ci: update version string in docs

---------

Co-authored-by: dante <45801863+alexander-camuto@users.noreply.github.com>

.github/workflows/engine.yml

@@ -1,4 +1,4 @@
-name: Build and Publish EZKL npm packages (wasm bindings and in-browser evm verifier)
+name: Build and Publish EZKL Engine npm package
 
 on:
   workflow_dispatch:
@@ -22,7 +22,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
@@ -30,13 +30,13 @@ jobs:
         run: rustup target add wasm32-unknown-unknown
 
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-01-04-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
       - name: Install binaryen
         run: |
-            set -e
-            curl -L https://github.com/WebAssembly/binaryen/releases/download/version_116/binaryen-version_116-x86_64-linux.tar.gz | tar xzf -
-            export PATH=$PATH:$PWD/binaryen-version_116/bin
-            wasm-opt --version
+          set -e
+          curl -L https://github.com/WebAssembly/binaryen/releases/download/version_116/binaryen-version_116-x86_64-linux.tar.gz | tar xzf -
+          export PATH=$PATH:$PWD/binaryen-version_116/bin
+          wasm-opt --version
       - name: Build wasm files for both web and nodejs compilation targets
         run: |
           wasm-pack build --release --target nodejs --out-dir ./pkg/nodejs . -- -Z build-std="panic_abort,std"
@@ -62,7 +62,7 @@ jobs:
               "web/ezkl_bg.wasm",
               "web/ezkl.js",
               "web/ezkl.d.ts",
-              "web/snippets/wasm-bindgen-rayon-7afa899f36665473/src/workerHelpers.js",
+              "web/snippets/**/*",
               "web/package.json",
               "web/utils.js",
               "ezkl.d.ts"
@@ -79,6 +79,10 @@ jobs:
         run: |
           sed -i "3s|.*|imports['env'] = {memory: new WebAssembly.Memory({initial:20,maximum:65536,shared:true})}|" pkg/nodejs/ezkl.js
 
+      - name: Replace `import.meta.url` with `import.meta.resolve` definition in workerHelpers.js
+        run: |
+          find ./pkg/web/snippets -type f -name "*.js" -exec sed -i "s|import.meta.url|import.meta.resolve|" {} +
+
       - name: Add serialize and deserialize methods to nodejs bundle
         run: |
           echo '
@@ -92,7 +96,7 @@ jobs:
             const jsonObject = JSONBig.parse(string);
             return jsonObject;
           }
-          
+
           function serialize(data) { // data is an object // return a Uint8ClampedArray
             // Step 1: Stringify the Object with BigInt support
             if (typeof data === "object") {
@@ -100,11 +104,11 @@ jobs:
             }
             // Step 2: Encode the JSON String
             const uint8Array = new TextEncoder().encode(data);
-          
+
             // Step 3: Convert to Uint8ClampedArray
             return new Uint8ClampedArray(uint8Array.buffer);
           }
-          
+
           module.exports = {
             deserialize,
             serialize
@@ -123,7 +127,7 @@ jobs:
             const jsonObject = parse(string);
             return jsonObject;
           }
-          
+
           export function serialize(data) { // data is an object // return a Uint8ClampedArray
             // Step 1: Stringify the Object with BigInt support
             if (typeof data === "object") {
@@ -131,7 +135,7 @@ jobs:
             }
             // Step 2: Encode the JSON String
             const uint8Array = new TextEncoder().encode(data);
-          
+
             // Step 3: Convert to Uint8ClampedArray
             return new Uint8ClampedArray(uint8Array.buffer);
           }
@@ -174,40 +178,3 @@ 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: 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 }}\"|" 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: 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
-          npm install
-          npm run build
-          npm ci
-          npm publish
-        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-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - name: nanoGPT Mock

.github/workflows/pypi-gpu.yml

@@ -26,7 +26,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.7
+          python-version: 3.12
           architecture: x64
 
       - name: Set pyproject.toml version to match github tag

.github/workflows/pypi.yml

@@ -25,7 +25,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.7
+          python-version: 3.12
           architecture: x64
 
       - name: Set Cargo.toml version to match github tag
@@ -70,7 +70,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.7
+          python-version: 3.12
           architecture: ${{ matrix.target }}
 
       - name: Set Cargo.toml version to match github tag
@@ -115,7 +115,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.7
+          python-version: 3.12
           architecture: x64
 
       - name: Set Cargo.toml version to match github tag
@@ -128,6 +128,7 @@ jobs:
           mv Cargo.lock Cargo.lock.orig
           sed "s/0\\.0\\.0/${RELEASE_TAG//v}/" Cargo.lock.orig >Cargo.lock
 
+
       - name: Install required libraries
         shell: bash
         run: |
@@ -139,6 +140,20 @@ jobs:
           target: ${{ matrix.target }}
           manylinux: auto
           args: --release --out dist --features python-bindings
+          before-script-linux: |
+            # If we're running on rhel centos, install needed packages.
+            if command -v yum &> /dev/null; then
+                yum update -y && yum install -y perl-core openssl openssl-devel pkgconfig libatomic
+
+                # If we're running on i686 we need to symlink libatomic
+                # in order to build openssl with -latomic flag.
+                if [[ ! -d "/usr/lib64" ]]; then
+                    ln -s /usr/lib/libatomic.so.1 /usr/lib/libatomic.so
+                fi
+            else
+                # If we're running on debian-based system.
+                apt update -y && apt-get install -y libssl-dev openssl pkg-config
+            fi
 
       - name: Install built wheel
         if: matrix.target == 'x86_64'
@@ -162,7 +177,7 @@ jobs:
   #   - uses: actions/checkout@v4
   #   - uses: actions/setup-python@v4
   #     with:
-  #       python-version: 3.7
+  #       python-version: 3.12
 
   #   - name: Install cross-compilation tools for aarch64
   #     if: matrix.target == 'aarch64'
@@ -214,7 +229,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.7
+          python-version: 3.12
           architecture: x64
 
       - name: Set Cargo.toml version to match github tag
@@ -249,7 +264,7 @@ jobs:
             apk add py3-pip
             pip3 install -U pip
             python3 -m venv .venv
-            source .venv/bin/activate            
+            source .venv/bin/activate
             pip3 install ezkl --no-index --find-links /io/dist/ --force-reinstall
             python3 -c "import ezkl"
 
@@ -273,7 +288,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.7
+          python-version: 3.12
 
       - name: Set Cargo.toml version to match github tag
         shell: bash
@@ -345,3 +360,17 @@ jobs:
         with:
           repository-url: https://test.pypi.org/legacy/
           packages-dir: ./
+
+  doc-publish:
+    name: Trigger ReadTheDocs Build
+    runs-on: ubuntu-latest
+    needs: pypi-publish
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Trigger RTDs build
+        uses: dfm/rtds-action@v1
+        with:
+          webhook_url: ${{ secrets.RTDS_WEBHOOK_URL }}
+          webhook_token: ${{ secrets.RTDS_WEBHOOK_TOKEN }}
+          commit_ref: ${{ github.ref_name }}

.github/workflows/release.yml

@@ -32,7 +32,7 @@ jobs:
           token: ${{ secrets.RELEASE_TOKEN }}
           tag_name: ${{ env.EZKL_VERSION }}
 
-  build-release-gpu: 
+  build-release-gpu:
     name: build-release-gpu
     needs: ["create-release"]
     runs-on: GPU
@@ -45,7 +45,7 @@ jobs:
     steps:
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - name: Checkout repo
@@ -60,16 +60,15 @@ jobs:
       - name: Set Cargo.toml version to match github tag
         shell: bash
         run: |
-            mv Cargo.toml Cargo.toml.orig
-            sed "s/0\\.0\\.0/${EZKL_VERSION//v}/" Cargo.toml.orig >Cargo.toml
-            mv Cargo.lock Cargo.lock.orig
-            sed "s/0\\.0\\.0/${EZKL_VERSION//v}/" Cargo.lock.orig >Cargo.lock
-
+          mv Cargo.toml Cargo.toml.orig
+          sed "s/0\\.0\\.0/${EZKL_VERSION//v}/" Cargo.toml.orig >Cargo.toml
+          mv Cargo.lock Cargo.lock.orig
+          sed "s/0\\.0\\.0/${EZKL_VERSION//v}/" Cargo.lock.orig >Cargo.lock
 
       - name: Install dependencies
         shell: bash
         run: |
-            sudo apt-get update
+          sudo apt-get update
 
       - name: Build release binary
         run: cargo build --release -Z sparse-registry --features icicle
@@ -91,7 +90,6 @@ jobs:
           asset_name: ${{ env.ASSET }}
           asset_content_type: application/octet-stream
 
-
   build-release:
     name: build-release
     needs: ["create-release"]

.github/workflows/rust.yml

@@ -26,7 +26,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - name: Build
@@ -38,7 +38,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - name: Docs
@@ -50,7 +50,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -73,7 +73,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -106,7 +106,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           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-2024-01-04
+          toolchain: nightly-2024-02-06
           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-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -184,12 +184,12 @@ jobs:
 
   wasm32-tests:
     runs-on: ubuntu-latest
-    # needs: [build,  library-tests, docs]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
@@ -199,7 +199,7 @@ jobs:
       - name: Install wasm32-unknown-unknown
         run: rustup target add wasm32-unknown-unknown
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-01-04-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2024-02-06-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
@@ -207,12 +207,12 @@ jobs:
 
   tutorial:
     runs-on: ubuntu-latest
-    needs: [build, library-tests, docs]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -224,12 +224,12 @@ jobs:
 
   mock-proving-tests:
     runs-on: non-gpu
-    # needs: [build,  library-tests, docs]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -281,12 +281,12 @@ jobs:
 
   prove-and-verify-evm-tests:
     runs-on: non-gpu
-    needs: [build, library-tests]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -303,10 +303,12 @@ jobs:
         with:
           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
       - name: Install dependencies for js tests and in-browser-evm-verifier package
         run: |
-          pnpm install --no-frozen-lockfile
-          pnpm install --dir ./in-browser-evm-verifier --no-frozen-lockfile
+          pnpm install --frozen-lockfile
+          pnpm install --dir ./in-browser-evm-verifier --frozen-lockfile
         env:
           CI: false
           NODE_ENV: development
@@ -324,7 +326,7 @@ jobs:
       - 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 b320f350156a0fb15c2eb13dc380deb2367c4474 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --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)
@@ -352,12 +354,12 @@ jobs:
 
   prove-and-verify-tests:
     runs-on: non-gpu
-    needs: [build, library-tests]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
@@ -365,7 +367,7 @@ jobs:
         run: rustup target add wasm32-unknown-unknown
 
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-01-04-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
       - uses: actions/checkout@v3
       - name: Use pnpm 8
         uses: pnpm/action-setup@v2
@@ -378,7 +380,7 @@ jobs:
           cache: "pnpm"
       - name: Install dependencies for js tests
         run: |
-          pnpm install --no-frozen-lockfile
+          pnpm install --frozen-lockfile
         env:
           CI: false
           NODE_ENV: development
@@ -429,11 +431,11 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-01-04-x86_64-unknown-linux-gnu
+        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:
@@ -458,12 +460,12 @@ jobs:
 
   prove-and-verify-mock-aggr-tests:
     runs-on: self-hosted
-    needs: [build, library-tests]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -481,7 +483,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -493,12 +495,12 @@ jobs:
 
   prove-and-verify-aggr-tests:
     runs-on: large-self-hosted
-    needs: [build, library-tests]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -510,12 +512,12 @@ jobs:
 
   prove-and-verify-aggr-evm-tests:
     runs-on: large-self-hosted
-    needs: [build, library-tests]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -525,7 +527,7 @@ jobs:
       - 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 b320f350156a0fb15c2eb13dc380deb2367c4474 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --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
 
@@ -536,7 +538,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -555,18 +557,20 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.7"
+          python-version: "3.12"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           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: Setup Virtual Env and Install python dependencies
-        run: python -m venv .env; source .env/bin/activate; pip install -r requirements.txt;
+        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 b320f350156a0fb15c2eb13dc380deb2367c4474 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
       - name: Build python ezkl
         run: source .env/bin/activate; unset CONDA_PREFIX; maturin develop --features python-bindings --release
       - name: Run pytest
@@ -574,15 +578,15 @@ jobs:
 
   accuracy-measurement-tests:
     runs-on: ubuntu-latest-32-cores
-    # needs: [build, library-tests, docs]
+    needs: [build, library-tests, docs, python-tests, python-integration-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.7"
+          python-version: "3.12"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -590,7 +594,7 @@ jobs:
           crate: cargo-nextest
           locked: true
       - name: Setup Virtual Env and Install python dependencies
-        run: python -m venv .env; source .env/bin/activate; pip install -r requirements.txt;
+        run: python -m venv .env --clear; source .env/bin/activate; pip install -r requirements.txt;
       - name: Build python ezkl
         run: source .env/bin/activate; unset CONDA_PREFIX; maturin develop --features python-bindings --release
       - name: Div rebase
@@ -606,14 +610,32 @@ jobs:
 
   python-integration-tests:
     runs-on: large-self-hosted
+    services:
+      # Label used to access the service container
+      postgres:
+        # Docker Hub image
+        image: postgres
+        env:
+          POSTGRES_USER: ubuntu
+          POSTGRES_HOST_AUTH_METHOD: trust
+        # Set health checks to wait until postgres has started
+        options: >-
+          --health-cmd pg_isready
+          --health-interval 10s
+          --health-timeout 5s
+          --health-retries 5
+          -v /var/run/postgresql:/var/run/postgresql
+        ports:
+          # Maps tcp port 5432 on service container to the host
+          - 5432:5432
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.10"
+          python-version: "3.11"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-01-04
+          toolchain: nightly-2024-02-06
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -623,11 +645,17 @@ jobs:
       - 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 b320f350156a0fb15c2eb13dc380deb2367c4474 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
+      - name: Install pip
+        run: python -m ensurepip --upgrade
       - name: Setup Virtual Env and Install python dependencies
-        run: python -m venv .env; source .env/bin/activate; pip install -r requirements.txt;
+        run: python -m venv .env --clear; source .env/bin/activate; pip install -r requirements.txt; python -m ensurepip --upgrade
       - name: Build python ezkl
         run: source .env/bin/activate; unset CONDA_PREFIX; maturin develop --features python-bindings --release
+      - name: Postgres tutorials
+        run: source .env/bin/activate; cargo nextest run py_tests::tests::postgres_ --no-capture
+      - name: Tictactoe tutorials
+        run: source .env/bin/activate; cargo nextest run py_tests::tests::tictactoe_ --test-threads 1
       # - name: authenticate-kaggle-cli
       #   shell: bash
       #   env:
@@ -643,7 +671,3 @@ jobs:
         run: source .env/bin/activate; cargo nextest run py_tests::tests::voice_
       - name: NBEATS tutorial
         run: source .env/bin/activate; cargo nextest run py_tests::tests::nbeats_
-      - name: Tictactoe tutorials
-        run: source .env/bin/activate; cargo nextest run py_tests::tests::tictactoe_
-      # - name: Postgres tutorials
-      #   run: source .env/bin/activate; cargo nextest run py_tests::tests::postgres_ --test-threads 1

.github/workflows/tagging.yml

@@ -14,6 +14,40 @@ jobs:
       - uses: actions/checkout@v4
       - name: Bump version and push tag
         id: tag_version
-        uses: mathieudutour/github-tag-action@v6.1
+        uses: mathieudutour/github-tag-action@v6.2
         with:
           github_token: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Set Cargo.toml version to match github tag for docs
+        shell: bash
+        env:
+          RELEASE_TAG: ${{ steps.tag_version.outputs.new_tag }}
+        run: |
+          mv docs/python/src/conf.py docs/python/src/conf.py.orig
+          sed "s/0\\.0\\.0/${RELEASE_TAG//v}/" docs/python/src/conf.py.orig >docs/python/src/conf.py
+          rm docs/python/src/conf.py.orig
+          mv docs/python/requirements-docs.txt docs/python/requirements-docs.txt.orig
+          sed "s/0\\.0\\.0/${RELEASE_TAG//v}/" docs/python/requirements-docs.txt.orig >docs/python/requirements-docs.txt
+          rm docs/python/requirements-docs.txt.orig
+
+      - name: Commit files and create tag
+        env:
+          RELEASE_TAG: ${{ steps.tag_version.outputs.new_tag }}
+        run: |
+          git config --local user.email "github-actions[bot]@users.noreply.github.com"
+          git config --local user.name "github-actions[bot]"
+          git fetch --tags
+          git checkout -b release-$RELEASE_TAG
+          git add .
+          git commit -m "ci: update version string in docs"
+          git tag -d $RELEASE_TAG
+          git tag $RELEASE_TAG
+
+      - name: Push changes
+        uses: ad-m/github-push-action@master
+        env:
+          RELEASE_TAG: ${{ steps.tag_version.outputs.new_tag }}
+        with:
+          branch: release-${{ steps.tag_version.outputs.new_tag }}
+          force: true
+          tags: true

.github/workflows/verify.yml

@@ -0,0 +1,54 @@
+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 }}\"|" 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: 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 }}

.gitignore

@@ -48,4 +48,6 @@ node_modules
 /dist
 timingData.json
 !tests/wasm/pk.key
-!tests/wasm/vk.key
+!tests/wasm/vk.key
+docs/python/build
+!tests/wasm/vk_aggr.key

.python-version

@@ -0,0 +1 @@
+3.12.1

.readthedocs.yaml

@@ -0,0 +1,26 @@
+# .readthedocs.yaml
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+version: 2
+
+build:
+  os: ubuntu-22.04
+  tools:
+    python: "3.12"
+
+# Build documentation in the "docs/" directory with Sphinx
+sphinx:
+  configuration: ./docs/python/src/conf.py
+
+# Optionally build your docs in additional formats such as PDF and ePub
+# formats:
+#    - pdf
+#    - epub
+
+# Optional but recommended, declare the Python requirements required
+# to build your documentation
+# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
+python:
+  install:
+  - requirements: ./docs/python/requirements-docs.txt

Cargo.toml

@@ -15,14 +15,14 @@ crate-type = ["cdylib", "rlib"]
 
 
 [dependencies]
-halo2_gadgets = { git = "https://github.com/zkonduit/halo2", branch = "main" }
-halo2_proofs = { git = "https://github.com/zkonduit/halo2", branch = "main" }
+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",
 ] }
 rand = { version = "0.8", default_features = false }
 itertools = { version = "0.10.3", default_features = false }
-clap = { version = "4.3.3", features = ["derive"] }
+clap = { version = "4.5.3", features = ["derive"] }
 serde = { version = "1.0.126", features = ["derive"], optional = true }
 serde_json = { version = "1.0.97", default_features = false, features = [
     "float_roundtrip",
@@ -80,7 +80,7 @@ pyo3-asyncio = { version = "0.20.0", features = [
     "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 = "7b1aa33b2f7d1f19b80e270c83320f0f94daff69", default_features = false, optional = true }
+tract-onnx = { git = "https://github.com/sonos/tract/", rev = "681a096f02c9d7d363102d9fb0e446d1710ac2c8", default_features = false, optional = true }
 tabled = { version = "0.12.0", optional = true }
 
 
@@ -95,10 +95,10 @@ getrandom = { version = "0.2.8", features = ["js"] }
 instant = { version = "0.1", features = ["wasm-bindgen", "inaccurate"] }
 
 [target.'cfg(all(target_arch = "wasm32", target_os = "unknown"))'.dependencies]
-wasm-bindgen-rayon = { version = "1.0", optional = true }
-wasm-bindgen-test = "0.3.34"
-serde-wasm-bindgen = "0.4"
-wasm-bindgen = { version = "0.2.81", features = ["serde-serialize"] }
+wasm-bindgen-rayon = { version = "1.2.1", optional = true }
+wasm-bindgen-test = "0.3.42"
+serde-wasm-bindgen = "0.6.5"
+wasm-bindgen = { version = "0.2.92", features = ["serde-serialize"] }
 console_error_panic_hook = "0.1.7"
 wasm-bindgen-console-logger = "0.1.1"
 
@@ -203,5 +203,9 @@ no-banner = []
 [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" }
+
+
 [profile.release]
 rustflags = ["-C", "relocation-model=pic"]

benches/accum_conv.rs

@@ -70,8 +70,8 @@ impl Circuit<Fr> for MyCircuit {
                         &mut region,
                         &[self.image.clone(), self.kernel.clone(), self.bias.clone()],
                         Box::new(PolyOp::Conv {
-                            padding: [(0, 0); 2],
-                            stride: (1, 1),
+                            padding: vec![(0, 0)],
+                            stride: vec![1; 2],
                         }),
                     )
                     .unwrap();

benches/accum_sumpool.rs

@@ -65,9 +65,9 @@ impl Circuit<Fr> for MyCircuit {
                         &mut region,
                         &[self.image.clone()],
                         Box::new(HybridOp::SumPool {
-                            padding: [(0, 0); 2],
-                            stride: (1, 1),
-                            kernel_shape: (2, 2),
+                            padding: vec![(0, 0); 2],
+                            stride: vec![1, 1],
+                            kernel_shape: vec![2, 2],
                             normalized: false,
                         }),
                     )

benches/poseidon.rs

@@ -1,3 +1,5 @@
+use std::collections::HashMap;
+
 use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
 use ezkl::circuit::modules::poseidon::spec::{PoseidonSpec, POSEIDON_RATE, POSEIDON_WIDTH};
 use ezkl::circuit::modules::poseidon::{PoseidonChip, PoseidonConfig};
@@ -48,7 +50,7 @@ impl Circuit<Fr> for MyCircuit {
     ) -> Result<(), Error> {
         let chip: PoseidonChip<PoseidonSpec, POSEIDON_WIDTH, POSEIDON_RATE, L> =
             PoseidonChip::new(config);
-        chip.layout(&mut layouter, &[self.image.clone()], 0)?;
+        chip.layout(&mut layouter, &[self.image.clone()], 0, &mut HashMap::new())?;
         Ok(())
     }
 }

docs/python/build.sh

@@ -0,0 +1,2 @@
+#!/bin/sh
+sphinx-build ./src build

docs/python/requirements-docs.txt

@@ -0,0 +1,4 @@
+ezkl==10.3.4
+sphinx
+sphinx-rtd-theme
+sphinxcontrib-napoleon

docs/python/src/conf.py

@@ -0,0 +1,29 @@
+import ezkl
+
+project = 'ezkl'
+release = '10.3.4'
+version = release
+
+
+extensions = [
+    'sphinx.ext.autodoc',
+    'sphinx.ext.autosummary',
+    'sphinx.ext.intersphinx',
+    'sphinx.ext.todo',
+    'sphinx.ext.inheritance_diagram',
+    'sphinx.ext.autosectionlabel',
+    'sphinx.ext.napoleon',
+    'sphinx_rtd_theme',
+]
+
+autosummary_generate = True
+autosummary_imported_members = True
+
+templates_path = ['_templates']
+exclude_patterns = []
+
+# -- Options for HTML output -------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
+
+html_theme = 'sphinx_rtd_theme'
+html_static_path = ['_static']

docs/python/src/index.rst

@@ -0,0 +1,11 @@
+.. extension documentation master file, created by
+   sphinx-quickstart on Mon Jun 19 15:02:05 2023.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+ezkl python bindings
+================================================
+
+.. automodule:: ezkl
+   :members:
+   :undoc-members:

examples/conv2d_mnist/main.rs

@@ -203,8 +203,8 @@ where
                     let mut region = RegionCtx::new(region, 0, NUM_INNER_COLS);
 
                     let op = PolyOp::Conv {
-                        padding: [(PADDING, PADDING); 2],
-                        stride: (STRIDE, STRIDE),
+                        padding: vec![(PADDING, PADDING); 2],
+                        stride: vec![STRIDE; 2],
                     };
                     let x = config
                         .layer_config

examples/notebooks/keras_simple_demo.ipynb

@@ -67,6 +67,7 @@
                 "model.add(Dense(128, activation='relu'))\n",
                 "model.add(Dropout(0.5))\n",
                 "model.add(Dense(10, activation='softmax'))\n",
+                "model.output_names=['output']\n",
                 "\n",
                 "\n",
                 "# Train the model as you like here (skipped for brevity)\n",

