Merge branch 'main' into example-reorg

.github/workflows/large-tests.yml

@@ -11,7 +11,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           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: 3.12
+          python-version: 3.7
           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: 3.12
+          python-version: 3.7
           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: 3.12
+          python-version: 3.7
           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: 3.12
+          python-version: 3.7
           architecture: x64
 
       - name: Set Cargo.toml version to match github tag
@@ -128,7 +128,6 @@ 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: |
@@ -140,20 +139,6 @@ 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'
@@ -177,7 +162,7 @@ jobs:
   #   - uses: actions/checkout@v4
   #   - uses: actions/setup-python@v4
   #     with:
-  #       python-version: 3.12
+  #       python-version: 3.7
 
   #   - name: Install cross-compilation tools for aarch64
   #     if: matrix.target == 'aarch64'
@@ -229,7 +214,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.12
+          python-version: 3.7
           architecture: x64
 
       - name: Set Cargo.toml version to match github tag
@@ -264,7 +249,7 @@ 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"
 
@@ -288,7 +273,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.12
+          python-version: 3.7
 
       - name: Set Cargo.toml version to match github tag
         shell: bash
@@ -360,17 +345,3 @@ 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-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - name: Checkout repo
@@ -60,15 +60,16 @@ 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
@@ -90,6 +91,7 @@ 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-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - name: Build
@@ -38,7 +38,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - name: Docs
@@ -50,7 +50,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           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-2024-02-06
+          toolchain: nightly-2023-08-24
           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-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -139,7 +139,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -172,7 +172,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           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, python-tests, python-integration-tests]
+    # needs: [build,  library-tests, docs]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
@@ -198,8 +198,10 @@ jobs:
         #   chromedriver-version: "115.0.5790.102"
       - name: Install wasm32-unknown-unknown
         run: rustup target add wasm32-unknown-unknown
+      - name: Install wasm runner
+        run: cargo install wasm-server-runner
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2023-08-24-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 +209,12 @@ jobs:
 
   tutorial:
     runs-on: ubuntu-latest
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
+    needs: [build, library-tests, docs]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -224,20 +226,18 @@ jobs:
 
   mock-proving-tests:
     runs-on: non-gpu
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
+    # needs: [build,  library-tests, docs]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
         with:
           crate: cargo-nextest
           locked: true
-      - name: public outputs and tolerance > 0
-        run: cargo nextest run --release --verbose tests::mock_tolerance_public_outputs_ --test-threads 32
       - name: public outputs + batch size == 10
         run: cargo nextest run --release --verbose tests::mock_large_batch_public_outputs_ --test-threads 32
       - name: kzg inputs
@@ -281,12 +281,12 @@ jobs:
 
   prove-and-verify-evm-tests:
     runs-on: non-gpu
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
+    needs: [build, library-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -303,30 +303,16 @@ 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
+      - name: Install dependencies
         run: |
           pnpm install --no-frozen-lockfile
-          pnpm install --dir ./in-browser-evm-verifier --no-frozen-lockfile
         env:
           CI: false
           NODE_ENV: development
-      - name: Build wasm package for nodejs target.
-        run: |
-          wasm-pack build --release --target nodejs --out-dir ./in-browser-evm-verifier/nodejs . -- -Z build-std="panic_abort,std"
-      - name: Replace memory definition in nodejs
-        run: |
-          sed -i "3s|.*|imports['env'] = {memory: new WebAssembly.Memory({initial:20,maximum:65536,shared:true})}|" in-browser-evm-verifier/nodejs/ezkl.js
-      - name: Build @ezkljs/verify package
-        run: |
-          cd in-browser-evm-verifier
-          pnpm build:commonjs
-          cd ..
       - name: Install solc
         run: (hash svm 2>/dev/null || cargo install svm-rs) && svm install 0.8.20 && solc --version
       - name: Install Anvil
-        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev 95a93cd397f25f3f8d49d2851eb52bc2d52dd983 --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)
@@ -354,20 +340,23 @@ jobs:
 
   prove-and-verify-tests:
     runs-on: non-gpu
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
+    needs: [build, library-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
       - name: Add wasm32-unknown-unknown target
         run: rustup target add wasm32-unknown-unknown
 
