #[cfg(feature = "python-bindings")]
 fn insert_poseidon_hash_pydict(pydict: &PyDict, poseidon_hash: &Vec<Fp>) -> Result<(), PyErr> {
-    let poseidon_hash: Vec<String> = poseidon_hash
-        .iter()
-        .map(field_to_string_montgomery)
-        .collect();
+    let poseidon_hash: Vec<String> = poseidon_hash.iter().map(field_to_string).collect();
     pydict.set_item("poseidon_hash", poseidon_hash)?;
 
     Ok(())
@@ -441,6 +449,10 @@ pub struct GraphSettings {
     pub total_assignments: usize,
     /// total const size
     pub total_const_size: usize,
+    /// total dynamic column size
+    pub total_dynamic_col_size: usize,
+    /// number of dynamic lookups
+    pub num_dynamic_lookups: usize,
     /// the shape of public inputs to the model (in order of appearance)
     pub model_instance_shapes: Vec<Vec<usize>>,
     /// model output scales
@@ -464,6 +476,24 @@ pub struct GraphSettings {
 }
 
 impl GraphSettings {
+    fn model_constraint_logrows(&self) -> u32 {
+        (self.num_rows as f64 + RESERVED_BLINDING_ROWS as f64)
+            .log2()
+            .ceil() as u32
+    }
+
+    fn dynamic_lookup_logrows(&self) -> u32 {
+        (self.total_dynamic_col_size as f64).log2().ceil() as u32
+    }
+
+    fn module_constraint_logrows(&self) -> u32 {
+        (self.module_sizes.max_constraints() as f64).log2().ceil() as u32
+    }
+
+    fn constants_logrows(&self) -> u32 {
+        (self.total_const_size as f64).log2().ceil() as u32
+    }
+
     /// calculate the total number of instances
     pub fn total_instances(&self) -> Vec<usize> {
         let mut instances: Vec<usize> = self
@@ -548,6 +578,11 @@ impl GraphSettings {
             || self.run_args.param_visibility.is_hashed()
     }
 
+    /// requires dynamic lookup  
+    pub fn requires_dynamic_lookup(&self) -> bool {
+        self.num_dynamic_lookups > 0
+    }
+
     /// any kzg visibility
     pub fn module_requires_kzg(&self) -> bool {
         self.run_args.input_visibility.is_kzgcommit()
@@ -996,18 +1031,10 @@ impl GraphCircuit {
         Ok(data)
     }
 
-    fn reserved_blinding_rows() -> f64 {
-        (ASSUMED_BLINDING_FACTORS + RESERVED_BLINDING_ROWS_PAD) as f64
-    }
-
-    fn calc_safe_lookup_range(
-        min_lookup_inputs: i128,
-        max_lookup_inputs: i128,
-        lookup_safety_margin: i128,
-    ) -> Range {
+    fn calc_safe_lookup_range(min_max_lookup: Range, lookup_safety_margin: i128) -> Range {
         let mut margin = (
-            lookup_safety_margin * min_lookup_inputs,
-            lookup_safety_margin * max_lookup_inputs,
+            lookup_safety_margin * min_max_lookup.0,
+            lookup_safety_margin * min_max_lookup.1,
         );
         if lookup_safety_margin == 1 {
             margin.0 += 4;
@@ -1017,18 +1044,34 @@ impl GraphCircuit {
         margin
     }
 
-    fn calc_num_cols(safe_range: Range, max_logrows: u32) -> usize {
-        let max_col_size = Table::<Fp>::cal_col_size(
-            max_logrows as usize,
-            Self::reserved_blinding_rows() as usize,
-        );
-        Table::<Fp>::num_cols_required(safe_range, max_col_size)
+    fn calc_num_cols(range_len: i128, max_logrows: u32) -> usize {
+        let max_col_size = Table::<Fp>::cal_col_size(max_logrows as usize, RESERVED_BLINDING_ROWS);
+        num_cols_required(range_len, max_col_size)
     }
 
-    fn calc_min_logrows(
+    fn table_size_logrows(
+        &self,
+        safe_lookup_range: Range,
+        max_range_size: i128,
+    ) -> Result<u32, Box<dyn std::error::Error>> {
+        // pick the range with the largest absolute size safe_lookup_range or max_range_size
+        let safe_range = std::cmp::max(
+            (safe_lookup_range.1 - safe_lookup_range.0).abs(),
+            max_range_size,
+        );
+
+        let min_bits = (safe_range as f64 + RESERVED_BLINDING_ROWS as f64 + 1.)
+            .log2()
+            .ceil() as u32;
+
+        Ok(min_bits)
+    }
+
+    /// calculate the minimum logrows required for the circuit
+    pub fn calc_min_logrows(
         &mut self,
-        min_lookup_inputs: i128,
-        max_lookup_inputs: i128,
+        min_max_lookup: Range,
+        max_range_size: i128,
         max_logrows: Option<u32>,
         lookup_safety_margin: i128,
     ) -> Result<(), Box<dyn std::error::Error>> {
@@ -1038,54 +1081,60 @@ impl GraphCircuit {
         let mut max_logrows = std::cmp::max(max_logrows, MIN_LOGROWS);
         let mut min_logrows = MIN_LOGROWS;
 
-        let reserved_blinding_rows = Self::reserved_blinding_rows();
+        let safe_lookup_range = Self::calc_safe_lookup_range(min_max_lookup, lookup_safety_margin);
+
         // check if has overflowed max lookup input
-        if max_lookup_inputs > MAX_LOOKUP_ABS / lookup_safety_margin
-            || min_lookup_inputs < -MAX_LOOKUP_ABS / lookup_safety_margin
-        {
-            let err_string = format!("max lookup input ({}) is too large", max_lookup_inputs);
+        if (min_max_lookup.1 - min_max_lookup.0).abs() > MAX_LOOKUP_ABS / lookup_safety_margin {
+            let err_string = format!("max lookup input {:?} is too large", min_max_lookup);
             return Err(err_string.into());
         }
 
-        let safe_range = Self::calc_safe_lookup_range(
-            min_lookup_inputs,
-            max_lookup_inputs,
-            lookup_safety_margin,
+        if max_range_size.abs() > MAX_LOOKUP_ABS {
+            let err_string = format!("max range check size {:?} is too large", max_range_size);
+            return Err(err_string.into());
+        }
+
+        // These are hard lower limits, we can't overflow instances or modules constraints
+        let instance_logrows = self.settings().log2_total_instances();
+        let module_constraint_logrows = self.settings().module_constraint_logrows();
+        let dynamic_lookup_logrows = self.settings().dynamic_lookup_logrows();
+        min_logrows = std::cmp::max(
+            min_logrows,
+            // max of the instance logrows and the module constraint logrows and the dynamic lookup logrows is the lower limit
+            *[
+                instance_logrows,
+                module_constraint_logrows,
+                dynamic_lookup_logrows,
+            ]
+            .iter()
+            .max()
+            .unwrap(),
         );
 
