ci: update version string in docs

This reverts commit d9f2adad99.

.github/workflows/engine.yml

@@ -22,15 +22,18 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
+        with:
+          # Pin to version 0.12.1
+          version: 'v0.12.1'
       - name: Add wasm32-unknown-unknown target
         run: rustup target add wasm32-unknown-unknown
 
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
       - name: Install binaryen
         run: |
           set -e
@@ -178,3 +181,58 @@ jobs:
           npm publish
         env:
           NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
+
+
+  in-browser-evm-ver-publish:
+    name: publish-in-browser-evm-verifier-package
+    needs: [publish-wasm-bindings]
+    runs-on: ubuntu-latest
+    if: startsWith(github.ref, 'refs/tags/')
+    steps:
+      - uses: actions/checkout@v4
+      - name: Update version in package.json
+        shell: bash
+        env:
+          RELEASE_TAG: ${{ github.ref_name }}
+        run: |
+          sed -i "s|\"version\": \".*\"|\"version\": \"${{ github.ref_name }}\"|" in-browser-evm-verifier/package.json
+      - name: Prepare tag and fetch package integrity
+        run: |
+          CLEANED_TAG=${{ github.ref_name }} # Get the tag from ref_name
+          CLEANED_TAG="${CLEANED_TAG#v}" # Remove leading 'v'
+          echo "CLEANED_TAG=${CLEANED_TAG}" >> $GITHUB_ENV # Set it as an environment variable for later steps
+          ENGINE_INTEGRITY=$(npm view @ezkljs/engine@$CLEANED_TAG dist.integrity)
+          echo "ENGINE_INTEGRITY=$ENGINE_INTEGRITY" >> $GITHUB_ENV
+      - name: Update @ezkljs/engine version in package.json
+        shell: bash
+        env:
+          RELEASE_TAG: ${{ github.ref_name }}
+        run: |
+          sed -i "s|\"@ezkljs/engine\": \".*\"|\"@ezkljs/engine\": \"$CLEANED_TAG\"|" in-browser-evm-verifier/package.json
+      - name: Update the engine import in in-browser-evm-verifier to use @ezkljs/engine package instead of the local one;
+        run: |
+          sed -i "s|import { encodeVerifierCalldata } from '../nodejs/ezkl';|import { encodeVerifierCalldata } from '@ezkljs/engine';|" in-browser-evm-verifier/src/index.ts
+      - name: Update pnpm-lock.yaml versions and integrity
+        run: |
+          awk -v integrity="$ENGINE_INTEGRITY" -v tag="$CLEANED_TAG" '
+          NR==30{$0="    specifier: \"" tag "\""}
+          NR==31{$0="    version: \"" tag "\""}
+          NR==400{$0="  /@ezkljs/engine@" tag ":"}
+          NR==401{$0="    resolution: {integrity: \"" integrity "\"}"} 1' in-browser-evm-verifier/pnpm-lock.yaml > temp.yaml && mv temp.yaml in-browser-evm-verifier/pnpm-lock.yaml  
+      - name: Use pnpm 8
+        uses: pnpm/action-setup@v2
+        with:
+          version: 8
+      - name: Set up Node.js
+        uses: actions/setup-node@v3
+        with:
+          node-version: "18.12.1"
+          registry-url: "https://registry.npmjs.org"
+      - name: Publish to npm
+        run: |
+          cd in-browser-evm-verifier
+          pnpm install --frozen-lockfile
+          pnpm run build
+          pnpm publish --no-git-checks
+        env:
+          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}  

.github/workflows/large-tests.yml

@@ -11,7 +11,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - name: nanoGPT Mock

.github/workflows/pypi.yml

@@ -40,7 +40,7 @@ jobs:
 
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2023-06-27
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
 
@@ -50,6 +50,7 @@ jobs:
           target: ${{ matrix.target }}
           args: --release --out dist --features python-bindings
       - name: Install built wheel
+        if: matrix.target == 'universal2-apple-darwin'
         run: |
           pip install ezkl --no-index --find-links dist --force-reinstall
           python -c "import ezkl"
@@ -85,7 +86,7 @@ jobs:
 
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2023-06-27
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
 
@@ -110,7 +111,7 @@ jobs:
     if: startsWith(github.ref, 'refs/tags/')
     strategy:
       matrix:
-        target: [x86_64, i686]
+        target: [x86_64]
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4

.github/workflows/release.yml

@@ -45,7 +45,7 @@ jobs:
     steps:
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - name: Checkout repo
@@ -102,28 +102,32 @@ jobs:
       PCRE2_SYS_STATIC: 1
     strategy:
       matrix:
-        build: [windows-msvc, macos, macos-aarch64, linux-musl, linux-gnu]
+        build: [windows-msvc, macos, macos-aarch64, linux-musl, linux-gnu, linux-aarch64]
         include:
           - build: windows-msvc
             os: windows-latest
-            rust: nightly-2023-06-27
+            rust: nightly-2024-07-18
             target: x86_64-pc-windows-msvc
           - build: macos
             os: macos-13
-            rust: nightly-2023-06-27
+            rust: nightly-2024-07-18
             target: x86_64-apple-darwin
           - build: macos-aarch64
             os: macos-13
-            rust: nightly-2023-06-27
+            rust: nightly-2024-07-18
             target: aarch64-apple-darwin
           - build: linux-musl
             os: ubuntu-22.04
-            rust: nightly-2023-06-27
+            rust: nightly-2024-07-18
             target: x86_64-unknown-linux-musl
           - build: linux-gnu
             os: ubuntu-22.04
-            rust: nightly-2023-06-27
+            rust: nightly-2024-07-18
             target: x86_64-unknown-linux-gnu
+          - build: linux-aarch64
+            os: ubuntu-22.04
+            rust: nightly-2024-07-18
+            target: aarch64-unknown-linux-gnu
 
     steps:
       - name: Checkout repo
@@ -177,11 +181,16 @@ jobs:
           echo "target flag is: ${{ env.TARGET_FLAGS }}"
           echo "target dir is: ${{ env.TARGET_DIR }}"
 
-      - name: Build release binary
+      - name: Build release binary (no asm)
+        if: matrix.build != 'linux-gnu'
         run: ${{ env.CARGO }} build --release ${{ env.TARGET_FLAGS }} -Z sparse-registry
 
+      - name: Build release binary (asm)
+        if: matrix.build == 'linux-gnu'
+        run: ${{ env.CARGO }} build --release ${{ env.TARGET_FLAGS }} -Z sparse-registry --features asm
+
       - name: Strip release binary
-        if: matrix.build != 'windows-msvc'
+        if: matrix.build != 'windows-msvc' && matrix.build != 'linux-aarch64'
         run: strip "target/${{ matrix.target }}/release/ezkl"
 
       - name: Strip release binary (Windows)

.github/workflows/rust.yml

@@ -26,7 +26,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - name: Build
@@ -38,7 +38,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - name: Docs
@@ -50,7 +50,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -65,40 +65,40 @@ jobs:
       - name: Library tests (original lookup)
         run: cargo nextest run --lib --verbose --no-default-features --features ezkl
 
-  ultra-overflow-tests-gpu:
-    runs-on: GPU
-    env:
-      ENABLE_ICICLE_GPU: true
-    steps:
-      - uses: actions/checkout@v4
-      - uses: actions-rs/toolchain@v1
-        with:
-          toolchain: nightly-2024-02-06
-          override: true
-          components: rustfmt, clippy
-      - uses: baptiste0928/cargo-install@v1
-        with:
-          crate: cargo-nextest
-          locked: true
-      - uses: mwilliamson/setup-wasmtime-action@v2
-        with:
-          wasmtime-version: "3.0.1"
-      - name: Install wasm32-wasi
-        run: rustup target add wasm32-wasi
-      - name: Install cargo-wasi
-        run: cargo install cargo-wasi
-      # - name: Matmul overflow (wasi)
-      #   run: cargo wasi test matmul_col_ultra_overflow -- --include-ignored --nocapture
-      # - name: Conv overflow (wasi)
-      #   run: cargo wasi test conv_col_ultra_overflow -- --include-ignored --nocapture
-      - name: lookup overflow
-        run: cargo nextest run  --release lookup_ultra_overflow --no-capture --features icicle -- --include-ignored
-      - name: Matmul overflow
-        run: RUST_LOG=debug cargo nextest run matmul_col_ultra_overflow --no-capture --features icicle -- --include-ignored
-      - name: Conv overflow
-        run: RUST_LOG=debug cargo nextest run conv_col_ultra_overflow --no-capture --features icicle -- --include-ignored
-      - name: Conv + relu overflow
-        run: cargo nextest run  --release conv_relu_col_ultra_overflow --no-capture --features icicle -- --include-ignored
+  # ultra-overflow-tests-gpu:
+  #   runs-on: GPU
+  #   env:
+  #     ENABLE_ICICLE_GPU: true
+  #   steps:
+  #     - uses: actions/checkout@v4
+  #     - uses: actions-rs/toolchain@v1
+  #       with:
+  #         toolchain: nightly-2024-07-18
+  #         override: true
+  #         components: rustfmt, clippy
+  #     - uses: baptiste0928/cargo-install@v1
+  #       with:
+  #         crate: cargo-nextest
+  #         locked: true
+  #     - uses: mwilliamson/setup-wasmtime-action@v2
+  #       with:
+  #         wasmtime-version: "3.0.1"
+  #     - name: Install wasm32-wasi
+  #       run: rustup target add wasm32-wasi
+  #     - name: Install cargo-wasi
+  #       run: cargo install cargo-wasi
+  #     # - name: Matmul overflow (wasi)
+  #     #   run: cargo wasi test matmul_col_ultra_overflow -- --include-ignored --nocapture
+  #     # - name: Conv overflow (wasi)
+  #     #   run: cargo wasi test conv_col_ultra_overflow -- --include-ignored --nocapture
+  #     - name: lookup overflow
+  #       run: cargo nextest run lookup_ultra_overflow --no-capture --features icicle -- --include-ignored
+  #     - name: Matmul overflow
+  #       run: RUST_LOG=debug cargo nextest run matmul_col_ultra_overflow --no-capture --features icicle -- --include-ignored
+  #     - name: Conv overflow
+  #       run: RUST_LOG=debug cargo nextest run conv_col_ultra_overflow --no-capture --features icicle -- --include-ignored
+  #     - name: Conv + relu overflow
+  #       run: cargo nextest run conv_relu_col_ultra_overflow --no-capture --features icicle -- --include-ignored
 
   ultra-overflow-tests_og-lookup:
     runs-on: non-gpu
@@ -106,7 +106,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -139,7 +139,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -172,7 +172,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -184,22 +184,24 @@ jobs:
 
   wasm32-tests:
     runs-on: ubuntu-latest
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
+        with:
+          # Pin to version 0.12.1
+          version: 'v0.12.1'
       - uses: nanasess/setup-chromedriver@v2
         # with:
         #   chromedriver-version: "115.0.5790.102"
       - name: Install wasm32-unknown-unknown
         run: rustup target add wasm32-unknown-unknown
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
       - name: Run wasm verifier tests
         # on mac:
         #   AR=/opt/homebrew/opt/llvm/bin/llvm-ar CC=/opt/homebrew/opt/llvm/bin/clang wasm-pack test --firefox --headless -- -Z build-std="panic_abort,std" --features web
@@ -212,7 +214,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -229,17 +231,19 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
         with:
           crate: cargo-nextest
           locked: true
+      # - name: The Worm Mock
+      #   run: cargo nextest run --release --verbose tests::large_mock_::large_tests_5_expects -- --include-ignored
       - name: public outputs and tolerance > 0
         run: cargo nextest run --release --verbose tests::mock_tolerance_public_outputs_ --test-threads 32
       - name: public outputs + batch size == 10
-        run: cargo nextest run --release --verbose tests::mock_large_batch_public_outputs_ --test-threads 32
+        run: cargo nextest run --release --verbose tests::mock_large_batch_public_outputs_ --test-threads 16
       - name: kzg inputs
         run: cargo nextest run --release --verbose tests::mock_kzg_input_::t  --test-threads 32
       - name: kzg params
@@ -258,6 +262,8 @@ jobs:
         run: cargo nextest run --release --verbose tests::mock_hashed_input_::t  --test-threads 32
       - name: hashed params
         run: cargo nextest run --release --verbose tests::mock_hashed_params_::t  --test-threads 32
+      - name: hashed params public inputs
+        run: cargo nextest run --release --verbose tests::mock_hashed_params_public_inputs_::t  --test-threads 32
       - name: hashed outputs
         run: cargo nextest run --release --verbose tests::mock_hashed_output_::t  --test-threads 32
       - name: hashed inputs + params + outputs
@@ -286,7 +292,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -304,7 +310,7 @@ jobs:
           node-version: "18.12.1"
           cache: "pnpm"
       - name: "Add rust-src"
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
       - name: Install dependencies for js tests and in-browser-evm-verifier package
         run: |
           pnpm install --frozen-lockfile
@@ -323,10 +329,10 @@ jobs:
           cd in-browser-evm-verifier
           pnpm build:commonjs
           cd ..
-      - name: Install solc
-        run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
+      # - name: Install solc
+      #   run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
       - name: Install Anvil
-        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev 62cdea8ff9e6efef011f77e295823b5f2dbeb3a1 --locked anvil --force
       - name: KZG prove and verify tests (EVM + VK rendered seperately)
         run: cargo nextest run --release --verbose tests_evm::kzg_evm_prove_and_verify_render_seperately_ --test-threads 1
       - name: KZG prove and verify tests (EVM + kzg all)
@@ -341,6 +347,12 @@ jobs:
         run: cargo nextest run --release --verbose tests_evm::kzg_evm_on_chain_output_prove_and_verify --test-threads 1
       - name: KZG prove and verify tests (EVM + on chain inputs & outputs)
         run: cargo nextest run --release --verbose tests_evm::kzg_evm_on_chain_input_output_prove_and_verify --test-threads 1
+      - name: KZG prove and verify tests (EVM + on chain inputs & kzg outputs + params)
+        run: cargo nextest run --release --verbose tests_evm::kzg_evm_on_chain_input_kzg_output_kzg_params_prove_and_verify --test-threads 1
+      - name: KZG prove and verify tests (EVM + on chain outputs & kzg inputs + params)
+        run: cargo nextest run --release --verbose tests_evm::kzg_evm_on_chain_output_kzg_input_kzg_params_prove_and_verify --test-threads 1
+      - name: KZG prove and verify tests (EVM + on chain all kzg)
+        run: cargo nextest run --release --verbose tests_evm::kzg_evm_on_chain_all_kzg_params_prove_and_verify --test-threads 1
       - name: KZG prove and verify tests (EVM + on chain inputs & outputs hashes)
         run: cargo nextest run --release --verbose tests_evm::kzg_evm_on_chain_input_output_hashed_prove_and_verify --test-threads 1
       - name: KZG prove and verify tests (EVM)
@@ -359,15 +371,18 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
+        with:
+          # Pin to version 0.12.1
+          version: 'v0.12.1'
       - name: Add wasm32-unknown-unknown target
         run: rustup target add wasm32-unknown-unknown
 
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
       - uses: actions/checkout@v3
       - name: Use pnpm 8
         uses: pnpm/action-setup@v2
@@ -425,40 +440,40 @@ jobs:
       - name: KZG prove and verify tests (hashed outputs)
         run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_hashed
 
-  prove-and-verify-tests-gpu:
-    runs-on: GPU
-    env:
-      ENABLE_ICICLE_GPU: true
-    steps:
-      - uses: actions/checkout@v4
-      - uses: actions-rs/toolchain@v1
-        with:
-          toolchain: nightly-2024-02-06
-          override: true
-          components: rustfmt, clippy
-      - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
-      - uses: actions/checkout@v3
-      - uses: baptiste0928/cargo-install@v1
-        with:
-          crate: cargo-nextest
-          locked: true
-      - name: KZG prove and verify tests (kzg outputs)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_kzg_output --features icicle --test-threads 1
-      - name: KZG prove and verify tests (public outputs + column overflow)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_with_overflow_::w --features icicle  --test-threads 1
-      - name: KZG prove and verify tests (public outputs + fixed params + column overflow)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_with_overflow_fixed_params_ --features icicle  --test-threads 1
-      - name: KZG prove and verify tests (public outputs)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_::t --features icicle  --test-threads 1
-      - name: KZG prove and verify tests (public outputs + column overflow)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_::t --features icicle  --test-threads 1
-      - name: KZG prove and verify tests (public inputs)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_public_input --features icicle  --test-threads 1
-      - name: KZG prove and verify tests (fixed params)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_fixed_params --features icicle  --test-threads 1
-      - name: KZG prove and verify tests (hashed outputs)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_hashed --features icicle  --test-threads 1
+  # prove-and-verify-tests-gpu:
+  #   runs-on: GPU
+  #   env:
+  #     ENABLE_ICICLE_GPU: true
+  #   steps:
+  #     - uses: actions/checkout@v4
+  #     - uses: actions-rs/toolchain@v1
+  #       with:
+  #         toolchain: nightly-2024-07-18
+  #         override: true
+  #         components: rustfmt, clippy
+  #     - name: Add rust-src
+  #       run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
+  #     - uses: actions/checkout@v3
+  #     - uses: baptiste0928/cargo-install@v1
+  #       with:
+  #         crate: cargo-nextest
+  #         locked: true
+  #     - name: KZG prove and verify tests (kzg outputs)
+  #       run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_kzg_output --features icicle --test-threads 1
+  #     - name: KZG prove and verify tests (public outputs + column overflow)
+  #       run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_with_overflow_::w --features icicle  --test-threads 1
+  #     - name: KZG prove and verify tests (public outputs + fixed params + column overflow)
+  #       run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_with_overflow_fixed_params_ --features icicle  --test-threads 1
+  #     - name: KZG prove and verify tests (public outputs)
+  #       run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_::t --features icicle  --test-threads 1
+  #     - name: KZG prove and verify tests (public outputs + column overflow)
+  #       run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_::t --features icicle  --test-threads 1
+  #     - name: KZG prove and verify tests (public inputs)
+  #       run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_public_input --features icicle  --test-threads 1
+  #     - name: KZG prove and verify tests (fixed params)
+  #       run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_fixed_params --features icicle  --test-threads 1
+  #     - name: KZG prove and verify tests (hashed outputs)
+  #       run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_hashed --features icicle  --test-threads 1
 
   prove-and-verify-mock-aggr-tests:
     runs-on: self-hosted
@@ -467,7 +482,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -485,7 +500,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -493,7 +508,7 @@ jobs:
           crate: cargo-nextest
           locked: true
       - name: KZG )tests
-        run: cargo nextest run --release --verbose tests_aggr::kzg_aggr_prove_and_verify_  --features icicle --test-threads 1 -- --include-ignored
+        run: cargo nextest run --verbose tests_aggr::kzg_aggr_prove_and_verify_  --features icicle --test-threads 1 -- --include-ignored
 
   prove-and-verify-aggr-tests:
     runs-on: large-self-hosted
@@ -502,7 +517,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -519,17 +534,17 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
         with:
           crate: cargo-nextest
           locked: true
-      - name: Install solc
-        run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
+      # - name: Install solc
+      #   run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
       - name: Install Anvil
-        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev 62cdea8ff9e6efef011f77e295823b5f2dbeb3a1 --locked anvil --force
       - name: KZG prove and verify aggr tests
         run: cargo nextest run  --release --verbose tests_evm::kzg_evm_aggr_prove_and_verify_::t --test-threads 4 -- --include-ignored
 
@@ -540,7 +555,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -560,21 +575,21 @@ jobs:
           python-version: "3.12"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - name: Install cmake
         run: sudo apt-get install -y cmake
-      - name: Install solc
-        run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
+      # - name: Install solc
+      #   run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
       - name: Setup Virtual Env and Install python dependencies
         run: python -m venv .env --clear; source .env/bin/activate; pip install -r requirements.txt;
       - name: Install Anvil
-        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev 62cdea8ff9e6efef011f77e295823b5f2dbeb3a1 --locked anvil --force
       - name: Build python ezkl
         run: source .env/bin/activate; unset CONDA_PREFIX; maturin develop --features python-bindings --release
       - name: Run pytest
-        run: source .env/bin/activate; pytest -vv
+        run: source .env/bin/activate; pip install pytest-asyncio; pytest -vv
 
   accuracy-measurement-tests:
     runs-on: ubuntu-latest-32-cores
@@ -586,7 +601,7 @@ jobs:
           python-version: "3.12"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -635,17 +650,17 @@ jobs:
           python-version: "3.11"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2024-07-18
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
         with:
           crate: cargo-nextest
           locked: true
-      - name: Install solc
-        run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
+      # - name: Install solc
+      #   run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
       - name: Install Anvil
-        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev 62cdea8ff9e6efef011f77e295823b5f2dbeb3a1 --locked anvil --force
       - name: Install pip
         run: python -m ensurepip --upgrade
       - name: Setup Virtual Env and Install python dependencies

.github/workflows/verify.yml

@@ -1,65 +0,0 @@
-name: Build and Publish EZKL npm packages (wasm bindings and in-browser evm verifier)
-
-on:
-  workflow_dispatch:
-    inputs:
-      tag:
-        description: "The tag to release"
-        required: true
-  push:
-    tags:
-      - "*"
-
-defaults:
-  run:
-    working-directory: .
-jobs:
-  in-browser-evm-ver-publish:
-    name: publish-in-browser-evm-verifier-package
-    runs-on: ubuntu-latest
-    if: startsWith(github.ref, 'refs/tags/')
-    steps:
-      - uses: actions/checkout@v4
-      - name: Update version in package.json
-        shell: bash
-        env:
-          RELEASE_TAG: ${{ github.ref_name }}
-        run: |
-          sed -i "s|\"version\": \".*\"|\"version\": \"${{ github.ref_name }}\"|" in-browser-evm-verifier/package.json
-      - name: Update @ezkljs/engine version in package.json
-        shell: bash
-        env:
-          RELEASE_TAG: ${{ github.ref_name }}
-        run: |
-          sed -i "s|\"@ezkljs/engine\": \".*\"|\"@ezkljs/engine\": \"${{ github.ref_name#v }}\"|" in-browser-evm-verifier/package.json
-      - name: Update the engine import in in-browser-evm-verifier to use @ezkljs/engine package instead of the local one;
-        run: |
-          sed -i "s|import { encodeVerifierCalldata } from '../nodejs/ezkl';|import { encodeVerifierCalldata } from '@ezkljs/engine';|" in-browser-evm-verifier/src/index.ts
-      - name: Fetch integrity
-        run: |
-          ENGINE_INTEGRITY=$(npm view @ezkljs/engine@${{ github.ref_name#v }} dist.integrity)
-          echo "ENGINE_INTEGRITY=$ENGINE_INTEGRITY" >> $GITHUB_ENV
-      - name: Update pnpm-lock.yaml versions and integrity
-        run: |
-          awk -v integrity="$ENGINE_INTEGRITY" -v tag="${{ github.ref_name#v }}" '
-          NR==30{$0="    specifier: \"" tag "\""}
-          NR==31{$0="    version: \"" tag "\""}
-          NR==400{$0="  /@ezkljs/engine@" tag ":"}
-          NR==401{$0="    resolution: {integrity: \"" integrity "\"}"} 1' in-browser-evm-verifier/pnpm-lock.yaml > temp.yaml && mv temp.yaml in-browser-evm-verifier/pnpm-lock.yaml  
-      - name: Use pnpm 8
-        uses: pnpm/action-setup@v2
-        with:
-          version: 8
-      - name: Set up Node.js
-        uses: actions/setup-node@v3
-        with:
-          node-version: "18.12.1"
-          registry-url: "https://registry.npmjs.org"
-      - name: Publish to npm
-        run: |
-          cd in-browser-evm-verifier
-          pnpm install --frozen-lockfile
-          pnpm run build
-          pnpm publish
-        env:
-          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}

Cargo.toml

@@ -16,10 +16,10 @@ crate-type = ["cdylib", "rlib"]
 
 [dependencies]
 halo2_gadgets = { git = "https://github.com/zkonduit/halo2", branch = "ac/optional-selector-poly" }
-halo2_proofs = { git = "https://github.com/zkonduit/halo2", branch = "ac/optional-selector-poly" }
-halo2curves = { git = "https://github.com/privacy-scaling-explorations/halo2curves", rev = "9fff22c", features = [
-    "derive_serde",
+halo2curves = { git = "https://github.com/privacy-scaling-explorations/halo2curves", rev = "b753a832e92d5c86c5c997327a9cf9de86a18851", features = [
+    "derive_serde"
 ] }
+halo2_proofs = { git = "https://github.com/zkonduit/halo2?branch=ac/cache-lookup-commitments#8b13a0d2a7a34d8daab010dadb2c47dfa47d37d0", package = "halo2_proofs", branch = "ac/cache-lookup-commitments" }
 rand = { version = "0.8", default_features = false }
 itertools = { version = "0.10.3", default_features = false }
 clap = { version = "4.5.3", features = ["derive"] }
@@ -28,64 +28,62 @@ serde_json = { version = "1.0.97", default_features = false, features = [
     "float_roundtrip",
     "raw_value",
 ], optional = true }
+clap_complete = "4.5.2"
 log = { version = "0.4.17", default_features = false, optional = true }
 thiserror = { version = "1.0.38", default_features = false }
 hex = { version = "0.4.3", default_features = false }
 halo2_wrong_ecc = { git = "https://github.com/zkonduit/halo2wrong", branch = "ac/chunked-mv-lookup", package = "ecc" }
-snark-verifier = { git = "https://github.com/zkonduit/snark-verifier", branch = "ac/chunked-mv-lookup", features = [
+snark-verifier = { git = "https://github.com/zkonduit/snark-verifier", branch = "ac/chunked-mv-lookup",  features = [
     "derive_serde",
 ] }
-halo2_solidity_verifier = { git = "https://github.com/alexander-camuto/halo2-solidity-verifier", branch = "main" }
+halo2_solidity_verifier = { git = "https://github.com/alexander-camuto/halo2-solidity-verifier", branch = "ac/update-h2-curves" }
 maybe-rayon = { version = "0.1.1", default_features = false }
 bincode = { version = "1.3.3", default_features = false }
-ark-std = { version = "^0.3.0", default-features = false }
 unzip-n = "0.1.2"
 num = "0.4.1"
 portable-atomic = "1.6.0"
 tosubcommand = { git = "https://github.com/zkonduit/enum_to_subcommand", package = "tosubcommand" }
-metal = { git = "https://github.com/gfx-rs/metal-rs", optional = true }
-
+semver = "1.0.22"
 