examples/notebooks/mean_postgres.ipynb

@@ -7,9 +7,9 @@
         "## Mean of ERC20 transfer amounts\n",
         "\n",
         "This notebook shows how to calculate the mean of ERC20 transfer amounts, pulling data in from a Postgres database. First we install and get the necessary libraries running. \n",
-        "The first of which is [e2pg](https://github.com/indexsupply/x/tree/main/docs/e2pg), which is a library that allows us to pull data from the Ethereum blockchain into a Postgres database.\n",
+        "The first of which is [shovel](https://indexsupply.com/shovel/docs/#getting-started), which is a library that allows us to pull data from the Ethereum blockchain into a Postgres database.\n",
         "\n",
-        "Make sure you install postgres if needed https://postgresapp.com/. \n",
+        "Make sure you install postgres if needed https://indexsupply.com/shovel/docs/#getting-started. \n",
         "\n"
       ]
     },
@@ -21,23 +21,81 @@
       "source": [
         "import os\n",
         "import getpass\n",
-        "\n",
+        "import json\n",
+        "import time\n",
+        "import subprocess\n",
         "\n",
         "# swap out for the relevant linux/amd64, darwin/arm64, darwin/amd64, windows/amd64\n",
-        "os.system(\"curl -LO https://indexsupply.net/bin/main/linux/amd64/e2pg\")\n",
-        "os.system(\"chmod +x e2pg\")\n",
+        "os.system(\"curl -LO https://indexsupply.net/bin/1.0/linux/amd64/shovel\")\n",
+        "os.system(\"chmod +x shovel\")\n",
         "\n",
         "\n",
-        "os.environ[\"PG_URL\"] = \"postgresql://\" + getpass.getuser() + \":@localhost:5432/e2pg\"\n",
-        "os.environ[\"RLPS_URL\"] = \"https://1.rlps.indexsupply.net\"\n",
+        "os.environ[\"PG_URL\"] = \"postgres://\" + getpass.getuser() + \":@localhost:5432/shovel\"\n",
+        "\n",
+        "# create a config.json file with the following contents\n",
+        "config = {\n",
+        "  \"pg_url\": \"$PG_URL\",\n",
+        "  \"eth_sources\": [\n",
+        "    {\"name\": \"mainnet\", \"chain_id\": 1, \"url\": \"https://ethereum-rpc.publicnode.com\"},\n",
+        "    {\"name\": \"base\", \"chain_id\": 8453, \"url\": \"https://base-rpc.publicnode.com\"}\n",
+        "  ],\n",
+        "  \"integrations\": [{\n",
+        "    \"name\": \"usdc_transfer\",\n",
+        "    \"enabled\": True,\n",
+        "    \"sources\": [{\"name\": \"mainnet\"}, {\"name\": \"base\"}],\n",
+        "    \"table\": {\n",
+        "      \"name\": \"usdc\",\n",
+        "      \"columns\": [\n",
+        "        {\"name\": \"log_addr\",  \"type\": \"bytea\"},\n",
+        "        {\"name\": \"block_num\", \"type\": \"numeric\"},\n",
+        "        {\"name\": \"f\",         \"type\": \"bytea\"},\n",
+        "        {\"name\": \"t\",         \"type\": \"bytea\"},\n",
+        "        {\"name\": \"v\",         \"type\": \"numeric\"}\n",
+        "      ]\n",
+        "    },\n",
+        "    \"block\": [\n",
+        "      {\"name\": \"block_num\", \"column\": \"block_num\"},\n",
+        "      {\n",
+        "        \"name\": \"log_addr\",\n",
+        "        \"column\": \"log_addr\",\n",
+        "        \"filter_op\": \"contains\",\n",
+        "        \"filter_arg\": [\n",
+        "          \"a0b86991c6218b36c1d19d4a2e9eb0ce3606eb48\",\n",
+        "          \"833589fCD6eDb6E08f4c7C32D4f71b54bdA02913\"\n",
+        "        ]\n",
+        "      }\n",
+        "    ],\n",
+        "    \"event\": {\n",
+        "      \"name\": \"Transfer\",\n",
+        "      \"type\": \"event\",\n",
+        "      \"anonymous\": False,\n",
+        "      \"inputs\": [\n",
+        "        {\"indexed\": True,  \"name\": \"from\",  \"type\": \"address\", \"column\": \"f\"},\n",
+        "        {\"indexed\": True,  \"name\": \"to\",    \"type\": \"address\", \"column\": \"t\"},\n",
+        "        {\"indexed\": False, \"name\": \"value\", \"type\": \"uint256\", \"column\": \"v\"}\n",
+        "      ]\n",
+        "    }\n",
+        "  }]\n",
+        "}\n",
+        "\n",
+        "# write the config to a file\n",
+        "with open(\"config.json\", \"w\") as f:\n",
+        "  f.write(json.dumps(config))\n",
+        "\n",
         "\n",
         "# print the two env variables\n",
         "os.system(\"echo $PG_URL\")\n",
-        "os.system(\"echo $RLPS_URL\")\n",
         "\n",
-        "os.system(\"createdb -h localhost -p 5432 e2pg\")\n",
-        "# equivalent of nohup ./e2pg -reset -e $RLPS_URL -pg $PG_URL &\n",
-        "e2pg_process = os.system(\"nohup ./e2pg -e $RLPS_URL -pg $PG_URL &\")\n",
+        "os.system(\"createdb -h localhost -p 5432 shovel\")\n",
+        "\n",
+        "os.system(\"echo shovel is now installed. starting:\")\n",
+        "\n",
+        "command = [\"./shovel\", \"-config\", \"config.json\"]\n",
+        "subprocess.Popen(command)\n",
+        "\n",
+        "os.system(\"echo shovel started.\")\n",
+        "\n",
+        "time.sleep(5)\n",
         "\n"
       ]
     },
@@ -79,11 +137,13 @@
         "import json\n",
         "import os\n",
         "\n",
-        "# import logging\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)"
+        "import logging\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",
+        "\n",
+        "print(\"ezkl version: \", ezkl.__version__)"
       ]
     },
     {
@@ -176,6 +236,7 @@
       },
       "outputs": [],
       "source": [
+        "import getpass\n",
         "# make an input.json file from the df above\n",
         "input_filename = os.path.join('input.json')\n",
         "\n",
@@ -183,9 +244,9 @@
         "  \"host\": \"localhost\",\n",
         "  # make sure you replace this with your own username\n",
         "  \"user\": getpass.getuser(),\n",
-        "  \"dbname\": \"e2pg\",\n",
+        "  \"dbname\": \"shovel\",\n",
         "  \"password\": \"\",\n",
-        "  \"query\": \"SELECT value FROM erc20_transfers ORDER BY block_number DESC LIMIT 5\",\n",
+        "  \"query\": \"SELECT v FROM usdc ORDER BY block_num DESC LIMIT 5\",\n",
         "  \"port\": \"5432\",\n",
         "})\n",
         "\n",
@@ -194,7 +255,7 @@
         "\n",
         "\n",
         "    # Serialize data into file:\n",
-        "json.dump( pg_input_file, open(input_filename, 'w' ))\n"
+        "json.dump(pg_input_file, open(input_filename, 'w' ))\n"
       ]
     },
     {
@@ -210,9 +271,9 @@
         "  \"host\": \"localhost\",\n",
         "  # make sure you replace this with your own username\n",
         "  \"user\": getpass.getuser(),\n",
-        "  \"dbname\": \"e2pg\",\n",
+        "  \"dbname\": \"shovel\",\n",
         "  \"password\": \"\",\n",
-        "  \"query\": \"SELECT value FROM erc20_transfers ORDER BY block_number DESC LIMIT 20\",\n",
+        "  \"query\": \"SELECT v FROM usdc ORDER BY block_num DESC LIMIT 20\",\n",
         "  \"port\": \"5432\",\n",
         "})\n",
         "\n",
@@ -229,22 +290,6 @@
         "**EZKL Workflow**"
       ]
     },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "onnx_filename = os.path.join('lol.onnx')\n",
-        "compiled_filename = os.path.join('lol.compiled')\n",
-        "settings_filename = os.path.join('settings.json')\n",
-        "\n",
-        "ezkl.gen_settings(onnx_filename, settings_filename)\n",
-        "\n",
-        "ezkl.calibrate_settings(\n",
-        "    input_filename, onnx_filename, settings_filename, \"resources\")"
-      ]
-    },
     {
       "cell_type": "code",
       "execution_count": null,
@@ -253,10 +298,21 @@
       },
       "outputs": [],
       "source": [
-        "# setup kzg params\n",
-        "params_path = os.path.join('kzg.params')\n",
+        "import subprocess\n",
+        "import os\n",
         "\n",
-        "res = ezkl.get_srs(params_path, settings_filename)"
+        "onnx_filename = os.path.join('lol.onnx')\n",
+        "compiled_filename = os.path.join('lol.compiled')\n",
+        "settings_filename = os.path.join('settings.json')\n",
+        "\n",
+        "# Generate settings using ezkl\n",
+        "res = ezkl.gen_settings(onnx_filename, settings_filename)\n",
+        "\n",
+        "assert res == True\n",
+        "\n",
+        "res = ezkl.calibrate_settings(input_filename, onnx_filename, settings_filename, \"resources\")\n",
+        "\n",
+        "assert res == True"
       ]
     },
     {
@@ -306,16 +362,13 @@
       "source": [
         "pk_path = os.path.join('test.pk')\n",
         "vk_path = os.path.join('test.vk')\n",
-        "params_path = os.path.join('kzg.params')\n",
         "\n",
         "\n",
         "# setup the proof\n",
         "res = ezkl.setup(\n",
         "        compiled_filename,\n",
         "        vk_path,\n",
-        "        pk_path,\n",
-        "        params_path,\n",
-        "        settings_filename,\n",
+        "        pk_path\n",
         "    )\n",
         "\n",
         "assert res == True\n",
@@ -331,11 +384,14 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "\n",
         "witness_path = \"witness.json\"\n",
         "\n",
-        "res = ezkl.gen_witness(input_filename, compiled_filename, witness_path)\n",
-        "assert os.path.isfile(witness_path)"
+        "# generate the witness\n",
+        "res = ezkl.gen_witness(\n",
+        "        input_filename,\n",
+        "        compiled_filename,\n",
+        "        witness_path\n",
+        "    )\n"
       ]
     },
     {
@@ -360,73 +416,14 @@
         "        compiled_filename,\n",
         "        pk_path,\n",
         "        proof_path,\n",
-        "        params_path,\n",
-        "        \"single\",\n",
+        "        \"single\"\n",
         "    )\n",
         "\n",
         "\n",
+        "print(\"proved\")\n",
+        "\n",
         "assert os.path.isfile(proof_path)\n",
-        "\n",
-        "# verify\n",
-        "res = ezkl.verify(\n",
-        "        proof_path,\n",
-        "        settings_filename,\n",
-        "        vk_path,\n",
-        "        params_path,\n",
-        "    )\n",
-        "\n",
-        "assert res == True\n",
-        "print(\"verified\")"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "W7tAa-DFAtvS"
-      },
-      "source": [
-        "# Part 2 (Using the ZK Computational Graph Onchain!)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "8Ym91kaVAIB6"
-      },
-      "source": [
-        "**Now How Do We Do It Onchain?????**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 339
-        },
-        "id": "fodkNgwS70FM",
-        "outputId": "827b5efd-f74f-44de-c114-861b3a86daf2"
-      },
-      "outputs": [],
-      "source": [
-        "# first we need to create evm verifier\n",
-        "print(vk_path)\n",
-        "print(params_path)\n",
-        "print(settings_filename)\n",
-        "\n",
-        "\n",
-        "abi_path = 'test.abi'\n",
-        "sol_code_path = 'test.sol'\n",
-        "\n",
-        "res = ezkl.create_evm_verifier(\n",
-        "        vk_path,\n",
-        "        params_path,\n",
-        "        settings_filename,\n",
-        "        sol_code_path,\n",
-        "        abi_path,\n",
-        "    )\n",
-        "assert res == True"
+        "\n"
       ]
     },
     {
@@ -435,51 +432,8 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "# Make sure anvil is running locally first\n",
-        "# run with $ anvil -p 3030\n",
-        "# we use the default anvil node here\n",
-        "import json\n",
-        "\n",
-        "address_path = os.path.join(\"address.json\")\n",
-        "\n",
-        "res = ezkl.deploy_evm(\n",
-        "    address_path,\n",
-        "    sol_code_path,\n",
-        "    'http://127.0.0.1:3030'\n",
-        ")\n",
-        "\n",
-        "assert res == True\n",
-        "\n",
-        "with open(address_path, 'r') as file:\n",
-        "    addr = file.read().rstrip()"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "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",
-        "    addr,\n",
-        "    proof_path,\n",
-        "    \"http://127.0.0.1:3030\"\n",
-        ")\n",
-        "assert res == True"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "os.system(\"killall -9 e2pg\");"
+        "# kill all shovel process \n",
+        "os.system(\"pkill -f shovel\")"
       ]
     }
   ],
@@ -501,7 +455,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.13"
+      "version": "3.12.2"
     }
   },
   "nbformat": 4,

examples/notebooks/mnist_gan.ipynb

@@ -38,7 +38,7 @@
                 "import logging\n",
                 "\n",
                 "import tensorflow as tf\n",
-                "from tensorflow.keras.optimizers.legacy import Adam\n",
+                "from tensorflow.keras.optimizers import Adam\n",
                 "from tensorflow.keras.layers import *\n",
                 "from tensorflow.keras.models import Model\n",
                 "from tensorflow.keras.datasets import mnist\n",
@@ -71,9 +71,11 @@
             },
             "outputs": [],
             "source": [
-                "opt = Adam()\n",
                 "ZDIM = 100\n",
                 "\n",
+                "opt = Adam()\n",
+                "\n",
+                "\n",
                 "# discriminator\n",
                 "# 0 if it's fake, 1 if it's real\n",
                 "x = in1 = Input((28,28))\n",
@@ -114,8 +116,11 @@
                 "\n",
                 "gm = Model(in1, x)\n",
                 "gm.compile('adam', 'mse')\n",
+                "gm.output_names=['output']\n",
                 "gm.summary()\n",
                 "\n",
+                "opt = Adam()\n",
+                "\n",
                 "# GAN\n",
                 "dm.trainable = False\n",
                 "x = dm(gm.output)\n",
@@ -415,7 +420,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.15"
+            "version": "3.12.2"
         }
     },
     "nbformat": 4,

examples/notebooks/mnist_vae.ipynb

@@ -349,6 +349,8 @@
                 "z_log_var = Dense(ZDIM)(x)\n",
                 "z = Lambda(lambda x: x[0] + K.exp(0.5 * x[1]) * K.random_normal(shape=K.shape(x[0])))([z_mu, z_log_var])\n",
                 "dec = get_decoder()\n",
+                "dec.output_names=['output']\n",
+                "\n",
                 "out = dec(z)\n",
                 "\n",
                 "mse_loss = mse(Reshape((28*28,))(in1), Reshape((28*28,))(out)) * 28 * 28\n",

examples/notebooks/random_forest.ipynb

@@ -61,11 +61,10 @@
                 "from sklearn.datasets import load_iris\n",
                 "from sklearn.model_selection import train_test_split\n",
                 "from sklearn.ensemble import RandomForestClassifier as Rf\n",
-                "import sk2torch\n",
                 "import torch\n",
                 "import ezkl\n",
                 "import os\n",
-                "from torch import nn\n",
+                "from hummingbird.ml import convert\n",
                 "\n",
                 "\n",
                 "\n",
@@ -77,28 +76,12 @@
                 "clr.fit(X_train, y_train)\n",
                 "\n",
                 "\n",
-                "trees = []\n",
-                "for tree in clr.estimators_:\n",
-                "    trees.append(sk2torch.wrap(tree))\n",
                 "\n",
-                "\n",
-                "class RandomForest(nn.Module):\n",
-                "    def __init__(self, trees):\n",
-                "        super(RandomForest, self).__init__()\n",
-                "        self.trees = nn.ModuleList(trees)\n",
-                "\n",
-                "    def forward(self, x):\n",
-                "        out = self.trees[0](x)\n",
-                "        for tree in self.trees[1:]:\n",
-                "            out += tree(x)\n",
-                "        return out / len(self.trees)\n",
-                "\n",
-                "\n",
-                "torch_rf = RandomForest(trees)\n",
+                "torch_rf = convert(clr, 'torch')\n",
                 "# assert predictions from torch are = to sklearn \n",
                 "diffs = []\n",
                 "for i in range(len(X_test)):\n",
-                "    torch_pred = torch_rf(torch.tensor(X_test[i].reshape(1, -1)))\n",
+                "    torch_pred = torch_rf.predict(torch.tensor(X_test[i].reshape(1, -1)))\n",
                 "    sk_pred = clr.predict(X_test[i].reshape(1, -1))\n",
                 "    diffs.append(torch_pred[0].round() - sk_pred[0])\n",
                 "\n",
@@ -134,14 +117,12 @@
                 "\n",
                 "# export to onnx format\n",
                 "\n",
-                "torch_rf.eval()\n",
-                "\n",
                 "# Input to the model\n",
                 "shape = X_train.shape[1:]\n",
                 "x = torch.rand(1, *shape, requires_grad=False)\n",
-                "torch_out = torch_rf(x)\n",
+                "torch_out = torch_rf.predict(x)\n",
                 "# Export the model\n",
-                "torch.onnx.export(torch_rf,               # model being run\n",
+                "torch.onnx.export(torch_rf.model,               # 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",
@@ -158,7 +139,7 @@
                 "\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",
+                "            output_data=[o.reshape([-1]).tolist() for o in torch_out])\n",
                 "\n",
                 "# Serialize data into file:\n",
                 "json.dump(data, open(\"input.json\", 'w'))\n"
@@ -321,7 +302,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.15"
+            "version": "3.12.2"
         }
     },
     "nbformat": 4,

examples/notebooks/tictactoe_autoencoder.ipynb

@@ -13,7 +13,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": null,
+            "execution_count": 1,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -57,7 +57,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": null,
+            "execution_count": 2,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -119,7 +119,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": null,
+            "execution_count": 3,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -163,7 +163,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": null,
+            "execution_count": 4,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -217,7 +217,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": null,
+            "execution_count": 6,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -227,6 +227,10 @@
                 "        self.length = self.compute_length(self.file_good)\n",
                 "        self.data = self.load_data(self.file_good)\n",
                 "\n",
+                "    def __iter__(self):\n",
+                "        for i in range(len(self.data)):\n",
+                "            yield self.data[i]\n",
+                "\n",
                 "    def parse_json_object(self, line):\n",
                 "        try:\n",
                 "            return json.loads(line)\n",
@@ -749,7 +753,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.15"
+            "version": "3.12.2"
         }
     },
     "nbformat": 4,

examples/notebooks/tictactoe_binary_classification.ipynb

@@ -209,6 +209,11 @@
                 "        self.length = self.compute_length(self.file_good, self.file_bad)\n",
                 "        self.data = self.load_data(self.file_good, self.file_bad)\n",
                 "\n",
+                "    def __iter__(self):\n",
+                "        for i in range(len(self.data)):\n",
+                "            yield self.data[i]\n",
+                "\n",
+                "\n",
                 "    def parse_json_object(self, line):\n",
                 "        try:\n",
                 "            return json.loads(line)\n",
@@ -637,7 +642,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.9.15"
+            "version": "3.12.2"
         }
     },
     "nbformat": 4,

examples/onnx/lstm_large/input.json

@@ -0,0 +1,13 @@
+{
+  "input_data": [
+    [
+      0.8894134163856506,
+      0.8894201517105103
+    ]
+  ],
+  "output_data": [
+    [
+      0.8436377
+    ]
+  ]
+}

in-browser-evm-verifier/package.json

@@ -17,19 +17,19 @@
     "clean": "rm -r dist || true",
     "build:commonjs": "tsc --project tsconfig.commonjs.json && resolve-tspaths -p tsconfig.commonjs.json",
     "build:esm": "tsc --project tsconfig.esm.json && resolve-tspaths -p tsconfig.esm.json",
-    "build": "pnpm run clean && pnpm run build:commonjs && pnpm run build:esm"
+    "build": "npm run clean && npm run build:commonjs && npm run build:esm"
   },
   "dependencies": {
-    "@ethereumjs/common": "^4.0.0",
-    "@ethereumjs/evm": "^2.0.0",
-    "@ethereumjs/statemanager": "^2.0.0",
-    "@ethereumjs/tx": "^5.0.0",
-    "@ethereumjs/util": "^9.0.0",
-    "@ethereumjs/vm": "^7.0.0",
-    "@ethersproject/abi": "^5.7.0",
+    "@ethereumjs/common": "4.0.0",
+    "@ethereumjs/evm": "2.0.0",
+    "@ethereumjs/statemanager": "2.0.0",
+    "@ethereumjs/tx": "5.0.0",
+    "@ethereumjs/util": "9.0.0",
+    "@ethereumjs/vm": "7.0.0",
+    "@ethersproject/abi": "5.7.0",
     "@ezkljs/engine": "^9.4.4",
-    "ethers": "^6.7.1",
-    "json-bigint": "^1.0.0"
+    "ethers": "6.7.1",
+    "json-bigint": "1.0.0"
   },
   "devDependencies": {
     "@types/node": "^20.8.3",

in-browser-evm-verifier/pnpm-lock.yaml

@@ -6,34 +6,34 @@ settings:
 
 dependencies:
   '@ethereumjs/common':
-    specifier: ^4.0.0
+    specifier: 4.0.0
     version: 4.0.0
   '@ethereumjs/evm':
-    specifier: ^2.0.0
+    specifier: 2.0.0
     version: 2.0.0
   '@ethereumjs/statemanager':
-    specifier: ^2.0.0
+    specifier: 2.0.0
     version: 2.0.0
   '@ethereumjs/tx':
-    specifier: ^5.0.0
+    specifier: 5.0.0
     version: 5.0.0
   '@ethereumjs/util':
-    specifier: ^9.0.0
+    specifier: 9.0.0
     version: 9.0.0
   '@ethereumjs/vm':
-    specifier: ^7.0.0
+    specifier: 7.0.0
     version: 7.0.0
   '@ethersproject/abi':
-    specifier: ^5.7.0
+    specifier: 5.7.0
     version: 5.7.0
   '@ezkljs/engine':
     specifier: ^9.4.4
     version: 9.4.4
   ethers:
-    specifier: ^6.7.1
+    specifier: 6.7.1
     version: 6.7.1
   json-bigint:
-    specifier: ^1.0.0
+    specifier: 1.0.0
     version: 1.0.0
 
 devDependencies:

install_ezkl_cli.sh

@@ -36,7 +36,7 @@ if  [ "$(which ezkl)s" != "s" ] && [ "$(which ezkl)" != "$EZKL_DIR/ezkl" ] ; the
     exit 1
 fi
 
-if [[ ":$PATH:" != *":${EZKl_DIR}:"* ]]; then
+if [[ ":$PATH:" != *":${EZKL_DIR}:"* ]]; then
     # Add the ezkl directory to the path and ensure the old PATH variables remain.
     echo >> $PROFILE && echo "export PATH=\"\$PATH:$EZKL_DIR\"" >> $PROFILE
 fi

pyproject.toml

@@ -1,5 +1,5 @@
 [build-system]
-requires = ["maturin>=0.14,<0.15"]
+requires = ["maturin>=1.0,<2.0"]
 build-backend = "maturin"
 