+        // These are upper limits, going above these is wasteful, but they are not hard limits
+        let model_constraint_logrows = self.settings().model_constraint_logrows();
+        let min_bits = self.table_size_logrows(safe_lookup_range, max_range_size)?;
+        let constants_logrows = self.settings().constants_logrows();
+        max_logrows = std::cmp::min(
+            max_logrows,
+            // max of the model constraint logrows, min_bits, and the constants logrows is the upper limit
+            *[model_constraint_logrows, min_bits, constants_logrows]
+                .iter()
+                .max()
+                .unwrap(),
+        );
+
+        // we now have a min and max logrows
+        max_logrows = std::cmp::max(min_logrows, max_logrows);
+
         // degrade the max logrows until the extended k is small enough
         while min_logrows < max_logrows
-            && !self.extended_k_is_small_enough(
-                min_logrows,
-                Self::calc_num_cols(safe_range, min_logrows),
-            )
-        {
-            min_logrows += 1;
-        }
-
-        if !self
-            .extended_k_is_small_enough(min_logrows, Self::calc_num_cols(safe_range, min_logrows))
-        {
-            let err_string = format!(
-                "extended k is too large to accommodate the quotient polynomial with logrows {}",
-                min_logrows
-            );
-            debug!("{}", err_string);
-            return Err(err_string.into());
-        }
-
-        while min_logrows < max_logrows
-            && !self.extended_k_is_small_enough(
-                max_logrows,
-                Self::calc_num_cols(safe_range, max_logrows),
-            )
+            && !self.extended_k_is_small_enough(max_logrows, safe_lookup_range, max_range_size)
         {
             max_logrows -= 1;
         }
 
-        if !self
-            .extended_k_is_small_enough(max_logrows, Self::calc_num_cols(safe_range, max_logrows))
-        {
+        if !self.extended_k_is_small_enough(max_logrows, safe_lookup_range, max_range_size) {
             let err_string = format!(
                 "extended k is too large to accommodate the quotient polynomial with logrows {}",
                 max_logrows
@@ -1094,67 +1143,27 @@ impl GraphCircuit {
             return Err(err_string.into());
         }
 
-        let min_bits = ((safe_range.1 - safe_range.0) as f64 + reserved_blinding_rows + 1.)
-            .log2()
-            .ceil() as usize;
-
-        let min_rows_from_constraints = (self.settings().num_rows as f64 + reserved_blinding_rows)
-            .log2()
-            .ceil() as usize;
-
-        let mut logrows = std::cmp::max(min_bits, min_rows_from_constraints);
-
-        // if public input then public inputs col will have public inputs len
-        if self.settings().run_args.input_visibility.is_public()
-            || self.settings().run_args.output_visibility.is_public()
-        {
-            let mut max_instance_len = self
-                .model()
-                .instance_shapes()?
-                .iter()
-                .fold(0, |acc, x| std::cmp::max(acc, x.iter().product::<usize>()))
-                as f64
-                + reserved_blinding_rows;
-            // if there are modules then we need to add the max module size
-            if self.settings().uses_modules() {
-                max_instance_len += self
-                    .settings()
-                    .module_sizes
-                    .num_instances()
-                    .iter()
-                    .sum::<usize>() as f64;
-            }
-            let instance_len_logrows = (max_instance_len).log2().ceil() as usize;
-            logrows = std::cmp::max(logrows, instance_len_logrows);
-            // this is for fixed const columns
-        }
-
-        // ensure logrows is at least 4
-        logrows = std::cmp::max(logrows, min_logrows as usize);
-        logrows = std::cmp::min(logrows, max_logrows as usize);
+        let logrows = max_logrows;
 
         let model = self.model().clone();
         let settings_mut = self.settings_mut();
-        settings_mut.run_args.lookup_range = safe_range;
-        settings_mut.run_args.logrows = logrows as u32;
+        settings_mut.run_args.lookup_range = safe_lookup_range;
+        settings_mut.run_args.logrows = logrows;
 
         *settings_mut = GraphCircuit::new(model, &settings_mut.run_args)?
             .settings()
             .clone();
 
-        // recalculate the total const size give nthe new logrows
-        let total_const_len = settings_mut.total_const_size;
-        let const_len_logrows = (total_const_len as f64).log2().ceil() as u32;
-        settings_mut.run_args.logrows =
-            std::cmp::max(settings_mut.run_args.logrows, const_len_logrows);
-        // recalculate the total number of constraints given the new logrows
-        let min_rows_from_constraints = (settings_mut.num_rows as f64 + reserved_blinding_rows)
-            .log2()
-            .ceil() as u32;
-        settings_mut.run_args.logrows =
-            std::cmp::max(settings_mut.run_args.logrows, min_rows_from_constraints);
-
-        settings_mut.run_args.logrows = std::cmp::min(max_logrows, settings_mut.run_args.logrows);
+        // recalculate the logrows if there has been overflow on the constants
+        settings_mut.run_args.logrows = std::cmp::max(
+            settings_mut.run_args.logrows,
+            settings_mut.constants_logrows(),
+        );
+        // recalculate the logrows if there has been overflow for the model constraints
+        settings_mut.run_args.logrows = std::cmp::max(
+            settings_mut.run_args.logrows,
+            settings_mut.model_constraint_logrows(),
+        );
 
         debug!(
             "setting lookup_range to: {:?}, setting logrows to: {}",
@@ -1165,12 +1174,29 @@ impl GraphCircuit {
         Ok(())
     }
 
-    fn extended_k_is_small_enough(&self, k: u32, num_lookup_cols: usize) -> bool {
-        let max_degree = self.settings().run_args.num_inner_cols + 2;
-        let max_lookup_degree = LOOKUP_DEG + num_lookup_cols - 1; // num_lookup_cols - 1 is the degree of the lookup synthetic selector
+    fn extended_k_is_small_enough(
+        &self,
+        k: u32,
+        safe_lookup_range: Range,
+        max_range_size: i128,
+    ) -> bool {
+        // if num cols is too large then the extended k is too large
+        if Self::calc_num_cols(safe_lookup_range.1 - safe_lookup_range.0, k) > MAX_NUM_LOOKUP_COLS {
+            return false;
+        } else if Self::calc_num_cols(max_range_size, k) > MAX_NUM_LOOKUP_COLS {
+            return false;
+        }
 
-        let max_degree = std::cmp::max(max_degree, max_lookup_degree);
+        let mut settings = self.settings().clone();
+        settings.run_args.lookup_range = safe_lookup_range;
+        settings.run_args.logrows = k;
+        settings.required_range_checks = vec![(0, max_range_size)];
+        let mut cs = ConstraintSystem::default();
+        Self::configure_with_params(&mut cs, settings);
+        #[cfg(feature = "mv-lookup")]
+        let cs = cs.chunk_lookups();
         // quotient_poly_degree * params.n - 1 is the degree of the quotient polynomial
+        let max_degree = cs.degree();
         let quotient_poly_degree = (max_degree - 1) as u64;
         // n = 2^k
         let n = 1u64 << k;
@@ -1185,29 +1211,13 @@ impl GraphCircuit {
         true
     }
 
-    /// Calibrate the circuit to the supplied data.
-    pub fn calibrate_from_min_max(
-        &mut self,
-        min_lookup_inputs: i128,
-        max_lookup_inputs: i128,
-        max_logrows: Option<u32>,
-        lookup_safety_margin: i128,
-    ) -> Result<(), Box<dyn std::error::Error>> {
-        self.calc_min_logrows(
-            min_lookup_inputs,
-            max_lookup_inputs,
-            max_logrows,
-            lookup_safety_margin,
-        )?;
-        Ok(())
-    }
-
     /// Runs the forward pass of the model / graph of computations and any associated hashing.
     pub fn forward(
         &self,
         inputs: &mut [Tensor<Fp>],
         vk: Option<&VerifyingKey<G1Affine>>,
         srs: Option<&ParamsKZG<Bn256>>,
+        throw_range_check_error: bool,
     ) -> Result<GraphWitness, Box<dyn std::error::Error>> {
         let original_inputs = inputs.to_vec();
 