 # evm related deps
 [target.'cfg(not(target_arch = "wasm32"))'.dependencies]
-ethers = { version = "2.0.11", default_features = false, features = [
-    "ethers-solc",
-] }
+alloy = { git = "https://github.com/alloy-rs/alloy", version = "0.1.0", rev="5fbf57bac99edef9d8475190109a7ea9fb7e5e83", features = ["provider-http", "signers", "contract", "rpc-types-eth", "signer-wallet", "node-bindings"] }
+foundry-compilers = {version = "0.4.1", features = ["svm-solc"]}
+ethabi = "18"
 indicatif = { version = "0.17.5", features = ["rayon"] }
 gag = { version = "1.0.0", default_features = false }
 instant = { version = "0.1" }
-reqwest = { version = "0.11.14", default-features = false, features = [
+reqwest = { version = "0.12.4", default-features = false, features = [
     "default-tls",
     "multipart",
     "stream",
 ] }
 openssl = { version = "0.10.55", features = ["vendored"] }
-postgres = "0.19.5"
+tokio-postgres = "0.7.10"
 pg_bigdecimal = "0.1.5"
 lazy_static = "1.4.0"
 colored_json = { version = "3.0.1", default_features = false, optional = true }
-plotters = { version = "0.3.0", default_features = false, optional = true }
 regex = { version = "1", default_features = false }
-tokio = { version = "1.26.0", default_features = false, features = [
+tokio = { version = "1.35.0", default_features = false, features = [
     "macros",
-    "rt",
+    "rt-multi-thread",
 ] }
-tokio-util = { version = "0.7.9", features = ["codec"] }
-pyo3 = { version = "0.20.2", features = [
+pyo3 = { version = "0.21.2", features = [
     "extension-module",
     "abi3-py37",
     "macros",
 ], default_features = false, optional = true }
-pyo3-asyncio = { version = "0.20.0", features = [
-    "attributes",
+pyo3-asyncio = { git = "https://github.com/jopemachine/pyo3-asyncio/", branch="migration-pyo3-0.21", features = [
+  "attributes",
     "tokio-runtime",
 ], default_features = false, optional = true }
-pyo3-log = { version = "0.9.0", default_features = false, optional = true }
-tract-onnx = { git = "https://github.com/sonos/tract/", rev = "05ebf550aa9922b221af4635c21a67a8d2af12a9", default_features = false, optional = true }
+
+pyo3-log = { version = "0.10.0", default_features = false, optional = true }
+tract-onnx = { git = "https://github.com/sonos/tract/", rev = "40c64319291184814d9fea5fdf4fa16f5a4f7116", default_features = false, optional = true }
 tabled = { version = "0.12.0", optional = true }
-
+metal = { git = "https://github.com/gfx-rs/metal-rs", optional = true }
 objc = { version = "0.2.4", optional = true }
-
+mimalloc = "0.1"
 
 [target.'cfg(not(all(target_arch = "wasm32", target_os = "unknown")))'.dependencies]
 colored = { version = "2.0.0", default_features = false, optional = true }
@@ -93,6 +91,7 @@ env_logger = { version = "0.10.0", default_features = false, optional = true }
 chrono = "0.4.31"
 sha256 = "1.4.0"
 
+
 [target.'cfg(target_arch = "wasm32")'.dependencies]
 getrandom = { version = "0.2.8", features = ["js"] }
 instant = { version = "0.1", features = ["wasm-bindgen", "inaccurate"] }
@@ -106,8 +105,10 @@ console_error_panic_hook = "0.1.7"
 wasm-bindgen-console-logger = "0.1.1"
 
 
+[target.'cfg(not(all(target_arch = "wasm32", target_os = "unknown")))'.dev-dependencies]
+criterion = { version = "0.5.1", features = ["html_reports"] }
+
 [dev-dependencies]
-criterion = { version = "0.3", features = ["html_reports"] }
 tempfile = "3.3.0"
 lazy_static = "1.4.0"
 mnist = "0.5"
@@ -161,6 +162,10 @@ harness = false
 name = "relu"
 harness = false
 
+[[bench]]
+name = "relu_lookupless"
+harness = false
+
 [[bench]]
 name = "accum_matmul_relu"
 harness = false
@@ -178,7 +183,7 @@ required-features = ["ezkl"]
 
 [features]
 web = ["wasm-bindgen-rayon"]
-default = ["ezkl", "mv-lookup"]
+default = ["ezkl", "mv-lookup", "precompute-coset", "no-banner", "parallel-poly-read"]
 onnx = ["dep:tract-onnx"]
 python-bindings = ["pyo3", "pyo3-log", "pyo3-asyncio"]
 ezkl = [
@@ -192,24 +197,31 @@ ezkl = [
     "colored_json",
     "halo2_proofs/circuit-params",
 ]
+parallel-poly-read = ["halo2_proofs/parallel-poly-read"]
 mv-lookup = [
     "halo2_proofs/mv-lookup",
     "snark-verifier/mv-lookup",
     "halo2_solidity_verifier/mv-lookup",
 ]
+asm = ["halo2curves/asm", "halo2_proofs/asm"]
+precompute-coset = ["halo2_proofs/precompute-coset"]
 det-prove = []
 icicle = ["halo2_proofs/icicle_gpu"]
 empty-cmd = []
 no-banner = []
-metal = ["dep:metal", "dep:objc"]
+no-update = []
+
 
 # icicle patch to 0.1.0 if feature icicle is enabled
 [patch.'https://github.com/ingonyama-zk/icicle']
 icicle = { git = "https://github.com/ingonyama-zk/icicle?rev=45b00fb", package = "icicle", branch = "fix/vhnat/ezkl-build-fix" }
 
 [patch.'https://github.com/zkonduit/halo2']
-halo2_proofs = { git = "https://github.com/zkonduit/halo2?branch=ac/optional-selector-poly#54f54453cf186aa5d89579c4e7663f9a27cfb89a", package = "halo2_proofs", branch = "ac/optional-selector-poly" }
-
+halo2_proofs = { git = "https://github.com/zkonduit/halo2?branch=ac/cache-lookup-commitments#8b13a0d2a7a34d8daab010dadb2c47dfa47d37d0", package = "halo2_proofs", branch = "ac/cache-lookup-commitments" }
 
 [profile.release]
 rustflags = ["-C", "relocation-model=pic"]
+lto = "fat"
+codegen-units = 1
+# panic = "abort"
+