 [tool.pytest.ini_options]

requirements.txt

@@ -1,14 +1,14 @@
-attrs==22.2.0
-exceptiongroup==1.1.1
-importlib-metadata==6.1.0
+attrs==23.2.0
+exceptiongroup==1.2.0
+importlib-metadata==7.1.0
 iniconfig==2.0.0
-maturin==1.0.1
-packaging==23.0
-pluggy==1.0.0
-pytest==7.2.2
+maturin==1.5.1
+packaging==24.0
+pluggy==1.4.0
+pytest==8.1.1
 tomli==2.0.1
-typing-extensions==4.5.0
-zipp==3.15.0
-onnx==1.14.1
-onnxruntime==1.14.1
-numpy==1.21.6
+typing-extensions==4.10.0
+zipp==3.18.1
+onnx==1.15.0
+onnxruntime==1.17.1
+numpy==1.26.4

rust-toolchain

@@ -1,3 +1,3 @@
 [toolchain]
-channel = "nightly-2023-08-24"
+channel = "nightly-2024-02-06"
 components = ["rustfmt", "clippy"]

src/circuit/modules/mod.rs

@@ -15,6 +15,8 @@ pub use planner::*;
 
 use crate::tensor::{TensorType, ValTensor};
 
+use super::region::ConstantsMap;
+
 /// Module trait used to extend ezkl functionality
 pub trait Module<F: PrimeField + TensorType + PartialOrd> {
     /// Config
@@ -39,6 +41,7 @@ pub trait Module<F: PrimeField + TensorType + PartialOrd> {
         &self,
         layouter: &mut impl Layouter<F>,
         input: &[ValTensor<F>],
+        constants: &mut ConstantsMap<F>,
     ) -> Result<Self::InputAssignments, Error>;
     /// Layout
     fn layout(
@@ -46,6 +49,7 @@ pub trait Module<F: PrimeField + TensorType + PartialOrd> {
         layouter: &mut impl Layouter<F>,
         input: &[ValTensor<F>],
         row_offset: usize,
+        constants: &mut ConstantsMap<F>,
     ) -> Result<ValTensor<F>, Error>;
     /// Number of instance values the module uses every time it is applied
     fn instance_increment_input(&self) -> Vec<usize>;

src/circuit/modules/polycommit.rs

@@ -4,6 +4,8 @@ is already implemented in halo2_gadgets, there is no wrapper chip that makes it
 Thanks to https://github.com/summa-dev/summa-solvency/blob/master/src/chips/poseidon/hash.rs for the inspiration (and also helping us understand how to use this).
 */
 
+use std::collections::HashMap;
+
 // This chip adds a set of advice columns to the gadget Chip to store the inputs of the hash
 use halo2_proofs::halo2curves::bn256::Fr as Fp;
 use halo2_proofs::poly::commitment::{Blind, CommitmentScheme, Params};
@@ -13,6 +15,7 @@ use halo2curves::group::prime::PrimeCurveAffine;
 use halo2curves::group::Curve;
 use halo2curves::CurveAffine;
 
+use crate::circuit::region::ConstantsMap;
 use crate::tensor::{Tensor, ValTensor, ValType, VarTensor};
 
 use super::Module;
@@ -107,6 +110,7 @@ impl Module<Fp> for PolyCommitChip {
         &self,
         _: &mut impl Layouter<Fp>,
         _: &[ValTensor<Fp>],
+        _: &mut ConstantsMap<Fp>,
     ) -> Result<Self::InputAssignments, Error> {
         Ok(())
     }
@@ -119,11 +123,24 @@ impl Module<Fp> for PolyCommitChip {
         layouter: &mut impl Layouter<Fp>,
         input: &[ValTensor<Fp>],
         _: usize,
+        constants: &mut ConstantsMap<Fp>,
     ) -> Result<ValTensor<Fp>, Error> {
         assert_eq!(input.len(), 1);
+
+        let local_constants = constants.clone();
         layouter.assign_region(
             || "PolyCommit",
-            |mut region| self.config.inputs.assign(&mut region, 0, &input[0]),
+            |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)
+            },
         )
     }
 
@@ -184,7 +201,12 @@ mod tests {
             mut layouter: impl Layouter<Fp>,
         ) -> Result<(), Error> {
             let polycommit_chip = PolyCommitChip::new(config);
-            polycommit_chip.layout(&mut layouter, &[self.message.clone()], 0);
+            polycommit_chip.layout(
+                &mut layouter,
+                &[self.message.clone()],
+                0,
+                &mut HashMap::new(),
+            );
 
             Ok(())
         }

src/circuit/modules/poseidon.rs

@@ -18,6 +18,7 @@ use maybe_rayon::slice::ParallelSlice;
 
 use std::marker::PhantomData;
 
+use crate::circuit::region::ConstantsMap;
 use crate::tensor::{Tensor, ValTensor, ValType};
 
 use super::Module;
@@ -172,12 +173,15 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
         &self,
         layouter: &mut impl Layouter<Fp>,
         message: &[ValTensor<Fp>],
+        constants: &mut ConstantsMap<Fp>,
     ) -> Result<Self::InputAssignments, Error> {
         assert_eq!(message.len(), 1);
         let message = message[0].clone();
 
         let start_time = instant::Instant::now();
 
+        let local_constants = constants.clone();
+
         let res = layouter.assign_region(
             || "load message",
             |mut region| {
@@ -199,12 +203,26 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
                                 ValType::PrevAssigned(v) | ValType::AssignedConstant(v, ..) => {
                                     Ok(v.clone())
                                 }
-                                ValType::Constant(f) => region.assign_advice_from_constant(
-                                    || format!("load message_{}", i),
-                                    self.config.hash_inputs[x],
-                                    y,
-                                    *f,
-                                ),
+                                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,
+                                        )?;
+
+                                        constants
+                                            .insert(*f, ValType::AssignedConstant(res.clone(), *f));
+
+                                        Ok(res)
+                                    }
+                                }
                                 e => {
                                     log::error!(
                                         "wrong input type {:?}, must be previously assigned",
@@ -270,8 +288,9 @@ impl<S: Spec<Fp, WIDTH, RATE> + Sync, const WIDTH: usize, const RATE: usize, con
         layouter: &mut impl Layouter<Fp>,
         input: &[ValTensor<Fp>],
         row_offset: usize,
+        constants: &mut ConstantsMap<Fp>,
     ) -> Result<ValTensor<Fp>, Error> {
-        let (mut input_cells, zero_val) = self.layout_inputs(layouter, input)?;
+        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>> =
             input_cells.iter().map(|e| ValType::from(e.clone())).into();
@@ -434,7 +453,7 @@ mod tests {
         *,
     };
 
-    use std::marker::PhantomData;
+    use std::{collections::HashMap, marker::PhantomData};
 
     use halo2_gadgets::poseidon::primitives::Spec;
     use halo2_proofs::{
@@ -477,7 +496,12 @@ mod tests {
             mut layouter: impl Layouter<Fp>,
         ) -> Result<(), Error> {
             let chip: PoseidonChip<PoseidonSpec, WIDTH, RATE, L> = PoseidonChip::new(config);
-            chip.layout(&mut layouter, &[self.message.clone()], 0)?;
+            chip.layout(
+                &mut layouter,
+                &[self.message.clone()],
+                0,
+                &mut HashMap::new(),
+            )?;
 
             Ok(())
         }

src/circuit/ops/chip.rs

@@ -345,7 +345,7 @@ pub struct BaseConfig<F: PrimeField + TensorType + PartialOrd> {
     _marker: PhantomData<F>,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> 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 {
@@ -956,20 +956,6 @@ impl<F: PrimeField + TensorType + PartialOrd> BaseConfig<F> {
         values: &[ValTensor<F>],
         op: Box<dyn Op<F>>,
     ) -> Result<Option<ValTensor<F>>, Box<dyn Error>> {
-        let res = op.layout(self, region, values)?;
-
-        if matches!(&self.check_mode, CheckMode::SAFE) && !region.is_dummy() {
-            if let Some(claimed_output) = &res {
-                // during key generation this will be unknown vals so we use this as a flag to check
-                let mut is_assigned = !claimed_output.any_unknowns()?;
-                for val in values.iter() {
-                    is_assigned = is_assigned && !val.any_unknowns()?;
-                }
-                if is_assigned {
-                    op.safe_mode_check(claimed_output, values)?;
-                }
-            }
-        };
-        Ok(res)
+        op.layout(self, region, values)
     }
 }

src/circuit/ops/hybrid.rs

@@ -1,9 +1,9 @@
 use super::*;
 use crate::{
     circuit::{layouts, utils, Tolerance},
-    fieldutils::{felt_to_i128, i128_to_felt},
+    fieldutils::i128_to_felt,
     graph::multiplier_to_scale,
-    tensor::{self, Tensor, TensorError, TensorType, ValTensor},
+    tensor::{self, Tensor, TensorType, ValTensor},
 };
 use halo2curves::ff::PrimeField;
 use serde::{Deserialize, Serialize};
@@ -29,15 +29,15 @@ pub enum HybridOp {
         dim: usize,
     },
     SumPool {
-        padding: [(usize, usize); 2],
-        stride: (usize, usize),
-        kernel_shape: (usize, usize),
+        padding: Vec<(usize, usize)>,
+        stride: Vec<usize>,
+        kernel_shape: Vec<usize>,
         normalized: bool,
     },
-    MaxPool2d {
-        padding: [(usize, usize); 2],
-        stride: (usize, usize),
-        pool_dims: (usize, usize),
+    MaxPool {
+        padding: Vec<(usize, usize)>,
+        stride: Vec<usize>,
+        pool_dims: Vec<usize>,
     },
     ReduceMin {
         axes: Vec<usize>,
@@ -46,7 +46,8 @@ pub enum HybridOp {
         dim: usize,
     },
     Softmax {
-        scale: utils::F32,
+        input_scale: utils::F32,
+        output_scale: utils::F32,
         axes: Vec<usize>,
     },
     RangeCheck(Tolerance),
@@ -70,7 +71,7 @@ pub enum HybridOp {
     },
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> 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 {
@@ -84,86 +85,6 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for HybridOp {
     fn as_any(&self) -> &dyn Any {
         self
     }
-    /// Matches a [Op] to an operation in the `tensor::ops` module.
-    fn f(&self, inputs: &[Tensor<F>]) -> Result<ForwardResult<F>, TensorError> {
-        let x = inputs[0].clone().map(|x| felt_to_i128(x));
-
-        let res = match &self {
-            HybridOp::ReduceMax { axes, .. } => tensor::ops::max_axes(&x, axes)?,
-            HybridOp::ReduceMin { axes, .. } => tensor::ops::min_axes(&x, axes)?,
-            HybridOp::Div { denom, .. } => {
-                crate::tensor::ops::nonlinearities::const_div(&x, denom.0 as f64)
-            }
-            HybridOp::Recip {
-                input_scale,
-                output_scale,
-                ..
-            } => crate::tensor::ops::nonlinearities::recip(
-                &x,
-                input_scale.0 as f64,
-                output_scale.0 as f64,
-            ),
-            HybridOp::ReduceArgMax { dim } => tensor::ops::argmax_axes(&x, *dim)?,
-            HybridOp::ReduceArgMin { dim } => tensor::ops::argmin_axes(&x, *dim)?,
-            HybridOp::Gather { dim, constant_idx } => {
-                if let Some(idx) = constant_idx {
-                    tensor::ops::gather(&x, idx, *dim)?
-                } else {
-                    let y = inputs[1].clone().map(|x| felt_to_i128(x));
-                    tensor::ops::gather(&x, &y.map(|x| x as usize), *dim)?
-                }
-            }
-            HybridOp::OneHot { dim, num_classes } => {
-                tensor::ops::one_hot(&x, *num_classes, *dim)?.clone()
-            }
-
-            HybridOp::TopK { dim, k, largest } => tensor::ops::topk_axes(&x, *k, *dim, *largest)?,
-            HybridOp::MaxPool2d {
-                padding,
-                stride,
-                pool_dims,
-                ..
-            } => tensor::ops::max_pool2d(&x, padding, stride, pool_dims)?,
-            HybridOp::SumPool {
-                padding,
-                stride,
-                kernel_shape,
-                normalized,
-            } => tensor::ops::sumpool(&x, *padding, *stride, *kernel_shape, *normalized)?,
-            HybridOp::Softmax { scale, axes } => {
-                tensor::ops::nonlinearities::softmax_axes(&x, scale.into(), axes)
-            }
-            HybridOp::RangeCheck(tol) => {
-                let y = inputs[1].clone().map(|x| felt_to_i128(x));
-                tensor::ops::nonlinearities::range_check_percent(&[x, y], 128, 128, tol.val)
-            }
-            HybridOp::Greater => {
-                let y = inputs[1].clone().map(|x| felt_to_i128(x));
-                tensor::ops::greater(&x, &y)?
-            }
-            HybridOp::GreaterEqual => {
-                let y = inputs[1].clone().map(|x| felt_to_i128(x));
-                tensor::ops::greater_equal(&x, &y)?
-            }
-            HybridOp::Less => {
-                let y = inputs[1].clone().map(|x| felt_to_i128(x));
-                tensor::ops::less(&x, &y)?
-            }
-            HybridOp::LessEqual => {
-                let y = inputs[1].clone().map(|x| felt_to_i128(x));
-                tensor::ops::less_equal(&x, &y)?
-            }
-            HybridOp::Equals => {
-                let y = inputs[1].clone().map(|x| felt_to_i128(x));
-                tensor::ops::equals(&x, &y)?
-            }
-        };
-
-        // convert back to felt
-        let output = res.map(|x| i128_to_felt(x));
-
-        Ok(ForwardResult { output })
-    }
 
     fn as_string(&self) -> String {
         match self {
@@ -193,18 +114,25 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for HybridOp {
             ),
             HybridOp::ReduceMax { axes } => format!("REDUCEMAX (axes={:?})", axes),
             HybridOp::ReduceArgMax { dim } => format!("REDUCEARGMAX (dim={})", dim),
-            HybridOp::MaxPool2d {
+            HybridOp::MaxPool {
                 padding,
                 stride,
                 pool_dims,
             } => format!(
-                "MAXPOOL2D (padding={:?}, stride={:?}, pool_dims={:?})",
+                "MaxPool (padding={:?}, stride={:?}, pool_dims={:?})",
                 padding, stride, pool_dims
             ),
             HybridOp::ReduceMin { axes } => format!("REDUCEMIN (axes={:?})", axes),
             HybridOp::ReduceArgMin { dim } => format!("REDUCEARGMIN (dim={})", dim),
-            HybridOp::Softmax { scale, axes } => {
-                format!("SOFTMAX (scale={}, axes={:?})", scale, axes)
+            HybridOp::Softmax {
+                input_scale,
+                output_scale,
+                axes,
+            } => {
+                format!(
+                    "SOFTMAX (input_scale={}, output_scale={}, axes={:?})",
+                    input_scale, output_scale, axes
+                )
             }
             HybridOp::RangeCheck(p) => format!("RANGECHECK (tol={:?})", p),
             HybridOp::Greater => "GREATER".into(),
@@ -238,9 +166,9 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for HybridOp {
                 config,
                 region,
                 values[..].try_into()?,
-                *padding,
-                *stride,
-                *kernel_shape,
+                padding,
+                stride,
+                kernel_shape,
                 *normalized,
             )?,
             HybridOp::Recip {
@@ -300,17 +228,17 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for HybridOp {
                 }
             }
 
-            HybridOp::MaxPool2d {
+            HybridOp::MaxPool {
                 padding,
                 stride,
                 pool_dims,
-            } => layouts::max_pool2d(
+            } => layouts::max_pool(
                 config,
                 region,
                 values[..].try_into()?,
-                *padding,
-                *stride,
-                *pool_dims,
+                padding,
+                stride,
+                pool_dims,
             )?,
             HybridOp::ReduceMax { axes } => {
                 layouts::max_axes(config, region, values[..].try_into()?, axes)?
@@ -324,9 +252,18 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for HybridOp {
             HybridOp::ReduceArgMin { dim } => {
                 layouts::argmin_axes(config, region, values[..].try_into()?, *dim)?
             }
-            HybridOp::Softmax { scale, axes } => {
-                layouts::softmax_axes(config, region, values[..].try_into()?, *scale, axes)?
-            }
+            HybridOp::Softmax {
+                input_scale,
+                output_scale,
+                axes,
+            } => layouts::softmax_axes(
+                config,
+                region,
+                values[..].try_into()?,
+                *input_scale,
+                *output_scale,
+                axes,
+            )?,
             HybridOp::RangeCheck(tol) => layouts::range_check_percent(
                 config,
                 region,
@@ -359,8 +296,9 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for HybridOp {
             | HybridOp::ReduceArgMax { .. }
             | HybridOp::OneHot { .. }
             | HybridOp::ReduceArgMin { .. } => 0,
-            HybridOp::Softmax { .. } => 2 * in_scales[0],
-            HybridOp::Recip { output_scale, .. } => multiplier_to_scale(output_scale.0 as f64),
+            HybridOp::Softmax { output_scale, .. } | HybridOp::Recip { output_scale, .. } => {
+                multiplier_to_scale(output_scale.0 as f64)
+            }
             _ => in_scales[0],
         };
         Ok(scale)

src/circuit/ops/lookup.rs

@@ -135,15 +135,12 @@ impl LookupOp {
         let range = range as i128;
         (-range, range)
     }
-}
 
-impl<F: PrimeField + TensorType + PartialOrd> Op<F> for LookupOp {
-    /// Returns a reference to the Any trait.
-    fn as_any(&self) -> &dyn Any {
-        self
-    }
     /// Matches a [Op] to an operation in the `tensor::ops` module.
-    fn f(&self, x: &[Tensor<F>]) -> Result<ForwardResult<F>, TensorError> {
+    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_i128(x));
         let res = match &self {
             LookupOp::Abs => Ok(tensor::ops::abs(&x)?),
@@ -235,6 +232,13 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for LookupOp {
 
         Ok(ForwardResult { output })
     }
+}
+
+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
+    }
 
     /// Returns the name of the operation
     fn as_string(&self) -> String {

src/circuit/ops/mod.rs

@@ -4,7 +4,7 @@ use serde::{Deserialize, Serialize};
 
 use crate::{
     graph::quantize_tensor,
-    tensor::{self, Tensor, TensorError, TensorType, ValTensor},
+    tensor::{self, Tensor, TensorType, ValTensor},
 };
 use halo2curves::ff::PrimeField;
 
@@ -27,14 +27,14 @@ pub mod region;
 
 /// 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> {
+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::fmt::Debug + Send + Sync + Any {
-    /// Matches a [Op] to an operation in the `tensor::ops` module.
-    fn f(&self, x: &[Tensor<F>]) -> Result<ForwardResult<F>, TensorError>;
+pub trait Op<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>:
+    std::fmt::Debug + Send + Sync + Any
+{
     /// Returns a string representation of the operation.
     fn as_string(&self) -> String;
 
@@ -69,36 +69,9 @@ pub trait Op<F: PrimeField + TensorType + PartialOrd>: std::fmt::Debug + Send +
 
     /// Returns a reference to the Any trait.
     fn as_any(&self) -> &dyn Any;
-
-    /// Safe mode output checl
-    fn safe_mode_check(
-        &self,
-        claimed_output: &ValTensor<F>,
-        original_values: &[ValTensor<F>],
-    ) -> Result<(), TensorError> {
-        let felt_evals = original_values
-            .iter()
-            .map(|v| {
-                let mut evals = v.get_felt_evals().map_err(|_| TensorError::FeltError)?;
-                evals.reshape(v.dims())?;
-                Ok(evals)
-            })
-            .collect::<Result<Vec<_>, _>>()?;
-
-        let ref_op: Tensor<F> = self.f(&felt_evals)?.output;
-
-        let mut output = claimed_output
-            .get_felt_evals()
-            .map_err(|_| TensorError::FeltError)?;
-        output.reshape(claimed_output.dims())?;
-
-        assert_eq!(output, ref_op);
-
-        Ok(())
-    }
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> 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()
     }
@@ -165,7 +138,7 @@ pub struct Input {
     pub datum_type: InputType,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> Op<F> for Input {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Input {
     fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>> {
         Ok(self.scale)
     }
@@ -174,12 +147,6 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for Input {
         self
     }
 
-    fn f(&self, x: &[Tensor<F>]) -> Result<ForwardResult<F>, TensorError> {
-        Ok(ForwardResult {
-            output: x[0].clone(),
-        })
-    }
-
     fn as_string(&self) -> String {
         "Input".into()
     }
@@ -226,16 +193,13 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for Input {
 #[derive(Clone, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, Serialize, Deserialize)]
 pub struct Unknown;
 
-impl<F: PrimeField + TensorType + PartialOrd> Op<F> for Unknown {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Unknown {
     fn out_scale(&self, _: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>> {
         Ok(0)
     }
     fn as_any(&self) -> &dyn Any {
         self
     }
-    fn f(&self, _: &[Tensor<F>]) -> Result<ForwardResult<F>, TensorError> {
-        Err(TensorError::WrongMethod)
-    }
 
     fn as_string(&self) -> String {
         "Unknown".into()
@@ -256,7 +220,7 @@ impl<F: PrimeField + TensorType + PartialOrd> Op<F> for Unknown {
 
 ///
 #[derive(Clone, Debug, Serialize, Deserialize)]
-pub struct Constant<F: PrimeField + TensorType + PartialOrd> {
+pub struct Constant<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> {
     ///
     pub quantized_values: Tensor<F>,
     ///
@@ -266,7 +230,7 @@ pub struct Constant<F: PrimeField + TensorType + PartialOrd> {
     pub pre_assigned_val: Option<ValTensor<F>>,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> 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 {
@@ -293,17 +257,18 @@ impl<F: PrimeField + TensorType + PartialOrd> Constant<F> {
     }
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<'de>> Op<F>
-    for Constant<F>
+impl<
+        F: PrimeField
+            + TensorType
+            + PartialOrd
+            + std::hash::Hash
+            + Serialize
+            + for<'de> Deserialize<'de>,
+    > Op<F> for Constant<F>
 {
     fn as_any(&self) -> &dyn Any {
         self
     }
-    fn f(&self, _: &[Tensor<F>]) -> Result<ForwardResult<F>, TensorError> {
-        let output = self.quantized_values.clone();
-
-        Ok(ForwardResult { output })
-    }
 
     fn as_string(&self) -> String {
         format!("CONST (scale={})", self.quantized_values.scale().unwrap())

src/circuit/ops/poly.rs

@@ -1,6 +1,5 @@
 use crate::{
     circuit::layouts,
-    fieldutils::felt_to_i128,
     tensor::{self, Tensor, TensorError},
 };
 
@@ -32,8 +31,8 @@ pub enum PolyOp {
         equation: String,
     },
     Conv {
-        padding: [(usize, usize); 2],
-        stride: (usize, usize),
+        padding: Vec<(usize, usize)>,
+        stride: Vec<usize>,
     },
     Downsample {
         axis: usize,
@@ -41,9 +40,9 @@ pub enum PolyOp {
         modulo: usize,
     },
     DeConv {
-        padding: [(usize, usize); 2],
-        output_padding: (usize, usize),
-        stride: (usize, usize),
+        padding: Vec<(usize, usize)>,
+        output_padding: Vec<usize>,
+        stride: Vec<usize>,
     },
     Add,
     Sub,
@@ -58,10 +57,13 @@ pub enum PolyOp {
         destination: usize,
     },
     Flatten(Vec<usize>),
-    Pad([(usize, usize); 2]),
+    Pad(Vec<(usize, usize)>),
     Sum {
         axes: Vec<usize>,
     },
+    MeanOfSquares {
+        axes: Vec<usize>,
+    },
     Prod {
         axes: Vec<usize>,
         len_prod: usize,
@@ -89,8 +91,14 @@ pub enum PolyOp {
     },
 }
 
-impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<'de>> Op<F>
-    for PolyOp
+impl<
+        F: PrimeField
+            + TensorType
+            + PartialOrd
+            + std::hash::Hash
+            + Serialize
+            + for<'de> Deserialize<'de>,
+    > Op<F> for PolyOp
 {
     /// Returns a reference to the Any trait.
     fn as_any(&self) -> &dyn Any {
@@ -99,10 +107,28 @@ impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<
 
     fn as_string(&self) -> String {
         match &self {
-            PolyOp::GatherElements { dim, .. } => format!("GATHERELEMENTS (dim={})", dim),
-            PolyOp::GatherND { batch_dims, .. } => format!("GATHERND (batch_dims={})", batch_dims),
-            PolyOp::ScatterElements { dim, .. } => format!("SCATTERELEMENTS (dim={})", dim),
-            PolyOp::ScatterND { .. } => "SCATTERND".into(),
+            PolyOp::GatherElements { dim, constant_idx } => format!(
+                "GATHERELEMENTS (dim={}, constant_idx{})",
+                dim,
+                constant_idx.is_some()
+            ),
+            PolyOp::GatherND {
+                batch_dims,
+                indices,
+            } => format!(
+                "GATHERND (batch_dims={}, constant_idx{})",
+                batch_dims,
+                indices.is_some()
+            ),
+            PolyOp::MeanOfSquares { axes } => format!("MEANOFSQUARES (axes={:?})", axes),
+            PolyOp::ScatterElements { dim, constant_idx } => format!(
+                "SCATTERELEMENTS (dim={}, constant_idx{})",
+                dim,
+                constant_idx.is_some()
+            ),
+            PolyOp::ScatterND { constant_idx } => {
+                format!("SCATTERND (constant_idx={})", constant_idx.is_some())
+            }
             PolyOp::MultiBroadcastTo { shape } => format!("MULTIBROADCASTTO (shape={:?})", shape),
             PolyOp::MoveAxis { .. } => "MOVEAXIS".into(),
             PolyOp::Downsample { .. } => "DOWNSAMPLE".into(),
@@ -114,15 +140,26 @@ impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<
             }
             PolyOp::Reshape(shape) => format!("RESHAPE (shape={:?})", shape),
             PolyOp::Flatten(_) => "FLATTEN".into(),
-            PolyOp::Pad(_) => "PAD".into(),
+            PolyOp::Pad(pads) => format!("PAD (pads={:?})", pads),
             PolyOp::Add => "ADD".into(),
             PolyOp::Mult => "MULT".into(),
             PolyOp::Sub => "SUB".into(),
             PolyOp::Sum { axes } => format!("SUM (axes={:?})", axes),
             PolyOp::Prod { .. } => "PROD".into(),
             PolyOp::Pow(_) => "POW".into(),
-            PolyOp::Conv { .. } => "CONV".into(),
-            PolyOp::DeConv { .. } => "DECONV".into(),
+            PolyOp::Conv { stride, padding } => {
+                format!("CONV (stride={:?}, padding={:?})", stride, padding)
+            }
+            PolyOp::DeConv {
+                stride,
+                padding,
+                output_padding,
+            } => {
+                format!(
+                    "DECONV (stride={:?}, padding={:?}, output_padding={:?})",
+                    stride, padding, output_padding
+                )
+            }
             PolyOp::Concat { axis } => format!("CONCAT (axis={})", axis),
             PolyOp::Slice { axis, start, end } => {
                 format!("SLICE (axis={}, start={}, end={})", axis, start, end)
@@ -136,146 +173,6 @@ impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<
         }
     }
 
-    /// Matches a [Op] to an operation in the `tensor::ops` module.
-    fn f(&self, inputs: &[Tensor<F>]) -> Result<ForwardResult<F>, TensorError> {
-        let mut inputs = inputs.to_vec();
-        let res = match &self {
-            PolyOp::MultiBroadcastTo { shape } => {
-                if 1 != inputs.len() {
-                    return Err(TensorError::DimMismatch(
-                        "multibroadcastto inputs".to_string(),
-                    ));
-                }
-                inputs[0].expand(shape)
-            }
-            PolyOp::And => tensor::ops::and(&inputs[0], &inputs[1]),
-            PolyOp::Or => tensor::ops::or(&inputs[0], &inputs[1]),
-            PolyOp::Xor => tensor::ops::xor(&inputs[0], &inputs[1]),
-            PolyOp::Not => tensor::ops::not(&inputs[0]),
-            PolyOp::Downsample {
-                axis,
-                stride,
-                modulo,
-            } => tensor::ops::downsample(&inputs[0], *axis, *stride, *modulo),
-            PolyOp::Resize { scale_factor } => tensor::ops::resize(&inputs[0], scale_factor),
-            PolyOp::Iff => tensor::ops::iff(&inputs[0], &inputs[1], &inputs[2]),
-            PolyOp::Einsum { equation } => tensor::ops::einsum(equation, &inputs),
-            PolyOp::Identity { .. } => Ok(inputs[0].clone()),
-            PolyOp::Reshape(new_dims) => {
-                let mut t = inputs[0].clone();
-                t.reshape(new_dims)?;
-                Ok(t)
-            }
-            PolyOp::MoveAxis {
-                source,
-                destination,
-            } => inputs[0].move_axis(*source, *destination),
-            PolyOp::Flatten(new_dims) => {
-                let mut t = inputs[0].clone();
-                t.reshape(new_dims)?;
-                Ok(t)
-            }
-            PolyOp::Pad(p) => {
-                if 1 != inputs.len() {
-                    return Err(TensorError::DimMismatch("pad inputs".to_string()));
-                }
-                tensor::ops::pad(&inputs[0], *p)
-            }
-            PolyOp::Add => tensor::ops::add(&inputs),
-            PolyOp::Neg => tensor::ops::neg(&inputs[0]),
-            PolyOp::Sub => tensor::ops::sub(&inputs),
-            PolyOp::Mult => tensor::ops::mult(&inputs),
-            PolyOp::Conv { padding, stride } => tensor::ops::conv(&inputs, *padding, *stride),
-            PolyOp::DeConv {
-                padding,
-                output_padding,
-                stride,
-            } => tensor::ops::deconv(&inputs, *padding, *output_padding, *stride),
-            PolyOp::Pow(u) => {
-                if 1 != inputs.len() {
-                    return Err(TensorError::DimMismatch("pow inputs".to_string()));
-                }
-                inputs[0].pow(*u)
-            }
-            PolyOp::Sum { axes } => {
-                if 1 != inputs.len() {
-                    return Err(TensorError::DimMismatch("sum inputs".to_string()));
-                }
-                tensor::ops::sum_axes(&inputs[0], axes)
-            }
-            PolyOp::Prod { axes, .. } => {
-                if 1 != inputs.len() {
-                    return Err(TensorError::DimMismatch("prod inputs".to_string()));
-                }
-                tensor::ops::prod_axes(&inputs[0], axes)
-            }
-            PolyOp::Concat { axis } => {
-                tensor::ops::concat(&inputs.iter().collect::<Vec<_>>(), *axis)
-            }
-            PolyOp::Slice { axis, start, end } => {
-                if 1 != inputs.len() {
-                    return Err(TensorError::DimMismatch("slice inputs".to_string()));
-                }
-                tensor::ops::slice(&inputs[0], axis, start, end)
-            }
-            PolyOp::GatherElements { dim, constant_idx } => {
-                let x = inputs[0].clone();
-                let y = if let Some(idx) = constant_idx {
-                    idx.clone()
-                } else {
-                    inputs[1].clone().map(|x| felt_to_i128(x) as usize)
-                };
-                tensor::ops::gather_elements(&x, &y, *dim)
-            }
-            PolyOp::GatherND {
-                indices,
-                batch_dims,
-            } => {
-                let x = inputs[0].clone();
-                let y = if let Some(idx) = indices {
-                    idx.clone()
-                } else {
-                    inputs[1].clone().map(|x| felt_to_i128(x) as usize)
-                };
-                tensor::ops::gather_nd(&x, &y, *batch_dims)
-            }
-            PolyOp::ScatterElements { dim, constant_idx } => {
-                let x = inputs[0].clone();
-
-                let idx = if let Some(idx) = constant_idx {
-                    idx.clone()
-                } else {
-                    inputs[1].clone().map(|x| felt_to_i128(x) as usize)
-                };
-
-                let src = if constant_idx.is_some() {
-                    inputs[1].clone()
-                } else {
-                    inputs[2].clone()
-                };
-                tensor::ops::scatter(&x, &idx, &src, *dim)
-            }
-
-            PolyOp::ScatterND { constant_idx } => {
-                let x = inputs[0].clone();
-                let idx = if let Some(idx) = constant_idx {
-                    idx.clone()
-                } else {
-                    inputs[1].clone().map(|x| felt_to_i128(x) as usize)
-                };
-                let src = if constant_idx.is_some() {
-                    inputs[1].clone()
-                } else {
-                    inputs[2].clone()
-                };
-                tensor::ops::scatter_nd(&x, &idx, &src)
-            }
-            PolyOp::Trilu { upper, k } => tensor::ops::trilu(&inputs[0], *k, *upper),
-        }?;
-
-        Ok(ForwardResult { output: res })
-    }
-
     fn layout(
         &self,
         config: &mut crate::circuit::BaseConfig<F>,
@@ -286,6 +183,9 @@ impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<
             PolyOp::MultiBroadcastTo { shape } => {
                 layouts::expand(config, region, values[..].try_into()?, shape)?
             }
+            PolyOp::MeanOfSquares { axes } => {
+                layouts::mean_of_squares_axes(config, region, values[..].try_into()?, axes)?
+            }
             PolyOp::Xor => layouts::xor(config, region, values[..].try_into()?)?,
             PolyOp::Or => layouts::or(config, region, values[..].try_into()?)?,
             PolyOp::And => layouts::and(config, region, values[..].try_into()?)?,
@@ -312,7 +212,7 @@ impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<
                 layouts::prod_axes(config, region, values[..].try_into()?, axes)?
             }
             PolyOp::Conv { padding, stride } => {
-                layouts::conv(config, region, values[..].try_into()?, *padding, *stride)?
+                layouts::conv(config, region, values[..].try_into()?, padding, stride)?
             }
             PolyOp::GatherElements { dim, constant_idx } => {
                 if let Some(idx) = constant_idx {
@@ -364,9 +264,9 @@ impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<
                 config,
                 region,
                 values[..].try_into()?,
-                *padding,
-                *output_padding,
-                *stride,
+                padding,
+                output_padding,
+                stride,
             )?,
             PolyOp::Add => layouts::pairwise(config, region, values[..].try_into()?, BaseOp::Add)?,
             PolyOp::Sub => layouts::pairwise(config, region, values[..].try_into()?, BaseOp::Sub)?,
@@ -382,7 +282,7 @@ impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<
                     )));
                 }
                 let mut input = values[0].clone();
-                input.pad(*p)?;
+                input.pad(p.clone(), 0)?;
                 input
             }
             PolyOp::Pow(exp) => layouts::pow(config, region, values[..].try_into()?, *exp)?,
@@ -398,6 +298,7 @@ impl<F: PrimeField + TensorType + PartialOrd + Serialize + for<'de> Deserialize<
 
     fn out_scale(&self, in_scales: Vec<crate::Scale>) -> Result<crate::Scale, Box<dyn Error>> {
         let scale = match self {
+            PolyOp::MeanOfSquares { .. } => 2 * in_scales[0],
             PolyOp::Xor | PolyOp::Or | PolyOp::And | PolyOp::Not => 0,
             PolyOp::Iff => in_scales[1],
             PolyOp::Einsum { .. } => {

src/circuit/ops/region.rs

@@ -2,24 +2,28 @@ use crate::{
     circuit::table::Range,
     tensor::{Tensor, TensorError, TensorType, ValTensor, ValType, VarTensor},
 };
+#[cfg(not(target_arch = "wasm32"))]
+use colored::Colorize;
 use halo2_proofs::{
     circuit::Region,
     plonk::{Error, Selector},
 };
 use halo2curves::ff::PrimeField;
+use portable_atomic::AtomicI128 as AtomicInt;
 use std::{
     cell::RefCell,
-    collections::HashSet,
+    collections::{HashMap, HashSet},
     sync::{
         atomic::{AtomicUsize, Ordering},
         Arc, Mutex,
     },
 };
 
-use portable_atomic::AtomicI128 as AtomicInt;
-
 use super::lookup::LookupOp;
 
+/// Constants map
+pub type ConstantsMap<F> = HashMap<F, ValType<F>>;
+
 /// Dynamic lookup index
 #[derive(Clone, Debug, Default)]
 pub struct DynamicLookupIndex {
@@ -120,12 +124,11 @@ impl From<Box<dyn std::error::Error>> for RegionError {
 
 #[derive(Debug)]
 /// A context for a region
-pub struct RegionCtx<'a, F: PrimeField + TensorType + PartialOrd> {
+pub struct RegionCtx<'a, F: PrimeField + TensorType + PartialOrd + std::hash::Hash> {
     region: Option<RefCell<Region<'a, F>>>,
     row: usize,
     linear_coord: usize,
     num_inner_cols: usize,
-    total_constants: usize,
     dynamic_lookup_index: DynamicLookupIndex,
     shuffle_index: ShuffleIndex,
     used_lookups: HashSet<LookupOp>,
@@ -133,13 +136,34 @@ pub struct RegionCtx<'a, F: PrimeField + TensorType + PartialOrd> {
     max_lookup_inputs: i128,
     min_lookup_inputs: i128,
     max_range_size: i128,
-    throw_range_check_error: bool,
+    witness_gen: bool,
+    assigned_constants: ConstantsMap<F>,
 }
 
-impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
+impl<'a, F: PrimeField + TensorType + PartialOrd + std::hash::Hash> RegionCtx<'a, F> {
+    #[cfg(not(target_arch = "wasm32"))]
     ///
-    pub fn increment_total_constants(&mut self, n: usize) {
-        self.total_constants += n;
+    pub fn debug_report(&self) {
+        log::debug!(
+            "(rows={}, coord={}, constants={}, max_lookup_inputs={}, min_lookup_inputs={}, max_range_size={}, dynamic_lookup_col_coord={}, shuffle_col_coord={})",
+            self.row().to_string().blue(),
+            self.linear_coord().to_string().yellow(),
+            self.total_constants().to_string().red(),
+            self.max_lookup_inputs().to_string().green(),
+            self.min_lookup_inputs().to_string().green(),
+            self.max_range_size().to_string().green(),
+            self.dynamic_lookup_col_coord().to_string().green(),
+            self.shuffle_col_coord().to_string().green());
+    }
+
+    ///
+    pub fn assigned_constants(&self) -> &ConstantsMap<F> {
+        &self.assigned_constants
+    }
+
+    ///
+    pub fn update_constants(&mut self, constants: ConstantsMap<F>) {
+        self.assigned_constants.extend(constants);
     }
 
     ///
@@ -163,8 +187,8 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
     }
 
     ///
-    pub fn throw_range_check_error(&self) -> bool {
-        self.throw_range_check_error
+    pub fn witness_gen(&self) -> bool {
+        self.witness_gen
     }
 
     /// Create a new region context
@@ -177,7 +201,6 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             num_inner_cols,
             row,
             linear_coord,
-            total_constants: 0,
             dynamic_lookup_index: DynamicLookupIndex::default(),
             shuffle_index: ShuffleIndex::default(),
             used_lookups: HashSet::new(),
@@ -185,9 +208,22 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
             max_range_size: 0,
-            throw_range_check_error: false,
+            witness_gen: true,
+            assigned_constants: HashMap::new(),
         }
     }
+
+    /// Create a new region context
+    pub fn new_with_constants(
+        region: Region<'a, F>,
+        row: usize,
+        num_inner_cols: usize,
+        constants: ConstantsMap<F>,
+    ) -> RegionCtx<'a, F> {
+        let mut new_self = Self::new(region, row, num_inner_cols);
+        new_self.assigned_constants = constants;
+        new_self
+    }
     /// Create a new region context from a wrapped region
     pub fn from_wrapped_region(
         region: Option<RefCell<Region<'a, F>>>,
@@ -202,7 +238,6 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             num_inner_cols,
             linear_coord,
             row,
-            total_constants: 0,
             dynamic_lookup_index,
             shuffle_index,
             used_lookups: HashSet::new(),
@@ -210,16 +245,13 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
             max_range_size: 0,
-            throw_range_check_error: false,
+            witness_gen: false,
+            assigned_constants: HashMap::new(),
         }
     }
 
     /// Create a new region context
-    pub fn new_dummy(
-        row: usize,
-        num_inner_cols: usize,
-        throw_range_check_error: bool,
-    ) -> RegionCtx<'a, F> {
+    pub fn new_dummy(row: usize, num_inner_cols: usize, witness_gen: bool) -> RegionCtx<'a, F> {
         let region = None;
         let linear_coord = row * num_inner_cols;
 
@@ -228,7 +260,6 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             num_inner_cols,
             linear_coord,
             row,
-            total_constants: 0,
             dynamic_lookup_index: DynamicLookupIndex::default(),
             shuffle_index: ShuffleIndex::default(),
             used_lookups: HashSet::new(),
@@ -236,17 +267,17 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
             max_range_size: 0,
-            throw_range_check_error,
+            witness_gen,
+            assigned_constants: HashMap::new(),
         }
     }
 
     /// Create a new region context
-    pub fn new_dummy_with_constants(
+    pub fn new_dummy_with_linear_coord(
         row: usize,
         linear_coord: usize,
-        total_constants: usize,
         num_inner_cols: usize,
-        throw_range_check_error: bool,
+        witness_gen: bool,
     ) -> RegionCtx<'a, F> {
         let region = None;
         RegionCtx {
@@ -254,7 +285,6 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             num_inner_cols,
             linear_coord,
             row,
-            total_constants,
             dynamic_lookup_index: DynamicLookupIndex::default(),
             shuffle_index: ShuffleIndex::default(),
             used_lookups: HashSet::new(),
@@ -262,7 +292,8 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             max_lookup_inputs: 0,
             min_lookup_inputs: 0,
             max_range_size: 0,
-            throw_range_check_error,
+            witness_gen,
+            assigned_constants: HashMap::new(),
         }
     }
 
@@ -312,29 +343,27 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
     ) -> Result<(), RegionError> {
         let row = AtomicUsize::new(self.row());
         let linear_coord = AtomicUsize::new(self.linear_coord());
-        let constants = AtomicUsize::new(self.total_constants());
         let max_lookup_inputs = AtomicInt::new(self.max_lookup_inputs());
         let min_lookup_inputs = AtomicInt::new(self.min_lookup_inputs());
         let lookups = Arc::new(Mutex::new(self.used_lookups.clone()));
         let range_checks = Arc::new(Mutex::new(self.used_range_checks.clone()));
         let dynamic_lookup_index = Arc::new(Mutex::new(self.dynamic_lookup_index.clone()));
         let shuffle_index = Arc::new(Mutex::new(self.shuffle_index.clone()));
+        let constants = Arc::new(Mutex::new(self.assigned_constants.clone()));
 
         *output = output
             .par_enum_map(|idx, _| {
                 // we kick off the loop with the current offset
                 let starting_offset = row.load(Ordering::SeqCst);
                 let starting_linear_coord = linear_coord.load(Ordering::SeqCst);
-                let starting_constants = constants.load(Ordering::SeqCst);
                 // get inner value of the locked lookups
 
                 // we need to make sure that the region is not shared between threads
-                let mut local_reg = Self::new_dummy_with_constants(
+                let mut local_reg = Self::new_dummy_with_linear_coord(
                     starting_offset,
                     starting_linear_coord,
-                    starting_constants,
                     self.num_inner_cols,
-                    self.throw_range_check_error,
+                    self.witness_gen,
                 );
                 let res = inner_loop_function(idx, &mut local_reg);
                 // we update the offset and constants
@@ -343,10 +372,6 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
                     local_reg.linear_coord() - starting_linear_coord,
                     Ordering::SeqCst,
                 );
-                constants.fetch_add(
-                    local_reg.total_constants() - starting_constants,
-                    Ordering::SeqCst,
-                );
 
                 max_lookup_inputs.fetch_max(local_reg.max_lookup_inputs(), Ordering::SeqCst);
                 min_lookup_inputs.fetch_min(local_reg.min_lookup_inputs(), Ordering::SeqCst);
@@ -362,11 +387,13 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
                 // update the shuffle index
                 let mut shuffle_index = shuffle_index.lock().unwrap();
                 shuffle_index.update(&local_reg.shuffle_index);
+                // update the constants
+                let mut constants = constants.lock().unwrap();
+                constants.extend(local_reg.assigned_constants);
 
                 res
             })
             .map_err(|e| RegionError::from(format!("dummy_loop: {:?}", e)))?;
-        self.total_constants = constants.into_inner();
         self.linear_coord = linear_coord.into_inner();
         #[allow(trivial_numeric_casts)]
         {
@@ -410,6 +437,14 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
             .map_err(|e| {
                 RegionError::from(format!("dummy_loop: failed to get shuffle index: {:?}", e))
             })?;
+        self.assigned_constants = Arc::try_unwrap(constants)
+            .map_err(|e| {
+                RegionError::from(format!("dummy_loop: failed to get constants: {:?}", e))
+            })?
+            .into_inner()
+            .map_err(|e| {
+                RegionError::from(format!("dummy_loop: failed to get constants: {:?}", e))
+            })?;
 
         Ok(())
     }
@@ -435,7 +470,7 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         range: Range,
     ) -> Result<(), Box<dyn std::error::Error>> {
         if range.0 > range.1 {
-            return Err("update_max_min_lookup_range: invalid range".into());
+            return Err(format!("update_max_min_lookup_range: invalid range {:?}", range).into());
         }
 
         let range_size = (range.1 - range.0).abs();
@@ -477,7 +512,7 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
 
     /// Get the total number of constants
     pub fn total_constants(&self) -> usize {
-        self.total_constants
+        self.assigned_constants.len()
     }
 
     /// Get the dynamic lookup index
@@ -525,26 +560,24 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         self.max_range_size
     }
 
-    /// Assign a constant value
-    pub fn assign_constant(&mut self, var: &VarTensor, value: F) -> Result<ValType<F>, Error> {
-        self.total_constants += 1;
-        if let Some(region) = &self.region {
-            let cell = var.assign_constant(&mut region.borrow_mut(), self.linear_coord, value)?;
-            Ok(cell.into())
-        } else {
-            Ok(value.into())
-        }
-    }
     /// Assign a valtensor to a vartensor
     pub fn assign(
         &mut self,
         var: &VarTensor,
         values: &ValTensor<F>,
     ) -> Result<ValTensor<F>, Error> {
-        self.total_constants += values.num_constants();
         if let Some(region) = &self.region {
-            var.assign(&mut region.borrow_mut(), self.linear_coord, values)
+            var.assign(
+                &mut region.borrow_mut(),
+                self.linear_coord,
+                values,
+                &mut self.assigned_constants,
+            )
         } else {
+            if !values.is_instance() {
+                let values_map = values.create_constants_map_iterator();
+                self.assigned_constants.extend(values_map);
+            }
             Ok(values.clone())
         }
     }
@@ -560,14 +593,18 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         var: &VarTensor,
         values: &ValTensor<F>,
     ) -> Result<ValTensor<F>, Error> {
-        self.total_constants += values.num_constants();
         if let Some(region) = &self.region {
             var.assign(
                 &mut region.borrow_mut(),
                 self.combined_dynamic_shuffle_coord(),
                 values,
+                &mut self.assigned_constants,
             )
         } else {
+            if !values.is_instance() {
+                let values_map = values.create_constants_map_iterator();
+                self.assigned_constants.extend(values_map);
+            }
             Ok(values.clone())
         }
     }
@@ -594,13 +631,20 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
                 self.linear_coord,
                 values,
                 ommissions,
+                &mut self.assigned_constants,
             )
         } else {
-            self.total_constants += values.num_constants();
             let inner_tensor = values.get_inner_tensor().unwrap();
+            let mut values_map = values.create_constants_map();
+
             for o in ommissions {
-                self.total_constants -= inner_tensor.get_flat_index(**o).is_constant() as usize;
+                if let ValType::Constant(value) = inner_tensor.get_flat_index(**o) {
+                    values_map.remove(&value);
+                }
             }
+
+            self.assigned_constants.extend(values_map);
+
             Ok(values.clone())
         }
     }
@@ -615,24 +659,24 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
     ) -> Result<(ValTensor<F>, usize), Error> {
         if let Some(region) = &self.region {
             // duplicates every nth element to adjust for column overflow
-            let (res, len, total_assigned_constants) = var.assign_with_duplication(
+            let (res, len) = var.assign_with_duplication(
                 &mut region.borrow_mut(),
                 self.row,
                 self.linear_coord,
                 values,
                 check_mode,
                 single_inner_col,
+                &mut self.assigned_constants,
             )?;
-            self.total_constants += total_assigned_constants;
             Ok((res, len))
         } else {
-            let (_, len, total_assigned_constants) = var.dummy_assign_with_duplication(
+            let (_, len) = var.dummy_assign_with_duplication(
                 self.row,
                 self.linear_coord,
                 values,
                 single_inner_col,
+                &mut self.assigned_constants,
             )?;
-            self.total_constants += total_assigned_constants;
             Ok((values.clone(), len))
         }
     }
@@ -699,9 +743,4 @@ impl<'a, F: PrimeField + TensorType + PartialOrd> RegionCtx<'a, F> {
         }
         Ok(())
     }
-
-    /// increment constants
-    pub fn increment_constants(&mut self, n: usize) {
-        self.total_constants += n
-    }
 }

src/circuit/table.rs

@@ -17,8 +17,6 @@ use crate::{
 
 use crate::circuit::lookup::LookupOp;
 