@@ -1248,7 +1258,9 @@ impl GraphCircuit {
             }
         }
 
-        let mut model_results = self.model().forward(inputs, &self.settings().run_args)?;
+        let mut model_results =
+            self.model()
+                .forward(inputs, &self.settings().run_args, throw_range_check_error)?;
 
         if visibility.output.requires_processing() {
             let module_outlets = visibility.output.overwrites_inputs();
@@ -1291,6 +1303,7 @@ impl GraphCircuit {
             processed_outputs,
             max_lookup_inputs: model_results.max_lookup_inputs,
             min_lookup_inputs: model_results.min_lookup_inputs,
+            max_range_size: model_results.max_range_size,
         };
 
         witness.generate_rescaled_elements(
@@ -1497,34 +1510,18 @@ impl Circuit<Fp> for GraphCircuit {
             params.run_args.logrows as usize,
         );
 
-        let mut vars = ModelVars::new(
-            cs,
-            params.run_args.logrows as usize,
-            params.total_assignments,
-            params.run_args.num_inner_cols,
-            params.total_const_size,
-            params.module_requires_fixed(),
-        );
+        let mut vars = ModelVars::new(cs, &params);
 
         module_configs.configure_complex_modules(cs, visibility, params.module_sizes.clone());
 
         vars.instantiate_instance(
             cs,
-            params.model_instance_shapes,
+            params.model_instance_shapes.clone(),
             params.run_args.input_scale,
             module_configs.instance,
         );
 
-        let base = Model::configure(
-            cs,
-            &vars,
-            params.run_args.lookup_range,
-            params.run_args.logrows as usize,
-            params.required_lookups,
-            params.required_range_checks,
-            params.check_mode,
-        )
-        .unwrap();
+        let base = Model::configure(cs, &vars, &params).unwrap();
 
         let model_config = ModelConfig { base, vars };
 

src/graph/model.rs

@@ -67,6 +67,8 @@ pub struct ForwardResult {
     pub max_lookup_inputs: i128,
     /// The minimum value of any input to a lookup operation.
     pub min_lookup_inputs: i128,
+    /// The max range check size
+    pub max_range_size: i128,
 }
 
 impl From<DummyPassRes> for ForwardResult {
@@ -75,6 +77,7 @@ impl From<DummyPassRes> for ForwardResult {
             outputs: res.outputs,
             max_lookup_inputs: res.max_lookup_inputs,
             min_lookup_inputs: res.min_lookup_inputs,
+            max_range_size: res.max_range_size,
         }
     }
 }
@@ -96,6 +99,10 @@ pub type NodeGraph = BTreeMap<usize, NodeType>;
 pub struct DummyPassRes {
     /// number of rows use
     pub num_rows: usize,
+    /// num dynamic lookups
+    pub num_dynamic_lookups: usize,
+    /// dynamic lookup col size
+    pub dynamic_lookup_col_coord: usize,
     /// linear coordinate
     pub linear_coord: usize,
     /// total const size
@@ -108,6 +115,8 @@ pub struct DummyPassRes {
     pub max_lookup_inputs: i128,
     /// min lookup inputs
     pub min_lookup_inputs: i128,
+    /// min range check
+    pub max_range_size: i128,
     /// outputs
     pub outputs: Vec<Tensor<Fp>>,
 }
@@ -521,7 +530,7 @@ impl Model {
             })
             .collect::<Result<Vec<_>, Box<dyn Error>>>()?;
 
-        let res = self.dummy_layout(run_args, &inputs)?;
+        let res = self.dummy_layout(run_args, &inputs, false)?;
 
         // if we're using percentage tolerance, we need to add the necessary range check ops for it.
 
@@ -535,6 +544,8 @@ impl Model {
             required_range_checks: res.range_checks.into_iter().collect(),
             model_output_scales: self.graph.get_output_scales()?,
             model_input_scales: self.graph.get_input_scales(),
+            num_dynamic_lookups: res.num_dynamic_lookups,
+            total_dynamic_col_size: res.dynamic_lookup_col_coord,
             total_const_size: res.total_const_size,
             check_mode,
             version: env!("CARGO_PKG_VERSION").to_string(),
@@ -560,12 +571,13 @@ impl Model {
         &self,
         model_inputs: &[Tensor<Fp>],
         run_args: &RunArgs,
+        throw_range_check_error: bool,
     ) -> Result<ForwardResult, Box<dyn Error>> {
         let valtensor_inputs: Vec<ValTensor<Fp>> = model_inputs
             .iter()
             .map(|x| x.map(|elem| ValType::Value(Value::known(elem))).into())
             .collect();
-        let res = self.dummy_layout(&run_args, &valtensor_inputs)?;
+        let res = self.dummy_layout(run_args, &valtensor_inputs, throw_range_check_error)?;
         Ok(res.into())
     }
 
@@ -997,24 +1009,25 @@ impl Model {
     /// # Arguments
     /// * `meta` - The constraint system.
     /// * `vars` - The variables for the circuit.
-    /// * `run_args` - [RunArgs]
-    /// * `required_lookups` - The required lookup operations for the circuit.
+    /// * `settings` - [GraphSettings]
     pub fn configure(
         meta: &mut ConstraintSystem<Fp>,
         vars: &ModelVars<Fp>,
-        lookup_range: Range,
-        logrows: usize,
-        required_lookups: Vec<LookupOp>,
-        required_range_checks: Vec<Range>,
-        check_mode: CheckMode,
+        settings: &GraphSettings,
     ) -> Result<PolyConfig<Fp>, Box<dyn Error>> {
-        info!("configuring model");
+        debug!("configuring model");
+
+        let lookup_range = settings.run_args.lookup_range;
+        let logrows = settings.run_args.logrows as usize;
+        let num_dynamic_lookups = settings.num_dynamic_lookups;
+        let required_lookups = settings.required_lookups.clone();
+        let required_range_checks = settings.required_range_checks.clone();
 
         let mut base_gate = PolyConfig::configure(
             meta,
             vars.advices[0..2].try_into()?,
             &vars.advices[2],
-            check_mode,
+            settings.check_mode,
         );
         // set scale for HybridOp::RangeCheck and call self.conf_lookup on that op for percentage tolerance case
         let input = &vars.advices[0];
@@ -1025,7 +1038,15 @@ impl Model {
         }
 
         for range in required_range_checks {
-            base_gate.configure_range_check(meta, input, range)?;
+            base_gate.configure_range_check(meta, input, index, range, logrows)?;
+        }
+
+        for _ in 0..num_dynamic_lookups {
+            base_gate.configure_dynamic_lookup(
+                meta,
+                vars.advices[0..2].try_into()?,
+                vars.advices[3..5].try_into()?,
+            )?;
         }
 
         Ok(base_gate)
@@ -1346,6 +1367,7 @@ impl Model {
         &self,
         run_args: &RunArgs,
         inputs: &[ValTensor<Fp>],
+        throw_range_check_error: bool,
     ) -> Result<DummyPassRes, Box<dyn Error>> {
         debug!("calculating num of constraints using dummy model layout...");
 
@@ -1364,7 +1386,7 @@ impl Model {
             vars: ModelVars::new_dummy(),
         };
 
-        let mut region = RegionCtx::new_dummy(0, run_args.num_inner_cols);
+        let mut region = RegionCtx::new_dummy(0, run_args.num_inner_cols, throw_range_check_error);
 
         let outputs = self.layout_nodes(&mut model_config, &mut region, &mut results)?;
 