README.md

@@ -91,9 +91,9 @@ You can install the library from source
 cargo install --locked --path .
 ```
 
-You will need a functioning installation of `solc` in order to run `ezkl` properly.
-[solc-select](https://github.com/crytic/solc-select) is recommended.
-Follow the instructions on [solc-select](https://github.com/crytic/solc-select) to activate `solc` in your environment.
+`ezkl` now auto-manages solc installation for you.
+
+
 
 
 #### building python bindings

benches/accum_conv.rs

@@ -64,7 +64,7 @@ impl Circuit<Fr> for MyCircuit {
         layouter.assign_region(
             || "",
             |region| {
-                let mut region = region::RegionCtx::new(region, 0, 1);
+                let mut region = region::RegionCtx::new(region, 0, 1, 1024, 2);
                 config
                     .layout(
                         &mut region,
@@ -72,6 +72,7 @@ impl Circuit<Fr> for MyCircuit {
                         Box::new(PolyOp::Conv {
                             padding: vec![(0, 0)],
                             stride: vec![1; 2],
+                            group: 1,
                         }),
                     )
                     .unwrap();

benches/accum_dot.rs

@@ -55,7 +55,7 @@ impl Circuit<Fr> for MyCircuit {
         layouter.assign_region(
             || "",
             |region| {
-                let mut region = region::RegionCtx::new(region, 0, 1);
+                let mut region = region::RegionCtx::new(region, 0, 1, 1024, 2);
                 config
                     .layout(
                         &mut region,

benches/accum_einsum_matmul.rs

@@ -57,7 +57,7 @@ impl Circuit<Fr> for MyCircuit {
         layouter.assign_region(
             || "",
             |region| {
-                let mut region = region::RegionCtx::new(region, 0, 1);
+                let mut region = region::RegionCtx::new(region, 0, 1, 1024, 2);
                 config
                     .layout(
                         &mut region,

benches/accum_matmul_relu.rs

@@ -57,7 +57,15 @@ impl Circuit<Fr> for MyCircuit {
 
         // sets up a new relu table
         base_config
-            .configure_lookup(cs, &b, &output, &a, BITS, K, &LookupOp::ReLU)
+            .configure_lookup(
+                cs,
+                &b,
+                &output,
+                &a,
+                BITS,
+                K,
+                &LookupOp::LeakyReLU { slope: 0.0.into() },
+            )
             .unwrap();
 
         MyConfig { base_config }
@@ -75,14 +83,18 @@ impl Circuit<Fr> for MyCircuit {
                 let op = PolyOp::Einsum {
                     equation: "ij,jk->ik".to_string(),
                 };
-                let mut region = region::RegionCtx::new(region, 0, 1);
+                let mut region = region::RegionCtx::new(region, 0, 1, 1024, 2);
                 let output = config
                     .base_config
                     .layout(&mut region, &self.inputs, Box::new(op))
                     .unwrap();
                 let _output = config
                     .base_config
-                    .layout(&mut region, &[output.unwrap()], Box::new(LookupOp::ReLU))
+                    .layout(
+                        &mut region,
+                        &[output.unwrap()],
+                        Box::new(LookupOp::LeakyReLU { slope: 0.0.into() }),
+                    )
                     .unwrap();
                 Ok(())
             },

benches/accum_matmul_relu_overflow.rs

@@ -58,7 +58,15 @@ impl Circuit<Fr> for MyCircuit {
 
         // sets up a new relu table
         base_config
-            .configure_lookup(cs, &b, &output, &a, BITS, k, &LookupOp::ReLU)
+            .configure_lookup(
+                cs,
+                &b,
+                &output,
+                &a,
+                BITS,
+                k,
+                &LookupOp::LeakyReLU { slope: 0.0.into() },
+            )
             .unwrap();
 
         MyConfig { base_config }
@@ -76,14 +84,18 @@ impl Circuit<Fr> for MyCircuit {
                 let op = PolyOp::Einsum {
                     equation: "ij,jk->ik".to_string(),
                 };
-                let mut region = region::RegionCtx::new(region, 0, 1);
+                let mut region = region::RegionCtx::new(region, 0, 1, 1024, 2);
                 let output = config
                     .base_config
                     .layout(&mut region, &self.inputs, Box::new(op))
                     .unwrap();
                 let _output = config
                     .base_config
-                    .layout(&mut region, &[output.unwrap()], Box::new(LookupOp::ReLU))
+                    .layout(
+                        &mut region,
+                        &[output.unwrap()],
+                        Box::new(LookupOp::LeakyReLU { slope: 0.0.into() }),
+                    )
                     .unwrap();
                 Ok(())
             },

benches/accum_sum.rs

@@ -55,7 +55,7 @@ impl Circuit<Fr> for MyCircuit {
         layouter.assign_region(
             || "",
             |region| {
-                let mut region = region::RegionCtx::new(region, 0, 1);
+                let mut region = region::RegionCtx::new(region, 0, 1, 1024, 2);
                 config
                     .layout(
                         &mut region,

benches/accum_sumpool.rs

@@ -59,7 +59,7 @@ impl Circuit<Fr> for MyCircuit {
         layouter.assign_region(
             || "",
             |region| {
-                let mut region = region::RegionCtx::new(region, 0, 1);
+                let mut region = region::RegionCtx::new(region, 0, 1, 1024, 2);
                 config
                     .layout(
                         &mut region,

benches/pairwise_add.rs

@@ -55,7 +55,7 @@ impl Circuit<Fr> for MyCircuit {
         layouter.assign_region(
             || "",
             |region| {
-                let mut region = region::RegionCtx::new(region, 0, 1);
+                let mut region = region::RegionCtx::new(region, 0, 1, 1024, 2);
                 config
                     .layout(&mut region, &self.inputs, Box::new(PolyOp::Add))
                     .unwrap();

benches/pairwise_pow.rs

@@ -56,7 +56,7 @@ impl Circuit<Fr> for MyCircuit {
         layouter.assign_region(
             || "",
             |region| {
-                let mut region = RegionCtx::new(region, 0, 1);
+                let mut region = RegionCtx::new(region, 0, 1, 1024, 2);
                 config
                     .layout(&mut region, &self.inputs, Box::new(PolyOp::Pow(4)))
                     .unwrap();

benches/relu.rs

@@ -2,6 +2,7 @@ use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Through
 use ezkl::circuit::region::RegionCtx;
 use ezkl::circuit::table::Range;
 use ezkl::circuit::{ops::lookup::LookupOp, BaseConfig as Config, CheckMode};
+use ezkl::fieldutils::IntegerRep;
 use ezkl::pfsys::create_proof_circuit;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
@@ -41,7 +42,7 @@ impl Circuit<Fr> for NLCircuit {
                 .map(|_| VarTensor::new_advice(cs, K, 1, LEN))
                 .collect::<Vec<_>>();
 
-            let nl = LookupOp::ReLU;
+            let nl = LookupOp::LeakyReLU { slope: 0.0.into() };
 
             let mut config = Config::default();
 
@@ -62,9 +63,13 @@ impl Circuit<Fr> for NLCircuit {
         layouter.assign_region(
             || "",
             |region| {
-                let mut region = RegionCtx::new(region, 0, 1);
+                let mut region = RegionCtx::new(region, 0, 1, 1024, 2);
                 config
-                    .layout(&mut region, &[self.input.clone()], Box::new(LookupOp::ReLU))
+                    .layout(
+                        &mut region,
+                        &[self.input.clone()],
+                        Box::new(LookupOp::LeakyReLU { slope: 0.0.into() }),
+                    )
                     .unwrap();
                 Ok(())
             },
@@ -84,7 +89,7 @@ fn runrelu(c: &mut Criterion) {
         };
 
         let input: Tensor<Value<Fr>> =
-            Tensor::<i32>::from((0..len).map(|_| rng.gen_range(0..10))).into();
+            Tensor::<IntegerRep>::from((0..len).map(|_| rng.gen_range(0..10))).into();
 
         let circuit = NLCircuit {
             input: ValTensor::from(input.clone()),

benches/relu_lookupless.rs

@@ -0,0 +1,143 @@
+use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
+use ezkl::circuit::poly::PolyOp;
+use ezkl::circuit::region::RegionCtx;
+use ezkl::circuit::{BaseConfig as Config, CheckMode};
+use ezkl::fieldutils::IntegerRep;
+use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::TranscriptType;
+use ezkl::pfsys::{create_keys, srs::gen_srs};
+use ezkl::tensor::*;
+use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
+use halo2_proofs::poly::kzg::multiopen::{ProverSHPLONK, VerifierSHPLONK};
+use halo2_proofs::poly::kzg::strategy::SingleStrategy;
+use halo2_proofs::{
+    circuit::{Layouter, SimpleFloorPlanner, Value},
+    plonk::{Circuit, ConstraintSystem, Error},
+};
+use halo2curves::bn256::{Bn256, Fr};
+use rand::Rng;
+use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
+
+static mut LEN: usize = 4;
+const K: usize = 16;
+
+#[derive(Clone)]
+struct NLCircuit {
+    pub input: ValTensor<Fr>,
+}
+
+impl Circuit<Fr> for NLCircuit {
+    type Config = Config<Fr>;
+    type FloorPlanner = SimpleFloorPlanner;
+    type Params = ();
+
+    fn without_witnesses(&self) -> Self {
+        self.clone()
+    }
+
+    fn configure(cs: &mut ConstraintSystem<Fr>) -> Self::Config {
+        unsafe {
+            let advices = (0..3)
+                .map(|_| VarTensor::new_advice(cs, K, 1, LEN))
+                .collect::<Vec<_>>();
+
+            let mut config = Config::default();
+
+            config
+                .configure_range_check(cs, &advices[0], &advices[1], (-1, 1), K)
+                .unwrap();
+
+            config
+                .configure_range_check(cs, &advices[0], &advices[1], (0, 1023), K)
+                .unwrap();
+
+            let _constant = VarTensor::constant_cols(cs, K, LEN, false);
+
+            config
+        }
+    }
+
+    fn synthesize(
+        &self,
+        mut config: Self::Config,
+        mut layouter: impl Layouter<Fr>, // layouter is our 'write buffer' for the circuit
+    ) -> Result<(), Error> {
+        config.layout_range_checks(&mut layouter).unwrap();
+        layouter.assign_region(
+            || "",
+            |region| {
+                let mut region = RegionCtx::new(region, 0, 1, 1024, 2);
+                config
+                    .layout(&mut region, &[self.input.clone()], Box::new(PolyOp::ReLU))
+                    .unwrap();
+                Ok(())
+            },
+        )?;
+        Ok(())
+    }
+}
+
+fn runrelu(c: &mut Criterion) {
+    let mut group = c.benchmark_group("relu");
+
+    let mut rng = rand::thread_rng();
+    let params = gen_srs::<KZGCommitmentScheme<_>>(17);
+    for &len in [4, 8].iter() {
+        unsafe {
+            LEN = len;
+        };
+
+        let input: Tensor<Value<Fr>> =
+            Tensor::<IntegerRep>::from((0..len).map(|_| rng.gen_range(0..10))).into();
+
+        let circuit = NLCircuit {
+            input: ValTensor::from(input.clone()),
+        };
+
+        group.throughput(Throughput::Elements(len as u64));
+        group.bench_with_input(BenchmarkId::new("pk", len), &len, |b, &_| {
+            b.iter(|| {
+                create_keys::<KZGCommitmentScheme<Bn256>, NLCircuit>(&circuit, &params, true)
+                    .unwrap();
+            });
+        });
+
+        let pk =
+            create_keys::<KZGCommitmentScheme<Bn256>, NLCircuit>(&circuit, &params, true).unwrap();
+
+        group.throughput(Throughput::Elements(len as u64));
+        group.bench_with_input(BenchmarkId::new("prove", len), &len, |b, &_| {
+            b.iter(|| {
+                let prover = create_proof_circuit::<
+                    KZGCommitmentScheme<_>,
+                    NLCircuit,
+                    ProverSHPLONK<_>,
+                    VerifierSHPLONK<_>,
+                    SingleStrategy<_>,
+                    _,
+                    EvmTranscript<_, _, _, _>,
+                    EvmTranscript<_, _, _, _>,
+                >(
+                    circuit.clone(),
+                    vec![],
+                    &params,
+                    &pk,
+                    CheckMode::UNSAFE,
+                    ezkl::Commitments::KZG,
+                    TranscriptType::EVM,
+                    None,
+                    None,
+                );
+                prover.unwrap();
+            });
+        });
+    }
+    group.finish();
+}
+
+criterion_group! {
+  name = benches;
+  config = Criterion::default().with_plots();
+  targets = runrelu
+}
+criterion_main!(benches);

contracts/AttestData.sol

@@ -1,6 +1,167 @@
 // SPDX-License-Identifier: MIT
 pragma solidity ^0.8.20;
-import './LoadInstances.sol';
+contract LoadInstances {
+    /**
+     * @dev Parse the instances array from the Halo2Verifier encoded calldata.
+     * @notice must pass encoded bytes from memory
+     * @param encoded - verifier calldata
+     */
+    function getInstancesMemory(
+        bytes memory encoded
+    ) internal pure returns (uint256[] memory instances) {
+        bytes4 funcSig;
+        uint256 instances_offset;
+        uint256 instances_length;
+        assembly {
+            // fetch function sig. Either `verifyProof(bytes,uint256[])` or `verifyProof(address,bytes,uint256[])`
+            funcSig := mload(add(encoded, 0x20))
+
+            // Fetch instances offset which is 4 + 32 + 32 bytes away from
+            // start of encoded for `verifyProof(bytes,uint256[])`,
+            // and 4 + 32 + 32 +32 away for `verifyProof(address,bytes,uint256[])`
+
+            instances_offset := mload(
+                add(encoded, add(0x44, mul(0x20, eq(funcSig, 0xaf83a18d))))
+            )
+
+            instances_length := mload(add(add(encoded, 0x24), instances_offset))
+        }
+        instances = new uint256[](instances_length); // Allocate memory for the instances array.
+        assembly {
+            // Now instances points to the start of the array data
+            // (right after the length field).
+            for {
+                let i := 0x20
+            } lt(i, add(mul(instances_length, 0x20), 0x20)) {
+                i := add(i, 0x20)
+            } {
+                mstore(
+                    add(instances, i),
+                    mload(add(add(encoded, add(i, 0x24)), instances_offset))
+                )
+            }
+        }
+    }
+    /**
+     * @dev Parse the instances array from the Halo2Verifier encoded calldata.
+     * @notice must pass encoded bytes from calldata
+     * @param encoded - verifier calldata
+     */
+    function getInstancesCalldata(
+        bytes calldata encoded
+    ) internal pure returns (uint256[] memory instances) {
+        bytes4 funcSig;
+        uint256 instances_offset;
+        uint256 instances_length;
+        assembly {
+            // fetch function sig. Either `verifyProof(bytes,uint256[])` or `verifyProof(address,bytes,uint256[])`
+            funcSig := calldataload(encoded.offset)
+
+            // Fetch instances offset which is 4 + 32 + 32 bytes away from
+            // start of encoded for `verifyProof(bytes,uint256[])`,
+            // and 4 + 32 + 32 +32 away for `verifyProof(address,bytes,uint256[])`
+
+            instances_offset := calldataload(
+                add(
+                    encoded.offset,
+                    add(0x24, mul(0x20, eq(funcSig, 0xaf83a18d)))
+                )
+            )
+
+            instances_length := calldataload(
+                add(add(encoded.offset, 0x04), instances_offset)
+            )
+        }
+        instances = new uint256[](instances_length); // Allocate memory for the instances array.
+        assembly {
+            // Now instances points to the start of the array data
+            // (right after the length field).
+
+            for {
+                let i := 0x20
+            } lt(i, add(mul(instances_length, 0x20), 0x20)) {
+                i := add(i, 0x20)
+            } {
+                mstore(
+                    add(instances, i),
+                    calldataload(
+                        add(add(encoded.offset, add(i, 0x04)), instances_offset)
+                    )
+                )
+            }
+        }
+    }
+}
+
+// The kzg commitments of a given model, all aggregated into a single bytes array.
+// At solidity generation time, the commitments are hardcoded into the contract via the COMMITMENT_KZG constant.
+// It will be used to check that the proof commitments match the expected commitments.
+bytes constant COMMITMENT_KZG = hex"";
+
+contract SwapProofCommitments {
+    /**
+     * @dev Swap the proof commitments
+     * @notice must pass encoded bytes from memory
+     * @param encoded - verifier calldata
+     */
+    function checkKzgCommits(
+        bytes calldata encoded
+    ) internal pure returns (bool equal) {
+        bytes4 funcSig;
+        uint256 proof_offset;
+        uint256 proof_length;
+        assembly {
+            // fetch function sig. Either `verifyProof(bytes,uint256[])` or `verifyProof(address,bytes,uint256[])`
+            funcSig := calldataload(encoded.offset)
+
+            // Fetch proof offset which is 4 + 32 bytes away from
+            // start of encoded for `verifyProof(bytes,uint256[])`,
+            // and 4 + 32 + 32 away for `verifyProof(address,bytes,uint256[])`
+
+            proof_offset := calldataload(
+                add(
+                    encoded.offset,
+                    add(0x04, mul(0x20, eq(funcSig, 0xaf83a18d)))
+                )
+            )
+
+            proof_length := calldataload(
+                add(add(encoded.offset, 0x04), proof_offset)
+            )
+        }
+        // Check the length of the commitment against the proof bytes
+        if (proof_length < COMMITMENT_KZG.length) {
+            return false;
+        }
+
+        // Load COMMITMENT_KZG into memory
+        bytes memory commitment = COMMITMENT_KZG;
+
+        // Compare the first N bytes of the proof with COMMITMENT_KZG
+        uint words = (commitment.length + 31) / 32; // Calculate the number of 32-byte words
+
+        assembly {
+            // Now we compare the commitment with the proof,
+            // ensuring that the commitments divided up into 32 byte words are all equal.
+            for {
+                let i := 0x20
+            } lt(i, add(mul(words, 0x20), 0x20)) {
+                i := add(i, 0x20)
+            } {
+                let wordProof := calldataload(
+                    add(add(encoded.offset, add(i, 0x04)), proof_offset)
+                )
+                let wordCommitment := mload(add(commitment, i))
+                equal := eq(wordProof, wordCommitment)
+                if eq(equal, 0) {
+                    return(0, 0)
+                }
+            }
+        }
+
+        return equal; // Return true if the commitment comparison passed
+    } /// end checkKzgCommits
+}
 
 // This contract serves as a Data Attestation Verifier for the EZKL model.
 // It is designed to read and attest to instances of proofs generated from a specified circuit.
@@ -13,9 +174,10 @@ import './LoadInstances.sol';
 // 4. Field Element Conversion: The fixed-point representation is then converted into a field element modulo P using the `toFieldElement` method.
 // 5. Data Attestation: The `attestData` method validates that the public instances match the data fetched and processed by the contract.
 // 6. Proof Verification: The `verifyWithDataAttestation` method parses the instances out of the encoded calldata and calls the `attestData` method to validate the public instances,
+// 6b. Optional KZG Commitment Verification: It also checks the KZG commitments in the proof against the expected commitments using the `checkKzgCommits` method.
 //  then calls the `verifyProof` method to verify the proof on the verifier.
 
-contract DataAttestation is LoadInstances {
+contract DataAttestation is LoadInstances, SwapProofCommitments {
     /**
      * @notice Struct used to make view only calls to accounts to fetch the data that EZKL reads from.
      * @param the address of the account to make calls to
@@ -34,11 +196,14 @@ contract DataAttestation is LoadInstances {
     address public admin;
 
     /**
-     * @notice EZKL P value 
+     * @notice EZKL P value
      * @dev In order to prevent the verifier from accepting two version of the same pubInput, n and the quantity (n + P),  where n + P <= 2^256, we require that all instances are stricly less than P. a
      * @dev The reason for this is that the assmebly code of the verifier performs all arithmetic operations modulo P and as a consequence can't distinguish between n and n + P.
      */
-    uint256 constant ORDER = uint256(0x30644e72e131a029b85045b68181585d2833e84879b9709143e1f593f0000001); 
+    uint256 constant ORDER =
+        uint256(
+            0x30644e72e131a029b85045b68181585d2833e84879b9709143e1f593f0000001
+        );
 
     uint256 constant INPUT_CALLS = 0;
 
@@ -69,7 +234,7 @@ contract DataAttestation is LoadInstances {
 
     function updateAdmin(address _admin) external {
         require(msg.sender == admin, "Only admin can update admin");
-        if(_admin == address(0)) {
+        if (_admin == address(0)) {
             revert();
         }
         admin = _admin;
@@ -80,7 +245,7 @@ contract DataAttestation is LoadInstances {
         bytes[][] memory _callData,
         uint256[][] memory _decimals
     ) external {
-        require(msg.sender == admin, "Only admin can update instanceOffset");
+        require(msg.sender == admin, "Only admin can update account calls");
         populateAccountCalls(_contractAddresses, _callData, _decimals);
     }
 
@@ -111,7 +276,10 @@ contract DataAttestation is LoadInstances {
             // count the total number of storage reads across all of the accounts
             counter += _callData[i].length;
         }
-        require(counter == INPUT_CALLS + OUTPUT_CALLS, "Invalid number of calls");
+        require(
+            counter == INPUT_CALLS + OUTPUT_CALLS,
+            "Invalid number of calls"
+        );
     }
 
     function mulDiv(
@@ -167,7 +335,7 @@ contract DataAttestation is LoadInstances {
      * @dev Quantize the data returned from the account calls to the scale used by the EZKL model.
      * @param data - The data returned from the account calls.
      * @param decimals - The number of decimals the data returned from the account calls has (for floating point representation).
-     * @param scale - The scale used to convert the floating point value into a fixed point value. 
+     * @param scale - The scale used to convert the floating point value into a fixed point value.
      */
     function quantizeData(
         bytes memory data,
@@ -181,7 +349,7 @@ contract DataAttestation is LoadInstances {
         if (mulmod(uint256(x), scale, decimals) * 2 >= decimals) {
             output += 1;
         }
-        quantized_data = neg ? -int256(output): int256(output);
+        quantized_data = neg ? -int256(output) : int256(output);
     }
     /**
      * @dev Make a static call to the account to fetch the data that EZKL reads from.
@@ -211,7 +379,9 @@ contract DataAttestation is LoadInstances {
      * @param x - The quantized data.
      * @return field_element - The field element.
      */
-    function toFieldElement(int256 x) internal pure returns (uint256 field_element) {
+    function toFieldElement(
+        int256 x
+    ) internal pure returns (uint256 field_element) {
         // The casting down to uint256 is safe because the order is about 2^254, and the value
         // of x ranges of -2^127 to 2^127, so x + int(ORDER) is always positive.
         return uint256(x + int(ORDER)) % ORDER;
@@ -251,13 +421,18 @@ contract DataAttestation is LoadInstances {
         }
     }
 
-
+    /**
+     * @dev Verify the proof with the data attestation.
+     * @param verifier - The address of the verifier contract.
+     * @param encoded - The verifier calldata.
+     */
     function verifyWithDataAttestation(
         address verifier,
         bytes calldata encoded
     ) public view returns (bool) {
-        require(verifier.code.length > 0,"Address: call to non-contract");
+        require(verifier.code.length > 0, "Address: call to non-contract");
         attestData(getInstancesCalldata(encoded));
+        require(checkKzgCommits(encoded), "Invalid KZG commitments");
         // static call the verifier contract to verify the proof
         (bool success, bytes memory returndata) = verifier.staticcall(encoded);
 

contracts/LoadInstances.sol

@@ -1,92 +0,0 @@
-// SPDX-License-Identifier: MIT
-pragma solidity ^0.8.20;
-contract LoadInstances {
-    /**
-     * @dev Parse the instances array from the Halo2Verifier encoded calldata. 
-     * @notice must pass encoded bytes from memory
-     * @param encoded - verifier calldata
-     */
-    function getInstancesMemory(
-        bytes memory encoded
-    ) internal pure returns (uint256[] memory instances) {
-        bytes4 funcSig;
-        uint256 instances_offset;
-        uint256 instances_length;
-        assembly {
-            // fetch function sig. Either `verifyProof(bytes,uint256[])` or `verifyProof(address,bytes,uint256[])`
-            funcSig := mload(add(encoded, 0x20))
-
-            // Fetch instances offset which is 4 + 32 + 32 bytes away from
-            // start of encoded for `verifyProof(bytes,uint256[])`,
-            // and 4 + 32 + 32 +32 away for `verifyProof(address,bytes,uint256[])`
-
-            instances_offset := mload(
-                add(encoded, add(0x44, mul(0x20, eq(funcSig, 0xaf83a18d))))
-            )
-
-            instances_length := mload(add(add(encoded, 0x24), instances_offset))
-        }
-        instances = new uint256[](instances_length); // Allocate memory for the instances array.
-        assembly {
-            // Now instances points to the start of the array data
-            // (right after the length field).
-            for {
-                let i := 0x20
-            } lt(i, add(mul(instances_length, 0x20), 0x20)) {
-                i := add(i, 0x20)
-            } {
-                mstore(
-                    add(instances, i),
-                    mload(add(add(encoded, add(i, 0x24)), instances_offset))
-                )
-            }
-        }
-    }
-    /**
-     * @dev Parse the instances array from the Halo2Verifier encoded calldata. 
-     * @notice must pass encoded bytes from calldata
-     * @param encoded - verifier calldata
-     */
-    function getInstancesCalldata(
-        bytes calldata encoded
-    ) internal pure returns (uint256[] memory instances) {
-        bytes4 funcSig;
-        uint256 instances_offset;
-        uint256 instances_length;
-        assembly {
-            // fetch function sig. Either `verifyProof(bytes,uint256[])` or `verifyProof(address,bytes,uint256[])`
-            funcSig := calldataload(encoded.offset)
-
-            // Fetch instances offset which is 4 + 32 + 32 bytes away from
-            // start of encoded for `verifyProof(bytes,uint256[])`,
-            // and 4 + 32 + 32 +32 away for `verifyProof(address,bytes,uint256[])`
-
-            instances_offset := calldataload(
-                add(
-                    encoded.offset,
-                    add(0x24, mul(0x20, eq(funcSig, 0xaf83a18d)))
-                )
-            )
-
-            instances_length := calldataload(add(add(encoded.offset, 0x04), instances_offset))
-        }
-        instances = new uint256[](instances_length); // Allocate memory for the instances array.
-        assembly{
-            // Now instances points to the start of the array data
-            // (right after the length field).
-
-            for {
-                let i := 0x20
-            } lt(i, add(mul(instances_length, 0x20), 0x20)) {
-                i := add(i, 0x20)
-            } {
-                mstore(
-                    add(instances, i),
-                    calldataload(
-                        add(add(encoded.offset, add(i, 0x04)), instances_offset)
-                    )
-                )
-            }
-        }
-    }
-}

contracts/QuantizeData.sol

@@ -1,135 +0,0 @@
-// SPDX-License-Identifier: GPL-3.0
-
-pragma solidity ^0.8.17;
-
-contract QuantizeData {
-    /**
-     * @notice EZKL P value
-     * @dev In order to prevent the verifier from accepting two version of the same instance, n and the quantity (n + P),  where n + P <= 2^256, we require that all instances are stricly less than P. a
-     * @dev The reason for this is that the assmebly code of the verifier performs all arithmetic operations modulo P and as a consequence can't distinguish between n and n + P.
-     */
-    uint256 constant ORDER =
-        uint256(
-            0x30644e72e131a029b85045b68181585d2833e84879b9709143e1f593f0000001
-        );
-
-    /**
-     * @notice Calculates floor(x * y / denominator) with full precision. Throws if result overflows a uint256 or denominator == 0
-     * @dev Original credit to Remco Bloemen under MIT license (https://xn--2-umb.com/21/muldiv)
-     * with further edits by Uniswap Labs also under MIT license.
-     */
-    function mulDiv(
-        uint256 x,
-        uint256 y,
-        uint256 denominator
-    ) internal pure returns (uint256 result) {
-        unchecked {
-            // 512-bit multiply [prod1 prod0] = x * y. Compute the product mod 2^256 and mod 2^256 - 1, then use
-            // use the Chinese Remainder Theorem to reconstruct the 512 bit result. The result is stored in two 256
-            // variables such that product = prod1 * 2^256 + prod0.
-            uint256 prod0; // Least significant 256 bits of the product
-            uint256 prod1; // Most significant 256 bits of the product
-            assembly {
-                let mm := mulmod(x, y, not(0))
-                prod0 := mul(x, y)
-                prod1 := sub(sub(mm, prod0), lt(mm, prod0))
-            }
-
-            // Handle non-overflow cases, 256 by 256 division.
-            if (prod1 == 0) {
-                // Solidity will revert if denominator == 0, unlike the div opcode on its own.
-                // The surrounding unchecked block does not change this fact.
-                // See https://docs.soliditylang.org/en/latest/control-structures.html#checked-or-unchecked-arithmetic.
-                return prod0 / denominator;
-            }
-
-            // Make sure the result is less than 2^256. Also prevents denominator == 0.
-            require(denominator > prod1, "Math: mulDiv overflow");
-
-            ///////////////////////////////////////////////
-            // 512 by 256 division.
-            ///////////////////////////////////////////////
-
-            // Make division exact by subtracting the remainder from [prod1 prod0].
-            uint256 remainder;
-            assembly {
-                // Compute remainder using mulmod.
-                remainder := mulmod(x, y, denominator)
-
-                // Subtract 256 bit number from 512 bit number.
-                prod1 := sub(prod1, gt(remainder, prod0))
-                prod0 := sub(prod0, remainder)
-            }
-
-            // Factor powers of two out of denominator and compute largest power of two divisor of denominator. Always >= 1.
-            // See https://cs.stackexchange.com/q/138556/92363.
-
-            // Does not overflow because the denominator cannot be zero at this stage in the function.
-            uint256 twos = denominator & (~denominator + 1);
-            assembly {
-                // Divide denominator by twos.
-                denominator := div(denominator, twos)
-
-                // Divide [prod1 prod0] by twos.
-                prod0 := div(prod0, twos)
-
-                // Flip twos such that it is 2^256 / twos. If twos is zero, then it becomes one.
-                twos := add(div(sub(0, twos), twos), 1)
-            }
-
-            // Shift in bits from prod1 into prod0.
-            prod0 |= prod1 * twos;
-
-            // Invert denominator mod 2^256. Now that denominator is an odd number, it has an inverse modulo 2^256 such
-            // that denominator * inv = 1 mod 2^256. Compute the inverse by starting with a seed that is correct for
-            // four bits. That is, denominator * inv = 1 mod 2^4.
-            uint256 inverse = (3 * denominator) ^ 2;
-
-            // Use the Newton-Raphson iteration to improve the precision. Thanks to Hensel's lifting lemma, this also works
-            // in modular arithmetic, doubling the correct bits in each step.
-            inverse *= 2 - denominator * inverse; // inverse mod 2^8
-            inverse *= 2 - denominator * inverse; // inverse mod 2^16
-            inverse *= 2 - denominator * inverse; // inverse mod 2^32
-            inverse *= 2 - denominator * inverse; // inverse mod 2^64
-            inverse *= 2 - denominator * inverse; // inverse mod 2^128
-            inverse *= 2 - denominator * inverse; // inverse mod 2^256
-
-            // Because the division is now exact we can divide by multiplying with the modular inverse of denominator.
-            // This will give us the correct result modulo 2^256. Since the preconditions guarantee that the outcome is
-            // less than 2^256, this is the final result. We don't need to compute the high bits of the result and prod1
-            // is no longer required.
-            result = prod0 * inverse;
-            return result;
-        }
-    }
-
-    function quantize_data(
-        bytes[] memory data,
-        uint256[] memory decimals,
-        uint256[] memory scales
-    ) external pure returns (int256[] memory quantized_data) {
-        quantized_data = new int256[](data.length);
-        for (uint i; i < data.length; i++) {
-            int x = abi.decode(data[i], (int256));
-            bool neg = x < 0;
-            if (neg) x = -x;
-            uint denom = 10 ** decimals[i];
-            uint scale = 1 << scales[i];
-            uint output = mulDiv(uint256(x), scale, denom);