-use super::Op;
-
 /// The range of the lookup table.
 pub type Range = (i128, i128);
 
@@ -98,7 +96,7 @@ pub struct Table<F: PrimeField> {
     _marker: PhantomData<F>,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Table<F> {
     /// get column index given input
     pub fn get_col_index(&self, input: F) -> F {
         //    range is split up into chunks of size col_size, find the chunk that input is in
@@ -113,11 +111,10 @@ impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
         let chunk = chunk as i128;
         // we index from 1 to prevent soundness issues
         let first_element = i128_to_felt(chunk * (self.col_size as i128) + self.range.0);
-        let op_f = Op::<F>::f(
-            &self.nonlinearity,
-            &[Tensor::from(vec![first_element].into_iter())],
-        )
-        .unwrap();
+        let op_f = self
+            .nonlinearity
+            .f(&[Tensor::from(vec![first_element].into_iter())])
+            .unwrap();
         (first_element, op_f.output[0])
     }
 
@@ -138,7 +135,7 @@ pub fn num_cols_required(range_len: i128, col_size: usize) -> usize {
     (range_len / (col_size as i128)) as usize + 1
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Table<F> {
     /// Configures the table.
     pub fn configure(
         cs: &mut ConstraintSystem<F>,
@@ -152,7 +149,7 @@ impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
         // number of cols needed to store the range
         let num_cols = num_cols_required((range.1 - range.0).abs(), col_size);
 
-        log::debug!("table range: {:?}", range);
+        debug!("table range: {:?}", range);
 
         let table_inputs = preexisting_inputs.unwrap_or_else(|| {
             let mut cols = vec![];
@@ -165,7 +162,7 @@ impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
         let num_cols = table_inputs.len();
 
         if num_cols > 1 {
-            debug!("Using {} columns for non-linearity table.", num_cols);
+            warn!("Using {} columns for non-linearity table.", num_cols);
         }
 
         let table_outputs = table_inputs
@@ -205,8 +202,8 @@ impl<F: PrimeField + TensorType + PartialOrd> Table<F> {
         let smallest = self.range.0;
         let largest = self.range.1;
 
-        let inputs = Tensor::from(smallest..=largest).map(|x| i128_to_felt(x));
-        let evals = Op::<F>::f(&self.nonlinearity, &[inputs.clone()])?;
+        let inputs: Tensor<F> = Tensor::from(smallest..=largest).map(|x| i128_to_felt(x));
+        let evals = self.nonlinearity.f(&[inputs.clone()])?;
         let chunked_inputs = inputs.chunks(self.col_size);
 
         self.is_assigned = true;
@@ -275,7 +272,7 @@ pub struct RangeCheck<F: PrimeField> {
     _marker: PhantomData<F>,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> RangeCheck<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> RangeCheck<F> {
     /// get first_element of column
     pub fn get_first_element(&self, chunk: usize) -> F {
         let chunk = chunk as i128;
@@ -303,7 +300,7 @@ impl<F: PrimeField + TensorType + PartialOrd> RangeCheck<F> {
     }
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> RangeCheck<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> RangeCheck<F> {
     /// Configures the table.
     pub fn configure(cs: &mut ConstraintSystem<F>, range: Range, logrows: usize) -> RangeCheck<F> {
         log::debug!("range check range: {:?}", range);

src/circuit/tests.rs

@@ -1048,8 +1048,8 @@ mod conv {
                                 &mut region,
                                 &self.inputs,
                                 Box::new(PolyOp::Conv {
-                                    padding: [(1, 1); 2],
-                                    stride: (2, 2),
+                                    padding: vec![(1, 1); 2],
+                                    stride: vec![2; 2],
                                 }),
                             )
                             .map_err(|_| Error::Synthesis)
@@ -1198,8 +1198,8 @@ mod conv_col_ultra_overflow {
                                 &mut region,
                                 &[self.image.clone(), self.kernel.clone()],
                                 Box::new(PolyOp::Conv {
-                                    padding: [(1, 1); 2],
-                                    stride: (2, 2),
+                                    padding: vec![(1, 1); 2],
+                                    stride: vec![2; 2],
                                 }),
                             )
                             .map_err(|_| Error::Synthesis)
@@ -1343,8 +1343,8 @@ mod conv_relu_col_ultra_overflow {
                                 &mut region,
                                 &[self.image.clone(), self.kernel.clone()],
                                 Box::new(PolyOp::Conv {
-                                    padding: [(1, 1); 2],
-                                    stride: (2, 2),
+                                    padding: vec![(1, 1); 2],
+                                    stride: vec![2; 2],
                                 }),
                             )
                             .map_err(|_| Error::Synthesis);
@@ -1911,6 +1911,8 @@ mod add_with_overflow {
 
 #[cfg(test)]
 mod add_with_overflow_and_poseidon {
+    use std::collections::HashMap;
+
     use halo2curves::bn256::Fr;
 
     use crate::circuit::modules::{
@@ -1969,8 +1971,10 @@ mod add_with_overflow_and_poseidon {
             let poseidon_chip: PoseidonChip<PoseidonSpec, WIDTH, RATE, WIDTH> =
                 PoseidonChip::new(config.poseidon.clone());
 
-            let assigned_inputs_a = poseidon_chip.layout(&mut layouter, &self.inputs[0..1], 0)?;
-            let assigned_inputs_b = poseidon_chip.layout(&mut layouter, &self.inputs[1..2], 1)?;
+            let assigned_inputs_a =
+                poseidon_chip.layout(&mut layouter, &self.inputs[0..1], 0, &mut HashMap::new())?;
+            let assigned_inputs_b =
+                poseidon_chip.layout(&mut layouter, &self.inputs[1..2], 1, &mut HashMap::new())?;
 
             layouter.assign_region(|| "_new_module", |_| Ok(()))?;
 

src/commands.rs

@@ -444,7 +444,7 @@ pub enum Commands {
         disable_selector_compression: bool,
         /// commitment used
         #[arg(long, default_value = DEFAULT_COMMITMENT)]
-        commitment: Commitments,
+        commitment: Option<Commitments>,
     },
     /// Aggregates proofs :)
     Aggregate {
@@ -479,7 +479,7 @@ pub enum Commands {
         split_proofs: bool,
         /// commitment used
         #[arg(long, default_value = DEFAULT_COMMITMENT)]
-        commitment: Commitments,
+        commitment: Option<Commitments>,
     },
     /// Compiles a circuit from onnx to a simplified graph (einsum + other ops) and parameters as sets of field elements
     CompileCircuit {
@@ -726,7 +726,7 @@ pub enum Commands {
         logrows: u32,
         /// commitment
         #[arg(long, default_value = DEFAULT_COMMITMENT)]
-        commitment: Commitments,
+        commitment: Option<Commitments>,
     },
     #[cfg(not(target_arch = "wasm32"))]
     /// Deploys an evm verifier that is generated by ezkl

src/execute.rs

@@ -24,6 +24,8 @@ use crate::pfsys::{
 use crate::pfsys::{save_vk, srs::*};
 use crate::tensor::TensorError;
 use crate::{Commitments, RunArgs};
+#[cfg(not(target_arch = "wasm32"))]
+use colored::Colorize;
 #[cfg(unix)]
 use gag::Gag;
 use halo2_proofs::dev::VerifyFailure;
@@ -194,7 +196,6 @@ pub async fn run(command: Commands) -> Result<String, Box<dyn Error>> {
             vk_path,
             srs_path,
         } => gen_witness(compiled_circuit, data, Some(output), vk_path, srs_path)
-            .await
             .map(|e| serde_json::to_string(&e).unwrap()),
         Commands::Mock { model, witness } => mock(model, witness),
         #[cfg(not(target_arch = "wasm32"))]
@@ -337,7 +338,7 @@ pub async fn run(command: Commands) -> Result<String, Box<dyn Error>> {
             logrows,
             split_proofs,
             disable_selector_compression,
-            commitment,
+            commitment.into(),
         ),
         Commands::Aggregate {
             proof_path,
@@ -358,7 +359,7 @@ pub async fn run(command: Commands) -> Result<String, Box<dyn Error>> {
             logrows,
             check_mode,
             split_proofs,
-            commitment,
+            commitment.into(),
         )
         .map(|e| serde_json::to_string(&e).unwrap()),
         Commands::Verify {
@@ -382,7 +383,7 @@ pub async fn run(command: Commands) -> Result<String, Box<dyn Error>> {
             srs_path,
             logrows,
             reduced_srs,
-            commitment,
+            commitment.into(),
         )
         .map(|e| serde_json::to_string(&e).unwrap()),
         #[cfg(not(target_arch = "wasm32"))]
@@ -538,7 +539,7 @@ fn check_srs_hash(
     let path = get_srs_path(logrows, srs_path, commitment);
     let hash = get_file_hash(&path)?;
 
-    let predefined_hash = match { crate::srs_sha::PUBLIC_SRS_SHA256_HASHES.get(&logrows) } {
+    let predefined_hash = match crate::srs_sha::PUBLIC_SRS_SHA256_HASHES.get(&logrows) {
         Some(h) => h,
         None => return Err(format!("SRS (k={}) hash not found in public set", logrows).into()),
     };
@@ -584,7 +585,7 @@ pub(crate) async fn get_srs_cmd(
     } else if let Some(settings_p) = settings_path {
         if settings_p.exists() {
             let settings = GraphSettings::load(&settings_p)?;
-            settings.run_args.commitment
+            settings.run_args.commitment.into()
         } else {
             return Err(err_string.into());
         }
@@ -635,7 +636,7 @@ pub(crate) fn table(model: PathBuf, run_args: RunArgs) -> Result<String, Box<dyn
     Ok(String::new())
 }
 
-pub(crate) async fn gen_witness(
+pub(crate) fn gen_witness(
     compiled_circuit_path: PathBuf,
     data: PathBuf,
     output: Option<PathBuf>,
@@ -658,33 +659,29 @@ pub(crate) async fn gen_witness(
     };
 
     #[cfg(not(target_arch = "wasm32"))]
-    let mut input = circuit.load_graph_input(&data).await?;
+    let mut input = circuit.load_graph_input(&data)?;
     #[cfg(target_arch = "wasm32")]
     let mut input = circuit.load_graph_input(&data)?;
 
     // if any of the settings have kzg visibility then we need to load the srs
 
+    let commitment: Commitments = settings.run_args.commitment.into();
+
     let start_time = Instant::now();
     let witness = if settings.module_requires_polycommit() {
-        if get_srs_path(
-            settings.run_args.logrows,
-            srs_path.clone(),
-            settings.run_args.commitment,
-        )
-        .exists()
-        {
-            match settings.run_args.commitment {
+        if get_srs_path(settings.run_args.logrows, srs_path.clone(), commitment).exists() {
+            match Commitments::from(settings.run_args.commitment) {
                 Commitments::KZG => {
                     let srs: ParamsKZG<Bn256> = load_params_prover::<KZGCommitmentScheme<Bn256>>(
                         srs_path.clone(),
                         settings.run_args.logrows,
-                        settings.run_args.commitment,
+                        commitment,
                     )?;
                     circuit.forward::<KZGCommitmentScheme<_>>(
                         &mut input,
                         vk.as_ref(),
                         Some(&srs),
-                        false,
+                        true,
                     )?
                 }
                 Commitments::IPA => {
@@ -692,22 +689,22 @@ pub(crate) async fn gen_witness(
                         load_params_prover::<IPACommitmentScheme<G1Affine>>(
                             srs_path.clone(),
                             settings.run_args.logrows,
-                            settings.run_args.commitment,
+                            commitment,
                         )?;
                     circuit.forward::<IPACommitmentScheme<_>>(
                         &mut input,
                         vk.as_ref(),
                         Some(&srs),
-                        false,
+                        true,
                     )?
                 }
             }
         } else {
             warn!("SRS for poly commit does not exist (will be ignored)");
-            circuit.forward::<KZGCommitmentScheme<Bn256>>(&mut input, vk.as_ref(), None, false)?
+            circuit.forward::<KZGCommitmentScheme<Bn256>>(&mut input, vk.as_ref(), None, true)?
         }
     } else {
-        circuit.forward::<KZGCommitmentScheme<Bn256>>(&mut input, vk.as_ref(), None, false)?
+        circuit.forward::<KZGCommitmentScheme<Bn256>>(&mut input, vk.as_ref(), None, true)?
     };
 
     // print each variable tuple (symbol, value) as symbol=value
@@ -819,7 +816,15 @@ impl AccuracyResults {
             let error = (original.clone() - calibrated.clone())?;
             let abs_error = error.map(|x| x.abs());
             let squared_error = error.map(|x| x.powi(2));
-            let percentage_error = error.enum_map(|i, x| Ok::<_, TensorError>(x / original[i]))?;
+            let percentage_error = error.enum_map(|i, x| {
+                // if everything is 0 then we can't divide by 0 so we just return 0
+                let res = if original[i] == 0.0 && x == 0.0 {
+                    0.0
+                } else {
+                    x / original[i]
+                };
+                Ok::<f32, TensorError>(res)
+            })?;
             let abs_percentage_error = percentage_error.map(|x| x.abs());
 
             errors.extend(error);
@@ -888,6 +893,7 @@ pub(crate) fn calibrate(
     only_range_check_rebase: bool,
     max_logrows: Option<u32>,
 ) -> Result<GraphSettings, Box<dyn Error>> {
+    use log::error;
     use std::collections::HashMap;
     use tabled::Table;
 
@@ -900,9 +906,9 @@ pub(crate) fn calibrate(
     let model = Model::from_run_args(&settings.run_args, &model_path)?;
 
     let chunks = data.split_into_batches(model.graph.input_shapes()?)?;
-    info!("num of calibration batches: {}", chunks.len());
+    info!("num calibration batches: {}", chunks.len());
 
-    info!("running onnx predictions...");
+    debug!("running onnx predictions...");
     let original_predictions = Model::run_onnx_predictions(
         &settings.run_args,
         &model_path,
@@ -970,10 +976,18 @@ pub(crate) fn calibrate(
     let pb = init_bar(range_grid.len() as u64);
     pb.set_message("calibrating...");
 
+    let mut num_failed = 0;
+    let mut num_passed = 0;
+
     for (((input_scale, param_scale), scale_rebase_multiplier), div_rebasing) in range_grid {
         pb.set_message(format!(
-            "input scale: {}, param scale: {}, scale rebase multiplier: {}, div rebasing: {}",
-            input_scale, param_scale, scale_rebase_multiplier, div_rebasing
+            "i-scale: {}, p-scale: {}, rebase-(x): {}, div-rebase: {}, fail: {}, pass: {}",
+            input_scale.to_string().blue(),
+            param_scale.to_string().blue(),
+            scale_rebase_multiplier.to_string().blue(),
+            div_rebasing.to_string().yellow(),
+            num_failed.to_string().red(),
+            num_passed.to_string().green()
         ));
 
         let key = (
@@ -1007,7 +1021,9 @@ pub(crate) fn calibrate(
         let mut circuit = match GraphCircuit::from_run_args(&local_run_args, &model_path) {
             Ok(c) => c,
             Err(e) => {
-                debug!("circuit creation from run args failed: {:?}", e);
+                error!("circuit creation from run args failed: {:?}", e);
+                pb.inc(1);
+                num_failed += 1;
                 continue;
             }
         };
@@ -1039,7 +1055,9 @@ pub(crate) fn calibrate(
             Ok(_) => (),
             // typically errors will be due to the circuit overflowing the i128 limit
             Err(e) => {
-                debug!("forward pass failed: {:?}", e);
+                error!("forward pass failed: {:?}", e);
+                pb.inc(1);
+                num_failed += 1;
                 continue;
             }
         }
@@ -1104,8 +1122,10 @@ pub(crate) fn calibrate(
                 "found settings: \n {}",
                 found_settings.as_json()?.to_colored_json_auto()?
             );
+            num_passed += 1;
         } else {
-            debug!("calibration failed {}", res.err().unwrap());
+            error!("calibration failed {}", res.err().unwrap());
+            num_failed += 1;
         }
 
         pb.inc(1);
@@ -1278,17 +1298,19 @@ pub(crate) fn create_evm_verifier(
     render_vk_seperately: bool,
 ) -> Result<String, Box<dyn Error>> {
     check_solc_requirement();
-    let circuit_settings = GraphSettings::load(&settings_path)?;
+
+    let settings = GraphSettings::load(&settings_path)?;
+    let commitment: Commitments = settings.run_args.commitment.into();
     let params = load_params_verifier::<KZGCommitmentScheme<Bn256>>(
         srs_path,
-        circuit_settings.run_args.logrows,
-        circuit_settings.run_args.commitment,
+        settings.run_args.logrows,
+        commitment,
     )?;
 
-    let num_instance = circuit_settings.total_instances();
+    let num_instance = settings.total_instances();
     let num_instance: usize = num_instance.iter().sum::<usize>();
 
-    let vk = load_vk::<KZGCommitmentScheme<Bn256>, GraphCircuit>(vk_path, circuit_settings)?;
+    let vk = load_vk::<KZGCommitmentScheme<Bn256>, GraphCircuit>(vk_path, settings)?;
     trace!("params computed");
 
     let generator = halo2_solidity_verifier::SolidityGenerator::new(
@@ -1322,17 +1344,18 @@ pub(crate) fn create_evm_vk(
     abi_path: PathBuf,
 ) -> Result<String, Box<dyn Error>> {
     check_solc_requirement();
-    let circuit_settings = GraphSettings::load(&settings_path)?;
+    let settings = GraphSettings::load(&settings_path)?;
+    let commitment: Commitments = settings.run_args.commitment.into();
     let params = load_params_verifier::<KZGCommitmentScheme<Bn256>>(
         srs_path,
-        circuit_settings.run_args.logrows,
-        circuit_settings.run_args.commitment,
+        settings.run_args.logrows,
+        commitment,
     )?;
 
-    let num_instance = circuit_settings.total_instances();
+    let num_instance = settings.total_instances();
     let num_instance: usize = num_instance.iter().sum::<usize>();
 
-    let vk = load_vk::<KZGCommitmentScheme<Bn256>, GraphCircuit>(vk_path, circuit_settings)?;
+    let vk = load_vk::<KZGCommitmentScheme<Bn256>, GraphCircuit>(vk_path, settings)?;
     trace!("params computed");
 
     let generator = halo2_solidity_verifier::SolidityGenerator::new(
@@ -1601,8 +1624,9 @@ pub(crate) fn setup(
     }
 
     let logrows = circuit.settings().run_args.logrows;
+    let commitment: Commitments = circuit.settings().run_args.commitment.into();
 
-    let pk = match circuit.settings().run_args.commitment {
+    let pk = match commitment {
         Commitments::KZG => {
             let params = load_params_prover::<KZGCommitmentScheme<Bn256>>(
                 srs_path,
@@ -1711,7 +1735,8 @@ pub(crate) fn prove(
     let transcript: TranscriptType = proof_type.into();
     let proof_split_commits: Option<ProofSplitCommit> = data.into();
 
-    let commitment = circuit_settings.run_args.commitment;
+    let commitment = circuit_settings.run_args.commitment.into();
+    let logrows = circuit_settings.run_args.logrows;
     // creates and verifies the proof
     let mut snark = match commitment {
         Commitments::KZG => {
@@ -1720,7 +1745,7 @@ pub(crate) fn prove(
 
             let params = load_params_prover::<KZGCommitmentScheme<Bn256>>(
                 srs_path,
-                circuit_settings.run_args.logrows,
+                logrows,
                 Commitments::KZG,
             )?;
             match strategy {
@@ -1879,7 +1904,9 @@ pub(crate) fn mock_aggregate(
             }
             Err(_) => {
                 return Err(
-                    format!("invalid sample commitment type for aggregation, must be KZG").into(),
+                    "invalid sample commitment type for aggregation, must be KZG"
+                        .to_string()
+                        .into(),
                 );
             }
         }
@@ -1922,7 +1949,9 @@ pub(crate) fn setup_aggregate(
             }
             Err(_) => {
                 return Err(
-                    format!("invalid sample commitment type for aggregation, must be KZG",).into(),
+                    "invalid sample commitment type for aggregation, must be KZG"
+                        .to_string()
+                        .into(),
                 );
             }
         }
@@ -1983,7 +2012,9 @@ pub(crate) fn aggregate(
             }
             Err(_) => {
                 return Err(
-                    format!("invalid sample commitment type for aggregation, must be KZG").into(),
+                    "invalid sample commitment type for aggregation, must be KZG"
+                        .to_string()
+                        .into(),
                 );
             }
         }
@@ -2156,8 +2187,9 @@ pub(crate) fn verify(
     let circuit_settings = GraphSettings::load(&settings_path)?;
 
     let logrows = circuit_settings.run_args.logrows;
+    let commitment = circuit_settings.run_args.commitment.into();
 
-    match circuit_settings.run_args.commitment {
+    match commitment {
         Commitments::KZG => {
             let proof = Snark::load::<KZGCommitmentScheme<Bn256>>(&proof_path)?;
             let params: ParamsKZG<Bn256> = if reduced_srs {

src/graph/input.rs

@@ -21,8 +21,6 @@ use std::io::BufWriter;
 use std::io::Read;
 use std::panic::UnwindSafe;
 #[cfg(not(target_arch = "wasm32"))]
-use std::thread;
-#[cfg(not(target_arch = "wasm32"))]
 use tract_onnx::tract_core::{
     tract_data::{prelude::Tensor as TractTensor, TVec},
     value::TValue,
@@ -234,21 +232,15 @@ impl PostgresSource {
             )
         };
 
-        let res: Vec<pg_bigdecimal::PgNumeric> = thread::spawn(move || {
-            let mut client = Client::connect(&config, NoTls).unwrap();
-            let mut res: Vec<pg_bigdecimal::PgNumeric> = Vec::new();
-            // extract rows from query
-            for row in client.query(&query, &[]).unwrap() {
-                // extract features from row
-                for i in 0..row.len() {
-                    res.push(row.get(i));
-                }
+        let mut client = Client::connect(&config, NoTls)?;
+        let mut res: Vec<pg_bigdecimal::PgNumeric> = Vec::new();
+        // extract rows from query
+        for row in client.query(&query, &[])? {
+            // extract features from row
+            for i in 0..row.len() {
+                res.push(row.get(i));
             }
-            res
-        })
-        .join()
-        .map_err(|_| "failed to fetch data from postgres")?;
-
+        }
         Ok(vec![res])
     }
 

src/graph/mod.rs

@@ -26,6 +26,7 @@ use self::input::{FileSource, GraphData};
 use self::modules::{GraphModules, ModuleConfigs, ModuleForwardResult, ModuleSizes};
 use crate::circuit::lookup::LookupOp;
 use crate::circuit::modules::ModulePlanner;
+use crate::circuit::region::ConstantsMap;
 use crate::circuit::table::{num_cols_required, Range, Table, RESERVED_BLINDING_ROWS_PAD};
 use crate::circuit::{CheckMode, InputType};
 use crate::fieldutils::felt_to_f64;
@@ -38,7 +39,7 @@ use halo2_proofs::{
     plonk::{Circuit, ConstraintSystem, Error as PlonkError},
 };
 use halo2curves::bn256::{self, Fr as Fp, G1Affine};
-use halo2curves::ff::PrimeField;
+use halo2curves::ff::{Field, PrimeField};
 #[cfg(not(target_arch = "wasm32"))]
 use lazy_static::lazy_static;
 use log::{debug, error, trace, warn};
@@ -155,7 +156,7 @@ use std::cell::RefCell;
 thread_local!(
     /// This is a global variable that holds the settings for the graph
     /// This is used to pass settings to the layouter and other parts of the circuit without needing to heavily modify the Halo2 API in a new fork
-    pub static GLOBAL_SETTINGS: RefCell<Option<GraphSettings>> = RefCell::new(None)
+    pub static GLOBAL_SETTINGS: RefCell<Option<GraphSettings>> = const { RefCell::new(None) }
 );
 