+      - name: Install wasm-server-runner
+        run: cargo install wasm-server-runner
+
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2023-08-24-x86_64-unknown-linux-gnu
       - uses: actions/checkout@v3
       - name: Use pnpm 8
         uses: pnpm/action-setup@v2
@@ -378,7 +367,7 @@ jobs:
         with:
           node-version: "18.12.1"
           cache: "pnpm"
-      - name: Install dependencies for js tests
+      - name: Install dependencies
         run: |
           pnpm install --no-frozen-lockfile
         env:
@@ -394,12 +383,6 @@ jobs:
       - name: Replace memory definition in nodejs
         run: |
           sed -i "3s|.*|imports['env'] = {memory: new WebAssembly.Memory({initial:20,maximum:65536,shared:true})}|" tests/wasm/nodejs/ezkl.js
-      - name: KZG prove and verify tests (public outputs)
-        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_tight_lookup_::t
-      - name: IPA prove and verify tests
-        run: cargo nextest run --release --verbose tests::ipa_prove_and_verify_::t --test-threads 1
-      - name: IPA prove and verify tests (ipa outputs)
-        run: cargo nextest run --release --verbose tests::ipa_prove_and_verify_ipa_output
       - name: KZG prove and verify tests (public outputs + column overflow)
         run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_with_overflow_::w
       - name: KZG prove and verify tests single inner col
@@ -416,6 +399,8 @@ jobs:
         run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_with_overflow_fixed_params_
       - name: KZG prove and verify tests (public outputs)
         run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_::t
+      - name: KZG prove and verify tests (public outputs + column overflow)
+        run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_::t
       - name: KZG prove and verify tests (public inputs)
         run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_public_input
       - name: KZG prove and verify tests (fixed params)
@@ -431,11 +416,11 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2023-08-24-x86_64-unknown-linux-gnu
       - uses: actions/checkout@v3
       - uses: baptiste0928/cargo-install@v1
         with:
@@ -458,21 +443,44 @@ jobs:
       - name: KZG prove and verify tests (hashed outputs)
         run: cargo nextest run --release --verbose tests::kzg_prove_and_verify_hashed --features icicle  --test-threads 1
 
-  prove-and-verify-mock-aggr-tests:
-    runs-on: self-hosted
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
+  fuzz-tests:
+    runs-on: ubuntu-latest-32-cores
+    needs: [build, library-tests, python-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
         with:
           crate: cargo-nextest
           locked: true
-      - name: Mock aggr tests (KZG)
+      - 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 95a93cd397f25f3f8d49d2851eb52bc2d52dd983 --profile local --locked anvil --force
+      - name: fuzz tests (EVM)
+        run: cargo nextest run --release --verbose tests_evm::kzg_evm_fuzz_ --test-threads 2
+      # - name: fuzz tests
+      #   run: cargo nextest run --release --verbose tests::kzg_fuzz_ --test-threads 6
+
+  prove-and-verify-mock-aggr-tests:
+    runs-on: self-hosted
+    needs: [build, library-tests]
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions-rs/toolchain@v1
+        with:
+          toolchain: nightly-2023-08-24
+          override: true
+          components: rustfmt, clippy
+      - uses: baptiste0928/cargo-install@v1
+        with:
+          crate: cargo-nextest
+          locked: true
+      - name: Mock aggr tests
         run: cargo nextest run --release --verbose tests_aggr::kzg_aggr_mock_prove_and_verify_  --test-threads 8
 
   prove-and-verify-aggr-tests-gpu:
@@ -483,7 +491,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -495,29 +503,29 @@ jobs:
 
   prove-and-verify-aggr-tests:
     runs-on: large-self-hosted
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
+    needs: [build, library-tests, python-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
         with:
           crate: cargo-nextest
           locked: true
-      - name: KZG tests
-        run: cargo nextest run --release --verbose tests_aggr::kzg_aggr_prove_and_verify_  --test-threads 4 -- --include-ignored
+      - name: KZG )tests
+        run: cargo nextest run --release --verbose tests_aggr::kzg_aggr_prove_and_verify_  --test-threads 8 -- --include-ignored
 
   prove-and-verify-aggr-evm-tests:
     runs-on: large-self-hosted
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
+    needs: [build, library-tests, python-tests]
     steps:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -527,7 +535,7 @@ 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 c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev 95a93cd397f25f3f8d49d2851eb52bc2d52dd983 --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
 