-            if (mulmod(uint256(x), scale, denom) * 2 >= denom) {
-                output += 1;
-            }
-
-            quantized_data[i] = neg ? -int256(output) : int256(output);
-        }
-    }
-
-    function to_field_element(
-        int64[] memory quantized_data
-    ) public pure returns (uint256[] memory output) {
-        output = new uint256[](quantized_data.length);
-        for (uint i; i < quantized_data.length; i++) {
-            output[i] = uint256(quantized_data[i] + int(ORDER)) % ORDER;
-        }
-    }
-}

contracts/TestReads.sol

@@ -1,12 +0,0 @@
-// SPDX-License-Identifier: UNLICENSED
-pragma solidity ^0.8.17;
-
-contract TestReads {
-    int[] public arr;
-
-    constructor(int256[] memory _numbers) {
-        for (uint256 i = 0; i < _numbers.length; i++) {
-            arr.push(_numbers[i]);
-        }
-    }
-}

docs/python/requirements-docs.txt

@@ -1,4 +1,4 @@
-ezkl==0.0.0
+ezkl==14.0.2
 sphinx
 sphinx-rtd-theme
 sphinxcontrib-napoleon

docs/python/src/conf.py

@@ -1,7 +1,7 @@
 import ezkl
 
 project = 'ezkl'
-release = '0.0.0'
+release = '14.0.2'
 version = release
 
 

examples/conv2d_mnist/main.rs

@@ -2,8 +2,7 @@ use ezkl::circuit::region::RegionCtx;
 use ezkl::circuit::{
     ops::lookup::LookupOp, ops::poly::PolyOp, BaseConfig as PolyConfig, CheckMode,
 };
-use ezkl::fieldutils;
-use ezkl::fieldutils::i32_to_felt;
+use ezkl::fieldutils::{self, integer_rep_to_felt, IntegerRep};
 use ezkl::tensor::*;
 use halo2_proofs::dev::MockProver;
 use halo2_proofs::poly::commitment::Params;
@@ -42,8 +41,8 @@ const NUM_INNER_COLS: usize = 1;
 struct Config<
     const LEN: usize, //LEN = CHOUT x OH x OW flattened //not supported yet in rust stable
     const CLASSES: usize,
-    const LOOKUP_MIN: i64,
-    const LOOKUP_MAX: i64,
+    const LOOKUP_MIN: IntegerRep,
+    const LOOKUP_MAX: IntegerRep,
     // Convolution
     const KERNEL_HEIGHT: usize,
     const KERNEL_WIDTH: usize,
@@ -66,8 +65,8 @@ struct Config<
 struct MyCircuit<
     const LEN: usize, //LEN = CHOUT x OH x OW flattened
     const CLASSES: usize,
-    const LOOKUP_MIN: i64,
-    const LOOKUP_MAX: i64,
+    const LOOKUP_MIN: IntegerRep,
+    const LOOKUP_MAX: IntegerRep,
     // Convolution
     const KERNEL_HEIGHT: usize,
     const KERNEL_WIDTH: usize,
@@ -90,8 +89,8 @@ struct MyCircuit<
 impl<
         const LEN: usize,
         const CLASSES: usize,
-        const LOOKUP_MIN: i64,
-        const LOOKUP_MAX: i64,
+        const LOOKUP_MIN: IntegerRep,
+        const LOOKUP_MAX: IntegerRep,
         // Convolution
         const KERNEL_HEIGHT: usize,
         const KERNEL_WIDTH: usize,
@@ -164,7 +163,7 @@ where
                 &params,
                 (LOOKUP_MIN, LOOKUP_MAX),
                 K,
-                &LookupOp::ReLU,
+                &LookupOp::LeakyReLU { slope: 0.0.into() },
             )
             .unwrap();
 
@@ -200,11 +199,12 @@ where
             .assign_region(
                 || "mlp_4d",
                 |region| {
-                    let mut region = RegionCtx::new(region, 0, NUM_INNER_COLS);
+                    let mut region = RegionCtx::new(region, 0, NUM_INNER_COLS, 1024, 2);
 
                     let op = PolyOp::Conv {
                         padding: vec![(PADDING, PADDING); 2],
                         stride: vec![STRIDE; 2],
+                        group: 1,
                     };
                     let x = config
                         .layer_config
@@ -221,7 +221,11 @@ where
 
                     let x = config
                         .layer_config
-                        .layout(&mut region, &[x.unwrap()], Box::new(LookupOp::ReLU))
+                        .layout(
+                            &mut region,
+                            &[x.unwrap()],
+                            Box::new(LookupOp::LeakyReLU { slope: 0.0.into() }),
+                        )
                         .unwrap();
 
                     let mut x = config
@@ -315,7 +319,11 @@ pub fn runconv() {
         .test_set_length(10_000)
         .finalize();
 
-    let mut train_data = Tensor::from(trn_img.iter().map(|x| i32_to_felt::<F>(*x as i32 / 16)));
+    let mut train_data = Tensor::from(
+        trn_img
+            .iter()
+            .map(|x| integer_rep_to_felt::<F>(*x as IntegerRep / 16)),
+    );
     train_data.reshape(&[50_000, 28, 28]).unwrap();
 
     let mut train_labels = Tensor::from(trn_lbl.iter().map(|x| *x as f32));
@@ -343,8 +351,8 @@ pub fn runconv() {
             .map(|fl| {
                 let dx = fl * 32_f32;
                 let rounded = dx.round();
-                let integral: i32 = unsafe { rounded.to_int_unchecked() };
-                fieldutils::i32_to_felt(integral)
+                let integral: IntegerRep = unsafe { rounded.to_int_unchecked() };
+                fieldutils::integer_rep_to_felt(integral)
             }),
     );
 
@@ -355,7 +363,8 @@ pub fn runconv() {
 
     let l0_kernels = l0_kernels.try_into().unwrap();
 
-    let mut l0_bias = Tensor::<F>::from((0..OUT_CHANNELS).map(|_| fieldutils::i32_to_felt(0)));
+    let mut l0_bias =
+        Tensor::<F>::from((0..OUT_CHANNELS).map(|_| fieldutils::integer_rep_to_felt(0)));
     l0_bias.set_visibility(&ezkl::graph::Visibility::Private);
 
     let l0_bias = l0_bias.try_into().unwrap();
@@ -363,8 +372,8 @@ pub fn runconv() {
     let mut l2_biases = Tensor::<F>::from(myparams.biases.into_iter().map(|fl| {
         let dx = fl * 32_f32;
         let rounded = dx.round();
-        let integral: i32 = unsafe { rounded.to_int_unchecked() };
-        fieldutils::i32_to_felt(integral)
+        let integral: IntegerRep = unsafe { rounded.to_int_unchecked() };
+        fieldutils::integer_rep_to_felt(integral)
     }));
     l2_biases.set_visibility(&ezkl::graph::Visibility::Private);
     l2_biases.reshape(&[l2_biases.len(), 1]).unwrap();
@@ -374,8 +383,8 @@ pub fn runconv() {
     let mut l2_weights = Tensor::<F>::from(myparams.weights.into_iter().flatten().map(|fl| {
         let dx = fl * 32_f32;
         let rounded = dx.round();
-        let integral: i32 = unsafe { rounded.to_int_unchecked() };
-        fieldutils::i32_to_felt(integral)
+        let integral: IntegerRep = unsafe { rounded.to_int_unchecked() };
+        fieldutils::integer_rep_to_felt(integral)
     }));
     l2_weights.set_visibility(&ezkl::graph::Visibility::Private);
     l2_weights.reshape(&[CLASSES, LEN]).unwrap();
@@ -401,13 +410,13 @@ pub fn runconv() {
         l2_params: [l2_weights, l2_biases],
     };
 
-    let public_input: Tensor<i32> = vec![
-        -25124i32, -19304, -16668, -4399, -6209, -4548, -2317, -8349, -6117, -23461,
+    let public_input: Tensor<IntegerRep> = vec![
+        -25124, -19304, -16668, -4399, -6209, -4548, -2317, -8349, -6117, -23461,
     ]
     .into_iter()
     .into();
 
-    let pi_inner: Tensor<F> = public_input.map(i32_to_felt::<F>);
+    let pi_inner: Tensor<F> = public_input.map(integer_rep_to_felt::<F>);
 
     println!("MOCK PROVING");
     let now = Instant::now();

examples/mlp_4d_einsum.rs

@@ -2,7 +2,7 @@ use ezkl::circuit::region::RegionCtx;
 use ezkl::circuit::{
     ops::lookup::LookupOp, ops::poly::PolyOp, BaseConfig as PolyConfig, CheckMode,
 };
-use ezkl::fieldutils::i32_to_felt;
+use ezkl::fieldutils::{integer_rep_to_felt, IntegerRep};
 use ezkl::tensor::*;
 use halo2_proofs::dev::MockProver;
 use halo2_proofs::{
@@ -23,8 +23,8 @@ struct MyConfig {
 #[derive(Clone)]
 struct MyCircuit<
     const LEN: usize, //LEN = CHOUT x OH x OW flattened
-    const LOOKUP_MIN: i64,
-    const LOOKUP_MAX: i64,
+    const LOOKUP_MIN: IntegerRep,
+    const LOOKUP_MAX: IntegerRep,
 > {
     // Given the stateless MyConfig type information, a DNN trace is determined by its input and the parameters of its layers.
     // Computing the trace still requires a forward pass. The intermediate activations are stored only by the layouter.
@@ -34,7 +34,7 @@ struct MyCircuit<
     _marker: PhantomData<F>,
 }
 
-impl<const LEN: usize, const LOOKUP_MIN: i64, const LOOKUP_MAX: i64> Circuit<F>
+impl<const LEN: usize, const LOOKUP_MIN: IntegerRep, const LOOKUP_MAX: IntegerRep> Circuit<F>
     for MyCircuit<LEN, LOOKUP_MIN, LOOKUP_MAX>
 {
     type Config = MyConfig;
@@ -69,7 +69,7 @@ impl<const LEN: usize, const LOOKUP_MIN: i64, const LOOKUP_MAX: i64> Circuit<F>
                 &params,
                 (LOOKUP_MIN, LOOKUP_MAX),
                 K,
-                &LookupOp::ReLU,
+                &LookupOp::LeakyReLU { slope: 0.0.into() },
             )
             .unwrap();
 
@@ -108,7 +108,7 @@ impl<const LEN: usize, const LOOKUP_MIN: i64, const LOOKUP_MAX: i64> Circuit<F>
             .assign_region(
                 || "mlp_4d",
                 |region| {
-                    let mut region = RegionCtx::new(region, 0, 1);
+                    let mut region = RegionCtx::new(region, 0, 1, 1024, 2);
                     let x = config
                         .layer_config
                         .layout(
@@ -141,7 +141,11 @@ impl<const LEN: usize, const LOOKUP_MIN: i64, const LOOKUP_MAX: i64> Circuit<F>
                     println!("x shape: {:?}", x.dims());
                     let mut x = config
                         .layer_config
-                        .layout(&mut region, &[x], Box::new(LookupOp::ReLU))
+                        .layout(
+                            &mut region,
+                            &[x],
+                            Box::new(LookupOp::LeakyReLU { slope: 0.0.into() }),
+                        )
                         .unwrap()
                         .unwrap();
                     println!("3");
@@ -177,7 +181,11 @@ impl<const LEN: usize, const LOOKUP_MIN: i64, const LOOKUP_MAX: i64> Circuit<F>
                     println!("x shape: {:?}", x.dims());
                     let x = config
                         .layer_config
-                        .layout(&mut region, &[x], Box::new(LookupOp::ReLU))
+                        .layout(
+                            &mut region,
+                            &[x],
+                            Box::new(LookupOp::LeakyReLU { slope: 0.0.into() }),
+                        )
                         .unwrap();
                     println!("6");
                     println!("offset: {}", region.row());
@@ -215,33 +223,33 @@ pub fn runmlp() {
     #[cfg(not(target_arch = "wasm32"))]
     env_logger::init();
     // parameters
-    let mut l0_kernel: Tensor<F> = Tensor::<i32>::new(
+    let mut l0_kernel: Tensor<F> = Tensor::<IntegerRep>::new(
         Some(&[10, 0, 0, -1, 0, 10, 1, 0, 0, 1, 10, 0, 1, 0, 0, 10]),
         &[4, 4],
     )
     .unwrap()
-    .map(i32_to_felt);
+    .map(integer_rep_to_felt);
     l0_kernel.set_visibility(&ezkl::graph::Visibility::Private);
 
-    let mut l0_bias: Tensor<F> = Tensor::<i32>::new(Some(&[0, 0, 0, 1]), &[4, 1])
+    let mut l0_bias: Tensor<F> = Tensor::<IntegerRep>::new(Some(&[0, 0, 0, 1]), &[4, 1])
         .unwrap()
-        .map(i32_to_felt);
+        .map(integer_rep_to_felt);
     l0_bias.set_visibility(&ezkl::graph::Visibility::Private);
 
-    let mut l2_kernel: Tensor<F> = Tensor::<i32>::new(
+    let mut l2_kernel: Tensor<F> = Tensor::<IntegerRep>::new(
         Some(&[0, 3, 10, -1, 0, 10, 1, 0, 0, 1, 0, 12, 1, -2, 32, 0]),
         &[4, 4],
     )
     .unwrap()
-    .map(i32_to_felt);
+    .map(integer_rep_to_felt);
     l2_kernel.set_visibility(&ezkl::graph::Visibility::Private);
     // input data, with 1 padding to allow for bias
-    let input: Tensor<Value<F>> = Tensor::<i32>::new(Some(&[-30, -21, 11, 40]), &[4, 1])
+    let input: Tensor<Value<F>> = Tensor::<IntegerRep>::new(Some(&[-30, -21, 11, 40]), &[4, 1])
         .unwrap()
         .into();
-    let mut l2_bias: Tensor<F> = Tensor::<i32>::new(Some(&[0, 0, 0, 1]), &[4, 1])
+    let mut l2_bias: Tensor<F> = Tensor::<IntegerRep>::new(Some(&[0, 0, 0, 1]), &[4, 1])
         .unwrap()
-        .map(i32_to_felt);
+        .map(integer_rep_to_felt);
     l2_bias.set_visibility(&ezkl::graph::Visibility::Private);
 
     let circuit = MyCircuit::<4, -8192, 8192> {
@@ -251,12 +259,12 @@ pub fn runmlp() {
         _marker: PhantomData,
     };
 
-    let public_input: Vec<i32> = unsafe {
+    let public_input: Vec<IntegerRep> = unsafe {
         vec![
-            (531f32 / 128f32).round().to_int_unchecked::<i32>(),
-            (103f32 / 128f32).round().to_int_unchecked::<i32>(),
-            (4469f32 / 128f32).round().to_int_unchecked::<i32>(),
-            (2849f32 / 128f32).to_int_unchecked::<i32>(),
+            (531f32 / 128f32).round().to_int_unchecked::<IntegerRep>(),
+            (103f32 / 128f32).round().to_int_unchecked::<IntegerRep>(),
+            (4469f32 / 128f32).round().to_int_unchecked::<IntegerRep>(),
+            (2849f32 / 128f32).to_int_unchecked::<IntegerRep>(),
         ]
     };
 
@@ -265,7 +273,10 @@ pub fn runmlp() {
     let prover = MockProver::run(
         K as u32,
         &circuit,
-        vec![public_input.iter().map(|x| i32_to_felt::<F>(*x)).collect()],
+        vec![public_input
+            .iter()
+            .map(|x| integer_rep_to_felt::<F>(*x))
+            .collect()],
     )
     .unwrap();
     prover.assert_satisfied();

examples/notebooks/data_attest.ipynb

@@ -251,7 +251,7 @@
                 "with open(cal_path, \"w\") as f:\n",
                 "    json.dump(cal_data, f)\n",
                 "\n",
-                "res = ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "res = await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -307,7 +307,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "ezkl.setup_test_evm_witness(\n",
+                "await ezkl.setup_test_evm_witness(\n",
                 "    data_path,\n",
                 "    compiled_model_path,\n",
                 "    # we write the call data to the same file as the input data\n",
@@ -333,7 +333,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "res = ezkl.get_srs( settings_path)\n"
+                "res = await ezkl.get_srs( settings_path)\n"
             ]
         },
         {
@@ -354,7 +354,7 @@
                 "\n",
                 "witness_path = \"witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)"
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)"
             ]
         },
         {
@@ -462,7 +462,7 @@
                 "abi_path = 'test.abi'\n",
                 "sol_code_path = 'test.sol'\n",
                 "\n",
-                "res = ezkl.create_evm_verifier(\n",
+                "res = await ezkl.create_evm_verifier(\n",
                 "        vk_path,\n",
                 "        \n",
                 "        settings_path,\n",
@@ -482,7 +482,7 @@
                 "\n",
                 "addr_path_verifier = \"addr_verifier.txt\"\n",
                 "\n",
-                "res = ezkl.deploy_evm(\n",
+                "res = await ezkl.deploy_evm(\n",
                 "    addr_path_verifier,\n",
                 "    sol_code_path,\n",
                 "    'http://127.0.0.1:3030'\n",
@@ -510,7 +510,7 @@
                 "sol_code_path = 'test.sol'\n",
                 "input_path = 'input.json'\n",
                 "\n",
-                "res = ezkl.create_evm_data_attestation(\n",
+                "res = await ezkl.create_evm_data_attestation(\n",
                 "        input_path,\n",
                 "        settings_path,\n",
                 "        sol_code_path,\n",
@@ -535,7 +535,7 @@
             "source": [
                 "addr_path_da = \"addr_da.txt\"\n",
                 "\n",
-                "res = ezkl.deploy_da_evm(\n",
+                "res = await ezkl.deploy_da_evm(\n",
                 "        addr_path_da,\n",
                 "        input_path,\n",
                 "        settings_path,\n",
@@ -567,7 +567,7 @@
                 "with open(addr_path_da, 'r') as f:\n",
                 "    addr_da = f.read()\n",
                 "\n",
-                "res = ezkl.verify_evm(\n",
+                "res = await ezkl.verify_evm(\n",
                 "    addr,\n",
                 "    proof_path,\n",
                 "    RPC_URL,\n",
@@ -592,7 +592,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.15"
+            "version": "3.12.2"
         },
         "orig_nbformat": 4
     },

examples/notebooks/data_attest_hashed.ipynb

@@ -249,7 +249,7 @@
                 "with open(cal_path, \"w\") as f:\n",
                 "    json.dump(cal_data, f)\n",
                 "\n",
-                "res = ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "res = await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -278,7 +278,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "res = ezkl.get_srs( settings_path)\n"
+                "res = await ezkl.get_srs( settings_path)\n"
             ]
         },
         {
@@ -299,7 +299,7 @@
                 "\n",
                 "witness_path = \"witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "\n"
             ]
         },
@@ -518,7 +518,7 @@
                 "abi_path = 'test.abi'\n",
                 "sol_code_path = 'test.sol'\n",
                 "\n",
-                "res = ezkl.create_evm_verifier(\n",
+                "res = await ezkl.create_evm_verifier(\n",
                 "        vk_path,\n",
                 "        \n",
                 "        settings_path,\n",
@@ -538,7 +538,7 @@
                 "\n",
                 "addr_path_verifier = \"addr_verifier.txt\"\n",
                 "\n",
-                "res = ezkl.deploy_evm(\n",
+                "res = await ezkl.deploy_evm(\n",
                 "    addr_path_verifier,\n",
                 "    sol_code_path,\n",
                 "    'http://127.0.0.1:3030'\n",
@@ -566,7 +566,7 @@
                 "sol_code_path = 'test.sol'\n",
                 "input_path = 'input.json'\n",
                 "\n",
-                "res = ezkl.create_evm_data_attestation(\n",
+                "res = await ezkl.create_evm_data_attestation(\n",
                 "        input_path,\n",
                 "        settings_path,\n",
                 "        sol_code_path,\n",
@@ -591,7 +591,7 @@
             "source": [
                 "addr_path_da = \"addr_da.txt\"\n",
                 "\n",
-                "res = ezkl.deploy_da_evm(\n",
+                "res = await ezkl.deploy_da_evm(\n",
                 "        addr_path_da,\n",
                 "        input_path,\n",
                 "        settings_path,\n",
@@ -623,7 +623,7 @@
                 "with open(addr_path_da, 'r') as f:\n",
                 "    addr_da = f.read()\n",
                 "\n",
-                "res = ezkl.verify_evm(\n",
+                "res = await ezkl.verify_evm(\n",
                 "    addr,\n",
                 "    proof_path,\n",
                 "    RPC_URL,\n",
@@ -654,4 +654,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 2
-}
+}

examples/notebooks/data_attest_kzg_vis.ipynb

@@ -0,0 +1,604 @@
+{
+    "cells": [
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "# data-attest-kzg-vis\n",
+                "\n",
+                "Here's an example leveraging EZKL whereby the inputs to the model are read and attested to from an on-chain source and the params and outputs are committed to using kzg-commitments. \n",
+                "\n",
+                "In this setup:\n",
+                "- the inputs and outputs are publicly known to the prover and verifier\n",
+                "- the on chain inputs will be fetched and then fed directly into the circuit\n",
+                "- the quantization of the on-chain inputs happens within the evm and is replicated at proving time \n",
+                "- The kzg commitment to the params and inputs will be read from the proof and checked to make sure it matches the expected commitment stored on-chain.\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "First we import the necessary dependencies and set up logging to be as informative as possible. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# check if notebook is in colab\n",
+                "try:\n",
+                "    # install ezkl\n",
+                "    import google.colab\n",
+                "    import subprocess\n",
+                "    import sys\n",
+                "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"ezkl\"])\n",
+                "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"onnx\"])\n",
+                "\n",
+                "# rely on local installation of ezkl if the notebook is not in colab\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "\n",
+                "from torch import nn\n",
+                "import ezkl\n",
+                "import os\n",
+                "import json\n",
+                "import logging\n",
+                "\n",
+                "# uncomment for more descriptive logging \n",
+                "FORMAT = '%(levelname)s %(name)s %(asctime)-15s %(filename)s:%(lineno)d %(message)s'\n",
+                "logging.basicConfig(format=FORMAT)\n",
+                "logging.getLogger().setLevel(logging.DEBUG)\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "Now we define our model. It is a very simple PyTorch model that has just one layer, an average pooling 2D layer. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import torch\n",
+                "# Defines the model\n",
+                "\n",
+                "class MyModel(nn.Module):\n",
+                "    def __init__(self):\n",
+                "        super(MyModel, self).__init__()\n",
+                "        self.layer = nn.AvgPool2d(2, 1, (1, 1))\n",
+                "\n",
+                "    def forward(self, x):\n",
+                "        return self.layer(x)[0]\n",
+                "\n",
+                "\n",
+                "circuit = MyModel()\n",
+                "\n",
+                "# this is where you'd train your model"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "We omit training for purposes of this demonstration. We've marked where training would happen in the cell above. \n",
+                "Now we export the model to onnx and create a corresponding (randomly generated) input. This input data will eventually be stored on chain and read from according to the call_data field in the graph input.\n",
+                "\n",
+                "You can replace the random `x` with real data if you so wish. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "x = 0.1*torch.rand(1,*[3, 2, 2], requires_grad=True)\n",
+                "\n",
+                "# Flips the neural net into inference mode\n",
+                "circuit.eval()\n",
+                "\n",
+                "    # Export the model\n",
+                "torch.onnx.export(circuit,               # model being run\n",
+                "                      x,                   # model input (or a tuple for multiple inputs)\n",
+                "                      \"network.onnx\",            # where to save the model (can be a file or file-like object)\n",
+                "                      export_params=True,        # store the trained parameter weights inside the model file\n",
+                "                      opset_version=10,          # the ONNX version to export the model to\n",
+                "                      do_constant_folding=True,  # whether to execute constant folding for optimization\n",
+                "                      input_names = ['input'],   # the model's input names\n",
+                "                      output_names = ['output'], # the model's output names\n",
+                "                      dynamic_axes={'input' : {0 : 'batch_size'},    # variable length axes\n",
+                "                                    'output' : {0 : 'batch_size'}})\n",
+                "\n",
+                "data_array = ((x).detach().numpy()).reshape([-1]).tolist()\n",
+                "\n",
+                "data = dict(input_data = [data_array])\n",
+                "\n",
+                "    # Serialize data into file:\n",
+                "json.dump(data, open(\"input.json\", 'w' ))\n",
+                "\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "We now define a function that will create a new anvil instance which we will deploy our test contract too. This contract will contain in its storage the data that we will read from and attest to. In production you would not need to set up a local anvil instance. Instead you would replace RPC_URL with the actual RPC endpoint of the chain you are deploying your verifiers too, reading from the data on said chain."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import subprocess\n",
+                "import time\n",
+                "import threading\n",
+                "\n",
+                "# make sure anvil is running locally\n",
+                "# $ anvil -p 3030\n",
+                "\n",
+                "RPC_URL = \"http://localhost:3030\"\n",
+                "\n",
+                "# Save process globally\n",
+                "anvil_process = None\n",
+                "\n",
+                "def start_anvil():\n",
+                "    global anvil_process\n",
+                "    if anvil_process is None:\n",
+                "        anvil_process = subprocess.Popen([\"anvil\", \"-p\", \"3030\", \"--code-size-limit=41943040\"])\n",
+                "        if anvil_process.returncode is not None:\n",
+                "            raise Exception(\"failed to start anvil process\")\n",
+                "        time.sleep(3)\n",
+                "\n",
+                "def stop_anvil():\n",
+                "    global anvil_process\n",
+                "    if anvil_process is not None:\n",
+                "        anvil_process.terminate()\n",
+                "        anvil_process = None\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "We define our `PyRunArgs` objects which contains the visibility parameters for out model. \n",
+                "- `input_visibility` defines the visibility of the model inputs\n",
+                "- `param_visibility` defines the visibility of the model weights and constants and parameters \n",
+                "- `output_visibility` defines the visibility of the model outputs\n",
+                "\n",
+                "Here we create the following setup:\n",
+                "- `input_visibility`: \"public\"\n",
+                "- `param_visibility`: \"polycommitment\" \n",
+                "- `output_visibility`: \"polycommitment\"\n",
+                "\n",
+                "**Note**:\n",
+                "When we set this to polycommitment, we are saying that the model parameters are committed to using a polynomial commitment scheme. This commitment will be stored on chain as a constant stored in the DA contract, and the proof will contain the commitment to the parameters. The DA verification will then check that the commitment in the proof matches the commitment stored on chain. \n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import ezkl\n",
+                "\n",
+                "model_path = os.path.join('network.onnx')\n",
+                "compiled_model_path = os.path.join('network.compiled')\n",
+                "pk_path = os.path.join('test.pk')\n",
+                "vk_path = os.path.join('test.vk')\n",
+                "settings_path = os.path.join('settings.json')\n",
+                "srs_path = os.path.join('kzg.srs')\n",
+                "data_path = os.path.join('input.json')\n",
+                "\n",
+                "run_args = ezkl.PyRunArgs()\n",
+                "run_args.input_visibility = \"public\"\n",
+                "run_args.param_visibility = \"polycommit\"\n",
+                "run_args.output_visibility = \"polycommit\"\n",
+                "run_args.num_inner_cols = 1\n",
+                "run_args.variables = [(\"batch_size\", 1)]\n",
+                "\n",
+                "\n",
+                "\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "Now we generate a settings file. This file basically instantiates a bunch of parameters that determine their circuit shape, size etc... Because of the way we represent nonlinearities in the circuit (using Halo2's [lookup tables](https://zcash.github.io/halo2/design/proving-system/lookup.html)), it is often best to _calibrate_ this settings file as some data can fall out of range of these lookups.\n",
+                "\n",
+                "You can pass a dataset for calibration that will be representative of real inputs you might find if and when you deploy the prover. Here we create a dummy calibration dataset for demonstration purposes. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "!RUST_LOG=trace\n",
+                "# TODO: Dictionary outputs\n",
+                "res = ezkl.gen_settings(model_path, settings_path, py_run_args=run_args)\n",
+                "assert res == True"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# generate a bunch of dummy calibration data\n",
+                "cal_data = {\n",
+                "    \"input_data\": [(0.1*torch.rand(2, *[3, 2, 2])).flatten().tolist()],\n",
+                "}\n",
+                "\n",
+                "cal_path = os.path.join('val_data.json')\n",
+                "# save as json file\n",
+                "with open(cal_path, \"w\") as f:\n",
+                "    json.dump(cal_data, f)\n",
+                "\n",
+                "res = await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "res = ezkl.compile_circuit(model_path, compiled_model_path, settings_path)\n",
+                "assert res == True"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "The graph input for on chain data sources is formatted completely differently compared to file based data sources.\n",
+                "\n",
+                "- For file data sources, the raw floating point values that eventually get quantized, converted into field elements and stored in `witness.json` to be consumed by the circuit are stored. The output data contains the expected floating point values returned as outputs from running your vanilla pytorch model on the given inputs.\n",
+                "- For on chain data sources, the input_data field contains all the data necessary to read and format the on chain data into something digestable by EZKL (aka field elements :-D). \n",
+                "Here is what the schema for an on-chain data source graph input file should look like:\n",
+                "    \n",
+                "```json\n",
+                "{\n",
+                "  \"input_data\": {\n",
+                "    \"rpc\": \"http://localhost:3030\", // The rpc endpoint of the chain you are deploying your verifier to\n",
+                "    \"calls\": [\n",
+                "      {\n",
+                "        \"call_data\": [\n",
+                "          [\n",
+                "            \"71e5ee5f0000000000000000000000000000000000000000000000000000000000000000\", // The abi encoded call data to a view function that returns a single on-chain data point (we only support uint256 returns for now)\n",
+                "            7 // The number of decimal places of the large uint256 value. This is our way of representing large wei values as floating points on chain, since the evm only natively supports integer values.\n",
+                "          ],\n",
+                "          [\n",
+                "            \"71e5ee5f0000000000000000000000000000000000000000000000000000000000000001\",\n",
+                "            5\n",
+                "          ],\n",
+                "          [\n",
+                "            \"71e5ee5f0000000000000000000000000000000000000000000000000000000000000002\",\n",
+                "            5\n",
+                "          ]\n",
+                "        ],\n",
+                "        \"address\": \"5fbdb2315678afecb367f032d93f642f64180aa3\" // The address of the contract that we are calling to get the data. \n",
+                "      }\n",
+                "    ]\n",
+                "  }\n",
+                "}"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "await ezkl.setup_test_evm_witness(\n",
+                "    data_path,\n",
+                "    compiled_model_path,\n",
+                "    # we write the call data to the same file as the input data\n",
+                "    data_path,\n",
+                "    input_source=ezkl.PyTestDataSource.OnChain,\n",
+                "    output_source=ezkl.PyTestDataSource.File,\n",
+                "    rpc_url=RPC_URL)"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "As we use Halo2 with KZG-commitments we need an SRS string from (preferably) a multi-party trusted setup ceremony. For an overview of the procedures for such a ceremony check out [this page](https://blog.ethereum.org/2023/01/16/announcing-kzg-ceremony). The `get_srs` command retrieves a correctly sized SRS given the calibrated settings file from [here](https://github.com/han0110/halo2-kzg-srs). \n",
+                "\n",
+                "These SRS were generated with [this](https://github.com/privacy-scaling-explorations/perpetualpowersoftau) ceremony. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "res = await ezkl.get_srs( settings_path)\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "We now need to generate the circuit witness. These are the model outputs (and any hashes) that are generated when feeding the previously generated `input.json` through the circuit / model. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "!export RUST_BACKTRACE=1\n",
+                "\n",
+                "witness_path = \"witness.json\"\n",
+                "\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path, vk_path)"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "Here we setup verifying and proving keys for the circuit. As the name suggests the proving key is needed for ... proving and the verifying key is needed for ... verifying. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# HERE WE SETUP THE CIRCUIT PARAMS\n",
+                "# WE GOT KEYS\n",
+                "# WE GOT CIRCUIT PARAMETERS\n",
+                "# EVERYTHING ANYONE HAS EVER NEEDED FOR ZK\n",
+                "res = ezkl.setup(\n",
+                "        compiled_model_path,\n",
+                "        vk_path,\n",