@@ -1431,6 +1453,9 @@ impl Model {
             range_checks: region.used_range_checks(),
             max_lookup_inputs: region.max_lookup_inputs(),
             min_lookup_inputs: region.min_lookup_inputs(),
+            max_range_size: region.max_range_size(),
+            num_dynamic_lookups: region.dynamic_lookup_index(),
+            dynamic_lookup_col_coord: region.dynamic_lookup_col_coord(),
             outputs,
         };
 

src/graph/utilities.rs

@@ -734,7 +734,7 @@ pub fn new_op_from_onnx(
             SupportedOp::Hybrid(HybridOp::Recip {
                 input_scale: (scale_to_multiplier(in_scale) as f32).into(),
                 output_scale: (scale_to_multiplier(max_scale) as f32).into(),
-                use_range_check_for_int: false,
+                use_range_check_for_int: true,
             })
         }
 

src/graph/vars.rs

@@ -420,20 +420,31 @@ impl<F: PrimeField + TensorType + PartialOrd> ModelVars<F> {
     }
 
     /// Allocate all columns that will be assigned to by a model.
-    pub fn new(
-        cs: &mut ConstraintSystem<F>,
-        logrows: usize,
-        var_len: usize,
-        num_inner_cols: usize,
-        num_constants: usize,
-        module_requires_fixed: bool,
-    ) -> Self {
+    pub fn new(cs: &mut ConstraintSystem<F>, params: &GraphSettings) -> Self {
         debug!("number of blinding factors: {}", cs.blinding_factors());
 
-        let advices = (0..3)
+        let logrows = params.run_args.logrows as usize;
+        let var_len = params.total_assignments;
+        let num_inner_cols = params.run_args.num_inner_cols;
+        let num_constants = params.total_const_size;
+        let module_requires_fixed = params.module_requires_fixed();
+        let requires_dynamic_lookup = params.requires_dynamic_lookup();
+        let dynamic_lookup_size = params.total_dynamic_col_size;
+
+        let mut advices = (0..3)
             .map(|_| VarTensor::new_advice(cs, logrows, num_inner_cols, var_len))
             .collect_vec();
 
+        if requires_dynamic_lookup {
+            for _ in 0..2 {
+                let dynamic_lookup = VarTensor::new_advice(cs, logrows, 1, dynamic_lookup_size);
+                if dynamic_lookup.num_blocks() > 1 {
+                    panic!("dynamic lookup should only have one block");
+                };
+                advices.push(dynamic_lookup);
+            }
+        }
+
         debug!(
             "model uses {} advice blocks (size={})",
             advices.iter().map(|v| v.num_blocks()).sum::<usize>(),

src/lib.rs

@@ -180,6 +180,9 @@ impl RunArgs {
         if self.num_inner_cols < 1 {
             return Err("num_inner_cols must be >= 1".into());
         }
+        if self.tolerance.val > 0.0 && self.output_visibility != Visibility::Public {
+            return Err("tolerance > 0.0 requires output_visibility to be public".into());
+        }
         Ok(())
     }
 

src/pfsys/mod.rs

@@ -197,7 +197,11 @@ impl std::fmt::Display for TranscriptType {
     }
 }
 
-impl ToFlags for TranscriptType {}
+impl ToFlags for TranscriptType {
+    fn to_flags(&self) -> Vec<String> {
+        vec![format!("{}", self)]
+    }
+}
 
 #[cfg(feature = "python-bindings")]
 impl ToPyObject for TranscriptType {
@@ -212,8 +216,8 @@ impl ToPyObject for TranscriptType {
 #[cfg(feature = "python-bindings")]
 ///
 pub fn g1affine_to_pydict(g1affine_dict: &PyDict, g1affine: &G1Affine) {
-    let g1affine_x = field_to_string_montgomery(&g1affine.x);
-    let g1affine_y = field_to_string_montgomery(&g1affine.y);
+    let g1affine_x = field_to_string(&g1affine.x);
+    let g1affine_y = field_to_string(&g1affine.y);
     g1affine_dict.set_item("x", g1affine_x).unwrap();
     g1affine_dict.set_item("y", g1affine_y).unwrap();
 }
@@ -223,23 +227,23 @@ use halo2curves::bn256::G1;
 #[cfg(feature = "python-bindings")]
 ///
 pub fn g1_to_pydict(g1_dict: &PyDict, g1: &G1) {
-    let g1_x = field_to_string_montgomery(&g1.x);
-    let g1_y = field_to_string_montgomery(&g1.y);
-    let g1_z = field_to_string_montgomery(&g1.z);
+    let g1_x = field_to_string(&g1.x);
+    let g1_y = field_to_string(&g1.y);
+    let g1_z = field_to_string(&g1.z);
     g1_dict.set_item("x", g1_x).unwrap();
     g1_dict.set_item("y", g1_y).unwrap();
     g1_dict.set_item("z", g1_z).unwrap();
 }
 
-/// converts fp into `Vec<u64>` in Montgomery form
-pub fn field_to_string_montgomery<F: PrimeField + SerdeObject + Serialize>(fp: &F) -> String {
+/// converts fp into a little endian Hex string
+pub fn field_to_string<F: PrimeField + SerdeObject + Serialize>(fp: &F) -> String {
     let repr = serde_json::to_string(&fp).unwrap();
     let b: String = serde_json::from_str(&repr).unwrap();
     b
 }
 
-/// converts `Vec<u64>` in Montgomery form into fp
-pub fn string_to_field_montgomery<F: PrimeField + SerdeObject + Serialize + DeserializeOwned>(
+/// converts a little endian Hex string into a field element
+pub fn string_to_field<F: PrimeField + SerdeObject + Serialize + DeserializeOwned>(
     b: &String,
 ) -> F {
     let repr = serde_json::to_string(&b).unwrap();
@@ -304,7 +308,7 @@ where
         let field_elems: Vec<Vec<String>> = self
             .instances
             .iter()
-            .map(|x| x.iter().map(|fp| field_to_string_montgomery(fp)).collect())
+            .map(|x| x.iter().map(|fp| field_to_string(fp)).collect())
             .collect::<Vec<_>>();
         dict.set_item("instances", field_elems).unwrap();
         let hex_proof = hex::encode(&self.proof);

src/python.rs

@@ -63,9 +63,9 @@ struct PyG1 {
 impl From<G1> for PyG1 {
     fn from(g1: G1) -> Self {
         PyG1 {
-            x: crate::pfsys::field_to_string_montgomery::<Fq>(&g1.x),
-            y: crate::pfsys::field_to_string_montgomery::<Fq>(&g1.y),
-            z: crate::pfsys::field_to_string_montgomery::<Fq>(&g1.z),
+            x: crate::pfsys::field_to_string::<Fq>(&g1.x),
+            y: crate::pfsys::field_to_string::<Fq>(&g1.y),
+            z: crate::pfsys::field_to_string::<Fq>(&g1.z),
         }
     }
 }
@@ -73,9 +73,9 @@ impl From<G1> for PyG1 {
 impl From<PyG1> for G1 {
     fn from(val: PyG1) -> Self {
         G1 {
-            x: crate::pfsys::string_to_field_montgomery::<Fq>(&val.x),
-            y: crate::pfsys::string_to_field_montgomery::<Fq>(&val.y),
-            z: crate::pfsys::string_to_field_montgomery::<Fq>(&val.z),
+            x: crate::pfsys::string_to_field::<Fq>(&val.x),
+            y: crate::pfsys::string_to_field::<Fq>(&val.y),
+            z: crate::pfsys::string_to_field::<Fq>(&val.z),
         }
     }
 }
@@ -106,8 +106,8 @@ pub struct PyG1Affine {
 impl From<G1Affine> for PyG1Affine {
     fn from(g1: G1Affine) -> Self {
         PyG1Affine {
-            x: crate::pfsys::field_to_string_montgomery::<Fq>(&g1.x),
-            y: crate::pfsys::field_to_string_montgomery::<Fq>(&g1.y),
+            x: crate::pfsys::field_to_string::<Fq>(&g1.x),
+            y: crate::pfsys::field_to_string::<Fq>(&g1.y),
         }
     }
 }
@@ -115,8 +115,8 @@ impl From<G1Affine> for PyG1Affine {
 impl From<PyG1Affine> for G1Affine {
     fn from(val: PyG1Affine) -> Self {
         G1Affine {
-            x: crate::pfsys::string_to_field_montgomery::<Fq>(&val.x),
-            y: crate::pfsys::string_to_field_montgomery::<Fq>(&val.y),
+            x: crate::pfsys::string_to_field::<Fq>(&val.x),
+            y: crate::pfsys::string_to_field::<Fq>(&val.y),
         }
     }
 }
@@ -217,53 +217,51 @@ impl Into<PyRunArgs> for RunArgs {
     }
 }
 