@@ -538,7 +546,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -557,36 +565,34 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.12"
+          python-version: "3.7"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           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 --clear; source .env/bin/activate; pip install -r requirements.txt;
+        run: python -m venv .env; source .env/bin/activate; pip install -r requirements.txt;
       - name: Install Anvil
-        run: cargo install --git https://github.com/foundry-rs/foundry --rev c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev 95a93cd397f25f3f8d49d2851eb52bc2d52dd983 --profile local --locked anvil --force
       - name: Build python ezkl
-        run: source .env/bin/activate; unset CONDA_PREFIX; maturin develop --features python-bindings --release
+        run: source .env/bin/activate; maturin develop --features python-bindings --release
       - name: Run pytest
         run: source .env/bin/activate; pytest -vv
 
   accuracy-measurement-tests:
     runs-on: ubuntu-latest-32-cores
-    needs: [build, library-tests, docs, python-tests, python-integration-tests]
+    # needs: [build, library-tests, docs]
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.12"
+          python-version: "3.7"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -594,9 +600,9 @@ jobs:
           crate: cargo-nextest
           locked: true
       - name: Setup Virtual Env and Install python dependencies
-        run: python -m venv .env --clear; source .env/bin/activate; pip install -r requirements.txt;
+        run: python -m venv .env; 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
+        run: source .env/bin/activate; maturin develop --features python-bindings --release
       - name: Div rebase
         run: source .env/bin/activate; cargo nextest run --release --verbose tests::accuracy_measurement_div_rebase_
       - name: Public inputs
@@ -614,10 +620,10 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.11"
+          python-version: "3.9"
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: baptiste0928/cargo-install@v1
@@ -627,15 +633,11 @@ 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 c2233ec9fe61e0920c61c6d779bc707252852037 --profile local --locked anvil --force
-      - name: Install pip
-        run: python -m ensurepip --upgrade
+        run: cargo install --git https://github.com/foundry-rs/foundry --rev 95a93cd397f25f3f8d49d2851eb52bc2d52dd983 --profile local --locked anvil --force
       - name: Setup Virtual Env and Install python dependencies
-        run: python -m venv .env --clear; source .env/bin/activate; pip install -r requirements.txt; python -m ensurepip --upgrade
+        run: python -m venv .env; 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: Tictactoe tutorials
-        run: source .env/bin/activate; cargo nextest run py_tests::tests::tictactoe_ --test-threads 1
+        run: source .env/bin/activate; maturin develop --features python-bindings --release
       # - name: authenticate-kaggle-cli
       #   shell: bash
       #   env:
@@ -646,10 +648,12 @@ jobs:
       #     echo $KAGGLE_API_KEY > /home/ubuntu/.kaggle/kaggle.json
       #     chmod 600 /home/ubuntu/.kaggle/kaggle.json
       - name: All notebooks
-        run: source .env/bin/activate; cargo nextest run py_tests::tests::run_notebook_ --test-threads 1
+        run: source .env/bin/activate; cargo nextest run py_tests::tests::run_notebook_ --no-capture
       - name: Voice tutorial
         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_ --no-capture
       # - name: Postgres tutorials
       #   run: source .env/bin/activate; cargo nextest run py_tests::tests::postgres_ --test-threads 1

.github/workflows/tagging.yml

@@ -14,40 +14,6 @@ jobs:
       - uses: actions/checkout@v4
       - name: Bump version and push tag
         id: tag_version
-        uses: mathieudutour/github-tag-action@v6.2
+        uses: mathieudutour/github-tag-action@v6.1
         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/wasm.yml