+                "        pk_path,\n",
+                "    )\n",
+                "\n",
+                "assert res == True\n",
+                "assert os.path.isfile(vk_path)\n",
+                "assert os.path.isfile(pk_path)\n",
+                "assert os.path.isfile(settings_path)"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "Now we generate a full proof. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# GENERATE A PROOF\n",
+                "\n",
+                "proof_path = os.path.join('test.pf')\n",
+                "\n",
+                "res = ezkl.prove(\n",
+                "        witness_path,\n",
+                "        compiled_model_path,\n",
+                "        pk_path,\n",
+                "        proof_path,\n",
+                "        \n",
+                "        \"single\",\n",
+                "    )\n",
+                "\n",
+                "print(res)\n",
+                "assert os.path.isfile(proof_path)"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "And verify it as a sanity check. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# VERIFY IT\n",
+                "\n",
+                "res = ezkl.verify(\n",
+                "        proof_path,\n",
+                "        settings_path,\n",
+                "        vk_path,\n",
+                "        \n",
+                "    )\n",
+                "\n",
+                "assert res == True\n",
+                "print(\"verified\")"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "We can now create and then deploy a vanilla evm verifier."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "abi_path = 'test.abi'\n",
+                "sol_code_path = 'test.sol'\n",
+                "\n",
+                "res = await ezkl.create_evm_verifier(\n",
+                "        vk_path,\n",
+                "        \n",
+                "        settings_path,\n",
+                "        sol_code_path,\n",
+                "        abi_path,\n",
+                "    )\n",
+                "assert res == True"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "\n",
+                "addr_path_verifier = \"addr_verifier.txt\"\n",
+                "\n",
+                "res = await ezkl.deploy_evm(\n",
+                "    addr_path_verifier,\n",
+                "    sol_code_path,\n",
+                "    'http://127.0.0.1:3030'\n",
+                ")\n",
+                "\n",
+                "assert res == True"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "When deploying a DA with kzg commitments, we need to make sure to also pass a witness file that contains the commitments to the parameters and inputs. This is because the verifier will need to check that the commitments in the proof match the commitments stored on chain."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "\n",
+                "abi_path = 'test.abi'\n",
+                "sol_code_path = 'test.sol'\n",
+                "input_path = 'input.json'\n",
+                "\n",
+                "res = await ezkl.create_evm_data_attestation(\n",
+                "        input_path,\n",
+                "        settings_path,\n",
+                "        sol_code_path,\n",
+                "        abi_path,\n",
+                "        witness_path = witness_path,\n",
+                "    )"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "Now we can deploy the data attest verifier contract. For security reasons, this binding will only deploy to a local anvil instance, using accounts generated by anvil. \n",
+                "So should only be used for testing purposes."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "addr_path_da = \"addr_da.txt\"\n",
+                "\n",
+                "res = await ezkl.deploy_da_evm(\n",
+                "        addr_path_da,\n",
+                "        input_path,\n",
+                "        settings_path,\n",
+                "        sol_code_path,\n",
+                "        RPC_URL,\n",
+                "    )\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "Call the view only verify method on the contract to verify the proof. Since it is a view function this is safe to use in production since you don't have to pass your private key."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# read the verifier address\n",
+                "addr_verifier = None\n",
+                "with open(addr_path_verifier, 'r') as f:\n",
+                "    addr = f.read()\n",
+                "#read the data attestation address\n",
+                "addr_da = None\n",
+                "with open(addr_path_da, 'r') as f:\n",
+                "    addr_da = f.read()\n",
+                "\n",
+                "res = await ezkl.verify_evm(\n",
+                "    addr,\n",
+                "    proof_path,\n",
+                "    RPC_URL,\n",
+                "    addr_da,\n",
+                ")"
+            ]
+        }
+    ],
+    "metadata": {
+        "kernelspec": {
+            "display_name": "ezkl",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.9.13"
+        },
+        "orig_nbformat": 4
+    },
+    "nbformat": 4,
+    "nbformat_minor": 2
+}

examples/notebooks/decision_tree.ipynb

@@ -150,7 +150,7 @@
                 "res = ezkl.gen_settings(model_path, settings_path)\n",
                 "assert res == True\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True"
             ]
         },
@@ -170,7 +170,7 @@
                 "with open(cal_path, \"w\") as f:\n",
                 "    json.dump(cal_data, f)\n",
                 "\n",
-                "res = ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "res = await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -192,7 +192,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -204,7 +204,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -303,4 +303,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/ezkl_demo.ipynb

@@ -352,14 +352,8 @@
         "# Specify all the files we need\n",
         "\n",
         "model_path = os.path.join('network.onnx')\n",
-        "compiled_model_path = os.path.join('network.ezkl')\n",
-        "pk_path = os.path.join('test.pk')\n",
-        "vk_path = os.path.join('test.vk')\n",
-        "settings_path = os.path.join('settings.json')\n",
-        "\n",
-        "witness_path = os.path.join('witness.json')\n",
         "data_path = os.path.join('input.json')\n",
-        "cal_data_path = os.path.join('cal_data.json')"
+        "cal_data_path = os.path.join('calibration.json')"
       ]
     },
     {
@@ -424,7 +418,7 @@
       "source": [
         "!RUST_LOG=trace\n",
         "# TODO: Dictionary outputs\n",
-        "res = ezkl.gen_settings(model_path, settings_path)\n",
+        "res = ezkl.gen_settings()\n",
         "assert res == True\n",
         "\n"
       ]
@@ -443,7 +437,7 @@
         "\n",
         "# Optimize for resources, we cap logrows at 12 to reduce setup and proving time, at the expense of accuracy\n",
         "# You may want to increase the max logrows if accuracy is a concern\n",
-        "res = ezkl.calibrate_settings(cal_data_path, model_path, settings_path, \"resources\", max_logrows = 12, scales = [2])"
+        "res = await ezkl.calibrate_settings(target = \"resources\", max_logrows = 12, scales = [2])"
       ]
     },
     {
@@ -463,7 +457,7 @@
       },
       "outputs": [],
       "source": [
-        "res = ezkl.compile_circuit(model_path, compiled_model_path, settings_path)\n",
+        "res = ezkl.compile_circuit()\n",
         "assert res == True"
       ]
     },
@@ -484,7 +478,7 @@
       },
       "outputs": [],
       "source": [
-        "res = ezkl.get_srs( settings_path)"
+        "res = await ezkl.get_srs()"
       ]
     },
     {
@@ -504,17 +498,10 @@
       },
       "outputs": [],
       "source": [
-        "res = ezkl.setup(\n",
-        "        compiled_model_path,\n",
-        "        vk_path,\n",
-        "        pk_path,\n",
-        "    )\n",
+        "res = ezkl.setup()\n",
         "\n",
         "\n",
-        "assert res == True\n",
-        "assert os.path.isfile(vk_path)\n",
-        "assert os.path.isfile(pk_path)\n",
-        "assert os.path.isfile(settings_path)"
+        "assert res == True"
       ]
     },
     {
@@ -539,7 +526,7 @@
         "# now generate the witness file\n",
         "witness_path = os.path.join('witness.json')\n",
         "\n",
-        "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+        "res = await ezkl.gen_witness()\n",
         "assert os.path.isfile(witness_path)"
       ]
     },
@@ -559,13 +546,7 @@
         "\n",
         "proof_path = os.path.join('proof.json')\n",
         "\n",
-        "proof = ezkl.prove(\n",
-        "        witness_path,\n",
-        "        compiled_model_path,\n",
-        "        pk_path,\n",
-        "        proof_path,\n",
-        "        \"single\",\n",
-        "    )\n",
+        "proof = ezkl.prove(proof_type=\"single\", proof_path=proof_path)\n",
         "\n",
         "print(proof)\n",
         "assert os.path.isfile(proof_path)"
@@ -585,11 +566,7 @@
       "source": [
         "# verify our proof\n",
         "\n",
-        "res = ezkl.verify(\n",
-        "        proof_path,\n",
-        "        settings_path,\n",
-        "        vk_path,\n",
-        "    )\n",
+        "res = ezkl.verify()\n",
         "\n",
         "assert res == True\n",
         "print(\"verified\")"
@@ -664,12 +641,9 @@
         "sol_code_path = os.path.join('Verifier.sol')\n",
         "abi_path = os.path.join('Verifier.abi')\n",
         "\n",
-        "res = ezkl.create_evm_verifier(\n",
-        "        vk_path,\n",
-        "        \n",
-        "        settings_path,\n",
-        "        sol_code_path,\n",
-        "        abi_path\n",
+        "res = await ezkl.create_evm_verifier(\n",
+        "        sol_code_path=sol_code_path,\n",
+        "        abi_path=abi_path, \n",
         "    )\n",
         "\n",
         "assert res == True\n",
@@ -757,7 +731,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.15"
+      "version": "3.12.2"
     }
   },
   "nbformat": 4,

examples/notebooks/gcn.ipynb

@@ -467,7 +467,7 @@
       "outputs": [],
       "source": [
         "\n",
-        "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+        "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
         "assert res == True"
       ]
     },
@@ -494,7 +494,7 @@
       "outputs": [],
       "source": [
         "# srs path\n",
-        "res = ezkl.get_srs( settings_path)"
+        "res = await ezkl.get_srs( settings_path)"
       ]
     },
     {
@@ -508,7 +508,7 @@
       "source": [
         "# now generate the witness file\n",
         "\n",
-        "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+        "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
         "assert os.path.isfile(witness_path)"
       ]
     },
@@ -625,4 +625,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 5
-}
+}

examples/notebooks/generalized_inverse.ipynb

@@ -195,7 +195,7 @@
         "json.dump(data, open(cal_path, 'w'))\n",
         "\n",
         "\n",
-        "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+        "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
         "assert res == True\n"
       ]
     },
@@ -222,7 +222,7 @@
       "outputs": [],
       "source": [
         "# srs path\n",
-        "res = ezkl.get_srs( settings_path)"
+        "res = await ezkl.get_srs( settings_path)"
       ]
     },
     {
@@ -236,7 +236,7 @@
       "source": [
         "# now generate the witness file\n",
         "\n",
-        "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+        "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
         "assert os.path.isfile(witness_path)"
       ]
     },

examples/notebooks/gradient_boosted_trees.ipynb

@@ -179,7 +179,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True\n"
             ]
         },
@@ -202,7 +202,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -214,7 +214,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -313,4 +313,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/hashed_vis.ipynb

@@ -241,7 +241,7 @@
                 "with open(cal_path, \"w\") as f:\n",
                 "    json.dump(cal_data, f)\n",
                 "\n",
-                "res = ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "res = await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -270,7 +270,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "res = ezkl.get_srs( settings_path)\n"
+                "res = await ezkl.get_srs( settings_path)\n"
             ]
         },
         {
@@ -291,7 +291,7 @@
                 "\n",
                 "witness_path = \"witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)"
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)"
             ]
         },
         {
@@ -420,7 +420,7 @@
                 "abi_path = 'test.abi'\n",
                 "sol_code_path = 'test.sol'\n",
                 "\n",
-                "res = ezkl.create_evm_verifier(\n",
+                "res = await ezkl.create_evm_verifier(\n",
                 "        vk_path,\n",
                 "        \n",
                 "        settings_path,\n",
@@ -451,7 +451,7 @@
                 "\n",
                 "address_path = os.path.join(\"address.json\")\n",
                 "\n",
-                "res = ezkl.deploy_evm(\n",
+                "res = await ezkl.deploy_evm(\n",
                 "    address_path,\n",
                 "    sol_code_path,\n",
                 "    'http://127.0.0.1:3030'\n",
@@ -472,7 +472,7 @@
                 "# make sure anvil is running locally\n",
                 "# $ anvil -p 3030\n",
                 "\n",
-                "res = ezkl.verify_evm(\n",
+                "res = await ezkl.verify_evm(\n",
                 "    addr,\n",
                 "    proof_path,\n",
                 "    \"http://127.0.0.1:3030\"\n",

examples/notebooks/keras_simple_demo.ipynb

@@ -152,7 +152,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True\n"
             ]
         },
@@ -175,7 +175,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs(settings_path = settings_path)"
+                "res = await ezkl.get_srs(settings_path = settings_path)"
             ]
         },
         {
@@ -188,7 +188,7 @@
                 "# now generate the witness file \n",
                 "witness_path = \"witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -284,4 +284,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/kmeans.ipynb

@@ -155,7 +155,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True\n"
             ]
         },
@@ -178,7 +178,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -190,7 +190,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -289,4 +289,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/kzg_vis.ipynb

@@ -233,7 +233,7 @@
                 "with open(cal_path, \"w\") as f:\n",
                 "    json.dump(cal_data, f)\n",
                 "\n",
-                "res = ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "res = await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -262,7 +262,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "res = ezkl.get_srs( settings_path)\n"
+                "res = await ezkl.get_srs( settings_path)\n"
             ]
         },
         {
@@ -315,7 +315,7 @@
                 "\n",
                 "witness_path = \"witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path, vk_path)\n"
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path, vk_path)\n"
             ]
         },
         {
@@ -429,7 +429,7 @@
                 "abi_path = 'test.abi'\n",
                 "sol_code_path = 'test.sol'\n",
                 "\n",
-                "res = ezkl.create_evm_verifier(\n",
+                "res = await ezkl.create_evm_verifier(\n",
                 "        vk_path,\n",
                 "        \n",
                 "        settings_path,\n",
@@ -460,7 +460,7 @@
                 "\n",
                 "address_path = os.path.join(\"address.json\")\n",
                 "\n",
-                "res = ezkl.deploy_evm(\n",
+                "res = await ezkl.deploy_evm(\n",
                 "    address_path,\n",
                 "    sol_code_path,\n",
                 "    'http://127.0.0.1:3030'\n",
@@ -481,7 +481,7 @@
                 "# make sure anvil is running locally\n",
                 "# $ anvil -p 3030\n",
                 "\n",
-                "res = ezkl.verify_evm(\n",
+                "res = await ezkl.verify_evm(\n",
                 "    addr,\n",
                 "    proof_path,\n",
                 "    \"http://127.0.0.1:3030\"\n",

examples/notebooks/lightgbm.ipynb

@@ -193,7 +193,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True\n"
             ]
         },
@@ -216,7 +216,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -228,7 +228,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -347,4 +347,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/linear_regression.ipynb

@@ -142,7 +142,7 @@
                 "# Serialize data into file:\n",
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True\n"
             ]
         },
@@ -165,7 +165,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -177,7 +177,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -276,4 +276,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/little_transformer.ipynb

@@ -347,7 +347,7 @@
                 "# Serialize data into file:\n",
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True\n"
             ]
         },
@@ -370,7 +370,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -383,7 +383,7 @@
                 "# now generate the witness file \n",
                 "witness_path = \"gan_witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -490,4 +490,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/logistic_regression.ipynb

@@ -0,0 +1,279 @@
+{
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "id": "cf69bb3f-94e6-4dba-92cd-ce08df117d67",
+            "metadata": {},
+            "source": [
+                "## Logistic Regression\n",
+                "\n",
+                "\n",
+                "Sklearn based models are slightly finicky to get into a suitable onnx format. \n",
+                "This notebook showcases how to do so using the `hummingbird-ml` python package for a Logistic Regression model. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "95613ee9",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# check if notebook is in colab\n",
+                "try:\n",
+                "    # install ezkl\n",
+                "    import google.colab\n",
+                "    import subprocess\n",
+                "    import sys\n",
+                "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"ezkl\"])\n",
+                "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"onnx\"])\n",
+                "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"hummingbird-ml\"])\n",
+                "\n",
+                "# rely on local installation of ezkl if the notebook is not in colab\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "import os\n",
+                "import torch\n",
+                "import ezkl\n",
+                "import json\n",
+                "from hummingbird.ml import convert\n",
+                "\n",
+                "\n",
+                "# here we create and (potentially train a model)\n",
+                "\n",
+                "# make sure you have the dependencies required here already installed\n",
+                "import numpy as np\n",
+                "from sklearn.linear_model import LogisticRegression\n",
+                "X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])\n",
+                "# y = 1 * x_0 + 2 * x_1 + 3\n",
+                "y = np.dot(X, np.array([1, 2])) + 3\n",
+                "reg = LogisticRegression().fit(X, y)\n",
+                "reg.score(X, y)\n",
+                "\n",
+                "circuit = convert(reg, \"torch\", X[:1]).model\n",
+                "\n",
+                "\n",
+                "\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "b37637c4",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "model_path = os.path.join('network.onnx')\n",
+                "compiled_model_path = os.path.join('network.compiled')\n",
+                "pk_path = os.path.join('test.pk')\n",
+                "vk_path = os.path.join('test.vk')\n",
+                "settings_path = os.path.join('settings.json')\n",
+                "\n",
+                "witness_path = os.path.join('witness.json')\n",
+                "data_path = os.path.join('input.json')"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "82db373a",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "\n",
+                "\n",
+                "# export to onnx format\n",
+                "# !!!!!!!!!!!!!!!!! This will flash a warning but it is fine !!!!!!!!!!!!!!!!!!!!!\n",
+                "\n",
+                "# Input to the model\n",
+                "shape = X.shape[1:]\n",
+                "x = torch.rand(1, *shape, requires_grad=True)\n",
+                "torch_out = circuit(x)\n",
+                "# Export the model\n",
+                "torch.onnx.export(circuit,               # model being run\n",
+                "                  # model input (or a tuple for multiple inputs)\n",
+                "                  x,\n",
+                "                  # where to save the model (can be a file or file-like object)\n",
+                "                  \"network.onnx\",\n",
+                "                  export_params=True,        # store the trained parameter weights inside the model file\n",
+                "                  opset_version=10,          # the ONNX version to export the model to\n",
+                "                  do_constant_folding=True,  # whether to execute constant folding for optimization\n",
+                "                  input_names=['input'],   # the model's input names\n",
+                "                  output_names=['output'],  # the model's output names\n",
+                "                  dynamic_axes={'input': {0: 'batch_size'},    # variable length axes\n",
+                "                                'output': {0: 'batch_size'}})\n",
+                "\n",
+                "d = ((x).detach().numpy()).reshape([-1]).tolist()\n",
+                "\n",
+                "data = dict(input_shapes=[shape],\n",
+                "            input_data=[d],\n",
+                "            output_data=[((o).detach().numpy()).reshape([-1]).tolist() for o in torch_out])\n",
+                "\n",
+                "# Serialize data into file:\n",
+                "json.dump(data, open(\"input.json\", 'w'))\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "d5e374a2",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "!RUST_LOG=trace\n",
+                "# TODO: Dictionary outputs\n",
+                "res = ezkl.gen_settings(model_path, settings_path)\n",
+                "assert res == True\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "cal_path = os.path.join(\"calibration.json\")\n",
+                "\n",
+                "data_array = (torch.randn(20, *shape).detach().numpy()).reshape([-1]).tolist()\n",
+                "\n",
+                "data = dict(input_data = [data_array])\n",
+                "\n",
+                "# Serialize data into file:\n",
+                "json.dump(data, open(cal_path, 'w'))\n",
+                "\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "assert res == True\n"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "3aa4f090",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "res = ezkl.compile_circuit(model_path, compiled_model_path, settings_path)\n",
+                "assert res == True"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "8b74dcee",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# srs path\n",
+                "res = await ezkl.get_srs( settings_path)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "18c8b7c7",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# now generate the witness file \n",
+                "\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "assert os.path.isfile(witness_path)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "b1c561a8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "\n",
+                "# HERE WE SETUP THE CIRCUIT PARAMS\n",
+                "# WE GOT KEYS\n",
+                "# WE GOT CIRCUIT PARAMETERS\n",
+                "# EVERYTHING ANYONE HAS EVER NEEDED FOR ZK\n",
+                "\n",
+                "\n",
+                "\n",
+                "res = ezkl.setup(\n",
+                "        compiled_model_path,\n",
+                "        vk_path,\n",
+                "        pk_path,\n",
+                "        \n",
+                "    )\n",
+                "\n",
+                "assert res == True\n",
+                "assert os.path.isfile(vk_path)\n",
+                "assert os.path.isfile(pk_path)\n",
+                "assert os.path.isfile(settings_path)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "c384cbc8",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# GENERATE A PROOF\n",
+                "\n",
+                "\n",
+                "proof_path = os.path.join('test.pf')\n",
+                "\n",
+                "res = ezkl.prove(\n",
+                "        witness_path,\n",
+                "        compiled_model_path,\n",
+                "        pk_path,\n",
+                "        proof_path,\n",
+                "        \n",
+                "        \"single\",\n",
+                "    )\n",
+                "\n",
+                "print(res)\n",
+                "assert os.path.isfile(proof_path)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "id": "76f00d41",
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# VERIFY IT\n",
+                "\n",
+                "res = ezkl.verify(\n",
+                "        proof_path,\n",
+                "        settings_path,\n",
+                "        vk_path,\n",
+                "        \n",
+                "    )\n",
+                "\n",
+                "assert res == True\n",
+                "print(\"verified\")"
+            ]
+        }
+    ],
+    "metadata": {
+        "kernelspec": {
+            "display_name": "Python 3 (ipykernel)",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.12.2"
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 5
+}

examples/notebooks/lstm.ipynb

@@ -139,7 +139,7 @@
                 "res = ezkl.gen_settings(model_path, settings_path, py_run_args=run_args)\n",
                 "assert res == True\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True\n"
             ]
         },
@@ -180,7 +180,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -193,7 +193,7 @@
                 "# now generate the witness file \n",
                 "witness_path = \"lstmwitness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -300,4 +300,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/mean_postgres.ipynb

@@ -91,11 +91,14 @@
         "os.system(\"echo shovel is now installed. starting:\")\n",
         "\n",
         "command = [\"./shovel\", \"-config\", \"config.json\"]\n",
-        "subprocess.Popen(command)\n",
+        "proc = subprocess.Popen(command)\n",
         "\n",
         "os.system(\"echo shovel started.\")\n",
         "\n",
-        "time.sleep(5)\n",
+        "time.sleep(10)\n",
+        "\n",
+        "# after we've fetched some data -- kill the process\n",
+        "proc.terminate()\n",
         "\n"
       ]
     },
@@ -310,7 +313,7 @@
         "\n",
         "assert res == True\n",
         "\n",
-        "res = ezkl.calibrate_settings(input_filename, onnx_filename, settings_filename, \"resources\")\n",
+        "res = await ezkl.calibrate_settings(input_filename, onnx_filename, settings_filename, \"resources\")\n",
         "\n",
         "assert res == True"
       ]
@@ -387,7 +390,7 @@
         "witness_path = \"witness.json\"\n",
         "\n",
         "# generate the witness\n",
-        "res = ezkl.gen_witness(\n",
+        "res = await ezkl.gen_witness(\n",
         "        input_filename,\n",
         "        compiled_filename,\n",
         "        witness_path\n",
@@ -425,16 +428,6 @@
         "assert os.path.isfile(proof_path)\n",
         "\n"
       ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "# kill all shovel process \n",
-        "os.system(\"pkill -f shovel\")"
-      ]
     }
   ],
   "metadata": {

examples/notebooks/mnist_classifier.ipynb

@@ -323,7 +323,7 @@
         "res = ezkl.gen_settings(model_path, settings_path, py_run_args=run_args)\n",
         "assert res == True\n",
         "\n",
-        "res = ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales=[2,7])\n",
+        "res = await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales=[2,7])\n",
         "assert res == True"
       ]
     },
@@ -348,7 +348,7 @@
       "outputs": [],
       "source": [
         "# srs path\n",
-        "res = ezkl.get_srs(settings_path)"
+        "res = await ezkl.get_srs(settings_path)"
       ]
     },
     {
@@ -362,7 +362,7 @@
         "# now generate the witness file\n",
         "witness_path = \"witness.json\"\n",
         "\n",
-        "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+        "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
         "assert os.path.isfile(witness_path)"
       ]
     },
@@ -469,7 +469,7 @@
         "abi_path = 'test.abi'\n",
         "sol_code_path = 'test_1.sol'\n",
         "\n",
-        "res = ezkl.create_evm_verifier(\n",
+        "res = await ezkl.create_evm_verifier(\n",
         "        vk_path,\n",
         "        settings_path,\n",
         "        sol_code_path,\n",
@@ -502,7 +502,7 @@
         "\n",
         "address_path = os.path.join(\"address.json\")\n",
         "\n",
-        "res = ezkl.deploy_evm(\n",
+        "res = await ezkl.deploy_evm(\n",
         "    address_path,\n",
         "    sol_code_path,\n",
         "    'http://127.0.0.1:3030'\n",
@@ -525,7 +525,7 @@
         "# make sure anvil is running locally\n",
         "# $ anvil -p 3030\n",
         "\n",
-        "res = ezkl.verify_evm(\n",
+        "res = await ezkl.verify_evm(\n",
         "    addr,\n",
         "    proof_path,\n",
         "    \"http://127.0.0.1:3030\"\n",
@@ -558,4 +558,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}

examples/notebooks/mnist_gan.ipynb

@@ -289,7 +289,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales=[0,6])"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales=[0,6])"
             ]
         },
         {
@@ -309,7 +309,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -321,7 +321,7 @@
                 "# now generate the witness file \n",
                 "witness_path = \"gan_witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },

examples/notebooks/mnist_vae.ipynb

@@ -215,7 +215,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -235,7 +235,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -247,7 +247,7 @@
                 "# now generate the witness file\n",
                 "witness_path = \"ae_witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -451,7 +451,7 @@
                 "res = ezkl.gen_settings(model_path, settings_path)\n",
                 "assert res == True\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True\n",
                 "print(\"verified\")"
             ]
@@ -473,7 +473,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -485,7 +485,7 @@
                 "# now generate the witness file \n",
                 "witness_path = \"vae_witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },

examples/notebooks/nbeats_timeseries_forecasting.ipynb

@@ -845,7 +845,7 @@
         "res = ezkl.gen_settings(model_path, settings_path)\n",
         "assert res == True\n",
         "\n",
-        "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\", max_logrows = 20, scales = [3])\n",
+        "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\", max_logrows = 20, scales = [3])\n",
         "assert res == True"
       ]
     },
@@ -870,7 +870,7 @@
       "outputs": [],
       "source": [
         "# srs path\n",
-        "res = ezkl.get_srs( settings_path)"
+        "res = await ezkl.get_srs( settings_path)"
       ]
     },
     {
@@ -881,7 +881,7 @@
       },
       "outputs": [],
       "source": [
-        "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+        "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
         "assert os.path.isfile(witness_path)"
       ]
     },
@@ -993,4 +993,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}

examples/notebooks/proof_splitting.ipynb

@@ -232,7 +232,7 @@
                 "run_args.param_visibility = \"fixed\"\n",
                 "run_args.output_visibility = \"public\"\n",
                 "run_args.input_scale = 2\n",
-                "run_args.logrows = 8\n",
+                "run_args.logrows = 15\n",
                 "\n",
                 "ezkl.get_srs(logrows=run_args.logrows, commitment=ezkl.PyCommitments.KZG)"
             ]
@@ -261,7 +261,7 @@
             "source": [
                 "# iterate over each submodel gen-settings, compile circuit and setup zkSNARK\n",
                 "\n",
-                "def setup(i):\n",
+                "async def setup(i):\n",
                 "    # file names\n",
                 "    model_path = os.path.join('network_split_'+str(i)+'.onnx')\n",
                 "    settings_path = os.path.join('settings_split_'+str(i)+'.json')\n",
@@ -282,7 +282,7 @@
                 "\n",
                 "    # generate settings for the current model\n",
                 "    res = ezkl.gen_settings(model_path, settings_path, py_run_args=run_args)\n",
-                "    res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\", scales=[run_args.input_scale], max_logrows=run_args.logrows)\n",
+                "    res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\", scales=[run_args.input_scale], max_logrows=run_args.logrows)\n",