-/// Converts 4 u64s to a field element
+/// Converts a felt to big endian
 #[pyfunction(signature = (
-    array,
+    felt,
 ))]
-fn string_to_felt(array: PyFelt) -> PyResult<String> {
-    Ok(format!(
-        "{:?}",
-        crate::pfsys::string_to_field_montgomery::<Fr>(&array)
-    ))
+fn felt_to_big_endian(felt: PyFelt) -> PyResult<String> {
+    let felt = crate::pfsys::string_to_field::<Fr>(&felt);
+    Ok(format!("{:?}", felt))
 }
 
-/// Converts 4 u64s representing a field element directly to an integer
+/// Converts a field element hex string to an integer
 #[pyfunction(signature = (
     array,
 ))]
-fn string_to_int(array: PyFelt) -> PyResult<i128> {
-    let felt = crate::pfsys::string_to_field_montgomery::<Fr>(&array);
+fn felt_to_int(array: PyFelt) -> PyResult<i128> {
+    let felt = crate::pfsys::string_to_field::<Fr>(&array);
     let int_rep = felt_to_i128(felt);
     Ok(int_rep)
 }
 
-/// Converts 4 u64s representing a field element directly to a (rescaled from fixed point scaling) floating point
+/// Converts a field eleement hex string to a floating point number
 #[pyfunction(signature = (
     array,
     scale
 ))]
-fn string_to_float(array: PyFelt, scale: crate::Scale) -> PyResult<f64> {
-    let felt = crate::pfsys::string_to_field_montgomery::<Fr>(&array);
+fn felt_to_float(array: PyFelt, scale: crate::Scale) -> PyResult<f64> {
+    let felt = crate::pfsys::string_to_field::<Fr>(&array);
     let int_rep = felt_to_i128(felt);
     let multiplier = scale_to_multiplier(scale);
     let float_rep = int_rep as f64 / multiplier;
     Ok(float_rep)
 }
 
-/// Converts a floating point element to 4 u64s representing a fixed point field element
+/// Converts a floating point element to a field element hex string
 #[pyfunction(signature = (
 input,
 scale
 ))]
-fn float_to_string(input: f64, scale: crate::Scale) -> PyResult<PyFelt> {
+fn float_to_felt(input: f64, scale: crate::Scale) -> PyResult<PyFelt> {
     let int_rep = quantize_float(&input, 0.0, scale)
         .map_err(|_| PyIOError::new_err("Failed to quantize input"))?;
     let felt = i128_to_felt(int_rep);
-    Ok(crate::pfsys::field_to_string_montgomery::<Fr>(&felt))
+    Ok(crate::pfsys::field_to_string::<Fr>(&felt))
 }
 
-/// Converts a buffer to vector of 4 u64s representing a fixed point field element
+/// Converts a buffer to vector of field elements
 #[pyfunction(signature = (
     buffer
     ))]
@@ -316,7 +314,10 @@ fn buffer_to_felts(buffer: Vec<u8>) -> PyResult<Vec<String>> {
         .map(|x| PrimeField::from_u128(u8_array_to_u128_le(*x)))
         .collect();
 
-    let field_elements: Vec<String> = field_elements.iter().map(|x| format!("{:?}", x)).collect();
+    let field_elements: Vec<String> = field_elements
+        .iter()
+        .map(|x| crate::pfsys::field_to_string::<Fr>(x))
+        .collect();
 
     Ok(field_elements)
 }
@@ -328,7 +329,7 @@ fn buffer_to_felts(buffer: Vec<u8>) -> PyResult<Vec<String>> {
 fn poseidon_hash(message: Vec<PyFelt>) -> PyResult<Vec<PyFelt>> {
     let message: Vec<Fr> = message
         .iter()
-        .map(crate::pfsys::string_to_field_montgomery::<Fr>)
+        .map(crate::pfsys::string_to_field::<Fr>)
         .collect::<Vec<_>>();
 
     let output =
@@ -339,7 +340,7 @@ fn poseidon_hash(message: Vec<PyFelt>) -> PyResult<Vec<PyFelt>> {
 
     let hash = output[0]
         .iter()
-        .map(crate::pfsys::field_to_string_montgomery::<Fr>)
+        .map(crate::pfsys::field_to_string::<Fr>)
         .collect::<Vec<_>>();
     Ok(hash)
 }
@@ -359,7 +360,7 @@ fn kzg_commit(
 ) -> PyResult<Vec<PyG1Affine>> {
     let message: Vec<Fr> = message
         .iter()
-        .map(crate::pfsys::string_to_field_montgomery::<Fr>)
+        .map(crate::pfsys::string_to_field::<Fr>)
         .collect::<Vec<_>>();
 
     let settings = GraphSettings::load(&settings_path)
@@ -1103,13 +1104,13 @@ fn ezkl(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
     m.add_class::<PyG1Affine>()?;
     m.add_class::<PyG1>()?;
     m.add_class::<PyTestDataSource>()?;
-    m.add_function(wrap_pyfunction!(string_to_felt, m)?)?;
-    m.add_function(wrap_pyfunction!(string_to_int, m)?)?;
-    m.add_function(wrap_pyfunction!(string_to_float, m)?)?;
+    m.add_function(wrap_pyfunction!(felt_to_big_endian, m)?)?;
+    m.add_function(wrap_pyfunction!(felt_to_int, m)?)?;
+    m.add_function(wrap_pyfunction!(felt_to_float, m)?)?;
     m.add_function(wrap_pyfunction!(kzg_commit, m)?)?;
     m.add_function(wrap_pyfunction!(swap_proof_commitments, m)?)?;
     m.add_function(wrap_pyfunction!(poseidon_hash, m)?)?;
-    m.add_function(wrap_pyfunction!(float_to_string, m)?)?;
+    m.add_function(wrap_pyfunction!(float_to_felt, m)?)?;
     m.add_function(wrap_pyfunction!(buffer_to_felts, m)?)?;
     m.add_function(wrap_pyfunction!(gen_vk_from_pk_aggr, m)?)?;
     m.add_function(wrap_pyfunction!(gen_vk_from_pk_single, m)?)?;

src/tensor/ops.rs

@@ -3773,6 +3773,30 @@ pub mod nonlinearities {
         .unwrap()
     }
 
+    /// Elementwise inverse.
+    /// # Arguments
+    /// * `out_scale` - Single value
+    /// # Examples
+    /// ```
+    /// use ezkl::tensor::Tensor;
+    /// use ezkl::tensor::ops::nonlinearities::zero_recip;
+    /// let k = 2_f64;
+    /// let result = zero_recip(1.0);
+    /// let expected = Tensor::<i128>::new(Some(&[4503599627370496]), &[1]).unwrap();
+    /// assert_eq!(result, expected);
+    /// ```
+    pub fn zero_recip(out_scale: f64) -> Tensor<i128> {
+        let a = Tensor::<i128>::new(Some(&[0]), &[1]).unwrap();
+
+        a.par_enum_map(|_, a_i| {
+            let rescaled = a_i as f64;
+            let denom = (1_f64) / (rescaled + f64::EPSILON);
+            let d_inv_x = out_scale * denom;
+            Ok::<_, TensorError>(d_inv_x.round() as i128)
+        })
+        .unwrap()
+    }
+
     /// Elementwise greater than
     /// # Arguments
     ///

src/wasm.rs

@@ -69,19 +69,19 @@ pub fn encodeVerifierCalldata(
     Ok(encoded)
 }
 
-/// Converts 4 u64s to a field element
+/// Converts a hex string to a byte array
 #[wasm_bindgen]
 #[allow(non_snake_case)]
-pub fn stringToFelt(array: wasm_bindgen::Clamped<Vec<u8>>) -> Result<String, JsError> {
+pub fn feltToBigEndian(array: wasm_bindgen::Clamped<Vec<u8>>) -> Result<String, JsError> {
     let felt: Fr = serde_json::from_slice(&array[..])
         .map_err(|e| JsError::new(&format!("Failed to deserialize field element: {}", e)))?;
     Ok(format!("{:?}", felt))
 }
 