@@ -1,4 +1,4 @@
-name: Build and Publish EZKL npm packages (wasm bindings and in-browser evm verifier)
+name: Build and Publish WASM<>JS Bindings
 
 on:
   workflow_dispatch:
@@ -14,7 +14,7 @@ defaults:
   run:
     working-directory: .
 jobs:
-  publish-wasm-bindings:
+  wasm-publish:
     name: publish-wasm-bindings
     runs-on: ubuntu-latest
     if: startsWith(github.ref, 'refs/tags/')
@@ -22,21 +22,24 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions-rs/toolchain@v1
         with:
-          toolchain: nightly-2024-02-06
+          toolchain: nightly-2023-08-24
           override: true
           components: rustfmt, clippy
       - uses: jetli/wasm-pack-action@v0.4.0
       - name: Add wasm32-unknown-unknown target
         run: rustup target add wasm32-unknown-unknown
 
+      - name: Install wasm-server-runner
+        run: cargo install wasm-server-runner
+
       - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-02-06-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2023-08-24-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"
@@ -92,7 +95,7 @@ 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 +103,11 @@ 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 +126,7 @@ 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 +134,7 @@ 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 +177,3 @@ 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 }}

.gitignore

@@ -45,9 +45,6 @@ var/
 *.whl
 *.bak
 node_modules
-/dist
 timingData.json
 !tests/wasm/pk.key
-!tests/wasm/vk.key
-docs/python/build
-!tests/wasm/vk_aggr.key
+!tests/wasm/vk.key

.python-version

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

.readthedocs.yaml

@@ -1,26 +0,0 @@
-# .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

@@ -15,96 +15,70 @@ crate-type = ["cdylib", "rlib"]
 
 
 [dependencies]
-halo2_gadgets = { git = "https://github.com/zkonduit/halo2", branch = "ac/optional-selector-poly" }
-halo2_proofs = { git = "https://github.com/zkonduit/halo2", branch = "ac/optional-selector-poly" }
-halo2curves = { git = "https://github.com/privacy-scaling-explorations/halo2curves", rev = "9fff22c", features = [
-    "derive_serde",
-] }
+halo2_gadgets = { git = "https://github.com/zkonduit/halo2", branch= "main" }
+halo2_proofs = { git = "https://github.com/zkonduit/halo2", branch= "main"  }
+halo2curves = { version = "0.6.0", features = ["derive_serde"] }
 rand = { version = "0.8", default_features = false }
 itertools = { version = "0.10.3", default_features = false }
-clap = { version = "4.5.3", features = ["derive"] }
+clap = { version = "4.3.3", features = ["derive"]}
 serde = { version = "1.0.126", features = ["derive"], optional = true }
-serde_json = { version = "1.0.97", default_features = false, features = [
-    "float_roundtrip",
-    "raw_value",
-], optional = true }
+serde_json = { version = "1.0.97", default_features = false, features = ["float_roundtrip", "raw_value"], optional = true }
 log = { version = "0.4.17", default_features = false, optional = true }
 thiserror = { version = "1.0.38", default_features = false }
 hex = { version = "0.4.3", default_features = false }
 halo2_wrong_ecc = { git = "https://github.com/zkonduit/halo2wrong", branch = "ac/chunked-mv-lookup", package = "ecc" }
-snark-verifier = { git = "https://github.com/zkonduit/snark-verifier", branch = "ac/chunked-mv-lookup", features = [
-    "derive_serde",
-] }
-halo2_solidity_verifier = { git = "https://github.com/alexander-camuto/halo2-solidity-verifier", branch = "main" }
-maybe-rayon = { version = "0.1.1", default_features = false }
+snark-verifier = { git = "https://github.com/zkonduit/snark-verifier", branch = "ac/chunked-mv-lookup", features=["derive_serde"]}
+halo2_solidity_verifier = { git = "https://github.com/alexander-camuto/halo2-solidity-verifier",  branch= "main" }
+maybe-rayon = { version = "0.1.1",  default_features = false }
 bincode = { version = "1.3.3", default_features = false }
 ark-std = { version = "^0.3.0", default-features = false }
 unzip-n = "0.1.2"
 num = "0.4.1"
-portable-atomic = "1.6.0"
-tosubcommand = { git = "https://github.com/zkonduit/enum_to_subcommand", package = "tosubcommand" }
-
 