                 "    assert res == True\n",
                 "\n",
                 "    # load settings and print them to the console\n",
@@ -303,11 +303,11 @@
                 "    assert os.path.isfile(vk_path)\n",
                 "    assert os.path.isfile(pk_path)\n",
                 "\n",
-                "    res = ezkl.gen_witness(data_path, compiled_model_path, witness_path, vk_path)\n",
+                "    res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path, vk_path)\n",
                 "    run_args.input_scale = settings[\"model_output_scales\"][0]\n",
                 "\n",
                 "for i in range(2):\n",
-                "    setup(i)\n"
+                "    await setup(i)\n"
             ]
         },
         {
@@ -404,7 +404,7 @@
                 "run_args.output_visibility = \"polycommit\"\n",
                 "run_args.variables = [(\"batch_size\", 1)]\n",
                 "run_args.input_scale = 2\n",
-                "run_args.logrows = 8\n"
+                "run_args.logrows = 15\n"
             ]
         },
         {
@@ -414,7 +414,7 @@
             "outputs": [],
             "source": [
                 "for i in range(2):\n",
-                "    setup(i)"
+                "    await setup(i)"
             ]
         },
         {
@@ -466,7 +466,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.15"
+            "version": "3.12.5"
         },
         "orig_nbformat": 4
     },

examples/notebooks/random_forest.ipynb

@@ -174,7 +174,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -196,7 +196,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -208,7 +208,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },

examples/notebooks/set_membership.ipynb

@@ -215,7 +215,7 @@
       "outputs": [],
       "source": [
         "# srs path\n",
-        "res = ezkl.get_srs( settings_path)"
+        "res = await ezkl.get_srs( settings_path)"
       ]
     },
     {
@@ -229,7 +229,7 @@
       "source": [
         "# now generate the witness file\n",
         "\n",
-        "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+        "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
         "assert os.path.isfile(witness_path)"
       ]
     },
@@ -265,7 +265,7 @@
         "    # Serialize data into file:\n",
         "json.dump( data, open(data_path_faulty, 'w' ))\n",
         "\n",
-        "res = ezkl.gen_witness(data_path_faulty, compiled_model_path, witness_path_faulty)\n",
+        "res = await ezkl.gen_witness(data_path_faulty, compiled_model_path, witness_path_faulty)\n",
         "assert os.path.isfile(witness_path_faulty)"
       ]
     },
@@ -310,7 +310,7 @@
         "# Serialize data into file:\n",
         "json.dump( data, open(data_path_truthy, 'w' ))\n",
         "\n",
-        "res = ezkl.gen_witness(data_path_truthy, compiled_model_path, witness_path_truthy)\n",
+        "res = await ezkl.gen_witness(data_path_truthy, compiled_model_path, witness_path_truthy)\n",
         "assert os.path.isfile(witness_path_truthy)"
       ]
     },
@@ -482,7 +482,7 @@
       "source": [
         "import pytest\n",
         "def test_verification():\n",
-        "    with pytest.raises(RuntimeError, match='Failed to run verify: The constraint system is not satisfied'):\n",
+        "    with pytest.raises(RuntimeError, match='Failed to run verify: \\\\[halo2\\\\] The constraint system is not satisfied'):\n",
         "        ezkl.verify(\n",
         "            proof_path_faulty,\n",
         "            settings_path,\n",
@@ -514,7 +514,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.15"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,

examples/notebooks/simple_demo_aggregated_proofs.ipynb

@@ -193,7 +193,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -205,7 +205,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -290,7 +290,7 @@
             "source": [
                 "# Generate a larger SRS. This is needed for the aggregated proof\n",
                 "\n",
-                "res = ezkl.get_srs(settings_path=None, logrows=21, commitment=ezkl.PyCommitments.KZG)"
+                "res = await ezkl.get_srs(settings_path=None, logrows=21, commitment=ezkl.PyCommitments.KZG)"
             ]
         },
         {
@@ -374,7 +374,7 @@
                 "sol_code_path = os.path.join(\"Verifier.sol\")\n",
                 "abi_path = os.path.join(\"Verifier_ABI.json\")\n",
                 "\n",
-                "res = ezkl.create_evm_verifier_aggr(\n",
+                "res = await ezkl.create_evm_verifier_aggr(\n",
                 "    [settings_path],\n",
                 "    aggregate_vk_path,\n",
                 "    sol_code_path,\n",
@@ -404,4 +404,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/simple_demo_all_public.ipynb

@@ -157,6 +157,7 @@
         {
             "cell_type": "code",
             "execution_count": null,
+            "id": "b78d3cbf",
             "metadata": {},
             "outputs": [],
             "source": [
@@ -170,7 +171,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -204,7 +205,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -298,7 +299,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.15"
+            "version": "3.12.3"
         }
     },
     "nbformat": 4,

examples/notebooks/simple_demo_public_input_output.ipynb

@@ -169,7 +169,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -191,7 +191,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -203,7 +203,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },

examples/notebooks/simple_demo_public_network_output.ipynb

@@ -170,7 +170,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -192,7 +192,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -204,7 +204,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },

examples/notebooks/sklearn_mlp.ipynb

@@ -149,7 +149,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -171,7 +171,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -183,7 +183,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -282,4 +282,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/solvency.ipynb

@@ -250,7 +250,7 @@
       "outputs": [],
       "source": [
         "# srs path\n",
-        "res = ezkl.get_srs( settings_path)"
+        "res = await ezkl.get_srs( settings_path)"
       ]
     },
     {
@@ -297,7 +297,7 @@
         "\n",
         "witness_path = \"witness.json\"\n",
         "\n",
-        "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path, vk_path)\n",
+        "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path, vk_path)\n",
         "assert os.path.isfile(witness_path)\n",
         "\n",
         "# 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",
@@ -411,7 +411,7 @@
       "source": [
         "# now generate the witness file\n",
         "\n",
-        "res = ezkl.gen_witness(data_path_faulty, compiled_model_path, witness_path, vk_path)\n",
+        "res = await ezkl.gen_witness(data_path_faulty, compiled_model_path, witness_path, vk_path)\n",
         "assert os.path.isfile(witness_path)\n",
         "\n",
         "# 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",
@@ -478,12 +478,11 @@
         "import pytest\n",
         "\n",
         "def test_verification():\n",
-        "    with pytest.raises(RuntimeError, match='Failed to run verify: The constraint system is not satisfied'):\n",
+        "    with pytest.raises(RuntimeError, match='Failed to run verify: \\\\[halo2\\\\] The constraint system is not satisfied'):\n",
         "        ezkl.verify(\n",
         "            proof_path,\n",
         "            settings_path,\n",
         "            vk_path,\n",
-        "            \n",
         "        )\n",
         "\n",
         "# Run the test function\n",
@@ -510,9 +509,9 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.15"
+      "version": "3.12.3"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 5
-}
+}

examples/notebooks/stacked_regression.ipynb

@@ -167,7 +167,7 @@
                 "res = ezkl.gen_settings(model_path, settings_path)\n",
                 "assert res == True\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True"
             ]
         },
@@ -187,7 +187,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -209,7 +209,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -221,7 +221,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -320,4 +320,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/notebooks/svm.ipynb

@@ -39,7 +39,7 @@
                 "import json\n",
                 "import numpy as np\n",
                 "from sklearn.svm import SVC\n",
-                "import sk2torch\n",
+                "from hummingbird.ml import convert\n",
                 "import torch\n",
                 "import ezkl\n",
                 "import os\n",
@@ -59,11 +59,11 @@
                 "# Train an SVM on the data and wrap it in PyTorch.\n",
                 "sk_model = SVC(probability=True)\n",
                 "sk_model.fit(xs, ys)\n",
-                "model = sk2torch.wrap(sk_model)\n",
-                "\n",
+                "model = convert(sk_model, \"torch\").model\n",
                 "\n",
                 "\n",
                 "\n",
+                "model\n",
                 "\n"
             ]
         },
@@ -84,33 +84,6 @@
                 "data_path = os.path.join('input.json')"
             ]
         },
-        {
-            "cell_type": "code",
-            "execution_count": null,
-            "id": "7f0ca328",
-            "metadata": {},
-            "outputs": [],
-            "source": [
-                "import matplotlib.pyplot as plt\n",
-                "# Create a coordinate grid to compute a vector field on.\n",
-                "spaced = np.linspace(-2, 2, num=25)\n",
-                "grid_xs = torch.tensor([[x, y] for x in spaced for y in spaced], requires_grad=True)\n",
-                "\n",
-                "\n",
-                "# Compute the gradients of the SVM output.\n",
-                "outputs = model.predict_proba(grid_xs)[:, 1]\n",
-                "(input_grads,) = torch.autograd.grad(outputs.sum(), (grid_xs,))\n",
-                "\n",
-                "\n",
-                "# Create a quiver plot of the vector field.\n",
-                "plt.quiver(\n",
-                "    grid_xs[:, 0].detach().numpy(),\n",
-                "    grid_xs[:, 1].detach().numpy(),\n",
-                "    input_grads[:, 0].detach().numpy(),\n",
-                "    input_grads[:, 1].detach().numpy(),\n",
-                ")\n"
-            ]
-        },
         {
             "cell_type": "code",
             "execution_count": null,
@@ -119,14 +92,14 @@
             "outputs": [],
             "source": [
                 "\n",
-                "\n",
+                "spaced = np.linspace(-2, 2, num=25)\n",
+                "grid_xs = torch.tensor([[x, y] for x in spaced for y in spaced], requires_grad=True)\n",
                 "# export to onnx format\n",
                 "# !!!!!!!!!!!!!!!!! This will flash a warning but it is fine !!!!!!!!!!!!!!!!!!!!!\n",
                 "\n",
                 "# Input to the model\n",
                 "shape = xs.shape[1:]\n",
                 "x = grid_xs[0:1]\n",
-                "torch_out = model.predict(x)\n",
                 "# Export the model\n",
                 "torch.onnx.export(model,               # model being run\n",
                 "                  # model input (or a tuple for multiple inputs)\n",
@@ -143,9 +116,7 @@
                 "\n",
                 "d = ((x).detach().numpy()).reshape([-1]).tolist()\n",
                 "\n",
-                "data = dict(input_shapes=[shape],\n",
-                "            input_data=[d],\n",
-                "            output_data=[o.reshape([-1]).tolist() for o in torch_out])\n",
+                "data = dict(input_data=[d])\n",
                 "\n",
                 "# Serialize data into file:\n",
                 "json.dump(data, open(\"input.json\", 'w'))\n"
@@ -167,6 +138,7 @@
         {
             "cell_type": "code",
             "execution_count": null,
+            "id": "0bee4d7f",
             "metadata": {},
             "outputs": [],
             "source": [
@@ -180,7 +152,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -202,7 +174,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -214,13 +186,13 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
         {
             "cell_type": "code",
-            "execution_count": 10,
+            "execution_count": null,
             "id": "b1c561a8",
             "metadata": {},
             "outputs": [],
@@ -420,7 +392,7 @@
                 "res = ezkl.gen_settings(model_path, settings_path)\n",
                 "assert res == True\n",
                 "\n",
-                "res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
+                "res = await ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\")\n",
                 "assert res == True"
             ]
         }
@@ -441,7 +413,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.15"
+            "version": "3.12.3"
         }
     },
     "nbformat": 4,

examples/notebooks/tictactoe_autoencoder.ipynb

@@ -13,7 +13,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 1,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -57,7 +57,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 2,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -119,7 +119,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 3,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -163,7 +163,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 4,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -217,7 +217,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 6,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -637,7 +637,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales = [11])"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales = [11])"
             ]
         },
         {
@@ -646,7 +646,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "ezkl.get_srs( settings_path)"
+                "await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -683,7 +683,7 @@
                 "    data = json.load(f)\n",
                 "    print(len(data['input_data'][0]))\n",
                 "\n",
-                "ezkl.gen_witness(data_path, compiled_model_path, witness_path)"
+                "await ezkl.gen_witness(data_path, compiled_model_path, witness_path)"
             ]
         },
         {

examples/notebooks/tictactoe_binary_classification.ipynb

@@ -525,7 +525,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales = [4])"
+                "await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales = [4])"
             ]
         },
         {
@@ -572,7 +572,7 @@
                 "    data = json.load(f)\n",
                 "    print(len(data['input_data'][0]))\n",
                 "\n",
-                "ezkl.gen_witness(data_path, compiled_model_path, witness_path)"
+                "await ezkl.gen_witness(data_path, compiled_model_path, witness_path)"
             ]
         },
         {

examples/notebooks/variance.ipynb

@@ -24,7 +24,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 1,
       "metadata": {
         "id": "9Byiv2Nc2MsK"
       },
@@ -49,7 +49,11 @@
         "import pandas as pd\n",
         "import requests\n",
         "import json\n",
-        "import os"
+        "import os\n",
+        "\n",
+        "import logging\n",
+        "\n",
+        "logging.basicConfig(level=logging.INFO)"
       ]
     },
     {
@@ -63,7 +67,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 2,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -71,7 +75,15 @@
         "id": "x1vl9ZXF3EEW",
         "outputId": "bda21d02-fe5f-4fb2-8106-f51a8e2e67aa"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "cpu\n"
+          ]
+        }
+      ],
       "source": [
         "from torch import nn\n",
         "import torch\n",
@@ -133,7 +145,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 3,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -141,7 +153,18 @@
         "id": "6RAMplxk5xPk",
         "outputId": "bd2158fe-0c00-44fd-e632-6a3f70cdb7c9"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "1715422870\n",
+            "1714818070\n",
+            "https://api.coingecko.com/api/v3/coins/ethereum/market_chart/range?vs_currency=usd&from=1714818070&to=1715422870\n",
+            "<Response [200]>\n"
+          ]
+        }
+      ],
       "source": [
         "\n",
         "def get_url(coin, currency, start, end):\n",
@@ -174,7 +197,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 4,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -183,7 +206,115 @@
         "id": "WSj1Uxln65vf",
         "outputId": "51422d71-9680-4b51-c4df-e400d20f988b"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>time</th>\n",
+              "      <th>prices</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1714820485367</td>\n",
+              "      <td>3146.785806</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>1714824033868</td>\n",
+              "      <td>3127.968728</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>1714828058243</td>\n",
+              "      <td>3156.141681</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>1714831650751</td>\n",
+              "      <td>3124.834064</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>1714834972229</td>\n",
+              "      <td>3133.115333</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>163</th>\n",
+              "      <td>1715407579346</td>\n",
+              "      <td>2918.049749</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>164</th>\n",
+              "      <td>1715411090715</td>\n",
+              "      <td>2920.330834</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>165</th>\n",
+              "      <td>1715414554830</td>\n",
+              "      <td>2923.986611</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>166</th>\n",
+              "      <td>1715418419843</td>\n",
+              "      <td>2910.537671</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>167</th>\n",
+              "      <td>1715421675338</td>\n",
+              "      <td>2907.702307</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>168 rows × 2 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "              time       prices\n",
+              "0    1714820485367  3146.785806\n",
+              "1    1714824033868  3127.968728\n",
+              "2    1714828058243  3156.141681\n",
+              "3    1714831650751  3124.834064\n",
+              "4    1714834972229  3133.115333\n",
+              "..             ...          ...\n",
+              "163  1715407579346  2918.049749\n",
+              "164  1715411090715  2920.330834\n",
+              "165  1715414554830  2923.986611\n",
+              "166  1715418419843  2910.537671\n",
+              "167  1715421675338  2907.702307\n",
+              "\n",
+              "[168 rows x 2 columns]"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "df = pd.DataFrame(new_data)\n",
         "df\n"
@@ -200,7 +331,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 5,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -217,7 +348,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 6,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -225,7 +356,98 @@
         "id": "4MmE9SX66_Il",
         "outputId": "16403639-66a4-4280-ac7f-6966b75de5a3"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "INFO:ezkl.execute:SRS already exists at that path\n",
+            "INFO:ezkl.execute:num calibration batches: 1\n",
+            "INFO:ezkl.execute:read 16777476 bytes from file (vector of len = 16777476)\n",
+            "WARNING:ezkl.execute:\n",
+            "\n",
+            " <------------- Numerical Fidelity Report (input_scale: 4, param_scale: 4, scale_input_multiplier: 10) ------------->\n",
+            "\n",
+            "+------------+--------------+-----------+-----------+----------------+------------------+---------------+---------------+--------------------+--------------------+------------------------+\n",
+            "| mean_error | median_error | max_error | min_error | mean_abs_error | median_abs_error | max_abs_error | min_abs_error | mean_squared_error | mean_percent_error | mean_abs_percent_error |\n",
+            "+------------+--------------+-----------+-----------+----------------+------------------+---------------+---------------+--------------------+--------------------+------------------------+\n",
+            "| -727.9929  | -727.9929    | -727.9929 | -727.9929 | 727.9929       | 727.9929         | 727.9929      | 727.9929      | 529973.7           | -0.24999964        | 0.24999964             |\n",
+            "+------------+--------------+-----------+-----------+----------------+------------------+---------------+---------------+--------------------+--------------------+------------------------+\n",
+            "\n",
+            "\n",
+            "INFO:ezkl.execute:file hash: 41509f380362a8d14401c5ae92073154922fe23e45459ce6f696f58607655db7\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{\n",
+            "  \"run_args\": {\n",
+            "    \"tolerance\": {\n",
+            "      \"val\": 0.0,\n",
+            "      \"scale\": 1.0\n",
+            "    },\n",
+            "    \"input_scale\": 4,\n",
+            "    \"param_scale\": 4,\n",
+            "    \"scale_rebase_multiplier\": 10,\n",
+            "    \"lookup_range\": [\n",
+            "      0,\n",
+            "      0\n",
+            "    ],\n",
+            "    \"logrows\": 6,\n",
+            "    \"num_inner_cols\": 2,\n",
+            "    \"variables\": [\n",
+            "      [\n",
+            "        \"batch_size\",\n",
+            "        1\n",
+            "      ]\n",
+            "    ],\n",
+            "    \"input_visibility\": \"Private\",\n",
+            "    \"output_visibility\": \"Public\",\n",
+            "    \"param_visibility\": \"Private\",\n",
+            "    \"div_rebasing\": false,\n",
+            "    \"rebase_frac_zero_constants\": false,\n",
+            "    \"check_mode\": \"UNSAFE\",\n",
+            "    \"commitment\": \"KZG\"\n",
+            "  },\n",
+            "  \"num_rows\": 21,\n",
+            "  \"total_assignments\": 42,\n",
+            "  \"total_const_size\": 0,\n",
+            "  \"total_dynamic_col_size\": 0,\n",
+            "  \"num_dynamic_lookups\": 0,\n",
+            "  \"num_shuffles\": 0,\n",
+            "  \"total_shuffle_col_size\": 0,\n",
+            "  \"model_instance_shapes\": [\n",
+            "    [\n",
+            "      1\n",
+            "    ]\n",
+            "  ],\n",
+            "  \"model_output_scales\": [\n",
+            "    8\n",
+            "  ],\n",
+            "  \"model_input_scales\": [\n",
+            "    4\n",
+            "  ],\n",
+            "  \"module_sizes\": {\n",
+            "    \"polycommit\": [],\n",
+            "    \"poseidon\": [\n",
+            "      0,\n",
+            "      [\n",
+            "        0\n",
+            "      ]\n",
+            "    ]\n",
+            "  },\n",
+            "  \"required_lookups\": [],\n",
+            "  \"required_range_checks\": [],\n",
+            "  \"check_mode\": \"UNSAFE\",\n",
+            "  \"version\": \"0.0.0\",\n",
+            "  \"num_blinding_factors\": null,\n",
+            "  \"timestamp\": 1715422871248\n",
+            "}\n"
+          ]
+        }
+      ],
       "source": [
         "# generate settings\n",
         "onnx_filename = os.path.join('lol.onnx')\n",
@@ -236,9 +458,9 @@
         "\n",
         "\n",
         "ezkl.gen_settings(onnx_filename, settings_filename)\n",
-        "ezkl.calibrate_settings(\n",
+        "await ezkl.calibrate_settings(\n",
         "    input_filename, onnx_filename, settings_filename, \"resources\", scales = [4])\n",
-        "res = ezkl.get_srs(settings_filename)\n",
+        "res = await ezkl.get_srs(settings_filename)\n",
         "ezkl.compile_circuit(onnx_filename, compiled_filename, settings_filename)\n",
         "\n",
         "# show the settings.json\n",
@@ -259,7 +481,24 @@
       "metadata": {
         "id": "fULvvnK7_CMb"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "INFO:ezkl.pfsys.srs:loading srs from \"/Users/dante/.ezkl/srs/kzg6.srs\"\n",
+            "INFO:ezkl.execute:downsizing params to 6 logrows\n",
+            "INFO:ezkl.graph.model:model layout...\n",
+            "INFO:ezkl.pfsys:VK took 0.8\n",
+            "INFO:ezkl.graph.model:model layout...\n",
+            "INFO:ezkl.pfsys:PK took 0.2\n",
+            "INFO:ezkl.pfsys:saving verification key 💾\n",
+            "INFO:ezkl.pfsys:done saving verification key ✅\n",
+            "INFO:ezkl.pfsys:saving proving key 💾\n",
+            "INFO:ezkl.pfsys:done saving proving key ✅\n"
+          ]
+        }
+      ],
       "source": [
         "pk_path = os.path.join('test.pk')\n",
         "vk_path = os.path.join('test.vk')\n",
@@ -281,20 +520,20 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 8,
       "metadata": {},
       "outputs": [],
       "source": [
         "\n",
         "witness_path = \"witness.json\"\n",
         "\n",
-        "res = ezkl.gen_witness(input_filename, compiled_filename, witness_path)\n",
+        "res = await ezkl.gen_witness(input_filename, compiled_filename, witness_path)\n",
         "assert os.path.isfile(witness_path)"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 9,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -302,7 +541,34 @@
         "id": "Oog3j6Kd-Wed",
         "outputId": "5839d0c1-5b43-476e-c2f8-6707de562260"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "INFO:ezkl.pfsys:loading proving key from \"test.pk\"\n",
+            "INFO:ezkl.pfsys:done loading proving key ✅\n",
+            "INFO:ezkl.pfsys.srs:loading srs from \"/Users/dante/.ezkl/srs/kzg6.srs\"\n",
+            "INFO:ezkl.execute:downsizing params to 6 logrows\n",
+            "INFO:ezkl.pfsys:proof started...\n",
+            "INFO:ezkl.graph.model:model layout...\n",
+            "INFO:ezkl.pfsys:proof took 0.15\n",
+            "INFO:ezkl.pfsys.srs:loading srs from \"/Users/dante/.ezkl/srs/kzg6.srs\"\n",
+            "INFO:ezkl.execute:downsizing params to 6 logrows\n",
+            "INFO:ezkl.pfsys:loading verification key from \"test.vk\"\n",
+            "INFO:ezkl.pfsys:done loading verification key ✅\n",
+            "INFO:ezkl.execute:verify took 0.2\n",
+            "INFO:ezkl.execute:verified: true\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "verified\n"
+          ]
+        }
+      ],
       "source": [
         "# prove the zk circuit\n",
         "# GENERATE A PROOF\n",
@@ -351,7 +617,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 10,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -360,7 +626,26 @@
         "id": "fodkNgwS70FM",
         "outputId": "827b5efd-f74f-44de-c114-861b3a86daf2"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "INFO:ezkl.pfsys.srs:loading srs from \"/Users/dante/.ezkl/srs/kzg6.srs\"\n",
+            "INFO:ezkl.execute:downsizing params to 6 logrows\n",
+            "INFO:ezkl.pfsys:loading verification key from \"test.vk\"\n",
+            "INFO:ezkl.pfsys:done loading verification key ✅\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "test.vk\n",
+            "settings.json\n"
+          ]
+        }
+      ],
       "source": [
         "# first we need to create evm verifier\n",
         "print(vk_path)\n",
@@ -370,7 +655,7 @@
         "abi_path = 'test.abi'\n",
         "sol_code_path = 'test.sol'\n",
         "\n",
-        "res = ezkl.create_evm_verifier(\n",
+        "res = await ezkl.create_evm_verifier(\n",
         "        vk_path,\n",
         "        settings_filename,\n",
         "        sol_code_path,\n",
@@ -381,9 +666,18 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 11,
       "metadata": {},
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "INFO:ezkl.eth:using chain 31337\n",
+            "INFO:ezkl.execute:Contract deployed at: 0x998abeb3e57409262ae5b751f60747921b33613e\n"
+          ]
+        }
+      ],
       "source": [
         "# Make sure anvil is running locally first\n",
         "# run with $ anvil -p 3030\n",
@@ -391,8 +685,9 @@
         "import json\n",
         "\n",
         "address_path = os.path.join(\"address.json\")\n",
-        "\n",
-        "res = ezkl.deploy_evm(\n",
+        "sol_code_path = 'test.sol'\n",
+        "# await\n",
+        "res = await ezkl.deploy_evm(\n",
         "    address_path,\n",
         "    sol_code_path,\n",
         "    'http://127.0.0.1:3030'\n",
@@ -406,16 +701,26 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 12,
       "metadata": {},
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "INFO:ezkl.eth:using chain 31337\n",
+            "INFO:ezkl.eth:estimated verify gas cost: 399775\n",
+            "INFO:ezkl.execute:Solidity verification result: true\n"
+          ]
+        }
+      ],
       "source": [
         "# read the address from addr_path\n",
         "addr = None\n",
         "with open(address_path, 'r') as f:\n",
         "    addr = f.read()\n",
         "\n",
-        "res = ezkl.verify_evm(\n",
+        "res = await ezkl.verify_evm(\n",
         "    addr,\n",
         "    proof_path,\n",
         "    \"http://127.0.0.1:3030\"\n",
@@ -451,7 +756,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.15"
+      "version": "3.12.2"
     }
   },
   "nbformat": 4,

examples/notebooks/verifier_abi.json

@@ -0,0 +1 @@
+[{"type":"function","name":"verifyProof","inputs":[{"name":"proof","type":"bytes","internalType":"bytes"},{"name":"instances","type":"uint256[]","internalType":"uint256[]"}],"outputs":[{"name":"","type":"bool","internalType":"bool"}],"stateMutability":"nonpayable"}]

examples/notebooks/voice_judge.ipynb

@@ -629,7 +629,7 @@
             "source": [
                 "\n",
                 "\n",
-                "res = ezkl.calibrate_settings(val_data, model_path, settings_path, \"resources\", scales = [4])\n",
+                "res = await ezkl.calibrate_settings(val_data, model_path, settings_path, \"resources\", scales = [4])\n",
                 "assert res == True\n",
                 "print(\"verified\")\n"
             ]
@@ -660,7 +660,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "res = ezkl.get_srs(settings_path)"
+                "res = await ezkl.get_srs(settings_path)"
             ]
         },
         {
@@ -680,7 +680,7 @@
                 "\n",
                 "witness_path = \"witness.json\"\n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -807,7 +807,7 @@
                 "settings_path = os.path.join('settings.json')\n",
                 "\n",
                 "\n",
-                "res = ezkl.create_evm_verifier(\n",
+                "res = await ezkl.create_evm_verifier(\n",
                 "        vk_path,\n",
                 "        \n",
                 "        settings_path,\n",
@@ -847,7 +847,7 @@
                 "\n",
                 "address_path = os.path.join(\"address.json\")\n",
                 "\n",
-                "res = ezkl.deploy_evm(\n",
+                "res = await ezkl.deploy_evm(\n",
                 "    address_path,\n",
                 "    sol_code_path,\n",
                 "    'http://127.0.0.1:3030'\n",
@@ -868,7 +868,7 @@
                 "# make sure anvil is running locally\n",
                 "# $ anvil -p 3030\n",
                 "\n",
-                "res = ezkl.verify_evm(\n",
+                "res = await ezkl.verify_evm(\n",
                 "    addr,\n",
                 "    proof_path,\n",
                 "    \"http://127.0.0.1:3030\"\n",
@@ -905,4 +905,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 2
-}
+}

examples/notebooks/world_rotation.ipynb

@@ -242,6 +242,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "2007dc77",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -257,6 +258,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "ab993958",
    "metadata": {},
    "source": [
     "As we use Halo2 with KZG-commitments we need an SRS string from (preferably) a multi-party trusted setup ceremony. For an overview of the procedures for such a ceremony check out [this page](https://blog.ethereum.org/2023/01/16/announcing-kzg-ceremony). The `get_srs` command retrieves a correctly sized SRS given the calibrated settings file from [here](https://github.com/han0110/halo2-kzg-srs). \n",
@@ -272,7 +274,7 @@
    "outputs": [],
    "source": [
     "# srs path\n",
-    "res = ezkl.get_srs( settings_path)"
+    "res = await ezkl.get_srs( settings_path)"
    ]
   },
   {
@@ -284,12 +286,13 @@
    "source": [
     "# now generate the witness file \n",
     "\n",
-    "witness = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+    "witness = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
     "assert os.path.isfile(witness_path)"
    ]
   },
   {
    "cell_type": "markdown",
+   "id": "ad58432e",
    "metadata": {},
    "source": [
     "Here we setup verifying and proving keys for the circuit. As the name suggests the proving key is needed for ... proving and the verifying key is needed for ... verifying. "
@@ -317,6 +320,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "1746c8d1",
    "metadata": {},
    "source": [
     "We can now create an EVM verifier contract from our circuit. This contract will be deployed to the chain we are using. In this case we are using a local anvil instance."
@@ -325,15 +329,15 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "d1920c0f",
    "metadata": {},
    "outputs": [],
    "source": [
     "abi_path = 'test.abi'\n",
     "sol_code_path = 'test.sol'\n",
     "\n",
-    "res = ezkl.create_evm_verifier(\n",
+    "res = await ezkl.create_evm_verifier(\n",
     "        vk_path,\n",
-    "        \n",
     "        settings_path,\n",
     "        sol_code_path,\n",
     "        abi_path,\n",
@@ -344,6 +348,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "0fd7f22b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -351,7 +356,7 @@