-/// Converts 4 u64s representing a field element directly to an integer
+/// Converts a hex string to a byte array
 #[wasm_bindgen]
 #[allow(non_snake_case)]
-pub fn stringToInt(
+pub fn feltToInt(
     array: wasm_bindgen::Clamped<Vec<u8>>,
 ) -> Result<wasm_bindgen::Clamped<Vec<u8>>, JsError> {
     let felt: Fr = serde_json::from_slice(&array[..])
@@ -92,10 +92,10 @@ pub fn stringToInt(
     ))
 }
 
-/// Converts 4 u64s representing a field element directly to a (rescaled from fixed point scaling) floating point
+/// Converts felts to a floating point element
 #[wasm_bindgen]
 #[allow(non_snake_case)]
-pub fn stringToFloat(
+pub fn feltToFloat(
     array: wasm_bindgen::Clamped<Vec<u8>>,
     scale: crate::Scale,
 ) -> Result<f64, JsError> {
@@ -106,26 +106,26 @@ pub fn stringToFloat(
     Ok(int_rep as f64 / multiplier)
 }
 
-/// Converts a floating point element to 4 u64s representing a fixed point field element
+/// Converts a floating point number to a hex string representing a fixed point field element
 #[wasm_bindgen]
 #[allow(non_snake_case)]
-pub fn floatTostring(
+pub fn floatToFelt(
     input: f64,
     scale: crate::Scale,
 ) -> Result<wasm_bindgen::Clamped<Vec<u8>>, JsError> {
     let int_rep =
         quantize_float(&input, 0.0, scale).map_err(|e| JsError::new(&format!("{}", e)))?;
     let felt = i128_to_felt(int_rep);
-    let vec = crate::pfsys::field_to_string_montgomery::<halo2curves::bn256::Fr>(&felt);
+    let vec = crate::pfsys::field_to_string::<halo2curves::bn256::Fr>(&felt);
     Ok(wasm_bindgen::Clamped(serde_json::to_vec(&vec).map_err(
-        |e| JsError::new(&format!("Failed to serialize string_montgomery{}", e)),
+        |e| JsError::new(&format!("Failed to serialize a float to felt{}", e)),
     )?))
 }
 
 /// Converts a buffer to vector of 4 u64s representing a fixed point field element
 #[wasm_bindgen]
 #[allow(non_snake_case)]
-pub fn bufferToVecOfstring(
+pub fn bufferToVecOfFelt(
     buffer: wasm_bindgen::Clamped<Vec<u8>>,
 ) -> Result<wasm_bindgen::Clamped<Vec<u8>>, JsError> {
     // Convert the buffer to a slice
@@ -211,7 +211,7 @@ pub fn genWitness(
         .map_err(|e| JsError::new(&format!("{}", e)))?;
 
     let witness = circuit
-        .forward(&mut input, None, None)
+        .forward(&mut input, None, None, false)
         .map_err(|e| JsError::new(&format!("{}", e)))?;
 
     serde_json::to_vec(&witness)

tests/integration_tests.rs

@@ -2,6 +2,8 @@
 #[cfg(test)]
 mod native_tests {
 
+    use ezkl::circuit::Tolerance;
+    use ezkl::fieldutils::{felt_to_i128, i128_to_felt};
     // use ezkl::circuit::table::RESERVED_BLINDING_ROWS_PAD;
     use ezkl::graph::input::{FileSource, FileSourceInner, GraphData};
     use ezkl::graph::{DataSource, GraphSettings, GraphWitness};
@@ -275,7 +277,7 @@ mod native_tests {
         "bitshift",
     ];
 
-    const WASM_TESTS: [&str; 48] = [
+    const WASM_TESTS: [&str; 46] = [
         "1l_mlp",
         "1l_slice",
         "1l_concat",
@@ -324,8 +326,6 @@ mod native_tests {
         "1l_where",
         "boolean",
         "boolean_identity",
-        "decision_tree", // "variable_cnn",
-        "random_forest",
         "gradient_boosted_trees",
         "1l_topk",
         // "xgboost",
@@ -585,6 +585,8 @@ mod native_tests {
                 test_dir.close().unwrap();
             }
 
+
+
             #(#[test_case(TESTS[N])])*
             fn mock_large_batch_public_outputs_(test: &str) {
                 crate::native_tests::init_binary();
@@ -840,7 +842,7 @@ mod native_tests {
 
             });
 
-            seq!(N in 0..=47 {
+            seq!(N in 0..=45 {
 
                 #(#[test_case(WASM_TESTS[N])])*
                 fn kzg_prove_and_verify_with_overflow_(test: &str) {
@@ -1287,6 +1289,7 @@ mod native_tests {
         scales_to_use: Option<Vec<u32>>,
         tolerance: f32,
     ) {
+        let mut tolerance = tolerance;
         gen_circuit_settings_and_witness(
             test_dir,
             example_name.clone(),
@@ -1298,20 +1301,131 @@ mod native_tests {
             scales_to_use,
             2,
             false,
-            tolerance,
+            &mut tolerance,
         );
 