 /// Result from a forward pass
@@ -917,7 +918,7 @@ impl GraphCircuit {
 
     ///
     #[cfg(not(target_arch = "wasm32"))]
-    pub async fn load_graph_input(
+    pub fn load_graph_input(
         &mut self,
         data: &GraphData,
     ) -> Result<Vec<Tensor<Fp>>, Box<dyn std::error::Error>> {
@@ -927,7 +928,6 @@ impl GraphCircuit {
         debug!("input scales: {:?}", scales);
 
         self.process_data_source(&data.input_data, shapes, scales, input_types)
-            .await
     }
 
     #[cfg(target_arch = "wasm32")]
@@ -951,7 +951,7 @@ impl GraphCircuit {
 
     #[cfg(not(target_arch = "wasm32"))]
     /// Process the data source for the model
-    async fn process_data_source(
+    fn process_data_source(
         &mut self,
         data: &DataSource,
         shapes: Vec<Vec<usize>>,
@@ -964,8 +964,16 @@ impl GraphCircuit {
                 for (i, shape) in shapes.iter().enumerate() {
                     per_item_scale.extend(vec![scales[i]; shape.iter().product::<usize>()]);
                 }
-                self.load_on_chain_data(source.clone(), &shapes, per_item_scale)
-                    .await
+
+                // start runtime and fetch data
+                let runtime = tokio::runtime::Builder::new_current_thread()
+                    .enable_all()
+                    .build()?;
+
+                runtime.block_on(async {
+                    self.load_on_chain_data(source.clone(), &shapes, per_item_scale)
+                        .await
+                })
             }
             DataSource::File(file_data) => {
                 self.load_file_data(file_data, &shapes, scales, input_types)
@@ -1051,12 +1059,10 @@ impl GraphCircuit {
     }
 
     fn calc_safe_lookup_range(min_max_lookup: Range, lookup_safety_margin: i128) -> Range {
-        let margin = (
+        (
             lookup_safety_margin * min_max_lookup.0,
             lookup_safety_margin * min_max_lookup.1,
-        );
-
-        margin
+        )
     }
 
     fn calc_num_cols(range_len: i128, max_logrows: u32) -> usize {
@@ -1240,7 +1246,7 @@ impl GraphCircuit {
         inputs: &mut [Tensor<Fp>],
         vk: Option<&VerifyingKey<G1Affine>>,
         srs: Option<&Scheme::ParamsProver>,
-        throw_range_check_error: bool,
+        witness_gen: bool,
     ) -> Result<GraphWitness, Box<dyn std::error::Error>> {
         let original_inputs = inputs.to_vec();
 
@@ -1289,7 +1295,7 @@ impl GraphCircuit {
 
         let mut model_results =
             self.model()
-                .forward(inputs, &self.settings().run_args, throw_range_check_error)?;
+                .forward(inputs, &self.settings().run_args, witness_gen)?;
 
         if visibility.output.requires_processing() {
             let module_outlets = visibility.output.overwrites_inputs();
@@ -1452,7 +1458,8 @@ impl GraphCircuit {
 }
 
 #[derive(Clone, Debug, Default, Serialize, Deserialize)]
-struct CircuitSize {
+/// The configuration for the graph circuit
+pub struct CircuitSize {
     num_instances: usize,
     num_advice_columns: usize,
     num_fixed: usize,
@@ -1462,7 +1469,8 @@ struct CircuitSize {
 }
 
 impl CircuitSize {
-    pub fn from_cs(cs: &ConstraintSystem<Fp>, logrows: u32) -> Self {
+    ///
+    pub fn from_cs<F: Field>(cs: &ConstraintSystem<F>, logrows: u32) -> Self {
         CircuitSize {
             num_instances: cs.num_instance_columns(),
             num_advice_columns: cs.num_advice_columns(),
@@ -1604,6 +1612,8 @@ impl Circuit<Fp> for GraphCircuit {
         let output_vis = &self.settings().run_args.output_visibility;
         let mut graph_modules = GraphModules::new();
 
+        let mut constants = ConstantsMap::new();
+
         let mut config = config.clone();
 
         let mut inputs = self
@@ -1649,6 +1659,7 @@ impl Circuit<Fp> for GraphCircuit {
                 &mut input_outlets,
                 input_visibility,
                 &mut instance_offset,
+                &mut constants,
             )?;
             // replace inputs with the outlets
             for (i, outlet) in outlets.iter().enumerate() {
@@ -1661,6 +1672,7 @@ impl Circuit<Fp> for GraphCircuit {
                 &mut inputs,
                 input_visibility,
                 &mut instance_offset,
+                &mut constants,
             )?;
         }
 
@@ -1697,6 +1709,7 @@ impl Circuit<Fp> for GraphCircuit {
                 &mut flattened_params,
                 param_visibility,
                 &mut instance_offset,
+                &mut constants,
             )?;
 
             let shapes = self.model().const_shapes();
@@ -1725,6 +1738,7 @@ impl Circuit<Fp> for GraphCircuit {
                 &inputs,
                 &mut vars,
                 &outputs,
+                &mut constants,
             )
             .map_err(|e| {
                 log::error!("{}", e);
@@ -1749,6 +1763,7 @@ impl Circuit<Fp> for GraphCircuit {
                 &mut output_outlets,
                 &self.settings().run_args.output_visibility,
                 &mut instance_offset,
+                &mut constants,
             )?;
 
             // replace outputs with the outlets
@@ -1762,6 +1777,7 @@ impl Circuit<Fp> for GraphCircuit {
                 &mut outputs,
                 &self.settings().run_args.output_visibility,
                 &mut instance_offset,
+                &mut constants,
             )?;
         }
 

src/graph/model.rs

@@ -5,6 +5,7 @@ use super::vars::*;
 use super::GraphError;
 use super::GraphSettings;
 use crate::circuit::hybrid::HybridOp;
+use crate::circuit::region::ConstantsMap;
 use crate::circuit::region::RegionCtx;
 use crate::circuit::table::Range;
 use crate::circuit::Input;
@@ -404,7 +405,7 @@ impl ParsedNodes {
                 .get(input)
                 .ok_or(GraphError::MissingNode(*input))?;
             let input_dims = node.out_dims();
-            let input_dim = input_dims.get(0).ok_or(GraphError::MissingNode(*input))?;
+            let input_dim = input_dims.first().ok_or(GraphError::MissingNode(*input))?;
             inputs.push(input_dim.clone());
         }
 
@@ -514,21 +515,24 @@ impl Model {
             instance_shapes.len().to_string().blue(),
             "instances".blue()
         );
-        // this is the total number of variables we will need to allocate
-        // for the circuit
-        let default_value = if !self.visibility.input.is_fixed() {
-            ValType::Value(Value::<Fp>::unknown())
-        } else {
-            ValType::Constant(Fp::ONE)
-        };
 
         let inputs: Vec<ValTensor<Fp>> = self
             .graph
             .input_shapes()?
             .iter()
             .map(|shape| {
-                let mut t: ValTensor<Fp> =
-                    vec![default_value.clone(); shape.iter().product()].into();
+                let len = shape.iter().product();
+                let mut t: ValTensor<Fp> = (0..len)
+                    .map(|_| {
+                        if !self.visibility.input.is_fixed() {
+                            ValType::Value(Value::<Fp>::unknown())
+                        } else {
+                            ValType::Constant(Fp::random(&mut rand::thread_rng()))
+                        }
+                    })
+                    .collect::<Vec<_>>()
+                    .into();
+
                 t.reshape(shape)?;
                 Ok(t)
             })
@@ -577,13 +581,13 @@ impl Model {
         &self,
         model_inputs: &[Tensor<Fp>],
         run_args: &RunArgs,
-        throw_range_check_error: bool,
+        witness_gen: bool,
     ) -> Result<ForwardResult, Box<dyn Error>> {
         let valtensor_inputs: Vec<ValTensor<Fp>> = model_inputs
             .iter()
             .map(|x| x.map(|elem| ValType::Value(Value::known(elem))).into())
             .collect();
-        let res = self.dummy_layout(run_args, &valtensor_inputs, throw_range_check_error)?;
+        let res = self.dummy_layout(run_args, &valtensor_inputs, witness_gen)?;
         Ok(res.into())
     }
 
@@ -799,13 +803,18 @@ impl Model {
                     let input_state_idx = input_state_idx(&input_mappings);
 
                     let mut output_mappings = vec![];
-                    for mapping in b.output_mapping.iter() {
+                    for (i, mapping) in b.output_mapping.iter().enumerate() {
                         let mut mappings = vec![];
                         if let Some(outlet) = mapping.last_value_slot {
                             mappings.push(OutputMapping::Single {
                                 outlet,
                                 is_state: mapping.state,
                             });
+                        } else if mapping.state {
+                            mappings.push(OutputMapping::Single {
+                                outlet: i,
+                                is_state: mapping.state,
+                            });
                         }
                         if let Some(last) = mapping.scan {
                             mappings.push(OutputMapping::Stacked {
@@ -814,6 +823,7 @@ impl Model {
                                 is_state: false,
                             });
                         }
+
                         output_mappings.push(mappings);
                     }
 
@@ -1071,6 +1081,8 @@ impl Model {
     /// * `layouter` - Halo2 Layouter.
     /// * `inputs` - The values to feed into the circuit.
     /// * `vars` - The variables for the circuit.
+    /// * `witnessed_outputs` - The values to compare against.
+    /// * `constants` - The constants for the circuit.
     pub fn layout(
         &self,
         mut config: ModelConfig,
@@ -1079,6 +1091,7 @@ impl Model {
         inputs: &[ValTensor<Fp>],
         vars: &mut ModelVars<Fp>,
         witnessed_outputs: &[ValTensor<Fp>],
+        constants: &mut ConstantsMap<Fp>,
     ) -> Result<Vec<ValTensor<Fp>>, Box<dyn Error>> {
         info!("model layout...");
 
@@ -1104,14 +1117,12 @@ impl Model {
         config.base.layout_tables(layouter)?;
         config.base.layout_range_checks(layouter)?;
 
-        let mut num_rows = 0;
-        let mut linear_coord = 0;
-        let mut total_const_size = 0;
+        let original_constants = constants.clone();
 
         let outputs = layouter.assign_region(
             || "model",
             |region| {
-                let mut thread_safe_region = RegionCtx::new(region, 0, run_args.num_inner_cols);
+                let mut thread_safe_region = RegionCtx::new_with_constants(region, 0, run_args.num_inner_cols, original_constants.clone());
                 // we need to do this as this loop is called multiple times
                 vars.set_instance_idx(instance_idx);
 
@@ -1157,29 +1168,17 @@ impl Model {
                         error!("{}", e);
                         halo2_proofs::plonk::Error::Synthesis
                     })?;
-                } else if !run_args.output_visibility.is_private() {
-                    for output in &outputs {
-                    thread_safe_region.increment_total_constants(output.num_constants());
-                    }
                 }
-                num_rows = thread_safe_region.row();
-                linear_coord = thread_safe_region.linear_coord();
-                total_const_size = thread_safe_region.total_constants();
+                // Then number of columns in the circuits
+                #[cfg(not(target_arch = "wasm32"))]
+                thread_safe_region.debug_report();
+
+                *constants = thread_safe_region.assigned_constants().clone();
 
                 Ok(outputs)
             },
-        )?;
 
-        // Then number of columns in the circuits
-        #[cfg(not(target_arch = "wasm32"))]
-        debug!(
-            "{} {} {} (coord={}, constants={})",
-            "model uses".blue(),
-            num_rows.to_string().blue(),
-            "rows".blue(),
-            linear_coord.to_string().yellow(),
-            total_const_size.to_string().red()
-        );
+        )?;
 
         let duration = start_time.elapsed();
         trace!("model layout took: {:?}", duration);
@@ -1201,6 +1200,20 @@ impl Model {
             .collect();
 
         for (idx, node) in self.graph.nodes.iter() {
+            debug!("laying out {}: {}", idx, node.as_str(),);
+            // Then number of columns in the circuits
+            #[cfg(not(target_arch = "wasm32"))]
+            region.debug_report();
+            debug!("input indices: {:?}", node.inputs());
+            debug!("output scales: {:?}", node.out_scales());
+            debug!(
+                "input scales: {:?}",
+                node.inputs()
+                    .iter()
+                    .map(|(idx, outlet)| self.graph.nodes[idx].out_scales()[*outlet])
+                    .collect_vec()
+            );
+
             let mut values: Vec<ValTensor<Fp>> = if !node.is_input() {
                 node.inputs()
                     .iter()
@@ -1212,31 +1225,11 @@ impl Model {
                 // we re-assign inputs, always from the 0 outlet
                 vec![results.get(idx).ok_or(GraphError::MissingResults)?[0].clone()]
             };
-
+            debug!("output dims: {:?}", node.out_dims());
             debug!(
-                "laying out {}: {}, row:{}, coord:{}, total_constants: {}, max_lookup_inputs: {}, min_lookup_inputs: {}",
-                idx,
-                node.as_str(),
-                region.row(),
-                region.linear_coord(),
-                region.total_constants(),
-                region.max_lookup_inputs(),
-                region.min_lookup_inputs()
-            );
-            debug!("dims: {:?}", node.out_dims());
-            debug!(
-                "input_dims {:?}",
+                "input dims {:?}",
                 values.iter().map(|v| v.dims()).collect_vec()
             );
-            debug!("output scales: {:?}", node.out_scales());
-            debug!("input indices: {:?}", node.inputs());
-            debug!(
-                "input scales: {:?}",
-                node.inputs()
-                    .iter()
-                    .map(|(idx, outlet)| self.graph.nodes[idx].out_scales()[*outlet])
-                    .collect_vec()
-            );
 
             match &node {
                 NodeType::Node(n) => {
@@ -1277,8 +1270,8 @@ impl Model {
                     let num_iter = number_of_iterations(&input_mappings, input_dims.collect());
 
                     debug!(
-                        "{} iteration(s) in a subgraph with inputs {:?} and sources {:?}",
-                        num_iter, inputs, model.graph.inputs
+                        "{} iteration(s) in a subgraph with inputs {:?}, sources {:?}, and outputs {:?}",
+                        num_iter, inputs, model.graph.inputs, model.graph.outputs
                     );
 
                     let mut full_results: Vec<ValTensor<Fp>> = vec![];
@@ -1310,6 +1303,7 @@ impl Model {
                         let res = model.layout_nodes(config, region, &mut subgraph_results)?;
 
                         let mut outlets = BTreeMap::new();
+                        let mut stacked_outlets = BTreeMap::new();
 
                         for (mappings, outlet_res) in output_mappings.iter().zip(res) {
                             for mapping in mappings {
@@ -1322,25 +1316,42 @@ impl Model {
                                             let stacked_res = full_results[*outlet]
                                                 .clone()
                                                 .concat_axis(outlet_res.clone(), axis)?;
-
-                                            outlets.insert(outlet, stacked_res);
-                                        } else {
-                                            outlets.insert(outlet, outlet_res.clone());
+                                            stacked_outlets.insert(outlet, stacked_res);
                                         }
+                                        outlets.insert(outlet, outlet_res.clone());
                                     }
                                 }
                             }
                         }
 
-                        full_results = outlets.into_values().collect_vec();
+                        // now extend with stacked elements
+                        let mut pre_stacked_outlets = outlets.clone();
+                        pre_stacked_outlets.extend(stacked_outlets);
+
+                        let outlets = outlets.into_values().collect_vec();
+
+                        full_results = pre_stacked_outlets.into_values().collect_vec();
 
                         let output_states = output_state_idx(output_mappings);
                         let input_states = input_state_idx(&input_mappings);
 
-                        assert_eq!(input_states.len(), output_states.len());
+                        assert_eq!(
+                            input_states.len(),
+                            output_states.len(),
+                            "input and output states must be the same length, got {:?} and {:?}",
+                            input_mappings,
+                            output_mappings
+                        );
 
                         for (input_idx, output_idx) in input_states.iter().zip(output_states) {
-                            values[*input_idx] = full_results[output_idx].clone();
+                            assert_eq!(
+                                values[*input_idx].dims(),
+                                outlets[output_idx].dims(),
+                                "input and output dims must be the same, got {:?} and {:?}",
+                                values[*input_idx].dims(),
+                                outlets[output_idx].dims()
+                            );
+                            values[*input_idx] = outlets[output_idx].clone();
                         }
                     }
 
@@ -1380,7 +1391,7 @@ impl Model {
         &self,
         run_args: &RunArgs,
         inputs: &[ValTensor<Fp>],
-        throw_range_check_error: bool,
+        witness_gen: bool,
     ) -> Result<DummyPassRes, Box<dyn Error>> {
         debug!("calculating num of constraints using dummy model layout...");
 
@@ -1399,29 +1410,31 @@ impl Model {
             vars: ModelVars::new_dummy(),
         };
 
-        let mut region = RegionCtx::new_dummy(0, run_args.num_inner_cols, throw_range_check_error);
+        let mut region = RegionCtx::new_dummy(0, run_args.num_inner_cols, witness_gen);
 
         let outputs = self.layout_nodes(&mut model_config, &mut region, &mut results)?;
 
         if self.visibility.output.is_public() || self.visibility.output.is_fixed() {
-            let default_value = if !self.visibility.output.is_fixed() {
-                ValType::Value(Value::<Fp>::unknown())
-            } else {
-                ValType::Constant(Fp::ONE)
-            };
-
             let output_scales = self.graph.get_output_scales()?;
             let res = outputs
                 .iter()
                 .enumerate()
                 .map(|(i, output)| {
+                    let mut comparator: ValTensor<Fp> = (0..output.len())
+                        .map(|_| {
+                            if !self.visibility.output.is_fixed() {
+                                ValType::Value(Value::<Fp>::unknown())
+                            } else {
+                                ValType::Constant(Fp::random(&mut rand::thread_rng()))
+                            }
+                        })
+                        .collect::<Vec<_>>()
+                        .into();
+                    comparator.reshape(output.dims())?;
+
                     let mut tolerance = run_args.tolerance;
                     tolerance.scale = scale_to_multiplier(output_scales[i]).into();
 
-                    let mut comparator: ValTensor<Fp> =
-                        vec![default_value.clone(); output.dims().iter().product::<usize>()].into();
-                    comparator.reshape(output.dims())?;
-
                     dummy_config.layout(
                         &mut region,
                         &[output.clone(), comparator],
@@ -1432,7 +1445,7 @@ impl Model {
             res?;
         } else if !self.visibility.output.is_private() {
             for output in &outputs {
-                region.increment_total_constants(output.num_constants());
+                region.update_constants(output.create_constants_map());
             }
         }
 
@@ -1441,14 +1454,7 @@ impl Model {
 
         // Then number of columns in the circuits
         #[cfg(not(target_arch = "wasm32"))]
-        debug!(
-            "{} {} {} (coord={}, constants={})",
-            "model uses".blue(),
-            region.row().to_string().blue(),
-            "rows".blue(),
-            region.linear_coord().to_string().yellow(),
-            region.total_constants().to_string().red()
-        );
+        region.debug_report();
 
         let outputs = outputs
             .iter()

src/graph/modules.rs

@@ -2,6 +2,7 @@ use crate::circuit::modules::polycommit::{PolyCommitChip, PolyCommitConfig};
 use crate::circuit::modules::poseidon::spec::{PoseidonSpec, POSEIDON_RATE, POSEIDON_WIDTH};
 use crate::circuit::modules::poseidon::{PoseidonChip, PoseidonConfig};
 use crate::circuit::modules::Module;
+use crate::circuit::region::ConstantsMap;
 use crate::tensor::{Tensor, ValTensor};
 use halo2_proofs::circuit::Layouter;
 use halo2_proofs::plonk::{Column, ConstraintSystem, Error, Instance, VerifyingKey};
@@ -211,12 +212,13 @@ impl GraphModules {
         layouter: &mut impl Layouter<Fp>,
         x: &mut Vec<ValTensor<Fp>>,
         instance_offset: &mut usize,
+        constants: &mut ConstantsMap<Fp>,
     ) -> Result<(), Error> {
         // reserve module 0 for ... modules
         // hash the input and replace the constrained cells in the input
         let cloned_x = (*x).clone();
         x[0] = module
-            .layout(layouter, &cloned_x, instance_offset.to_owned())
+            .layout(layouter, &cloned_x, instance_offset.to_owned(), constants)
             .unwrap();
         for inc in module.instance_increment_input().iter() {
             // increment the instance offset to make way for future module layouts
@@ -234,6 +236,7 @@ impl GraphModules {
         values: &mut [ValTensor<Fp>],
         element_visibility: &Visibility,
         instance_offset: &mut usize,
+        constants: &mut ConstantsMap<Fp>,
     ) -> Result<(), Error> {
         if element_visibility.is_polycommit() && !values.is_empty() {
             // concat values and sk to get the inputs
@@ -248,7 +251,7 @@ impl GraphModules {
                 layouter
                     .assign_region(|| format!("_enter_module_{}", module_offset), |_| Ok(()))
                     .unwrap();
-                Self::layout_module(&chip, layouter, x, instance_offset).unwrap();
+                Self::layout_module(&chip, layouter, x, instance_offset, constants).unwrap();
                 // increment the current index
                 self.polycommit_idx += 1;
             });
@@ -270,7 +273,7 @@ impl GraphModules {
                 let mut inputs = values.iter_mut().map(|x| vec![x.clone()]).collect_vec();
                 // layout the module
                 inputs.iter_mut().for_each(|x| {
-                    Self::layout_module(&chip, layouter, x, instance_offset).unwrap();
+                    Self::layout_module(&chip, layouter, x, instance_offset, constants).unwrap();
                 });
                 // replace the inputs with the outputs
                 values.iter_mut().enumerate().for_each(|(i, x)| {

src/graph/node.rs

@@ -14,7 +14,6 @@ use crate::circuit::Op;
 use crate::circuit::Unknown;
 #[cfg(not(target_arch = "wasm32"))]
 use crate::graph::new_op_from_onnx;
-use crate::tensor::Tensor;
 use crate::tensor::TensorError;
 use halo2curves::bn256::Fr as Fp;
 #[cfg(not(target_arch = "wasm32"))]
@@ -61,20 +60,6 @@ impl Op<Fp> for Rescaled {
     fn as_any(&self) -> &dyn std::any::Any {
         self
     }
-    fn f(&self, x: &[Tensor<Fp>]) -> Result<crate::circuit::ForwardResult<Fp>, TensorError> {
-        if self.scale.len() != x.len() {
-            return Err(TensorError::DimMismatch("rescaled inputs".to_string()));
-        }
-
-        let mut rescaled_inputs = vec![];
-        let inputs = &mut x.to_vec();
-        for (i, ri) in inputs.iter_mut().enumerate() {
-            let mult_tensor = Tensor::from([Fp::from(self.scale[i].1 as u64)].into_iter());
-            let res = (ri.clone() * mult_tensor)?;
-            rescaled_inputs.push(res);
-        }
-        Op::<Fp>::f(&*self.inner, &rescaled_inputs)
-    }
 
     fn as_string(&self) -> String {
         format!("RESCALED INPUT ({})", self.inner.as_string())
@@ -215,13 +200,6 @@ impl Op<Fp> for RebaseScale {
     fn as_any(&self) -> &dyn std::any::Any {
         self
     }
-    fn f(&self, x: &[Tensor<Fp>]) -> Result<crate::circuit::ForwardResult<Fp>, TensorError> {
-        let mut res = Op::<Fp>::f(&*self.inner, x)?;
-        let rebase_res = Op::<Fp>::f(&self.rebase_op, &[res.output])?;
-        res.output = rebase_res.output;
-
-        Ok(res)
-    }
 
     fn as_string(&self) -> String {
         format!(
@@ -389,13 +367,6 @@ impl From<Box<dyn Op<Fp>>> for SupportedOp {
 }
 
 impl Op<Fp> for SupportedOp {
-    fn f(
-        &self,
-        inputs: &[Tensor<Fp>],
-    ) -> Result<crate::circuit::ForwardResult<Fp>, crate::tensor::TensorError> {
-        self.as_op().f(inputs)
-    }
-
     fn layout(
         &self,
         config: &mut crate::circuit::BaseConfig<Fp>,

src/graph/utilities.rs

@@ -509,7 +509,7 @@ pub fn new_op_from_onnx(
             // if param_visibility.is_public() {
             if let Some(c) = inputs[1].opkind().get_mutable_constant() {
                 inputs[1].decrement_use();
-                deleted_indices.push(inputs.len() - 1);
+                deleted_indices.push(1);
                 op = SupportedOp::Linear(crate::circuit::ops::poly::PolyOp::ScatterND {
                     constant_idx: Some(c.raw_values.map(|x| x as usize)),
                 })
@@ -545,7 +545,7 @@ pub fn new_op_from_onnx(
             // if param_visibility.is_public() {
             if let Some(c) = inputs[1].opkind().get_mutable_constant() {
                 inputs[1].decrement_use();
-                deleted_indices.push(inputs.len() - 1);
+                deleted_indices.push(1);
                 op = SupportedOp::Linear(crate::circuit::ops::poly::PolyOp::GatherND {
                     batch_dims,
                     indices: Some(c.raw_values.map(|x| x as usize)),
@@ -582,7 +582,7 @@ pub fn new_op_from_onnx(
             // if param_visibility.is_public() {
             if let Some(c) = inputs[1].opkind().get_mutable_constant() {
                 inputs[1].decrement_use();
-                deleted_indices.push(inputs.len() - 1);
+                deleted_indices.push(1);
                 op = SupportedOp::Linear(crate::circuit::ops::poly::PolyOp::GatherElements {
                     dim: axis,
                     constant_idx: Some(c.raw_values.map(|x| x as usize)),
@@ -734,6 +734,19 @@ pub fn new_op_from_onnx(
 
