fix!: cleanup felt serialization language in python and wasm (#724)

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

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/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,
     },
@@ -540,7 +540,9 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
         &mut self,
         cs: &mut ConstraintSystem<F>,
         input: &VarTensor,
+        index: &VarTensor,
         range: Range,
+        logrows: usize,
     ) -> Result<(), Box<dyn Error>>
     where
         F: Field,
@@ -556,7 +558,7 @@ 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 {
@@ -565,32 +567,60 @@ 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();
+
+                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 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 input_query = match &input {
+                            VarTensor::Advice { inner: advices, .. } => {
+                                cs.query_advice(advices[x][y], Rotation(0))
+                            }
+                            _ => unreachable!(),
+                        };
 
-                cs.lookup("", |cs| {
-                    let mut res = vec![];
-                    let sel = cs.query_selector(single_col_sel);
+                        let default_x = range_check.get_first_element(col_idx);
 
-                    let input_query = match &input {
-                        VarTensor::Advice { inner: advices, .. } => {
-                            cs.query_advice(advices[x][y], Rotation(0))
-                        }
-                        _ => unreachable!(),
-                    };
+                        let col_expr = sel.clone()
+                            * range_check
+                                .selector_constructor
+                                .get_expr_at_idx(col_idx, synthetic_sel);
 
-                    let default_x = range_check.get_first_element();
+                        let multiplier = range_check
+                            .selector_constructor
+                            .get_selector_val_at_idx(col_idx);
 
-                    let not_sel = Expression::Constant(F::ONE) - sel.clone();
+                        let not_expr = Expression::Constant(multiplier) - col_expr.clone();
 
-                    res.extend([(
-                        sel.clone() * input_query.clone()
-                            + not_sel.clone() * Expression::Constant(default_x),
-                        range_check.input,
-                    )]);
+                        res.extend([(
+                            col_expr.clone() * input_query.clone()
+                                + not_expr.clone() * Expression::Constant(default_x),
+                            *input_col,
+                        )]);
 
-                    res
-                });
-                selectors.insert((range, x, y), single_col_sel);
+                        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
+                    });
+                }
+                selectors.insert((range, x, y), multi_col_selector);
             }
         }
         self.range_check_selectors.extend(selectors);
@@ -600,6 +630,11 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
             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/layouts.rs

@@ -20,7 +20,7 @@ use super::{
 use crate::{
     circuit::{
         ops::base::BaseOp,
-        utils::{self},
+        utils::{self, F32},
     },
     fieldutils::{felt_to_i128, i128_to_felt},
     tensor::{
@@ -105,6 +105,8 @@ pub fn div<F: PrimeField + TensorType + PartialOrd>(
         BaseOp::Sub,
     )?;
 
+    log::debug!("diff_with_input: {:?}", diff_with_input.get_int_evals()?);
+
     range_check(
         config,
         region,
@@ -2482,6 +2484,28 @@ 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| {
@@ -2972,44 +2996,22 @@ pub fn range_check_percent<F: PrimeField + TensorType + PartialOrd>(
         &[values[0].clone()],
         &LookupOp::Recip {
             input_scale: scale,
-            output_scale: scale,
+            // multiply by 100 to get the percent error
+            output_scale: F32(scale.0 * 100.0),
         },
     )?;
 
     // Multiply the difference by the recip
     let product = pairwise(config, region, &[diff, recip], BaseOp::Mult)?;
+    let rebased_product = div(config, region, &[product], F::from(scale.0 as u64))?;
 
-    let scale_squared = scale.0 * scale.0;
-
-    // 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(
-        config,
-        region,
-        &[product.clone()],
-        &LookupOp::GreaterThan {
-            a: utils::F32(tol * scale_squared),
-        },
-    )?;
-
-    // Negate the product
-    let neg_product = neg(config, region, &[product])?;
+    let scaled_tol = (tol * scale.0) as i128;
 
-    // Use the greater than look up table to check if the percent error is within the tolerance for lower bound
-    let lower_bound = nonlinearity(
+    // check that it is within the tolerance range
+    range_check(
         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],
+        &(-scaled_tol, scaled_tol),
+    )
 }