     "\n",
     "addr_path_verifier = \"addr_verifier.txt\"\n",
     "\n",
-    "res = ezkl.deploy_evm(\n",
+    "res = await ezkl.deploy_evm(\n",
     "    addr_path_verifier,\n",
     "    sol_code_path,\n",
     "    'http://127.0.0.1:3030'\n",
@@ -362,6 +367,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "9c0dffab",
    "metadata": {},
    "source": [
     "With the vanilla verifier deployed, we can now create the data attestation contract, which will read in the instances from the calldata to the verifier, attest to them, call the verifier and then return the result. \n",
@@ -371,6 +377,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "cc888848",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -378,6 +385,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "c2db14d7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -385,7 +393,7 @@
     "sol_code_path = 'test.sol'\n",
     "input_path = 'input.json'\n",
     "\n",
-    "res = ezkl.create_evm_data_attestation(\n",
+    "res = await ezkl.create_evm_data_attestation(\n",
     "        input_path,\n",
     "        settings_path,\n",
     "        sol_code_path,\n",
@@ -396,12 +404,13 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "5a018ba6",
    "metadata": {},
    "outputs": [],
    "source": [
     "addr_path_da = \"addr_da.txt\"\n",
     "\n",
-    "res = ezkl.deploy_da_evm(\n",
+    "res = await ezkl.deploy_da_evm(\n",
     "        addr_path_da,\n",
     "        input_path,\n",
     "        settings_path,\n",
@@ -412,6 +421,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "2adad845",
    "metadata": {},
    "source": [
     "Now we can pull in the data from the contract and calculate a new set of coordinates. We then rotate the world by 1 transform and submit the proof to the contract. The contract could then update the world rotation (logic not inserted here). For demo purposes we do this repeatedly, rotating the world by 1 transform. "
@@ -444,6 +454,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "90eda56e",
    "metadata": {},
    "source": [
     "Call the view only verify method on the contract to verify the proof. Since it is a view function this is safe to use in production since you don't have to pass your private key."
@@ -528,7 +539,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.12.2"
   }
  },
  "nbformat": 4,

examples/notebooks/xgboost.ipynb

@@ -193,7 +193,7 @@
                 "with open(cal_path, \"w\") as f:\n",
                 "    json.dump(cal_data, f)\n",
                 "\n",
-                "res = ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
+                "res = await ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\")"
             ]
         },
         {
@@ -215,7 +215,7 @@
             "outputs": [],
             "source": [
                 "# srs path\n",
-                "res = ezkl.get_srs( settings_path)"
+                "res = await ezkl.get_srs( settings_path)"
             ]
         },
         {
@@ -227,7 +227,7 @@
             "source": [
                 "# now generate the witness file \n",
                 "\n",
-                "res = ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
+                "res = await ezkl.gen_witness(data_path, compiled_model_path, witness_path)\n",
                 "assert os.path.isfile(witness_path)"
             ]
         },
@@ -346,4 +346,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 5
-}
+}

examples/onnx/1l_conv_transpose/settings.json

@@ -0,0 +1 @@
+{"run_args":{"tolerance":{"val":0.0,"scale":1.0},"input_scale":7,"param_scale":7,"scale_rebase_multiplier":10,"lookup_range":[0,0],"logrows":13,"variables":[["batch_size",1]],"input_visibility":"Private","output_visibility":"Public","param_visibility":"Private"},"num_constraints":5619,"total_const_size":513,"model_instance_shapes":[[1,3,10,10]],"model_output_scales":[14],"model_input_scales":[7],"module_sizes":{"kzg":[],"poseidon":[0,[0]],"elgamal":[0,[0]]},"required_lookups":[],"check_mode":"UNSAFE","version":"0.0.0","num_blinding_factors":null}

examples/onnx/boolean/gen.py

@@ -9,7 +9,9 @@ class MyModel(nn.Module):
         super(MyModel, self).__init__()
 
     def forward(self, w, x, y, z):
-        return [((x & y)) == (x & (y | (z ^ w)))]
+        a = (x & y)
+        b = (y & (z ^ w))
+        return [a & b]
 
 
 circuit = MyModel()

examples/onnx/boolean/input.json

@@ -1 +1 @@
-{"input_data": [[false, true, false], [true, false, false], [true, false, false], [false, false, false]]}
+{"input_data": [[false, true, true], [false, true, true], [true, false, false], [false, true, true]]}

examples/onnx/boolean/network.onnx

@@ -1,21 +1,17 @@
-pytorch1.12.1:«
-+
+pytorch2.2.2:„
+*
 input1
-input2
-onnx::Equal_4And_0"And
+input2
+/And_output_0/And"And
 )
-input3
-input
-onnx::Or_5Xor_1"Xor
+input3
+input
 /Xor_output_0/Xor"Xor
-input2
-
-onnx::Or_5onnx::And_6Or_2"Or
-0
-input1
-onnx::And_6
-onnx::Equal_7And_3"And
-6
+5
+input2
+
+/Xor_output_0/And_1_output_0/And_1"And
+5
 
 /And_output_0
 /And_1_output_0output/And_2"And

examples/onnx/lstm_medium/input.json

@@ -0,0 +1,9 @@
+{
+  "input_data": [
+    [
+      1.514470100402832, 1.519423007965088, 1.5182757377624512,
+      1.5262789726257324, 1.5298409461975098
+    ]
+  ],
+  "output_data": [[-0.1862019]]
+}

examples/onnx/multihead_attention/gen.py

@@ -104,5 +104,5 @@ json.dump(data, open("input.json", 'w'))
 # ezkl.gen_settings("network.onnx", "settings.json")
 
 # !RUST_LOG = full
-# res = ezkl.calibrate_settings(
+# res = await ezkl.calibrate_settings(
 #     "input.json", "network.onnx", "settings.json", "resources")

examples/onnx/smallworm/.gitattributes

@@ -0,0 +1 @@
+network.onnx filter=lfs diff=lfs merge=lfs -text

examples/onnx/smallworm/Readme.md

@@ -0,0 +1,47 @@
+## The worm 
+
+This is an onnx file for a [WormVAE](https://github.com/TuragaLab/wormvae?tab=readme-ov-file) model, which is a VAE / latent-space representation of the C. elegans connectome.
+
+The model "is a large-scale latent variable model with a very high-dimensional latent space
+consisting of voltage dynamics of 300 neurons over 5 minutes of time at the simulation frequency
+of 160 Hz. The generative model for these latent variables is described by stochastic differential
+equations modeling the nonlinear dynamics of the network activity." (see [here](https://openreview.net/pdf?id=CJzi3dRlJE-)). 
+
+In effect this is a generative model for a worm's voltage dynamics, which can be used to generate new worm-like voltage dynamics given previous connectome state.
+
+Using ezkl you can create a zk circuit equivalent to the wormvae model, allowing you to "prove" execution of the worm model. If you're feeling particularly adventurous, you can also use the zk circuit to generate new worm-state that can be verified on chain. 
+
+To do so you'll first want to fetch the files using git-lfs (as the onnx file is too large to be stored in git). 
+
+```bash
+git lfs fetch --all
+```
+
+You'll then want to use the usual ezkl loop to generate the zk circuit. We recommend using fixed visibility for the model parameters, as the model is quite large and this will prune the circuit significantly. 
+
+```bash
+ezkl gen-settings --param-visibility=fixed
+cp input.json calibration.json
+ezkl calibrate-settings
+ezkl compile-circuit
+ezkl gen-witness
+ezkl prove
+```
+
+You might also need to aggregate the proof to get it to fit on chain.
+
+```bash
+ezkl aggregate
+```
+
+You can then create a smart contract that verifies this aggregate proof
+
+```bash
+ezkl create-evm-verifier-aggr
+```
+
+This can then be deployed on the chain of your choice.
+
+
+> Note: the model is large and thus we recommend a machine with at least 512GB of RAM to run the above commands. If you're ever compute constrained you can always use the lilith service to generate the zk circuit. Message us on discord or telegram for more details :)
+

examples/onnx/smallworm/network.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2f88c5901d3768ec21e3cf2f2840d255e84fa13c364df86b24d960cca3333769
+size 82095882

examples/onnx/smallworm/settings.json

@@ -0,0 +1 @@
+{"run_args":{"tolerance":{"val":0.0,"scale":1.0},"input_scale":0,"param_scale":6,"scale_rebase_multiplier":1,"lookup_range":[-32768,32768],"logrows":17,"variables":[["batch_size",1]],"input_visibility":"Private","output_visibility":"Public","param_visibility":"Fixed"},"num_constraints":367422820,"total_const_size":365577160,"model_instance_shapes":[[1,300,1200]],"model_output_scales":[6],"model_input_scales":[0,0,0],"module_sizes":{"kzg":[],"poseidon":[0,[0]],"elgamal":[0,[0]]},"required_lookups":[{"Div":{"denom":64.0}},"ReLU",{"Ln":{"scale":64.0}},{"Exp":{"scale":64.0}}],"check_mode":"UNSAFE","version":"0.0.0","num_blinding_factors":null}

in-browser-evm-verifier/src/index.ts

@@ -9,7 +9,6 @@ import { EVM } from '@ethereumjs/evm'
 import { buildTransaction, encodeDeployment } from './utils/tx-builder'
 import { getAccountNonce, insertAccount } from './utils/account-utils'
 import { encodeVerifierCalldata } from '../nodejs/ezkl';
-import { error } from 'console'
 
 async function deployContract(
   vm: VM,
@@ -66,7 +65,7 @@ async function verify(
     vkAddress = new Uint8Array(uint8Array.buffer);
 
     // convert uitn8array of length
-    error('vkAddress', vkAddress)
+    console.error('vkAddress', vkAddress)
   }
   const data = encodeVerifierCalldata(proof, vkAddress)
 

install_ezkl_cli.sh

@@ -99,6 +99,10 @@ fi
 echo "Removing old ezkl binary if it exists"
 [ -e file ] && rm file
 
+# echo platform and architecture
+echo "Platform: $PLATFORM"
+echo "Architecture: $ARCHITECTURE"
+
 # download the release and unpack the right tarball
 if [ "$PLATFORM" == "windows-msvc" ]; then
     JSON_RESPONSE=$(curl -s "$RELEASE_URL")
@@ -126,7 +130,6 @@ elif [ "$PLATFORM" == "macos" ]; then
 
         echo "Cleaning up"
         rm "$EZKL_DIR/build-artifacts.ezkl-macos-aarch64.tar.gz"
-
     else
         JSON_RESPONSE=$(curl -s "$RELEASE_URL")
         FILE_URL=$(echo "$JSON_RESPONSE" | grep -o 'https://github.com[^"]*' | grep "build-artifacts.ezkl-macos.tar.gz")
@@ -143,7 +146,7 @@ elif [ "$PLATFORM" == "macos" ]; then
     fi
 
 elif [ "$PLATFORM" == "linux" ]; then
-    if [ "${ARCHITECTURE}" = "amd64" ]; then
+    if [ "$ARCHITECTURE" == "amd64" ]; then
         JSON_RESPONSE=$(curl -s "$RELEASE_URL")
         FILE_URL=$(echo "$JSON_RESPONSE" | grep -o 'https://github.com[^"]*' | grep "build-artifacts.ezkl-linux-gnu.tar.gz")
 
@@ -155,9 +158,20 @@ elif [ "$PLATFORM" == "linux" ]; then
 
         echo "Cleaning up"
         rm "$EZKL_DIR/build-artifacts.ezkl-linux-gnu.tar.gz"
+    elif [ "$ARCHITECTURE" == "aarch64" ]; then
+        JSON_RESPONSE=$(curl -s "$RELEASE_URL")
+        FILE_URL=$(echo "$JSON_RESPONSE" | grep -o 'https://github.com[^"]*' | grep "build-artifacts.ezkl-linux-aarch64.tar.gz")
 
+        echo "Downloading package"
+        curl -L "$FILE_URL" -o "$EZKL_DIR/build-artifacts.ezkl-linux-aarch64.tar.gz"
+
+        echo "Unpacking package"
+        tar -xzf "$EZKL_DIR/build-artifacts.ezkl-linux-aarch64.tar.gz" -C "$EZKL_DIR"
+
+        echo "Cleaning up"
+        rm "$EZKL_DIR/build-artifacts.ezkl-linux-aarch64.tar.gz"
     else
-        echo "ARM architectures are not supported for Linux at the moment. If you would need support for the ARM architectures on linux please submit an issue https://github.com/zkonduit/ezkl/issues/new/choose"
+        echo "Non aarch ARM architectures are not supported for Linux at the moment. If you would need support for the ARM architectures on linux please submit an issue https://github.com/zkonduit/ezkl/issues/new/choose"
         exit 1
     fi
 else

pyproject.toml

@@ -8,6 +8,7 @@ addopts = "-rfEX -p pytester --strict-markers"
 testpaths = [
     "tests/python/*_tests.py",
 ]
+asyncio_mode = "auto"
 
 [project]
 name = "ezkl"

rust-toolchain

@@ -1,3 +1,3 @@
 [toolchain]
-channel = "nightly-2024-02-06"
+channel = "nightly-2024-07-18"
 components = ["rustfmt", "clippy"]

src/bin/ezkl.rs

@@ -1,7 +1,10 @@
 // ignore file if compiling for wasm
+#[global_allocator]
+#[cfg(not(target_arch = "wasm32"))]
+static GLOBAL: mimalloc::MiMalloc = mimalloc::MiMalloc;
 
 #[cfg(not(target_arch = "wasm32"))]
-use clap::Parser;
+use clap::{CommandFactory, Parser};
 #[cfg(not(target_arch = "wasm32"))]
 use colored_json::ToColoredJson;
 #[cfg(not(target_arch = "wasm32"))]
@@ -11,35 +14,49 @@ use ezkl::execute::run;
 #[cfg(not(target_arch = "wasm32"))]
 use ezkl::logger::init_logger;
 #[cfg(not(target_arch = "wasm32"))]
-use log::{debug, error, info};
+use log::{error, info};
 #[cfg(not(any(target_arch = "wasm32", feature = "no-banner")))]
 use rand::prelude::SliceRandom;
 #[cfg(not(target_arch = "wasm32"))]
 #[cfg(feature = "icicle")]
 use std::env;
-#[cfg(not(target_arch = "wasm32"))]
-use std::error::Error;
 
 #[tokio::main(flavor = "current_thread")]
 #[cfg(not(target_arch = "wasm32"))]
-pub async fn main() -> Result<(), Box<dyn Error>> {
+pub async fn main() {
     let args = Cli::parse();
-    init_logger();
-    #[cfg(not(any(target_arch = "wasm32", feature = "no-banner")))]
-    banner();
-    #[cfg(feature = "icicle")]
-    if env::var("ENABLE_ICICLE_GPU").is_ok() {
-        info!("Running with ICICLE GPU");
+
+    if let Some(generator) = args.generator {
+        ezkl::commands::print_completions(generator, &mut Cli::command());
+    } else if let Some(command) = args.command {
+        init_logger();
+        #[cfg(not(any(target_arch = "wasm32", feature = "no-banner")))]
+        banner();
+        #[cfg(feature = "icicle")]
+        if env::var("ENABLE_ICICLE_GPU").is_ok() {
+            info!("Running with ICICLE GPU");
+        } else {
+            info!("Running with CPU");
+        }
+        info!(
+            "command: \n {}",
+            &command.as_json().to_colored_json_auto().unwrap()
+        );
+        let res = run(command).await;
+        match &res {
+            Ok(_) => {
+                info!("succeeded");
+            }
+            Err(e) => {
+                error!("{}", e);
+                std::process::exit(1)
+            }
+        }
     } else {
-        info!("Running with CPU");
+        init_logger();
+        error!("No command provided");
+        std::process::exit(1)
     }
-    debug!("command: \n {}", &args.as_json()?.to_colored_json_auto()?);
-    let res = run(args.command).await;
-    match &res {
-        Ok(_) => info!("succeeded"),
-        Err(e) => error!("failed: {}", e),
-    };
-    res.map(|_| ())
 }
 
 #[cfg(target_arch = "wasm32")]

src/circuit/modules/errors.rs

@@ -0,0 +1,25 @@
+use halo2_proofs::plonk::Error as PlonkError;
+use thiserror::Error;
+
+/// Error type for the circuit module
+#[derive(Error, Debug)]
+pub enum ModuleError {
+    /// Halo 2 error
+    #[error("[halo2] {0}")]
+    Halo2Error(#[from] PlonkError),
+    /// Wrong input type for a module
+    #[error("wrong input type {0} must be {1}")]
+    WrongInputType(String, String),
+    /// A constant was not previously assigned
+    #[error("constant was not previously assigned")]
+    ConstantNotAssigned,
+    /// Input length is wrong
+    #[error("input length is wrong {0}")]
+    InputWrongLength(usize),
+}
+
+impl From<ModuleError> for PlonkError {
+    fn from(_e: ModuleError) -> PlonkError {
+        PlonkError::Synthesis
+    }
+}

src/circuit/modules/mod.rs

@@ -6,10 +6,11 @@ pub mod polycommit;
 
 ///
 pub mod planner;
-use halo2_proofs::{
-    circuit::Layouter,
-    plonk::{ConstraintSystem, Error},
-};
+
+///
+pub mod errors;
+
+use halo2_proofs::{circuit::Layouter, plonk::ConstraintSystem};
 use halo2curves::ff::PrimeField;
 pub use planner::*;
 
@@ -35,14 +36,14 @@ pub trait Module<F: PrimeField + TensorType + PartialOrd> {
     /// Name
     fn name(&self) -> &'static str;
     /// Run the operation the module represents
-    fn run(input: Self::RunInputs) -> Result<Vec<Vec<F>>, Box<dyn std::error::Error>>;
+    fn run(input: Self::RunInputs) -> Result<Vec<Vec<F>>, errors::ModuleError>;
     /// Layout inputs
     fn layout_inputs(
         &self,
         layouter: &mut impl Layouter<F>,
         input: &[ValTensor<F>],
         constants: &mut ConstantsMap<F>,
-    ) -> Result<Self::InputAssignments, Error>;
+    ) -> Result<Self::InputAssignments, errors::ModuleError>;
     /// Layout
     fn layout(
         &self,
@@ -50,7 +51,7 @@ pub trait Module<F: PrimeField + TensorType + PartialOrd> {
         input: &[ValTensor<F>],
         row_offset: usize,
         constants: &mut ConstantsMap<F>,
-    ) -> Result<ValTensor<F>, Error>;
+    ) -> Result<ValTensor<F>, errors::ModuleError>;
     /// Number of instance values the module uses every time it is applied
     fn instance_increment_input(&self) -> Vec<usize>;
     /// Number of rows used by the module

src/circuit/modules/polycommit.rs

@@ -18,6 +18,7 @@ use halo2curves::CurveAffine;
 use crate::circuit::region::ConstantsMap;
 use crate::tensor::{Tensor, ValTensor, ValType, VarTensor};
 
+use super::errors::ModuleError;
 use super::Module;
 
 /// The number of instance columns used by the PolyCommit hash function
@@ -110,7 +111,7 @@ impl Module<Fp> for PolyCommitChip {
         _: &mut impl Layouter<Fp>,
         _: &[ValTensor<Fp>],
         _: &mut ConstantsMap<Fp>,
-    ) -> Result<Self::InputAssignments, Error> {
+    ) -> Result<Self::InputAssignments, ModuleError> {
         Ok(())
     }
 
@@ -123,28 +124,30 @@ impl Module<Fp> for PolyCommitChip {
         input: &[ValTensor<Fp>],
         _: usize,
         constants: &mut ConstantsMap<Fp>,
-    ) -> Result<ValTensor<Fp>, Error> {
+    ) -> Result<ValTensor<Fp>, ModuleError> {
         assert_eq!(input.len(), 1);
 
         let local_constants = constants.clone();
-        layouter.assign_region(
-            || "PolyCommit",
-            |mut region| {
-                let mut local_inner_constants = local_constants.clone();
-                let res = self.config.inputs.assign(
-                    &mut region,
-                    0,
-                    &input[0],
-                    &mut local_inner_constants,
-                )?;
-                *constants = local_inner_constants;
-                Ok(res)
-            },
-        )
+        layouter
+            .assign_region(
+                || "PolyCommit",
+                |mut region| {
+                    let mut local_inner_constants = local_constants.clone();
+                    let res = self.config.inputs.assign(
+                        &mut region,
+                        0,
+                        &input[0],
+                        &mut local_inner_constants,
+                    )?;
+                    *constants = local_inner_constants;
+                    Ok(res)
+                },
+            )
+            .map_err(|e| e.into())
     }
 
     ///
-    fn run(message: Vec<Fp>) -> Result<Vec<Vec<Fp>>, Box<dyn std::error::Error>> {
+    fn run(message: Vec<Fp>) -> Result<Vec<Vec<Fp>>, ModuleError> {
         Ok(vec![message])
     }
 

src/circuit/modules/poseidon.rs

@@ -21,6 +21,7 @@ use std::marker::PhantomData;
 use crate::circuit::region::ConstantsMap;
 use crate::tensor::{Tensor, ValTensor, ValType};
 
+use super::errors::ModuleError;
 use super::Module;
 
 /// The number of instance columns used by the Poseidon hash function
@@ -174,7 +175,7 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
         layouter: &mut impl Layouter<Fp>,
         message: &[ValTensor<Fp>],
         constants: &mut ConstantsMap<Fp>,
-    ) -> Result<Self::InputAssignments, Error> {
+    ) -> Result<Self::InputAssignments, ModuleError> {
         assert_eq!(message.len(), 1);
         let message = message[0].clone();
 
@@ -185,78 +186,82 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
         let res = layouter.assign_region(
             || "load message",
             |mut region| {
-                let assigned_message: Result<Vec<AssignedCell<Fp, Fp>>, Error> = match &message {
-                    ValTensor::Value { inner: v, .. } => v
-                        .iter()
-                        .enumerate()
-                        .map(|(i, value)| {
-                            let x = i % WIDTH;
-                            let y = i / WIDTH;
+                let assigned_message: Result<Vec<AssignedCell<Fp, Fp>>, ModuleError> =
+                    match &message {
+                        ValTensor::Value { inner: v, .. } => {
+                            v.iter()
+                                .enumerate()
+                                .map(|(i, value)| {
+                                    let x = i % WIDTH;
+                                    let y = i / WIDTH;
 
-                            match value {
-                                ValType::Value(v) => region.assign_advice(
-                                    || format!("load message_{}", i),
-                                    self.config.hash_inputs[x],
-                                    y,
-                                    || *v,
-                                ),
-                                ValType::PrevAssigned(v) | ValType::AssignedConstant(v, ..) => {
-                                    Ok(v.clone())
-                                }
-                                ValType::Constant(f) => {
-                                    if local_constants.contains_key(f) {
-                                        Ok(constants.get(f).unwrap().assigned_cell().ok_or({
-                                            log::error!("constant not previously assigned");
-                                            Error::Synthesis
-                                        })?)
-                                    } else {
-                                        let res = region.assign_advice_from_constant(
-                                            || format!("load message_{}", i),
-                                            self.config.hash_inputs[x],
-                                            y,
-                                            *f,
-                                        )?;
+                                    match value {
+                                        ValType::Value(v) => region
+                                            .assign_advice(
+                                                || format!("load message_{}", i),
+                                                self.config.hash_inputs[x],
+                                                y,
+                                                || *v,
+                                            )
+                                            .map_err(|e| e.into()),
+                                        ValType::PrevAssigned(v)
+                                        | ValType::AssignedConstant(v, ..) => Ok(v.clone()),
+                                        ValType::Constant(f) => {
+                                            if local_constants.contains_key(f) {
+                                                Ok(constants
+                                                    .get(f)
+                                                    .unwrap()
+                                                    .assigned_cell()
+                                                    .ok_or(ModuleError::ConstantNotAssigned)?)
+                                            } else {
+                                                let res = region.assign_advice_from_constant(
+                                                    || format!("load message_{}", i),
+                                                    self.config.hash_inputs[x],
+                                                    y,
+                                                    *f,
+                                                )?;
 
-                                        constants
-                                            .insert(*f, ValType::AssignedConstant(res.clone(), *f));
+                                                constants.insert(
+                                                    *f,
+                                                    ValType::AssignedConstant(res.clone(), *f),
+                                                );
 
-                                        Ok(res)
+                                                Ok(res)
+                                            }
+                                        }
+                                        e => Err(ModuleError::WrongInputType(
+                                            format!("{:?}", e),
+                                            "PrevAssigned".to_string(),
+                                        )),
                                     }
-                                }
-                                e => {
-                                    log::error!(
-                                        "wrong input type {:?}, must be previously assigned",
-                                        e
-                                    );
-                                    Err(Error::Synthesis)
-                                }
-                            }
-                        })
-                        .collect(),
-                    ValTensor::Instance {
-                        dims,
-                        inner: col,
-                        idx,
-                        initial_offset,
-                        ..
-                    } => {
-                        // this should never ever fail
-                        let num_elems = dims[*idx].iter().product::<usize>();
-                        (0..num_elems)
-                            .map(|i| {
-                                let x = i % WIDTH;
-                                let y = i / WIDTH;
-                                region.assign_advice_from_instance(
-                                    || "pub input anchor",
-                                    *col,
-                                    initial_offset + i,
-                                    self.config.hash_inputs[x],
-                                    y,
-                                )
-                            })
-                            .collect()
-                    }
-                };
+                                })
+                                .collect()
+                        }
+                        ValTensor::Instance {
+                            dims,
+                            inner: col,
+                            idx,
+                            initial_offset,
+                            ..
+                        } => {
+                            // this should never ever fail
+                            let num_elems = dims[*idx].iter().product::<usize>();
+                            (0..num_elems)
+                                .map(|i| {
+                                    let x = i % WIDTH;
+                                    let y = i / WIDTH;
+                                    region.assign_advice_from_instance(
+                                        || "pub input anchor",
+                                        *col,
+                                        initial_offset + i,
+                                        self.config.hash_inputs[x],
+                                        y,
+                                    )
+                                })
+                                .collect::<Result<Vec<_>, _>>()
+                                .map_err(|e| e.into())
+                        }
+                    };
 
                 let offset = message.len() / WIDTH + 1;
 
@@ -277,7 +282,7 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
             message.len(),
             start_time.elapsed()
         );
-        res
+        res.map_err(|e| e.into())
     }
 
     /// L is the number of inputs to the hash function
@@ -289,7 +294,7 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
         input: &[ValTensor<Fp>],
         row_offset: usize,
         constants: &mut ConstantsMap<Fp>,
-    ) -> Result<ValTensor<Fp>, Error> {
+    ) -> Result<ValTensor<Fp>, ModuleError> {
         let (mut input_cells, zero_val) = self.layout_inputs(layouter, input, constants)?;
         // extract the values from the input cells
         let mut assigned_input: Tensor<ValType<Fp>> =
@@ -301,7 +306,7 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
         let mut one_iter = false;
         // do the Tree dance baby
         while input_cells.len() > 1 || !one_iter {
-            let hashes: Result<Vec<AssignedCell<Fp, Fp>>, Error> = input_cells
+            let hashes: Result<Vec<AssignedCell<Fp, Fp>>, ModuleError> = input_cells
                 .chunks(L)
                 .enumerate()
                 .map(|(i, block)| {
@@ -332,7 +337,8 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
 
                     hash
                 })
-                .collect();
+                .collect::<Result<Vec<_>, _>>()
+                .map_err(|e| e.into());
 
             log::trace!("hashes (N={:?}) took: {:?}", len, start_time.elapsed());
             one_iter = true;
@@ -348,7 +354,7 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
             ValType::PrevAssigned(v) => v,
             _ => {
                 log::error!("wrong input type, must be previously assigned");
-                return Err(Error::Synthesis);
+                return Err(Error::Synthesis.into());
             }
         };
 
@@ -380,7 +386,7 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
     }
 
     ///
-    fn run(message: Vec<Fp>) -> Result<Vec<Vec<Fp>>, Box<dyn std::error::Error>> {
+    fn run(message: Vec<Fp>) -> Result<Vec<Vec<Fp>>, ModuleError> {
         let mut hash_inputs = message;
 
         let len = hash_inputs.len();
@@ -400,7 +406,11 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
                         block.extend(vec![Fp::ZERO; L - remainder].iter());
                     }
 
-                    let message = block.try_into().map_err(|_| Error::Synthesis)?;
+                    let block_len = block.len();
+
+                    let message = block
+                        .try_into()
+                        .map_err(|_| ModuleError::InputWrongLength(block_len))?;
 
                     Ok(halo2_gadgets::poseidon::primitives::Hash::<
                         _,
@@ -411,7 +421,7 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
                     >::init()
                     .hash(message))
                 })
-                .collect::<Result<Vec<_>, Error>>()?;
+                .collect::<Result<Vec<_>, ModuleError>>()?;
             one_iter = true;
             hash_inputs = hashes;
         }

src/circuit/ops/chip.rs

@@ -1,7 +1,5 @@
 use std::str::FromStr;
 
-use thiserror::Error;
-
 use halo2_proofs::{
     circuit::Layouter,
     plonk::{ConstraintSystem, Constraints, Expression, Selector},
@@ -24,33 +22,13 @@ use crate::{
         table::{Range, RangeCheck, Table},
         utils,
     },
-    tensor::{IntoI64, Tensor, TensorType, ValTensor, VarTensor},
+    tensor::{Tensor, TensorType, ValTensor, VarTensor},
 };
-use std::{collections::BTreeMap, error::Error, marker::PhantomData};
+use std::{collections::BTreeMap, marker::PhantomData};
 
-use super::{lookup::LookupOp, region::RegionCtx, Op};
+use super::{lookup::LookupOp, region::RegionCtx, CircuitError, Op};
 use halo2curves::ff::{Field, PrimeField};
 
-/// circuit related errors.
-#[derive(Debug, Error)]
-pub enum CircuitError {
-    /// Shape mismatch in circuit construction
-    #[error("dimension mismatch in circuit construction for op: {0}")]
-    DimMismatch(String),
-    /// Error when instantiating lookup tables
-    #[error("failed to instantiate lookup tables")]
-    LookupInstantiation,
-    /// A lookup table was was already assigned
-    #[error("attempting to initialize an already instantiated lookup table")]
-    TableAlreadyAssigned,
-    /// This operation is unsupported
-    #[error("unsupported operation in graph")]
-    UnsupportedOp,
-    ///
-    #[error("invalid einsum expression")]
-    InvalidEinsum,
-}
-
 #[allow(missing_docs)]
 /// An enum representing activating the sanity checks we can perform on the accumulated arguments
 #[derive(
@@ -80,14 +58,18 @@ impl ToFlags for CheckMode {
 
 impl From<String> for CheckMode {
     fn from(value: String) -> Self {
-        match value.to_lowercase().as_str() {
-            "safe" => CheckMode::SAFE,
-            "unsafe" => CheckMode::UNSAFE,
-            _ => {
-                log::error!("Invalid value for CheckMode");
-                log::warn!("defaulting to SAFE");
-                CheckMode::SAFE
-            }
+        Self::from_str(value.as_str()).unwrap()
+    }
+}
+
+impl FromStr for CheckMode {
+    type Err = String;
+
+    fn from_str(s: &str) -> Result<Self, Self::Err> {
+        match s.to_lowercase().as_str() {
+            "safe" => Ok(CheckMode::SAFE),
+            "unsafe" => Ok(CheckMode::UNSAFE),
+            _ => Err("Invalid value for CheckMode".to_string()),
         }
     }
 }
@@ -345,7 +327,7 @@ pub struct BaseConfig<F: PrimeField + TensorType + PartialOrd> {
     _marker: PhantomData<F>,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseConfig<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> BaseConfig<F> {
     /// Returns a new [BaseConfig] with no inputs, no selectors, and no tables.
     pub fn dummy(col_size: usize, num_inner_cols: usize) -> Self {
         Self {
@@ -509,18 +491,18 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseCo
         lookup_range: Range,
         logrows: usize,
         nl: &LookupOp,
-    ) -> Result<(), Box<dyn Error>>
+    ) -> Result<(), CircuitError>
     where
         F: Field,
     {
         if !index.is_advice() {
-            return Err("wrong input type for lookup index".into());
+            return Err(CircuitError::WrongColumnType(index.name().to_string()));
         }
         if !input.is_advice() {
-            return Err("wrong input type for lookup input".into());
+            return Err(CircuitError::WrongColumnType(input.name().to_string()));
         }
         if !output.is_advice() {
-            return Err("wrong input type for lookup output".into());