-        let status = Command::new(format!("{}/release/ezkl", *CARGO_TARGET_DIR))
-            .args([
-                "mock",
-                "-W",
-                format!("{}/{}/witness.json", test_dir, example_name).as_str(),
-                "-M",
-                format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
-            ])
-            .status()
-            .expect("failed to execute process");
-        assert!(status.success());
+        if tolerance > 0.0 {
+            // load witness and shift the output by a small amount that is less than tolerance percent
+            let witness = GraphWitness::from_path(
+                format!("{}/{}/witness.json", test_dir, example_name).into(),
+            )
+            .unwrap();
+            let witness = witness.clone();
+            let outputs = witness.outputs.clone();
+
+            // get values as i128
+            let output_perturbed_safe: Vec<Vec<halo2curves::bn256::Fr>> = outputs
+                .iter()
+                .map(|sv| {
+                    sv.iter()
+                        .map(|v| {
+                            // randomly perturb by a small amount less than tolerance
+                            let perturbation = if v == &halo2curves::bn256::Fr::zero() {
+                                halo2curves::bn256::Fr::zero()
+                            } else {
+                                i128_to_felt(
+                                    (felt_to_i128(*v) as f32
+                                        * (rand::thread_rng().gen_range(-0.01..0.01) * tolerance))
+                                        as i128,
+                                )
+                            };
+
+                            *v + perturbation
+                        })
+                        .collect::<Vec<_>>()
+                })
+                .collect::<Vec<_>>();
+
+            // get values as i128
+            let output_perturbed_bad: Vec<Vec<halo2curves::bn256::Fr>> = outputs
+                .iter()
+                .map(|sv| {
+                    sv.iter()
+                        .map(|v| {
+                            // randomly perturb by a small amount less than tolerance
+                            let perturbation = if v == &halo2curves::bn256::Fr::zero() {
+                                halo2curves::bn256::Fr::from(2)
+                            } else {
+                                i128_to_felt(
+                                    (felt_to_i128(*v) as f32
+                                        * (rand::thread_rng().gen_range(0.02..0.1) * tolerance))
+                                        as i128,
+                                )
+                            };
+                            *v + perturbation
+                        })
+                        .collect::<Vec<_>>()
+                })
+                .collect::<Vec<_>>();
+
+            let good_witness = GraphWitness {
+                outputs: output_perturbed_safe,
+                ..witness.clone()
+            };
+
+            // save
+            good_witness
+                .save(format!("{}/{}/witness_ok.json", test_dir, example_name).into())
+                .unwrap();
+
+            let bad_witness = GraphWitness {
+                outputs: output_perturbed_bad,
+                ..witness.clone()
+            };
+
+            // save
+            bad_witness
+                .save(format!("{}/{}/witness_bad.json", test_dir, example_name).into())
+                .unwrap();
+
+            let status = Command::new(format!("{}/release/ezkl", *CARGO_TARGET_DIR))
+                .args([
+                    "mock",
+                    "-W",
+                    format!("{}/{}/witness.json", test_dir, example_name).as_str(),
+                    "-M",
+                    format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
+                ])
+                .status()
+                .expect("failed to execute process");
+            assert!(status.success());
+
+            let status = Command::new(format!("{}/release/ezkl", *CARGO_TARGET_DIR))
+                .args([
+                    "mock",
+                    "-W",
+                    format!("{}/{}/witness_ok.json", test_dir, example_name).as_str(),
+                    "-M",
+                    format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
+                ])
+                .status()
+                .expect("failed to execute process");
+            assert!(status.success());
+
+            let status = Command::new(format!("{}/release/ezkl", *CARGO_TARGET_DIR))
+                .args([
+                    "mock",
+                    "-W",
+                    format!("{}/{}/witness_bad.json", test_dir, example_name).as_str(),
+                    "-M",
+                    format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
+                ])
+                .status()
+                .expect("failed to execute process");
+            assert!(!status.success());
+        } else {
+            let status = Command::new(format!("{}/release/ezkl", *CARGO_TARGET_DIR))
+                .args([
+                    "mock",
+                    "-W",
+                    format!("{}/{}/witness.json", test_dir, example_name).as_str(),
+                    "-M",
+                    format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
+                ])
+                .status()
+                .expect("failed to execute process");
+            assert!(status.success());
+        }
     }
 
     #[allow(clippy::too_many_arguments)]
@@ -1326,7 +1440,7 @@ mod native_tests {
         scales_to_use: Option<Vec<u32>>,
         num_inner_columns: usize,
         div_rebasing: bool,
-        tolerance: f32,
+        tolerance: &mut f32,
     ) {
         let mut args = vec![
             "gen-settings".to_string(),
@@ -1384,6 +1498,24 @@ mod native_tests {
             .expect("failed to execute process");
         assert!(status.success());
 
+        let mut settings =
+            GraphSettings::load(&format!("{}/{}/settings.json", test_dir, example_name).into())
+                .unwrap();
+
+        let any_output_scales_smol = settings.model_output_scales.iter().any(|s| *s <= 0);
+
+        if any_output_scales_smol {
+            // set the tolerance to 0.0
+            settings.run_args.tolerance = Tolerance {
+                val: 0.0,
+                scale: 0.0.into(),
+            };
+            settings
+                .save(&format!("{}/{}/settings.json", test_dir, example_name).into())
+                .unwrap();
+            *tolerance = 0.0;
+        }
+
         let status = Command::new(format!("{}/release/ezkl", *CARGO_TARGET_DIR))
             .args([
                 "compile-circuit",
@@ -1441,7 +1573,7 @@ mod native_tests {
             None,
             2,
             div_rebasing,
-            0.0,
+            &mut 0.0,
         );
 
         println!(
@@ -1701,7 +1833,7 @@ mod native_tests {
             scales_to_use,
             num_inner_columns,
             false,
-            0.0,
+            &mut 0.0,
         );
 
         let settings_path = format!("{}/{}/settings.json", test_dir, example_name);
@@ -1803,7 +1935,7 @@ mod native_tests {
             None,
             2,
             false,
-            0.0,
+            &mut 0.0,
         );
 
         let status = Command::new(format!("{}/release/ezkl", *CARGO_TARGET_DIR))
@@ -2080,7 +2212,7 @@ mod native_tests {
             Some(vec![4]),
             1,
             false,
-            0.0,
+            &mut 0.0,
         );
 
         let model_path = format!("{}/{}/network.compiled", test_dir, example_name);

tests/output_comparison.py

@@ -12,7 +12,7 @@ def get_ezkl_output(witness_file, settings_file):
     outputs = witness_output['outputs']
     with open(settings_file) as f:
         settings = json.load(f)
-    ezkl_outputs = [[ezkl.string_to_float(
+    ezkl_outputs = [[ezkl.felt_to_float(
         outputs[i][j], settings['model_output_scales'][i]) for j in range(len(outputs[i]))] for i in range(len(outputs))]
     return ezkl_outputs
 
@@ -91,9 +91,7 @@ def compare_outputs(zk_output, onnx_output):
                 print("------- zk_output: ", list1_i)
                 print("------- onnx_output: ", list2_i)
 
-
-
-    return np.mean(np.abs(res))
+    return res
 
 
 if __name__ == '__main__':
@@ -113,6 +111,9 @@ if __name__ == '__main__':
     onnx_output = get_onnx_output(model_file, input_file)
     # compare the outputs
     percentage_difference = compare_outputs(ezkl_output, onnx_output)
+    mean_percentage_difference = np.mean(np.abs(percentage_difference))
+    max_percentage_difference = np.max(np.abs(percentage_difference))
     # print the percentage difference
-    print("mean percent diff: ", percentage_difference)
-    assert percentage_difference < target, "Percentage difference is too high"
+    print("mean percent diff: ", mean_percentage_difference)
+    print("max percent diff: ", max_percentage_difference)
+    assert mean_percentage_difference < target, "Percentage difference is too high"

tests/python/binding_tests.py

@@ -56,9 +56,9 @@ def test_poseidon_hash():
     Test for poseidon_hash
     """
     message = [1.0, 2.0, 3.0, 4.0]
-    message = [ezkl.float_to_string(x, 7) for x in message]
+    message = [ezkl.float_to_felt(x, 7) for x in message]
     res = ezkl.poseidon_hash(message)
-    assert ezkl.string_to_felt(
+    assert ezkl.felt_to_big_endian(
         res[0]) == "0x0da7e5e5c8877242fa699f586baf770d731defd54f952d4adeb85047a0e32f45"
 
 
@@ -70,14 +70,14 @@ def test_field_serialization():
 
     input = 890
     scale = 7
-    felt = ezkl.float_to_string(input, scale)
-    roundtrip_input = ezkl.string_to_float(felt, scale)
+    felt = ezkl.float_to_felt(input, scale)
+    roundtrip_input = ezkl.felt_to_float(felt, scale)
     assert input == roundtrip_input
 
     input = -700
     scale = 7
-    felt = ezkl.float_to_string(input, scale)
-    roundtrip_input = ezkl.string_to_float(felt, scale)
+    felt = ezkl.float_to_felt(input, scale)
+    roundtrip_input = ezkl.felt_to_float(felt, scale)
     assert input == roundtrip_input
 