             SupportedOp::Linear(PolyOp::Sum { axes })
         }
+        "Reduce<MeanOfSquares>" => {
+            if inputs.len() != 1 {
+                return Err(Box::new(GraphError::InvalidDims(
+                    idx,
+                    "mean of squares".to_string(),
+                )));
+            };
+            let op = load_op::<Reduce>(node.op(), idx, node.op().name().to_string())?;
+            let axes = op.axes.into_iter().collect();
+
+            SupportedOp::Linear(PolyOp::MeanOfSquares { axes })
+        }
+
         "Max" => {
             // Extract the max value
             // first find the input that is a constant
@@ -1072,8 +1085,12 @@ pub fn new_op_from_onnx(
                 }
             };
 
+            let in_scale = inputs[0].out_scales()[0];
+            let max_scale = std::cmp::max(scales.get_max(), in_scale);
+
             SupportedOp::Hybrid(HybridOp::Softmax {
-                scale: scale_to_multiplier(inputs[0].out_scales()[0]).into(),
+                input_scale: scale_to_multiplier(in_scale).into(),
+                output_scale: scale_to_multiplier(max_scale).into(),
                 axes: softmax_op.axes.to_vec(),
             })
         }
@@ -1102,17 +1119,7 @@ pub fn new_op_from_onnx(
                 .ok_or(GraphError::MissingParams("stride".to_string()))?;
             let padding = match &pool_spec.padding {
                 PaddingSpec::Explicit(b, a) | PaddingSpec::ExplicitOnnxPool(b, a, _) => {
-                    if b.len() == 2 && a.len() == 2 {
-                        [(b[0], b[1]), (a[0], a[1])]
-                    } else if b.len() == 1 && a.len() == 1 {
-                        [(b[0], b[0]), (a[0], a[0])]
-                    } else if b.len() == 1 && a.len() == 2 {
-                        [(b[0], b[0]), (a[0], a[1])]
-                    } else if b.len() == 2 && a.len() == 1 {
-                        [(b[0], b[1]), (a[0], a[0])]
-                    } else {
-                        return Err(Box::new(GraphError::MissingParams("padding".to_string())));
-                    }
+                    b.iter().zip(a.iter()).map(|(b, a)| (*b, *a)).collect()
                 }
                 _ => {
                     return Err(Box::new(GraphError::MissingParams("padding".to_string())));
@@ -1120,26 +1127,10 @@ pub fn new_op_from_onnx(
             };
             let kernel_shape = &pool_spec.kernel_shape;
 
-            let (stride_h, stride_w) = if stride.len() == 1 {
-                (1, stride[0])
-            } else if stride.len() == 2 {
-                (stride[0], stride[1])
-            } else {
-                return Err(Box::new(GraphError::MissingParams("stride".to_string())));
-            };
-
-            let (kernel_height, kernel_width) = if kernel_shape.len() == 1 {
-                (1, kernel_shape[0])
-            } else if kernel_shape.len() == 2 {
-                (kernel_shape[0], kernel_shape[1])
-            } else {
-                return Err(Box::new(GraphError::MissingParams("kernel".to_string())));
-            };
-
-            SupportedOp::Hybrid(HybridOp::MaxPool2d {
+            SupportedOp::Hybrid(HybridOp::MaxPool {
                 padding,
-                stride: (stride_h, stride_w),
-                pool_dims: (kernel_height, kernel_width),
+                stride: stride.to_vec(),
+                pool_dims: kernel_shape.to_vec(),
             })
         }
         "Ceil" => SupportedOp::Nonlinear(LookupOp::Ceil {
@@ -1161,7 +1152,7 @@ pub fn new_op_from_onnx(
             // if param_visibility.is_public() {
             if let Some(c) = inputs[1].opkind().get_mutable_constant() {
                 inputs[1].decrement_use();
-                deleted_indices.push(inputs.len() - 1);
+                deleted_indices.push(1);
                 if c.raw_values.len() > 1 {
                     unimplemented!("only support scalar pow")
                 }
@@ -1201,15 +1192,7 @@ pub fn new_op_from_onnx(
             }
 
             let stride = match conv_node.pool_spec.strides.clone() {
-                Some(s) => {
-                    if s.len() == 1 {
-                        (s[0], s[0])
-                    } else if s.len() == 2 {
-                        (s[0], s[1])
-                    } else {
-                        return Err(Box::new(GraphError::MissingParams("strides".to_string())));
-                    }
-                }
+                Some(s) => s.to_vec(),
                 None => {
                     return Err(Box::new(GraphError::MissingParams("strides".to_string())));
                 }
@@ -1217,17 +1200,7 @@ pub fn new_op_from_onnx(
 
             let padding = match &conv_node.pool_spec.padding {
                 PaddingSpec::Explicit(b, a) | PaddingSpec::ExplicitOnnxPool(b, a, _) => {
-                    if b.len() == 2 && a.len() == 2 {
-                        [(b[0], b[1]), (a[0], a[1])]
-                    } else if b.len() == 1 && a.len() == 1 {
-                        [(b[0], b[0]), (a[0], a[0])]
-                    } else if b.len() == 1 && a.len() == 2 {
-                        [(b[0], b[0]), (a[0], a[1])]
-                    } else if b.len() == 2 && a.len() == 1 {
-                        [(b[0], b[1]), (a[0], a[0])]
-                    } else {
-                        return Err(Box::new(GraphError::MissingParams("padding".to_string())));
-                    }
+                    b.iter().zip(a.iter()).map(|(b, a)| (*b, *a)).collect()
                 }
                 _ => {
                     return Err(Box::new(GraphError::MissingParams("padding".to_string())));
@@ -1282,33 +1255,20 @@ pub fn new_op_from_onnx(
             }
 
             let stride = match deconv_node.pool_spec.strides.clone() {
-                Some(s) => (s[0], s[1]),
+                Some(s) => s.to_vec(),
                 None => {
                     return Err(Box::new(GraphError::MissingParams("strides".to_string())));
                 }
             };
             let padding = match &deconv_node.pool_spec.padding {
                 PaddingSpec::Explicit(b, a) | PaddingSpec::ExplicitOnnxPool(b, a, _) => {
-                    if b.len() == 2 && a.len() == 2 {
-                        [(b[0], b[1]), (a[0], a[1])]
-                    } else if b.len() == 1 && a.len() == 1 {
-                        [(b[0], b[0]), (a[0], a[0])]
-                    } else if b.len() == 1 && a.len() == 2 {
-                        [(b[0], b[0]), (a[0], a[1])]
-                    } else if b.len() == 2 && a.len() == 1 {
-                        [(b[0], b[1]), (a[0], a[0])]
-                    } else {
-                        return Err(Box::new(GraphError::MissingParams("padding".to_string())));
-                    }
+                    b.iter().zip(a.iter()).map(|(b, a)| (*b, *a)).collect()
                 }
                 _ => {
                     return Err(Box::new(GraphError::MissingParams("padding".to_string())));
                 }
             };
 
-            let output_padding: (usize, usize) =
-                (deconv_node.adjustments[0], deconv_node.adjustments[1]);
-
             // if bias exists then rescale it to the input + kernel scale
             if input_scales.len() == 3 {
                 let bias_scale = input_scales[2];
@@ -1327,7 +1287,7 @@ pub fn new_op_from_onnx(
 
             SupportedOp::Linear(PolyOp::DeConv {
                 padding,
-                output_padding,
+                output_padding: deconv_node.adjustments.to_vec(),
                 stride,
             })
         }
@@ -1428,46 +1388,17 @@ pub fn new_op_from_onnx(
                 .ok_or(GraphError::MissingParams("stride".to_string()))?;
             let padding = match &pool_spec.padding {
                 PaddingSpec::Explicit(b, a) | PaddingSpec::ExplicitOnnxPool(b, a, _) => {
-                    if b.len() == 2 && a.len() == 2 {
-                        [(b[0], b[1]), (a[0], a[1])]
-                    } else if b.len() == 1 && a.len() == 1 {
-                        [(b[0], b[0]), (a[0], a[0])]
-                    } else if b.len() == 1 && a.len() == 2 {
-                        [(b[0], b[0]), (a[0], a[1])]
-                    } else if b.len() == 2 && a.len() == 1 {
-                        [(b[0], b[1]), (a[0], a[0])]
-                    } else {
-                        return Err(Box::new(GraphError::MissingParams("padding".to_string())));
-                    }
+                    b.iter().zip(a.iter()).map(|(b, a)| (*b, *a)).collect()
                 }
                 _ => {
                     return Err(Box::new(GraphError::MissingParams("padding".to_string())));
                 }
             };
-            let kernel_shape = &pool_spec.kernel_shape;
-
-            let (stride_h, stride_w) = if stride.len() == 1 {
-                (1, stride[0])
-            } else if stride.len() == 2 {
-                (stride[0], stride[1])
-            } else {
-                return Err(Box::new(GraphError::MissingParams("stride".to_string())));
-            };
-
-            let (kernel_height, kernel_width) = if kernel_shape.len() == 1 {
-                (1, kernel_shape[0])
-            } else if kernel_shape.len() == 2 {
-                (kernel_shape[0], kernel_shape[1])
-            } else {
-                return Err(Box::new(GraphError::MissingParams(
-                    "kernel shape".to_string(),
-                )));
-            };
 
             SupportedOp::Hybrid(HybridOp::SumPool {
                 padding,
-                stride: (stride_h, stride_w),
-                kernel_shape: (kernel_height, kernel_width),
+                stride: stride.to_vec(),
+                kernel_shape: pool_spec.kernel_shape.to_vec(),
                 normalized: sumpool_node.normalize,
             })
         }
@@ -1494,29 +1425,7 @@ pub fn new_op_from_onnx(
                 )));
             }
 
-            let padding_len = pad_node.pads.len();
-
-            // we only support symmetrical padding that affects the last 2 dims (height and width params)
-            for (i, pad_params) in pad_node.pads.iter().enumerate() {
-                if (i < padding_len - 2) && ((pad_params.0 != 0) || (pad_params.1 != 0)) {
-                    return Err(Box::new(GraphError::MisformedParams(
-                        "ezkl currently only supports padding height and width dimensions"
-                            .to_string(),
-                    )));
-                }
-            }
-
-            let padding = [
-                (
-                    pad_node.pads[padding_len - 2].0,
-                    pad_node.pads[padding_len - 1].0,
-                ),
-                (
-                    pad_node.pads[padding_len - 2].1,
-                    pad_node.pads[padding_len - 1].1,
-                ),
-            ];
-            SupportedOp::Linear(PolyOp::Pad(padding))
+            SupportedOp::Linear(PolyOp::Pad(pad_node.pads.to_vec()))
         }
         "RmAxis" | "Reshape" | "AddAxis" => {
             // Extract the slope layer hyperparams

src/graph/vars.rs

@@ -346,7 +346,7 @@ pub struct ModelVars<F: PrimeField + TensorType + PartialOrd> {
     pub instance: Option<ValTensor<F>>,
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> ModelVars<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> ModelVars<F> {
     /// Get instance col
     pub fn get_instance_col(&self) -> Option<&Column<Instance>> {
         if let Some(instance) = &self.instance {

src/lib.rs

@@ -23,7 +23,6 @@
 )]
 // we allow this for our dynamic range based indexing scheme
 #![allow(clippy::single_range_in_vec_init)]
-#![feature(round_ties_even)]
 
 //! A library for turning computational graphs, such as neural networks, into ZK-circuits.
 //!
@@ -115,6 +114,12 @@ pub enum Commitments {
     IPA,
 }
 
+impl From<Option<Commitments>> for Commitments {
+    fn from(value: Option<Commitments>) -> Self {
+        value.unwrap_or(Commitments::KZG)
+    }
+}
+
 impl FromStr for Commitments {
     type Err = String;
     fn from_str(s: &str) -> Result<Self, Self::Err> {
@@ -215,7 +220,7 @@ pub struct RunArgs {
     pub check_mode: CheckMode,
     /// commitment scheme
     #[arg(long, default_value = "kzg")]
-    pub commitment: Commitments,
+    pub commitment: Option<Commitments>,
 }
 
 impl Default for RunArgs {
@@ -235,7 +240,7 @@ impl Default for RunArgs {
             div_rebasing: false,
             rebase_frac_zero_constants: false,
             check_mode: CheckMode::UNSAFE,
-            commitment: Commitments::KZG,
+            commitment: None,
         }
     }
 }

src/pfsys/evm/aggregation_kzg.rs

@@ -1,4 +1,8 @@
+#[cfg(not(target_arch = "wasm32"))]
+use crate::graph::CircuitSize;
 use crate::pfsys::{Snark, SnarkWitness};
+#[cfg(not(target_arch = "wasm32"))]
+use colored_json::ToColoredJson;
 use halo2_proofs::circuit::AssignedCell;
 use halo2_proofs::plonk::{self};
 use halo2_proofs::{
@@ -16,6 +20,8 @@ use halo2_wrong_ecc::{
 use halo2curves::bn256::{Bn256, Fq, Fr, G1Affine};
 use halo2curves::ff::PrimeField;
 use itertools::Itertools;
+#[cfg(not(target_arch = "wasm32"))]
+use log::debug;
 use log::trace;
 use rand::rngs::OsRng;
 use snark_verifier::loader::native::NativeLoader;
@@ -193,6 +199,23 @@ impl AggregationConfig {
         let main_gate_config = MainGate::<F>::configure(meta);
         let range_config =
             RangeChip::<F>::configure(meta, &main_gate_config, composition_bits, overflow_bits);
+
+        #[cfg(not(target_arch = "wasm32"))]
+        {
+            let circuit_size = CircuitSize::from_cs(meta, 23);
+
+            // not wasm
+
+            debug!(
+                "circuit size: \n {}",
+                circuit_size
+                    .as_json()
+                    .unwrap()
+                    .to_colored_json_auto()
+                    .unwrap()
+            );
+        }
+
         AggregationConfig {
             main_gate_config,
             range_config,

src/tensor/mod.rs

@@ -60,6 +60,9 @@ pub enum TensorError {
     /// Unsupported operation
     #[error("Unsupported operation on a tensor type")]
     Unsupported,
+    /// Overflow
+    #[error("Unsigned integer overflow or underflow error in op: {0}")]
+    Overflow(String),
 }
 
 /// The (inner) type of tensor elements.
@@ -378,7 +381,7 @@ impl<F: PrimeField + Clone + TensorType + PartialOrd> From<Tensor<AssignedCell<A
 {
     fn from(value: Tensor<AssignedCell<Assigned<F>, F>>) -> Tensor<Value<F>> {
         let mut output = Vec::new();
-        for (_, x) in value.iter().enumerate() {
+        for x in value.iter() {
             output.push(x.value_field().evaluate());
         }
         Tensor::new(Some(&output), value.dims()).unwrap()
@@ -434,6 +437,18 @@ impl<F: PrimeField + TensorType + Clone> From<Tensor<i128>> for Tensor<Value<F>>
     }
 }
 
+impl<T: Clone + TensorType + std::marker::Send + std::marker::Sync>
+    maybe_rayon::iter::FromParallelIterator<T> for Tensor<T>
+{
+    fn from_par_iter<I>(par_iter: I) -> Self
+    where
+        I: maybe_rayon::iter::IntoParallelIterator<Item = T>,
+    {
+        let inner: Vec<T> = par_iter.into_par_iter().collect();
+        Tensor::new(Some(&inner), &[inner.len()]).unwrap()
+    }
+}
+
 impl<T: Clone + TensorType + std::marker::Send + std::marker::Sync>
     maybe_rayon::iter::IntoParallelIterator for Tensor<T>
 {
@@ -922,6 +937,7 @@ impl<T: Clone + TensorType> Tensor<T> {
     pub fn move_axis(&mut self, source: usize, destination: usize) -> Result<Self, TensorError> {
         assert!(source < self.dims.len());
         assert!(destination < self.dims.len());
+
         let mut new_dims = self.dims.clone();
         new_dims.remove(source);
         new_dims.insert(destination, self.dims[source]);
@@ -953,6 +969,8 @@ impl<T: Clone + TensorType> Tensor<T> {
                     old_coord[source - 1] = *c;
                 } else if (i < source && source < destination)
                     || (i < destination && source > destination)
+                    || (i > source && source > destination)
+                    || (i > destination && source < destination)
                 {
                     old_coord[i] = *c;
                 } else if i > source && source < destination {
@@ -965,7 +983,10 @@ impl<T: Clone + TensorType> Tensor<T> {
                     ));
                 }
             }
-            output.set(&coord, self.get(&old_coord));
+
+            let value = self.get(&old_coord);
+
+            output.set(&coord, value);
         }
 
         Ok(output)

src/tensor/val.rs

@@ -1,8 +1,12 @@
+use core::{iter::FilterMap, slice::Iter};
+
+use crate::circuit::region::ConstantsMap;
+
 use super::{
     ops::{intercalate_values, pad, resize},
     *,
 };
-use halo2_proofs::{arithmetic::Field, plonk::Instance};
+use halo2_proofs::{arithmetic::Field, circuit::Cell, plonk::Instance};
 
 pub(crate) fn create_constant_tensor<
     F: PrimeField + TensorType + std::marker::Send + std::marker::Sync + PartialOrd,
@@ -51,6 +55,24 @@ pub enum ValType<F: PrimeField + TensorType + std::marker::Send + std::marker::S
 }
 
 impl<F: PrimeField + TensorType + std::marker::Send + std::marker::Sync + PartialOrd> ValType<F> {
+    /// Returns the inner cell of the [ValType].
+    pub fn cell(&self) -> Option<Cell> {
+        match self {
+            ValType::PrevAssigned(cell) => Some(cell.cell()),
+            ValType::AssignedConstant(cell, _) => Some(cell.cell()),
+            _ => None,
+        }
+    }
+
+    /// Returns the assigned cell of the [ValType].
+    pub fn assigned_cell(&self) -> Option<AssignedCell<F, F>> {
+        match self {
+            ValType::PrevAssigned(cell) => Some(cell.clone()),
+            ValType::AssignedConstant(cell, _) => Some(cell.clone()),
+            _ => None,
+        }
+    }
+
     /// Returns true if the value is previously assigned.
     pub fn is_prev_assigned(&self) -> bool {
         matches!(
@@ -293,7 +315,13 @@ impl<F: PrimeField + TensorType + PartialOrd> From<Tensor<AssignedCell<F, F>>> f
     }
 }
 
-impl<F: PrimeField + TensorType + PartialOrd> ValTensor<F> {
+impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> ValTensor<F> {
+    /// Allocate a new [ValTensor::Value] from the given [Tensor] of [i128].
+    pub fn from_i128_tensor(t: Tensor<i128>) -> ValTensor<F> {
+        let inner = t.map(|x| ValType::Value(Value::known(i128_to_felt(x))));
+        inner.into()
+    }
+
     /// Allocate a new [ValTensor::Instance] from the ConstraintSystem with the given tensor `dims`, optionally enabling `equality`.
     pub fn new_instance(
         cs: &mut ConstraintSystem<F>,
@@ -428,10 +456,37 @@ impl<F: PrimeField + TensorType + PartialOrd> ValTensor<F> {
     }
 
     /// Returns the number of constants in the [ValTensor].
-    pub fn num_constants(&self) -> usize {
+    pub fn create_constants_map_iterator(
+        &self,
+    ) -> FilterMap<Iter<'_, ValType<F>>, fn(&ValType<F>) -> Option<(F, ValType<F>)>> {
         match self {
-            ValTensor::Value { inner, .. } => inner.iter().filter(|x| x.is_constant()).count(),
-            ValTensor::Instance { .. } => 0,
+            ValTensor::Value { inner, .. } => inner.iter().filter_map(|x| {
+                if let ValType::Constant(v) = x {
+                    Some((*v, x.clone()))
+                } else {
+                    None
+                }
+            }),
+            ValTensor::Instance { .. } => {
+                unreachable!("Instance tensors do not have constants")
+            }
+        }
+    }
+
+    /// Returns the number of constants in the [ValTensor].
+    pub fn create_constants_map(&self) -> ConstantsMap<F> {
+        match self {
+            ValTensor::Value { inner, .. } => inner
+                .par_iter()
+                .filter_map(|x| {
+                    if let ValType::Constant(v) = x {
+                        Some((*v, x.clone()))
+                    } else {
+                        None
+                    }
+                })
+                .collect(),
+            ValTensor::Instance { .. } => ConstantsMap::new(),
         }
     }
 
@@ -824,13 +879,13 @@ impl<F: PrimeField + TensorType + PartialOrd> ValTensor<F> {
         };
         Ok(())
     }
-    /// Calls `pad` on the inner [Tensor].
-    pub fn pad(&mut self, padding: [(usize, usize); 2]) -> Result<(), TensorError> {
+    /// Calls `pad_spatial_dims` on the inner [Tensor].
+    pub fn pad(&mut self, padding: Vec<(usize, usize)>, offset: usize) -> Result<(), TensorError> {
         match self {
             ValTensor::Value {
                 inner: v, dims: d, ..
             } => {
-                *v = pad(v, padding)?;
+                *v = pad(v, padding, offset)?;
                 *d = v.dims().to_vec();
             }
             ValTensor::Instance { .. } => {

src/tensor/var.rs

@@ -2,7 +2,7 @@ use std::collections::HashSet;
 
 use log::{debug, error, warn};
 