+            return Err(CircuitError::WrongColumnType(output.name().to_string()));
         }
 
         // we borrow mutably twice so we need to do this dance
@@ -650,19 +632,19 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseCo
         cs: &mut ConstraintSystem<F>,
         lookups: &[VarTensor; 3],
         tables: &[VarTensor; 3],
-    ) -> Result<(), Box<dyn Error>>
+    ) -> Result<(), CircuitError>
     where
         F: Field,
     {
         for l in lookups.iter() {
             if !l.is_advice() {
-                return Err("wrong input type for dynamic lookup".into());
+                return Err(CircuitError::WrongDynamicColumnType(l.name().to_string()));
             }
         }
 
         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());
+                return Err(CircuitError::WrongDynamicColumnType(t.name().to_string()));
             }
         }
 
@@ -733,19 +715,19 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseCo
         cs: &mut ConstraintSystem<F>,
         inputs: &[VarTensor; 2],
         references: &[VarTensor; 2],
-    ) -> Result<(), Box<dyn Error>>
+    ) -> Result<(), CircuitError>
     where
         F: Field,
     {
         for l in inputs.iter() {
             if !l.is_advice() {
-                return Err("wrong input type for dynamic lookup".into());
+                return Err(CircuitError::WrongDynamicColumnType(l.name().to_string()));
             }
         }
 
         for t in references.iter() {
             if !t.is_advice() || t.num_blocks() > 1 || t.num_inner_cols() > 1 {
-                return Err("wrong table type for dynamic lookup".into());
+                return Err(CircuitError::WrongDynamicColumnType(t.name().to_string()));
             }
         }
 
@@ -818,12 +800,12 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseCo
         index: &VarTensor,
         range: Range,
         logrows: usize,
-    ) -> Result<(), Box<dyn Error>>
+    ) -> Result<(), CircuitError>
     where
         F: Field,
     {
         if !input.is_advice() {
-            return Err("wrong input type for lookup input".into());
+            return Err(CircuitError::WrongColumnType(input.name().to_string()));
         }
 
         // we borrow mutably twice so we need to do this dance
@@ -914,7 +896,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseCo
     }
 
     /// layout_tables must be called before layout.
-    pub fn layout_tables(&mut self, layouter: &mut impl Layouter<F>) -> Result<(), Box<dyn Error>> {
+    pub fn layout_tables(&mut self, layouter: &mut impl Layouter<F>) -> Result<(), CircuitError> {
         for (i, table) in self.static_lookups.tables.values_mut().enumerate() {
             if !table.is_assigned {
                 debug!(
@@ -935,7 +917,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseCo
     pub fn layout_range_checks(
         &mut self,
         layouter: &mut impl Layouter<F>,
-    ) -> Result<(), Box<dyn Error>> {
+    ) -> Result<(), CircuitError> {
         for range_check in self.range_checks.ranges.values_mut() {
             if !range_check.is_assigned {
                 debug!("laying out range check for {:?}", range_check.range);
@@ -955,7 +937,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> BaseCo
         region: &mut RegionCtx<F>,
         values: &[ValTensor<F>],
         op: Box<dyn Op<F>>,
-    ) -> Result<Option<ValTensor<F>>, Box<dyn Error>> {
+    ) -> Result<Option<ValTensor<F>>, CircuitError> {
         op.layout(self, region, values)
     }
 }

src/circuit/ops/errors.rs

@@ -0,0 +1,97 @@
+use std::convert::Infallible;
+
+use crate::{fieldutils::IntegerRep, tensor::TensorError};
+use halo2_proofs::plonk::Error as PlonkError;
+use thiserror::Error;
+
+/// Error type for the circuit module
+#[derive(Error, Debug)]
+pub enum CircuitError {
+    /// Halo 2 error
+    #[error("[halo2] {0}")]
+    Halo2Error(#[from] PlonkError),
+    /// Tensor error
+    #[error("[tensor] {0}")]
+    TensorError(#[from] TensorError),
+    /// Shape mismatch in circuit construction
+    #[error("dimension mismatch in circuit construction for op: {0}")]
+    DimMismatch(String),
+    /// Error when instantiating lookup tables
+    #[error("failed to instantiate lookup tables")]
+    LookupInstantiation,
+    /// A lookup table was was already assigned
+    #[error("attempting to initialize an already instantiated lookup table")]
+    TableAlreadyAssigned,
+    /// This operation is unsupported
+    #[error("unsupported operation in graph")]
+    UnsupportedOp,
+    ///
+    #[error("invalid einsum expression")]
+    InvalidEinsum,
+    /// Flush error
+    #[error("failed to flush, linear coord is not aligned with the next row")]
+    FlushError,
+    /// Constrain error
+    #[error("constrain_equal: one of the tensors is assigned and the other is not")]
+    ConstrainError,
+    /// Failed to get lookups
+    #[error("failed to get lookups for op: {0}")]
+    GetLookupsError(String),
+    /// Failed to get range checks
+    #[error("failed to get range checks for op: {0}")]
+    GetRangeChecksError(String),
+    /// Failed to get dynamic lookup
+    #[error("failed to get dynamic lookup for op: {0}")]
+    GetDynamicLookupError(String),
+    /// Failed to get shuffle
+    #[error("failed to get shuffle for op: {0}")]
+    GetShuffleError(String),
+    /// Failed to get constants
+    #[error("failed to get constants for op: {0}")]
+    GetConstantsError(String),
+    /// Slice length mismatch
+    #[error("slice length mismatch: {0}")]
+    SliceLengthMismatch(#[from] std::array::TryFromSliceError),
+    /// Bad conversion
+    #[error("invalid conversion: {0}")]
+    InvalidConversion(#[from] Infallible),
+    /// Invalid min/max lookup range
+    #[error("invalid min/max lookup range: min: {0}, max: {1}")]
+    InvalidMinMaxRange(IntegerRep, IntegerRep),
+    /// Missing product in einsum
+    #[error("missing product in einsum")]
+    MissingEinsumProduct,
+    /// Mismatched lookup length
+    #[error("mismatched lookup lengths: {0} and {1}")]
+    MismatchedLookupLength(usize, usize),
+    /// Mismatched shuffle length
+    #[error("mismatched shuffle lengths: {0} and {1}")]
+    MismatchedShuffleLength(usize, usize),
+    /// Mismatched lookup table lengths
+    #[error("mismatched lookup table lengths: {0} and {1}")]
+    MismatchedLookupTableLength(usize, usize),
+    /// Wrong column type for lookup
+    #[error("wrong column type for lookup: {0}")]
+    WrongColumnType(String),
+    /// Wrong column type for dynamic lookup
+    #[error("wrong column type for dynamic lookup: {0}")]
+    WrongDynamicColumnType(String),
+    /// Missing selectors
+    #[error("missing selectors for op: {0}")]
+    MissingSelectors(String),
+    /// Table lookup error
+    #[error("value ({0}) out of range: ({1}, {2})")]
+    TableOOR(IntegerRep, IntegerRep, IntegerRep),
+    /// Loookup not configured
+    #[error("lookup not configured: {0}")]
+    LookupNotConfigured(String),
+    /// Range check not configured
+    #[error("range check not configured: {0}")]
+    RangeCheckNotConfigured(String),
+    /// Missing layout
+    #[error("missing layout for op: {0}")]
+    MissingLayout(String),
+    #[error("[io] {0}")]
+    /// IO error
+    IoError(#[from] std::io::Error),
+}

src/circuit/ops/hybrid.rs

@@ -1,7 +1,7 @@
 use super::*;
 use crate::{
     circuit::{layouts, utils, Tolerance},
-    fieldutils::i64_to_felt,
+    fieldutils::integer_rep_to_felt,
     graph::multiplier_to_scale,
     tensor::{self, Tensor, TensorType, ValTensor},
 };
@@ -71,12 +71,17 @@ pub enum HybridOp {
     },
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F> for HybridOp {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for HybridOp {
     ///
     fn requires_homogenous_input_scales(&self) -> Vec<usize> {
         match self {
-            HybridOp::Greater | HybridOp::Less | HybridOp::Equals => vec![0, 1],
-            HybridOp::GreaterEqual | HybridOp::LessEqual => vec![0, 1],
+            HybridOp::Greater { .. }
+            | HybridOp::Less { .. }
+            | HybridOp::Equals { .. }
+            | HybridOp::GreaterEqual { .. }
+            | HybridOp::LessEqual { .. } => {
+                vec![0, 1]
+            }
             _ => vec![],
         }
     }
@@ -135,10 +140,10 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
                 )
             }
             HybridOp::RangeCheck(p) => format!("RANGECHECK (tol={:?})", p),
-            HybridOp::Greater => "GREATER".into(),
-            HybridOp::GreaterEqual => "GREATEREQUAL".into(),
-            HybridOp::Less => "LESS".into(),
-            HybridOp::LessEqual => "LESSEQUAL".into(),
+            HybridOp::Greater => "GREATER".to_string(),
+            HybridOp::GreaterEqual => "GREATEREQUAL".to_string(),
+            HybridOp::Less => "LESS".to_string(),
+            HybridOp::LessEqual => "LESSEQUAL".to_string(),
             HybridOp::Equals => "EQUALS".into(),
             HybridOp::Gather { dim, .. } => format!("GATHER (dim={})", dim),
             HybridOp::TopK { k, dim, largest } => {
@@ -155,7 +160,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
         config: &mut crate::circuit::BaseConfig<F>,
         region: &mut RegionCtx<F>,
         values: &[ValTensor<F>],
-    ) -> Result<Option<ValTensor<F>>, Box<dyn std::error::Error>> {
+    ) -> Result<Option<ValTensor<F>>, CircuitError> {
         Ok(Some(match self {
             HybridOp::SumPool {
                 padding,
@@ -184,8 +189,8 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
                         config,
                         region,
                         values[..].try_into()?,
-                        i64_to_felt(input_scale.0 as i64),
-                        i64_to_felt(output_scale.0 as i64),
+                        integer_rep_to_felt(input_scale.0 as i128),
+                        integer_rep_to_felt(output_scale.0 as i128),
                     )?
                 } else {
                     layouts::nonlinearity(
@@ -209,7 +214,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
                         config,
                         region,
                         values[..].try_into()?,
-                        i64_to_felt(denom.0 as i64),
+                        integer_rep_to_felt(denom.0 as i128),
                     )?
                 } else {
                     layouts::nonlinearity(
@@ -287,7 +292,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
         }))
     }
 
-    fn out_scale(&self, in_scales: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>> {
+    fn out_scale(&self, in_scales: Vec<crate::Scale>) -> Result<crate::Scale, CircuitError> {
         let scale = match self {
             HybridOp::Greater { .. }
             | HybridOp::GreaterEqual { .. }

src/circuit/ops/lookup.rs

@@ -1,12 +1,11 @@
 use super::*;
 use serde::{Deserialize, Serialize};
-use std::error::Error;
 
 use crate::{
     circuit::{layouts, table::Range, utils},
-    fieldutils::{felt_to_i64, i64_to_felt},
+    fieldutils::{felt_to_integer_rep, integer_rep_to_felt, IntegerRep},
     graph::multiplier_to_scale,
-    tensor::{self, IntoI64, Tensor, TensorError, TensorType},
+    tensor::{self, Tensor, TensorError, TensorType},
 };
 
 use super::Op;
@@ -16,14 +15,12 @@ use halo2curves::ff::PrimeField;
 /// An enum representing the operations that can be used to express more complex operations via accumulation
 #[derive(Clone, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, Deserialize, Serialize)]
 pub enum LookupOp {
-    Abs,
     Div {
         denom: utils::F32,
     },
     Cast {
         scale: utils::F32,
     },
-    ReLU,
     Max {
         scale: utils::F32,
         a: utils::F32,
@@ -105,19 +102,6 @@ pub enum LookupOp {
     Erf {
         scale: utils::F32,
     },
-    GreaterThan {
-        a: utils::F32,
-    },
-    LessThan {
-        a: utils::F32,
-    },
-    GreaterThanEqual {
-        a: utils::F32,
-    },
-    LessThanEqual {
-        a: utils::F32,
-    },
-    Sign,
     KroneckerDelta,
     Pow {
         scale: utils::F32,
@@ -132,109 +116,165 @@ impl LookupOp {
     /// Returns the range of values that can be represented by the table
     pub fn bit_range(max_len: usize) -> Range {
         let range = (max_len - 1) as f64 / 2_f64;
-        let range = range as i64;
+        let range = range as IntegerRep;
         (-range, range)
     }
 
-    /// Matches a [Op] to an operation in the `tensor::ops` module.
-    pub(crate) fn f<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64>(
-        &self,
-        x: &[Tensor<F>],
-    ) -> Result<ForwardResult<F>, TensorError> {
-        let x = x[0].clone().map(|x| felt_to_i64(x));
-        let res = match &self {
-            LookupOp::Abs => Ok(tensor::ops::abs(&x)?),
-            LookupOp::Ceil { scale } => Ok(tensor::ops::nonlinearities::ceil(&x, scale.into())),
-            LookupOp::Floor { scale } => Ok(tensor::ops::nonlinearities::floor(&x, scale.into())),
-            LookupOp::Round { scale } => Ok(tensor::ops::nonlinearities::round(&x, scale.into())),
-            LookupOp::RoundHalfToEven { scale } => Ok(
-                tensor::ops::nonlinearities::round_half_to_even(&x, scale.into()),
-            ),
-            LookupOp::Pow { scale, a } => Ok(tensor::ops::nonlinearities::pow(
-                &x,
-                scale.0.into(),
-                a.0.into(),
-            )),
-            LookupOp::KroneckerDelta => Ok(tensor::ops::nonlinearities::kronecker_delta(&x)),
-            LookupOp::Max { scale, a } => Ok(tensor::ops::nonlinearities::max(
-                &x,
-                scale.0.into(),
-                a.0.into(),
-            )),
-            LookupOp::Min { scale, a } => Ok(tensor::ops::nonlinearities::min(
-                &x,
-                scale.0.into(),
-                a.0.into(),
-            )),
-            LookupOp::Sign => Ok(tensor::ops::nonlinearities::sign(&x)),
-            LookupOp::LessThan { a } => Ok(tensor::ops::nonlinearities::less_than(
-                &x,
-                f32::from(*a).into(),
-            )),
-            LookupOp::LessThanEqual { a } => Ok(tensor::ops::nonlinearities::less_than_equal(
-                &x,
-                f32::from(*a).into(),
-            )),
-            LookupOp::GreaterThan { a } => Ok(tensor::ops::nonlinearities::greater_than(
-                &x,
-                f32::from(*a).into(),
-            )),
-            LookupOp::GreaterThanEqual { a } => Ok(
-                tensor::ops::nonlinearities::greater_than_equal(&x, f32::from(*a).into()),
-            ),
-            LookupOp::Div { denom } => Ok(tensor::ops::nonlinearities::const_div(
-                &x,
-                f32::from(*denom).into(),
-            )),
-            LookupOp::Cast { scale } => Ok(tensor::ops::nonlinearities::const_div(
-                &x,
-                f32::from(*scale).into(),
-            )),
+    /// as path
+    pub fn as_path(&self) -> String {
+        match self {
+            LookupOp::Ceil { scale } => format!("ceil_{}", scale),
+            LookupOp::Floor { scale } => format!("floor_{}", scale),
+            LookupOp::Round { scale } => format!("round_{}", scale),
+            LookupOp::RoundHalfToEven { scale } => format!("round_half_to_even_{}", scale),
+            LookupOp::Pow { scale, a } => format!("pow_{}_{}", scale, a),
+            LookupOp::KroneckerDelta => "kronecker_delta".into(),
+            LookupOp::Max { scale, a } => format!("max_{}_{}", scale, a),
+            LookupOp::Min { scale, a } => format!("min_{}_{}", scale, a),
+            LookupOp::Div { denom } => format!("div_{}", denom),
+            LookupOp::Cast { scale } => format!("cast_{}", scale),
             LookupOp::Recip {
                 input_scale,
                 output_scale,
-            } => Ok(tensor::ops::nonlinearities::recip(
-                &x,
-                input_scale.into(),
-                output_scale.into(),
-            )),
-            LookupOp::ReLU => Ok(tensor::ops::nonlinearities::leakyrelu(&x, 0_f64)),
+            } => format!("recip_{}_{}", input_scale, output_scale),
+            LookupOp::LeakyReLU { slope: a } => format!("leaky_relu_{}", a),
+            LookupOp::Sigmoid { scale } => format!("sigmoid_{}", scale),
+            LookupOp::Sqrt { scale } => format!("sqrt_{}", scale),
+            LookupOp::Rsqrt { scale } => format!("rsqrt_{}", scale),
+            LookupOp::Erf { scale } => format!("erf_{}", scale),
+            LookupOp::Exp { scale } => format!("exp_{}", scale),
+            LookupOp::Ln { scale } => format!("ln_{}", scale),
+            LookupOp::Cos { scale } => format!("cos_{}", scale),
+            LookupOp::ACos { scale } => format!("acos_{}", scale),
+            LookupOp::Cosh { scale } => format!("cosh_{}", scale),
+            LookupOp::ACosh { scale } => format!("acosh_{}", scale),
+            LookupOp::Sin { scale } => format!("sin_{}", scale),
+            LookupOp::ASin { scale } => format!("asin_{}", scale),
+            LookupOp::Sinh { scale } => format!("sinh_{}", scale),
+            LookupOp::ASinh { scale } => format!("asinh_{}", scale),
+            LookupOp::Tan { scale } => format!("tan_{}", scale),
+            LookupOp::ATan { scale } => format!("atan_{}", scale),
+            LookupOp::ATanh { scale } => format!("atanh_{}", scale),
+            LookupOp::Tanh { scale } => format!("tanh_{}", scale),
+            LookupOp::HardSwish { scale } => format!("hardswish_{}", scale),
+        }
+    }
 
-            LookupOp::LeakyReLU { slope: a } => {
-                Ok(tensor::ops::nonlinearities::leakyrelu(&x, a.0.into()))
-            }
-            LookupOp::Sigmoid { scale } => {
-                Ok(tensor::ops::nonlinearities::sigmoid(&x, scale.into()))
-            }
-            LookupOp::Sqrt { scale } => Ok(tensor::ops::nonlinearities::sqrt(&x, scale.into())),
-            LookupOp::Rsqrt { scale } => Ok(tensor::ops::nonlinearities::rsqrt(&x, scale.into())),
-            LookupOp::Erf { scale } => Ok(tensor::ops::nonlinearities::erffunc(&x, scale.into())),
-            LookupOp::Exp { scale } => Ok(tensor::ops::nonlinearities::exp(&x, scale.into())),
-            LookupOp::Ln { scale } => Ok(tensor::ops::nonlinearities::ln(&x, scale.into())),
-            LookupOp::Cos { scale } => Ok(tensor::ops::nonlinearities::cos(&x, scale.into())),
-            LookupOp::ACos { scale } => Ok(tensor::ops::nonlinearities::acos(&x, scale.into())),
-            LookupOp::Cosh { scale } => Ok(tensor::ops::nonlinearities::cosh(&x, scale.into())),
-            LookupOp::ACosh { scale } => Ok(tensor::ops::nonlinearities::acosh(&x, scale.into())),
-            LookupOp::Sin { scale } => Ok(tensor::ops::nonlinearities::sin(&x, scale.into())),
-            LookupOp::ASin { scale } => Ok(tensor::ops::nonlinearities::asin(&x, scale.into())),
-            LookupOp::Sinh { scale } => Ok(tensor::ops::nonlinearities::sinh(&x, scale.into())),
-            LookupOp::ASinh { scale } => Ok(tensor::ops::nonlinearities::asinh(&x, scale.into())),
-            LookupOp::Tan { scale } => Ok(tensor::ops::nonlinearities::tan(&x, scale.into())),
-            LookupOp::ATan { scale } => Ok(tensor::ops::nonlinearities::atan(&x, scale.into())),
-            LookupOp::ATanh { scale } => Ok(tensor::ops::nonlinearities::atanh(&x, scale.into())),
-            LookupOp::Tanh { scale } => Ok(tensor::ops::nonlinearities::tanh(&x, scale.into())),
-            LookupOp::HardSwish { scale } => {
-                Ok(tensor::ops::nonlinearities::hardswish(&x, scale.into()))
-            }
-        }?;
+    /// Matches a [Op] to an operation in the `tensor::ops` module.
+    pub(crate) fn f<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
+        &self,
+        x: &[Tensor<F>],
+    ) -> Result<ForwardResult<F>, TensorError> {
+        let x = x[0].clone().map(|x| felt_to_integer_rep(x));
+        let res =
+            match &self {
+                LookupOp::Ceil { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::ceil(&x, scale.into()))
+                }
+                LookupOp::Floor { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::floor(&x, scale.into()))
+                }
+                LookupOp::Round { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::round(&x, scale.into()))
+                }
+                LookupOp::RoundHalfToEven { scale } => Ok::<_, TensorError>(
+                    tensor::ops::nonlinearities::round_half_to_even(&x, scale.into()),
+                ),
+                LookupOp::Pow { scale, a } => Ok::<_, TensorError>(
+                    tensor::ops::nonlinearities::pow(&x, scale.0.into(), a.0.into()),
+                ),
+                LookupOp::KroneckerDelta => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::kronecker_delta(&x))
+                }
+                LookupOp::Max { scale, a } => Ok::<_, TensorError>(
+                    tensor::ops::nonlinearities::max(&x, scale.0.into(), a.0.into()),
+                ),
+                LookupOp::Min { scale, a } => Ok::<_, TensorError>(
+                    tensor::ops::nonlinearities::min(&x, scale.0.into(), a.0.into()),
+                ),
+                LookupOp::Div { denom } => Ok::<_, TensorError>(
+                    tensor::ops::nonlinearities::const_div(&x, f32::from(*denom).into()),
+                ),
+                LookupOp::Cast { scale } => Ok::<_, TensorError>(
+                    tensor::ops::nonlinearities::const_div(&x, f32::from(*scale).into()),
+                ),
+                LookupOp::Recip {
+                    input_scale,
+                    output_scale,
+                } => Ok::<_, TensorError>(tensor::ops::nonlinearities::recip(
+                    &x,
+                    input_scale.into(),
+                    output_scale.into(),
+                )),
+                LookupOp::LeakyReLU { slope: a } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::leakyrelu(&x, a.0.into()))
+                }
+                LookupOp::Sigmoid { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::sigmoid(&x, scale.into()))
+                }
+                LookupOp::Sqrt { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::sqrt(&x, scale.into()))
+                }
+                LookupOp::Rsqrt { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::rsqrt(&x, scale.into()))
+                }
+                LookupOp::Erf { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::erffunc(&x, scale.into()))
+                }
+                LookupOp::Exp { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::exp(&x, scale.into()))
+                }
+                LookupOp::Ln { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::ln(&x, scale.into()))
+                }
+                LookupOp::Cos { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::cos(&x, scale.into()))
+                }
+                LookupOp::ACos { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::acos(&x, scale.into()))
+                }
+                LookupOp::Cosh { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::cosh(&x, scale.into()))
+                }
+                LookupOp::ACosh { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::acosh(&x, scale.into()))
+                }
+                LookupOp::Sin { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::sin(&x, scale.into()))
+                }
+                LookupOp::ASin { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::asin(&x, scale.into()))
+                }
+                LookupOp::Sinh { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::sinh(&x, scale.into()))
+                }
+                LookupOp::ASinh { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::asinh(&x, scale.into()))
+                }
+                LookupOp::Tan { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::tan(&x, scale.into()))
+                }
+                LookupOp::ATan { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::atan(&x, scale.into()))
+                }
+                LookupOp::ATanh { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::atanh(&x, scale.into()))
+                }
+                LookupOp::Tanh { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::tanh(&x, scale.into()))
+                }
+                LookupOp::HardSwish { scale } => {
+                    Ok::<_, TensorError>(tensor::ops::nonlinearities::hardswish(&x, scale.into()))
+                }
+            }?;
 
-        let output = res.map(|x| i64_to_felt(x));
+        let output = res.map(|x| integer_rep_to_felt(x));
 
         Ok(ForwardResult { output })
     }
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F> for LookupOp {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for LookupOp {
     /// Returns a reference to the Any trait.
     fn as_any(&self) -> &dyn Any {
         self
@@ -243,7 +283,6 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
     /// Returns the name of the operation
     fn as_string(&self) -> String {
         match self {
-            LookupOp::Abs => "ABS".into(),
             LookupOp::Ceil { scale } => format!("CEIL(scale={})", scale),
             LookupOp::Floor { scale } => format!("FLOOR(scale={})", scale),
             LookupOp::Round { scale } => format!("ROUND(scale={})", scale),
@@ -252,11 +291,6 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
             LookupOp::KroneckerDelta => "K_DELTA".into(),
             LookupOp::Max { scale, a } => format!("MAX(scale={}, a={})", scale, a),
             LookupOp::Min { scale, a } => format!("MIN(scale={}, a={})", scale, a),
-            LookupOp::Sign => "SIGN".into(),
-            LookupOp::GreaterThan { a } => format!("GREATER_THAN(a={})", a),
-            LookupOp::GreaterThanEqual { a } => format!("GREATER_THAN_EQUAL(a={})", a),
-            LookupOp::LessThan { a } => format!("LESS_THAN(a={})", a),
-            LookupOp::LessThanEqual { a } => format!("LESS_THAN_EQUAL(a={})", a),
             LookupOp::Recip {
                 input_scale,
                 output_scale,
@@ -267,7 +301,6 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
             LookupOp::Div { denom, .. } => format!("DIV(denom={})", denom),
             LookupOp::Cast { scale } => format!("CAST(scale={})", scale),
             LookupOp::Ln { scale } => format!("LN(scale={})", scale),
-            LookupOp::ReLU => "RELU".to_string(),
             LookupOp::LeakyReLU { slope: a } => format!("L_RELU(slope={})", a),
             LookupOp::Sigmoid { scale } => format!("SIGMOID(scale={})", scale),
             LookupOp::Sqrt { scale } => format!("SQRT(scale={})", scale),
@@ -295,7 +328,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
         config: &mut crate::circuit::BaseConfig<F>,
         region: &mut RegionCtx<F>,
         values: &[ValTensor<F>],
-    ) -> Result<Option<ValTensor<F>>, Box<dyn Error>> {
+    ) -> Result<Option<ValTensor<F>>, CircuitError> {
         Ok(Some(layouts::nonlinearity(
             config,
             region,
@@ -305,19 +338,14 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
     }
 
     /// Returns the scale of the output of the operation.
-    fn out_scale(&self, inputs_scale: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>> {
+    fn out_scale(&self, inputs_scale: Vec<crate::Scale>) -> Result<crate::Scale, CircuitError> {
         let scale = match self {
             LookupOp::Cast { scale } => {
                 let in_scale = inputs_scale[0];
                 in_scale + multiplier_to_scale(1. / scale.0 as f64)
             }
             LookupOp::Recip { output_scale, .. } => multiplier_to_scale(output_scale.into()),
-            LookupOp::Sign
-            | LookupOp::GreaterThan { .. }
-            | LookupOp::LessThan { .. }
-            | LookupOp::GreaterThanEqual { .. }
-            | LookupOp::LessThanEqual { .. }
-            | LookupOp::KroneckerDelta => 0,
+            LookupOp::KroneckerDelta => 0,
             _ => inputs_scale[0],
         };
         Ok(scale)

src/circuit/ops/mod.rs

@@ -1,10 +1,10 @@
-use std::{any::Any, error::Error};
+use std::any::Any;
 
 use serde::{Deserialize, Serialize};
 
 use crate::{
     graph::quantize_tensor,
-    tensor::{self, IntoI64, Tensor, TensorType, ValTensor},
+    tensor::{self, Tensor, TensorType, ValTensor},
 };
 use halo2curves::ff::PrimeField;
 
@@ -15,6 +15,8 @@ pub mod base;
 ///
 pub mod chip;
 ///
+pub mod errors;
+///
 pub mod hybrid;
 /// Layouts for specific functions (composed of base ops)
 pub mod layouts;
@@ -25,14 +27,16 @@ pub mod poly;
 ///
 pub mod region;
 
+pub use errors::CircuitError;
+
 /// A struct representing the result of a forward pass.
 #[derive(Clone, Debug, PartialEq, Eq, PartialOrd, Ord, Serialize, Deserialize)]
-pub struct ForwardResult<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> {
+pub struct ForwardResult<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> {
     pub(crate) output: Tensor<F>,
 }
 
 /// A trait representing operations that can be represented as constraints in a circuit.
-pub trait Op<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64>:
+pub trait Op<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>:
     std::fmt::Debug + Send + Sync + Any
 {
     /// Returns a string representation of the operation.
@@ -44,10 +48,10 @@ pub trait Op<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64
         config: &mut crate::circuit::BaseConfig<F>,
         region: &mut RegionCtx<F>,
         values: &[ValTensor<F>],
-    ) -> Result<Option<ValTensor<F>>, Box<dyn Error>>;
+    ) -> Result<Option<ValTensor<F>>, CircuitError>;
 
     /// Returns the scale of the output of the operation.
-    fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>>;
+    fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, CircuitError>;
 
     /// Do any of the inputs to this op require homogenous input scales?
     fn requires_homogenous_input_scales(&self) -> Vec<usize> {
@@ -71,7 +75,7 @@ pub trait Op<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64
     fn as_any(&self) -> &dyn Any;
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Clone for Box<dyn Op<F>> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Clone for Box<dyn Op<F>> {
     fn clone(&self) -> Self {
         self.clone_dyn()
     }
@@ -138,8 +142,8 @@ pub struct Input {
     pub datum_type: InputType,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F> for Input {
-    fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Input {
+    fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, CircuitError> {
         Ok(self.scale)
     }
 
@@ -156,7 +160,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
         config: &mut crate::circuit::BaseConfig<F>,
         region: &mut RegionCtx<F>,
         values: &[ValTensor<F>],
-    ) -> Result<Option<ValTensor<F>>, Box<dyn Error>> {
+    ) -> Result<Option<ValTensor<F>>, CircuitError> {
         let value = values[0].clone();
         if !value.all_prev_assigned() {
             match self.datum_type {
@@ -193,8 +197,8 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
 #[derive(Clone, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, Serialize, Deserialize)]
 pub struct Unknown;
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F> for Unknown {
-    fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Unknown {
+    fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, CircuitError> {
         Ok(0)
     }
     fn as_any(&self) -> &dyn Any {
@@ -209,8 +213,8 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
         _: &mut crate::circuit::BaseConfig<F>,
         _: &mut RegionCtx<F>,
         _: &[ValTensor<F>],
-    ) -> Result<Option<ValTensor<F>>, Box<dyn Error>> {
-        Err(Box::new(super::CircuitError::UnsupportedOp))
+    ) -> Result<Option<ValTensor<F>>, CircuitError> {
+        Err(super::CircuitError::UnsupportedOp)
     }
 
     fn clone_dyn(&self) -> Box<dyn Op<F>> {
@@ -220,7 +224,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Op<F>
 
 ///
 #[derive(Clone, Debug, Serialize, Deserialize)]
-pub struct Constant<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> {
+pub struct Constant<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> {
     ///
     pub quantized_values: Tensor<F>,
     ///
@@ -230,7 +234,7 @@ pub struct Constant<F: PrimeField + TensorType + PartialOrd + std::hash::Hash +
     pub pre_assigned_val: Option<ValTensor<F>>,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Constant<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Constant<F> {
     ///
     pub fn new(quantized_values: Tensor<F>, raw_values: Tensor<f32>) -> Self {
         Self {
@@ -240,7 +244,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI64> Consta
         }
     }
     /// Rebase the scale of the constant
-    pub fn rebase_scale(&mut self, new_scale: crate::Scale) -> Result<(), Box<dyn Error>> {
+    pub fn rebase_scale(&mut self, new_scale: crate::Scale) -> Result<(), CircuitError> {
         let visibility = self.quantized_values.visibility().unwrap();
         self.quantized_values = quantize_tensor(self.raw_values.clone(), new_scale, &visibility)?;
         Ok(())
@@ -263,8 +267,7 @@ impl<
             + PartialOrd
             + std::hash::Hash
             + Serialize
-            + for<'de> Deserialize<'de>
-            + IntoI64,
+            + for<'de> Deserialize<'de>,
     > Op<F> for Constant<F>
 {
     fn as_any(&self) -> &dyn Any {
@@ -279,7 +282,7 @@ impl<
         config: &mut crate::circuit::BaseConfig<F>,
         region: &mut RegionCtx<F>,
         _: &[ValTensor<F>],
-    ) -> Result<Option<ValTensor<F>>, Box<dyn Error>> {
+    ) -> Result<Option<ValTensor<F>>, CircuitError> {
         let value = if let Some(value) = &self.pre_assigned_val {
             value.clone()
         } else {
@@ -293,7 +296,7 @@ impl<
         Box::new(self.clone()) // Forward to the derive(Clone) impl
     }
 
-    fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>> {
+    fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, CircuitError> {
         Ok(self.quantized_values.scale().unwrap())
     }