 
@@ -88,12 +88,12 @@ def test_buffer_to_felts():
     buffer = bytearray("a sample string!", 'utf-8')
     felts = ezkl.buffer_to_felts(buffer)
     ref_felt_1 = "0x0000000000000000000000000000000021676e6972747320656c706d61732061"
-    assert felts == [ref_felt_1]
+    assert ezkl.felt_to_big_endian(felts[0]) == ref_felt_1
 
     buffer = bytearray("a sample string!"+"high", 'utf-8')
     felts = ezkl.buffer_to_felts(buffer)
     ref_felt_2 = "0x0000000000000000000000000000000000000000000000000000000068676968"
-    assert felts == [ref_felt_1, ref_felt_2]
+    assert [ezkl.felt_to_big_endian(felts[0]),  ezkl.felt_to_big_endian(felts[1])] == [ref_felt_1, ref_felt_2]
 
 
 def test_gen_srs():

tests/wasm.rs

@@ -8,9 +8,9 @@ mod wasm32 {
     use ezkl::graph::GraphWitness;
     use ezkl::pfsys;
     use ezkl::wasm::{
-        bufferToVecOfstring, compiledCircuitValidation, encodeVerifierCalldata, genPk, genVk,
-        genWitness, inputValidation, pkValidation, poseidonHash, proofValidation, prove,
-        settingsValidation, srsValidation, stringToFelt, stringToFloat, stringToInt,
+        bufferToVecOfFelt, compiledCircuitValidation, encodeVerifierCalldata, feltToBigEndian,
+        feltToFloat, feltToInt, genPk, genVk, genWitness, inputValidation, pkValidation,
+        poseidonHash, proofValidation, prove, settingsValidation, srsValidation,
         u8_array_to_u128_le, verify, vkValidation, witnessValidation,
     };
     use halo2_solidity_verifier::encode_calldata;
@@ -76,21 +76,21 @@ mod wasm32 {
         for i in 0..32 {
             let field_element = Fr::from(i);
             let serialized = serde_json::to_vec(&field_element).unwrap();
+
             let clamped = wasm_bindgen::Clamped(serialized);
             let scale = 2;
-            let floating_point = stringToFloat(clamped.clone(), scale)
+            let floating_point = feltToFloat(clamped.clone(), scale)
                 .map_err(|_| "failed")
                 .unwrap();
             assert_eq!(floating_point, (i as f64) / 4.0);
 
-            let integer: i128 = serde_json::from_slice(
-                &stringToInt(clamped.clone()).map_err(|_| "failed").unwrap(),
-            )
-            .unwrap();
+            let integer: i128 =
+                serde_json::from_slice(&feltToInt(clamped.clone()).map_err(|_| "failed").unwrap())
+                    .unwrap();
             assert_eq!(integer, i as i128);
 
             let hex_string = format!("{:?}", field_element);
-            let returned_string = stringToFelt(clamped).map_err(|_| "failed").unwrap();
+            let returned_string: String = feltToBigEndian(clamped).map_err(|_| "failed").unwrap();
             assert_eq!(hex_string, returned_string);
         }
     }
@@ -101,7 +101,7 @@ mod wasm32 {
         let mut buffer = string_high.clone().into_bytes();
         let clamped = wasm_bindgen::Clamped(buffer.clone());
 
-        let field_elements_ser = bufferToVecOfstring(clamped).map_err(|_| "failed").unwrap();
+        let field_elements_ser = bufferToVecOfFelt(clamped).map_err(|_| "failed").unwrap();
 
         let field_elements: Vec<Fr> = serde_json::from_slice(&field_elements_ser[..]).unwrap();
 
@@ -118,7 +118,7 @@ mod wasm32 {
         let buffer = string_sample.clone().into_bytes();
         let clamped = wasm_bindgen::Clamped(buffer.clone());
 
-        let field_elements_ser = bufferToVecOfstring(clamped).map_err(|_| "failed").unwrap();
+        let field_elements_ser = bufferToVecOfFelt(clamped).map_err(|_| "failed").unwrap();
 
         let field_elements: Vec<Fr> = serde_json::from_slice(&field_elements_ser[..]).unwrap();
 
@@ -133,7 +133,7 @@ mod wasm32 {
         let buffer = string_concat.into_bytes();
         let clamped = wasm_bindgen::Clamped(buffer.clone());
 
-        let field_elements_ser = bufferToVecOfstring(clamped).map_err(|_| "failed").unwrap();
+        let field_elements_ser = bufferToVecOfFelt(clamped).map_err(|_| "failed").unwrap();
 
         let field_elements: Vec<Fr> = serde_json::from_slice(&field_elements_ser[..]).unwrap();
 

tests/wasm/settings.json

@@ -27,6 +27,8 @@
         "check_mode": "UNSAFE"
     },
     "num_rows": 16,
+    "total_dynamic_col_size": 0,
+    "num_dynamic_lookups": 0,
     "total_assignments": 32,
     "total_const_size": 8,
     "model_instance_shapes": [

tests/wasm/witness.json

@@ -1 +1 @@
-{"inputs":[["0200000000000000000000000000000000000000000000000000000000000000","0100000000000000000000000000000000000000000000000000000000000000","0100000000000000000000000000000000000000000000000000000000000000"]],"pretty_elements":{"rescaled_inputs":[["2","1","1"]],"inputs":[["0x0000000000000000000000000000000000000000000000000000000000000002","0x0000000000000000000000000000000000000000000000000000000000000001","0x0000000000000000000000000000000000000000000000000000000000000001"]],"processed_inputs":[],"processed_params":[],"processed_outputs":[],"rescaled_outputs":[["0","0","0","0"]],"outputs":[["0x0000000000000000000000000000000000000000000000000000000000000000","0x0000000000000000000000000000000000000000000000000000000000000000","0x0000000000000000000000000000000000000000000000000000000000000000","0x0000000000000000000000000000000000000000000000000000000000000000"]]},"outputs":[["0000000000000000000000000000000000000000000000000000000000000000","0000000000000000000000000000000000000000000000000000000000000000","0000000000000000000000000000000000000000000000000000000000000000","0000000000000000000000000000000000000000000000000000000000000000"]],"processed_inputs":null,"processed_params":null,"processed_outputs":null,"max_lookup_inputs":0,"min_lookup_inputs":-1}
+{"inputs":[["0200000000000000000000000000000000000000000000000000000000000000","0100000000000000000000000000000000000000000000000000000000000000","0100000000000000000000000000000000000000000000000000000000000000"]],"pretty_elements":{"rescaled_inputs":[["2","1","1"]],"inputs":[["0x0000000000000000000000000000000000000000000000000000000000000002","0x0000000000000000000000000000000000000000000000000000000000000001","0x0000000000000000000000000000000000000000000000000000000000000001"]],"processed_inputs":[],"processed_params":[],"processed_outputs":[],"rescaled_outputs":[["0","0","0","0"]],"outputs":[["0x0000000000000000000000000000000000000000000000000000000000000000","0x0000000000000000000000000000000000000000000000000000000000000000","0x0000000000000000000000000000000000000000000000000000000000000000","0x0000000000000000000000000000000000000000000000000000000000000000"]]},"outputs":[["0000000000000000000000000000000000000000000000000000000000000000","0000000000000000000000000000000000000000000000000000000000000000","0000000000000000000000000000000000000000000000000000000000000000","0000000000000000000000000000000000000000000000000000000000000000"]],"processed_inputs":null,"processed_params":null,"processed_outputs":null,"max_lookup_inputs":0,"min_lookup_inputs":-1,"max_range_size":0}