-use crate::circuit::CheckMode;
+use crate::circuit::{region::ConstantsMap, CheckMode};
 
 use super::*;
 /// A wrapper around Halo2's `Column<Fixed>` or `Column<Advice>`.
@@ -289,9 +289,10 @@ impl VarTensor {
         &self,
         region: &mut Region<F>,
         offset: usize,
+        coord: usize,
         constant: F,
     ) -> Result<AssignedCell<F, F>, halo2_proofs::plonk::Error> {
-        let (x, y, z) = self.cartesian_coord(offset);
+        let (x, y, z) = self.cartesian_coord(offset + coord);
         match &self {
             VarTensor::Advice { inner: advices, .. } => {
                 region.assign_advice_from_constant(|| "constant", advices[x][y], z, constant)
@@ -304,33 +305,28 @@ impl VarTensor {
     }
 
     /// Assigns [ValTensor] to the columns of the inner tensor.
-    pub fn assign_with_omissions<F: PrimeField + TensorType + PartialOrd>(
+    pub fn assign_with_omissions<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
         &self,
         region: &mut Region<F>,
         offset: usize,
         values: &ValTensor<F>,
         omissions: &HashSet<&usize>,
+        constants: &mut ConstantsMap<F>,
     ) -> Result<ValTensor<F>, halo2_proofs::plonk::Error> {
         let mut assigned_coord = 0;
         let mut res: ValTensor<F> = match values {
             ValTensor::Instance { .. } => {
                 unimplemented!("cannot assign instance to advice columns with omissions")
             }
-            ValTensor::Value { inner: v, .. } => Ok::<_, halo2_proofs::plonk::Error>(
+            ValTensor::Value { inner: v, .. } => Ok::<ValTensor<F>, halo2_proofs::plonk::Error>(
                 v.enum_map(|coord, k| {
                     if omissions.contains(&coord) {
-                        return Ok(k);
+                        return Ok::<_, halo2_proofs::plonk::Error>(k);
                     }
-                    let cell = self.assign_value(region, offset, k.clone(), assigned_coord)?;
+                    let cell =
+                        self.assign_value(region, offset, k.clone(), assigned_coord, constants)?;
                     assigned_coord += 1;
-
-                    match k {
-                        ValType::Constant(f) => Ok::<ValType<F>, halo2_proofs::plonk::Error>(
-                            ValType::AssignedConstant(cell, f),
-                        ),
-                        ValType::AssignedConstant(_, f) => Ok(ValType::AssignedConstant(cell, f)),
-                        _ => Ok(ValType::PrevAssigned(cell)),
-                    }
+                    Ok::<_, halo2_proofs::plonk::Error>(cell)
                 })?
                 .into(),
             ),
@@ -340,11 +336,12 @@ impl VarTensor {
     }
 
     /// Assigns [ValTensor] to the columns of the inner tensor.
-    pub fn assign<F: PrimeField + TensorType + PartialOrd>(
+    pub fn assign<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
         &self,
         region: &mut Region<F>,
         offset: usize,
         values: &ValTensor<F>,
+        constants: &mut ConstantsMap<F>,
     ) -> Result<ValTensor<F>, halo2_proofs::plonk::Error> {
         let mut res: ValTensor<F> = match values {
             ValTensor::Instance {
@@ -382,14 +379,7 @@ impl VarTensor {
             },
             ValTensor::Value { inner: v, .. } => Ok(v
                 .enum_map(|coord, k| {
-                    let cell = self.assign_value(region, offset, k.clone(), coord)?;
-                    match k {
-                        ValType::Constant(f) => Ok::<ValType<F>, halo2_proofs::plonk::Error>(
-                            ValType::AssignedConstant(cell, f),
-                        ),
-                        ValType::AssignedConstant(_, f) => Ok(ValType::AssignedConstant(cell, f)),
-                        _ => Ok(ValType::PrevAssigned(cell)),
-                    }
+                    self.assign_value(region, offset, k.clone(), coord, constants)
                 })?
                 .into()),
         }?;
@@ -399,13 +389,16 @@ impl VarTensor {
 
     /// Assigns specific values (`ValTensor`) to the columns of the inner tensor but allows for column wrapping for accumulated operations.
     /// Duplication occurs by copying the last cell of the column to the first cell next column and creating a copy constraint between the two.
-    pub fn dummy_assign_with_duplication<F: PrimeField + TensorType + PartialOrd>(
+    pub fn dummy_assign_with_duplication<
+        F: PrimeField + TensorType + PartialOrd + std::hash::Hash,
+    >(
         &self,
         row: usize,
         offset: usize,
         values: &ValTensor<F>,
         single_inner_col: bool,
-    ) -> Result<(ValTensor<F>, usize, usize), halo2_proofs::plonk::Error> {
+        constants: &mut ConstantsMap<F>,
+    ) -> Result<(ValTensor<F>, usize), halo2_proofs::plonk::Error> {
         match values {
             ValTensor::Instance { .. } => unimplemented!("duplication is not supported on instance columns. increase K if you require more rows."),
             ValTensor::Value { inner: v, dims , ..} => {
@@ -430,21 +423,24 @@ impl VarTensor {
 
                 // duplicates every nth element to adjust for column overflow
                 let mut res: ValTensor<F> = v.duplicate_every_n(duplication_freq, num_repeats, duplication_offset).unwrap().into();
+
+                let constants_map = res.create_constants_map();
+                constants.extend(constants_map);
+
                 let total_used_len = res.len();
-                let total_constants = res.num_constants();
                 res.remove_every_n(duplication_freq, num_repeats, duplication_offset).unwrap();
 
                 res.reshape(dims).unwrap();
                 res.set_scale(values.scale());
 
-                Ok((res, total_used_len, total_constants))
+                Ok((res, total_used_len))
             }
         }
     }
 
     /// Assigns specific values (`ValTensor`) to the columns of the inner tensor but allows for column wrapping for accumulated operations.
     /// Duplication occurs by copying the last cell of the column to the first cell next column and creating a copy constraint between the two.
-    pub fn assign_with_duplication<F: PrimeField + TensorType + PartialOrd>(
+    pub fn assign_with_duplication<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
         &self,
         region: &mut Region<F>,
         row: usize,
@@ -452,7 +448,8 @@ impl VarTensor {
         values: &ValTensor<F>,
         check_mode: &CheckMode,
         single_inner_col: bool,
-    ) -> Result<(ValTensor<F>, usize, usize), halo2_proofs::plonk::Error> {
+        constants: &mut ConstantsMap<F>,
+    ) -> Result<(ValTensor<F>, usize), halo2_proofs::plonk::Error> {
         let mut prev_cell = None;
 
         match values {
@@ -494,7 +491,7 @@ impl VarTensor {
                         assert_eq!(Into::<i32>::into(k.clone()), Into::<i32>::into(v[coord - 1].clone()));
                     };
 
-                    let cell = self.assign_value(region, offset, k.clone(), coord * step)?;
+                    let cell = self.assign_value(region, offset, k.clone(), coord * step, constants)?;
 
                     if single_inner_col {
                     if z == 0 {
@@ -502,28 +499,23 @@ impl VarTensor {
                         prev_cell = Some(cell.clone());
                     } else if coord > 0 && z == 0 && single_inner_col {
                         if let Some(prev_cell) = prev_cell.as_ref() {
-                            region.constrain_equal(prev_cell.cell(),cell.cell())?;
+                            let cell = cell.cell().ok_or({
+                                error!("Error getting cell: {:?}", (x,y));
+                                halo2_proofs::plonk::Error::Synthesis})?;
+                            let prev_cell = prev_cell.cell().ok_or({
+                                error!("Error getting cell: {:?}", (x,y));
+                                halo2_proofs::plonk::Error::Synthesis})?;
+                            region.constrain_equal(prev_cell,cell)?;
                         } else {
                             error!("Error copy-constraining previous value: {:?}", (x,y));
                             return Err(halo2_proofs::plonk::Error::Synthesis);
                         }
                     }}
 
-                    match k {
-                        ValType::Constant(f) => {
-                            Ok(ValType::AssignedConstant(cell, f))
-                        },
-                        ValType::AssignedConstant(_, f) => {
-                            Ok(ValType::AssignedConstant(cell, f))
-                        },
-                        _ => {
-                            Ok(ValType::PrevAssigned(cell))
-                        }
-                    }
+                    Ok(cell)
 
                 })?.into()};
                 let total_used_len = res.len();
-                let total_constants = res.num_constants();
                 res.remove_every_n(duplication_freq, num_repeats, duplication_offset).unwrap();
 
                 res.reshape(dims).unwrap();
@@ -542,42 +534,61 @@ impl VarTensor {
                     )};
                 }
 
-                Ok((res, total_used_len, total_constants))
+                Ok((res, total_used_len))
             }
         }
     }
 
-    fn assign_value<F: PrimeField + TensorType + PartialOrd>(
+    fn assign_value<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
         &self,
         region: &mut Region<F>,
         offset: usize,
         k: ValType<F>,
         coord: usize,
-    ) -> Result<AssignedCell<F, F>, halo2_proofs::plonk::Error> {
+        constants: &mut ConstantsMap<F>,
+    ) -> Result<ValType<F>, halo2_proofs::plonk::Error> {
         let (x, y, z) = self.cartesian_coord(offset + coord);
-        match k {
+        let res = match k {
             ValType::Value(v) => match &self {
                 VarTensor::Advice { inner: advices, .. } => {
-                    region.assign_advice(|| "k", advices[x][y], z, || v)
+                    ValType::PrevAssigned(region.assign_advice(|| "k", advices[x][y], z, || v)?)
                 }
                 _ => unimplemented!(),
             },
-            ValType::PrevAssigned(v) | ValType::AssignedConstant(v, ..) => match &self {
+            ValType::PrevAssigned(v) => match &self {
                 VarTensor::Advice { inner: advices, .. } => {
-                    v.copy_advice(|| "k", region, advices[x][y], z)
+                    ValType::PrevAssigned(v.copy_advice(|| "k", region, advices[x][y], z)?)
                 }
-                _ => {
-                    error!("PrevAssigned is only supported for advice columns");
-                    Err(halo2_proofs::plonk::Error::Synthesis)
+                _ => unimplemented!(),
+            },
+            ValType::AssignedConstant(v, val) => match &self {
+                VarTensor::Advice { inner: advices, .. } => {
+                    ValType::AssignedConstant(v.copy_advice(|| "k", region, advices[x][y], z)?, val)
                 }
+                _ => unimplemented!(),
             },
             ValType::AssignedValue(v) => match &self {
-                VarTensor::Advice { inner: advices, .. } => region
-                    .assign_advice(|| "k", advices[x][y], z, || v)
-                    .map(|a| a.evaluate()),
+                VarTensor::Advice { inner: advices, .. } => ValType::PrevAssigned(
+                    region
+                        .assign_advice(|| "k", advices[x][y], z, || v)?
+                        .evaluate(),
+                ),
                 _ => unimplemented!(),
             },
-            ValType::Constant(v) => self.assign_constant(region, offset + coord, v),
-        }
+            ValType::Constant(v) => {
+                if let std::collections::hash_map::Entry::Vacant(e) = constants.entry(v) {
+                    let value = ValType::AssignedConstant(
+                        self.assign_constant(region, offset, coord, v)?,
+                        v,
+                    );
+                    e.insert(value.clone());
+                    value
+                } else {
+                    let cell = constants.get(&v).unwrap();
+                    self.assign_value(region, offset, cell.clone(), coord, constants)?
+                }
+            }
+        };
+        Ok(res)
     }
 }

src/wasm.rs

@@ -8,12 +8,14 @@ use crate::graph::quantize_float;
 use crate::graph::scale_to_multiplier;
 use crate::graph::{GraphCircuit, GraphSettings};
 use crate::pfsys::create_proof_circuit;
+use crate::pfsys::evm::aggregation_kzg::AggregationCircuit;
 use crate::pfsys::evm::aggregation_kzg::PoseidonTranscript;
 use crate::pfsys::verify_proof_circuit;
 use crate::pfsys::TranscriptType;
 use crate::tensor::TensorType;
 use crate::CheckMode;
 use crate::Commitments;
+use console_error_panic_hook;
 use halo2_proofs::plonk::*;
 use halo2_proofs::poly::commitment::{CommitmentScheme, ParamsProver};
 use halo2_proofs::poly::ipa::multiopen::{ProverIPA, VerifierIPA};
@@ -33,11 +35,10 @@ use halo2curves::bn256::{Bn256, Fr, G1Affine};
 use halo2curves::ff::{FromUniformBytes, PrimeField};
 use snark_verifier::loader::native::NativeLoader;
 use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
+use std::str::FromStr;
 use wasm_bindgen::prelude::*;
 use wasm_bindgen_console_logger::DEFAULT_LOGGER;
 
-use console_error_panic_hook;
-
 #[cfg(feature = "web")]
 pub use wasm_bindgen_rayon::init_thread_pool;
 
@@ -336,8 +337,94 @@ pub fn verify(
 
     let orig_n = 1 << circuit_settings.run_args.logrows;
 
+    let commitment = circuit_settings.run_args.commitment.into();
+
     let mut reader = std::io::BufReader::new(&srs[..]);
-    let result = match circuit_settings.run_args.commitment {
+    let result = match commitment {
+        Commitments::KZG => {
+            let params: ParamsKZG<Bn256> =
+                halo2_proofs::poly::commitment::Params::<'_, G1Affine>::read(&mut reader)
+                    .map_err(|e| JsError::new(&format!("Failed to deserialize params: {}", e)))?;
+            let strategy = KZGSingleStrategy::new(params.verifier_params());
+            match proof.transcript_type {
+                TranscriptType::EVM => verify_proof_circuit::<
+                    VerifierSHPLONK<'_, Bn256>,
+                    KZGCommitmentScheme<Bn256>,
+                    KZGSingleStrategy<_>,
+                    _,
+                    EvmTranscript<G1Affine, _, _, _>,
+                >(&proof, &params, &vk, strategy, orig_n),
+
+                TranscriptType::Poseidon => {
+                    verify_proof_circuit::<
+                        VerifierSHPLONK<'_, Bn256>,
+                        KZGCommitmentScheme<Bn256>,
+                        KZGSingleStrategy<_>,
+                        _,
+                        PoseidonTranscript<NativeLoader, _>,
+                    >(&proof, &params, &vk, strategy, orig_n)
+                }
+            }
+        }
+        Commitments::IPA => {
+            let params: ParamsIPA<_> =
+                halo2_proofs::poly::commitment::Params::<'_, G1Affine>::read(&mut reader)
+                    .map_err(|e| JsError::new(&format!("Failed to deserialize params: {}", e)))?;
+            let strategy = IPASingleStrategy::new(params.verifier_params());
+            match proof.transcript_type {
+                TranscriptType::EVM => verify_proof_circuit::<
+                    VerifierIPA<_>,
+                    IPACommitmentScheme<G1Affine>,
+                    IPASingleStrategy<_>,
+                    _,
+                    EvmTranscript<G1Affine, _, _, _>,
+                >(&proof, &params, &vk, strategy, orig_n),
+                TranscriptType::Poseidon => {
+                    verify_proof_circuit::<
+                        VerifierIPA<_>,
+                        IPACommitmentScheme<G1Affine>,
+                        IPASingleStrategy<_>,
+                        _,
+                        PoseidonTranscript<NativeLoader, _>,
+                    >(&proof, &params, &vk, strategy, orig_n)
+                }
+            }
+        }
+    };
+
+    match result {
+        Ok(_) => Ok(true),
+        Err(e) => Err(JsError::new(&format!("{}", e))),
+    }
+}
+
+#[wasm_bindgen]
+#[allow(non_snake_case)]
+/// Verify aggregate proof in browser using wasm
+pub fn verifyAggr(
+    proof_js: wasm_bindgen::Clamped<Vec<u8>>,
+    vk: wasm_bindgen::Clamped<Vec<u8>>,
+    logrows: u64,
+    srs: wasm_bindgen::Clamped<Vec<u8>>,
+    commitment: &str,
+) -> Result<bool, JsError> {
+    let proof: crate::pfsys::Snark<Fr, G1Affine> = serde_json::from_slice(&proof_js[..])
+        .map_err(|e| JsError::new(&format!("Failed to deserialize proof: {}", e)))?;
+
+    let mut reader = std::io::BufReader::new(&vk[..]);
+    let vk = VerifyingKey::<G1Affine>::read::<_, AggregationCircuit>(
+        &mut reader,
+        halo2_proofs::SerdeFormat::RawBytes,
+        (),
+    )
+    .map_err(|e| JsError::new(&format!("Failed to deserialize vk: {}", e)))?;
+
+    let commit = Commitments::from_str(commitment).map_err(|e| JsError::new(&format!("{}", e)))?;
+
+    let orig_n = 1 << logrows;
+
+    let mut reader = std::io::BufReader::new(&srs[..]);
+    let result = match commit {
         Commitments::KZG => {
             let params: ParamsKZG<Bn256> =
                 halo2_proofs::poly::commitment::Params::<'_, G1Affine>::read(&mut reader)
@@ -436,8 +523,9 @@ pub fn prove(
 
     // read in kzg params
     let mut reader = std::io::BufReader::new(&srs[..]);
+    let commitment = circuit.settings().run_args.commitment.into();
     // creates and verifies the proof
-    let proof = match circuit.settings().run_args.commitment {
+    let proof = match commitment {
         Commitments::KZG => {
             let params: ParamsKZG<Bn256> =
                 halo2_proofs::poly::commitment::Params::<'_, G1Affine>::read(&mut reader)

tests/integration_tests.rs

@@ -122,7 +122,7 @@ mod native_tests {
         let settings: GraphSettings = serde_json::from_str(&settings).unwrap();
         let logrows = settings.run_args.logrows;
 
-        download_srs(logrows, settings.run_args.commitment);
+        download_srs(logrows, settings.run_args.commitment.into());
     }
 
     fn mv_test_(test_dir: &str, test: &str) {
@@ -200,7 +200,7 @@ mod native_tests {
         "1l_tiny_div",
     ];
 
-    const TESTS: [&str; 91] = [
+    const TESTS: [&str; 92] = [
         "1l_mlp", //0
         "1l_slice",
         "1l_concat",
@@ -296,6 +296,7 @@ mod native_tests {
         "reducel1",
         "reducel2", // 89
         "1l_lppool",
+        "lstm_large", // 91
     ];
 
     const WASM_TESTS: [&str; 46] = [
@@ -534,7 +535,7 @@ mod native_tests {
             }
         });
 
-            seq!(N in 0..=90 {
+            seq!(N in 0..=91 {
 
             #(#[test_case(TESTS[N])])*
             #[ignore]
@@ -622,7 +623,7 @@ mod native_tests {
             #(#[test_case(TESTS[N])])*
             fn mock_large_batch_public_outputs_(test: &str) {
                 // currently variable output rank is not supported in ONNX
-                if test != "gather_nd" {
+                if test != "gather_nd" && test != "lstm_large" {
                     crate::native_tests::init_binary();
                     let test_dir = TempDir::new(test).unwrap();
                     let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
@@ -1970,7 +1971,7 @@ mod native_tests {
             .expect("failed to parse settings file");
 
         // get_srs for the graph_settings_num_instances
-        download_srs(1, graph_settings.run_args.commitment);
+        download_srs(1, graph_settings.run_args.commitment.into());
 
         let status = Command::new(format!("{}/release/ezkl", *CARGO_TARGET_DIR))
             .args([

tests/py_integration_tests.rs

@@ -56,33 +56,38 @@ mod py_tests {
             // source .env/bin/activate
             // pip install -r requirements.txt
             // maturin develop --release --features python-bindings
-
+            // first install tf2onnx as it has protobuf conflict with onnx
+            let status = Command::new("pip")
+                .args(["install", "tf2onnx==1.16.1"])
+                .status()
+                .expect("failed to execute process");
+            assert!(status.success());
             // now install torch, pandas, numpy, seaborn, jupyter
             let status = Command::new("pip")
                 .args([
                     "install",
-                    "torch-geometric==2.5.0",
-                    "torch==2.0.1",
-                    "torchvision==0.15.2",
-                    "pandas==2.0.3",
-                    "numpy==1.23",
-                    "seaborn==0.12.2",
-                    "jupyter==1.0.0",
-                    "onnx==1.14.0",
-                    "kaggle==1.5.15",
-                    "py-solc-x==1.1.1",
-                    "web3==6.5.0",
-                    "librosa==0.10.0.post2",
-                    "keras==2.12.0",
-                    "tensorflow==2.12.0",
-                    "tensorflow-datasets==4.9.3",
-                    "tf2onnx==1.14.0",
-                    "pytorch-lightning==2.0.6",
+                    "torch-geometric==2.5.2",
+                    "torch==2.2.2",
+                    "torchvision==0.17.2",
+                    "pandas==2.2.1",
+                    "numpy==1.26.4",
+                    "seaborn==0.13.2",
+                    "notebook==7.1.2",
+                    "nbconvert==7.16.3",
+                    "onnx==1.16.0",
+                    "kaggle==1.6.8",
+                    "py-solc-x==2.0.2",
+                    "web3==6.16.0",
+                    "librosa==0.10.1",
+                    "keras==3.1.1",
+                    "tensorflow==2.16.1",
+                    "tensorflow-datasets==4.9.4",
+                    "pytorch-lightning==2.2.1",
                     "sk2torch==1.2.0",
-                    "scikit-learn==1.3.1",
-                    "xgboost==1.7.6",
-                    "hummingbird-ml==0.4.9",
-                    "lightgbm==4.0.0",
+                    "scikit-learn==1.4.1.post1",
+                    "xgboost==2.0.3",
+                    "hummingbird-ml==0.4.11",
+                    "lightgbm==4.3.0",
                 ])
                 .status()
                 .expect("failed to execute process");

tests/wasm.rs

@@ -11,7 +11,7 @@ mod wasm32 {
         bufferToVecOfFelt, compiledCircuitValidation, encodeVerifierCalldata, feltToBigEndian,
         feltToFloat, feltToInt, feltToLittleEndian, genPk, genVk, genWitness, inputValidation,
         pkValidation, poseidonHash, proofValidation, prove, settingsValidation, srsValidation,
-        u8_array_to_u128_le, verify, vkValidation, witnessValidation,
+        u8_array_to_u128_le, verify, verifyAggr, vkValidation, witnessValidation,
     };
     use halo2_solidity_verifier::encode_calldata;
     use halo2curves::bn256::{Fr, G1Affine};
@@ -27,10 +27,29 @@ mod wasm32 {
     pub const NETWORK: &[u8] = include_bytes!("../tests/wasm/network.onnx");
     pub const INPUT: &[u8] = include_bytes!("../tests/wasm/input.json");
     pub const PROOF: &[u8] = include_bytes!("../tests/wasm/proof.json");
+    pub const PROOF_AGGR: &[u8] = include_bytes!("../tests/wasm/proof_aggr.json");
     pub const SETTINGS: &[u8] = include_bytes!("../tests/wasm/settings.json");
     pub const PK: &[u8] = include_bytes!("../tests/wasm/pk.key");
     pub const VK: &[u8] = include_bytes!("../tests/wasm/vk.key");
+    pub const VK_AGGR: &[u8] = include_bytes!("../tests/wasm/vk_aggr.key");
     pub const SRS: &[u8] = include_bytes!("../tests/wasm/kzg");
+    pub const SRS1: &[u8] = include_bytes!("../tests/wasm/kzg1.srs");
+
+    #[wasm_bindgen_test]
+    async fn can_verify_aggr() {
+        let value = verifyAggr(
+            wasm_bindgen::Clamped(PROOF_AGGR.to_vec()),
+            wasm_bindgen::Clamped(VK_AGGR.to_vec()),
+            21,
+            wasm_bindgen::Clamped(SRS1.to_vec()),
+            "kzg",
+        )
+        .map_err(|_| "failed")
+        .unwrap();
+
+        // should not fail
+        assert!(value);
+    }
 
     #[wasm_bindgen_test]
     async fn verify_encode_verifier_calldata() {

tests/wasm/settings.json

@@ -24,8 +24,7 @@
         "param_visibility": "Private",
         "div_rebasing": false,
         "rebase_frac_zero_constants": false,
-        "check_mode": "UNSAFE",
-        "commitment": "KZG"
+        "check_mode": "UNSAFE"
     },
     "num_rows": 16,
     "total_dynamic_col_size": 0,