 # evm related deps
 [target.'cfg(not(target_arch = "wasm32"))'.dependencies]
-ethers = { version = "2.0.11", default_features = false, features = [
-    "ethers-solc",
-] }
-indicatif = { version = "0.17.5", features = ["rayon"] }
-gag = { version = "1.0.0", default_features = false }
+ethers = { version = "2.0.7", default_features = false, features = ["ethers-solc"] }
+indicatif = {version = "0.17.5", features = ["rayon"]}
+gag =  { version = "1.0.0", default_features = false}
 instant = { version = "0.1" }
-reqwest = { version = "0.11.14", default-features = false, features = [
-    "default-tls",
-    "multipart",
-    "stream",
-] }
+reqwest = { version = "0.11.14", default-features = false, features = ["default-tls", "multipart", "stream"] }
 openssl = { version = "0.10.55", features = ["vendored"] }
 postgres = "0.19.5"
 pg_bigdecimal = "0.1.5"
 lazy_static = "1.4.0"
-colored_json = { version = "3.0.1", default_features = false, optional = true }
+colored_json =  { version = "3.0.1",  default_features = false, optional = true}
 plotters = { version = "0.3.0", default_features = false, optional = true }
 regex = { version = "1", default_features = false }
-tokio = { version = "1.26.0", default_features = false, features = [
-    "macros",
-    "rt",
-] }
+tokio = { version = "1.26.0",  default_features = false, features = ["macros", "rt"] }
 tokio-util = { version = "0.7.9", features = ["codec"] }
-pyo3 = { version = "0.20.2", features = [
-    "extension-module",
-    "abi3-py37",
-    "macros",
-], default_features = false, optional = true }
-pyo3-asyncio = { version = "0.20.0", features = [
-    "attributes",
-    "tokio-runtime",
-], default_features = false, optional = true }
+pyo3 = { version = "0.20.2", features = ["extension-module", "abi3-py37", "macros"],  default_features = false, optional = true }
+pyo3-asyncio = { version = "0.20.0",  features = ["attributes", "tokio-runtime"],  default_features = false, optional = true }
 pyo3-log = { version = "0.9.0", default_features = false, optional = true }
-tract-onnx = { git = "https://github.com/sonos/tract/", rev = "681a096f02c9d7d363102d9fb0e446d1710ac2c8", default_features = false, optional = true }
+tract-onnx = { git = "https://github.com/sonos/tract/", rev= "7b1aa33b2f7d1f19b80e270c83320f0f94daff69", default_features = false, optional = true }
 tabled = { version = "0.12.0", optional = true }
 
 
 [target.'cfg(not(all(target_arch = "wasm32", target_os = "unknown")))'.dependencies]
-colored = { version = "2.0.0", default_features = false, optional = true }
-env_logger = { version = "0.10.0", default_features = false, optional = true }
+colored = { version = "2.0.0",  default_features = false, optional = true}
+env_logger = { version = "0.10.0",  default_features = false, optional = true}
 chrono = "0.4.31"
 sha256 = "1.4.0"
 
 [target.'cfg(target_arch = "wasm32")'.dependencies]
 getrandom = { version = "0.2.8", features = ["js"] }
-instant = { version = "0.1", features = ["wasm-bindgen", "inaccurate"] }
+instant = { version = "0.1", features = [ "wasm-bindgen", "inaccurate" ] }
 
 [target.'cfg(all(target_arch = "wasm32", target_os = "unknown"))'.dependencies]
-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"] }
+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"]}
 console_error_panic_hook = "0.1.7"
 wasm-bindgen-console-logger = "0.1.1"
 
 
 [dev-dependencies]
-criterion = { version = "0.3", features = ["html_reports"] }
+criterion = {version = "0.3",  features = ["html_reports"]}
 tempfile = "3.3.0"
 lazy_static = "1.4.0"
 mnist = "0.5"
@@ -176,36 +150,18 @@ required-features = ["ezkl"]
 [features]
 web = ["wasm-bindgen-rayon"]
 default = ["ezkl", "mv-lookup"]
+render = ["halo2_proofs/dev-graph", "plotters"]
 onnx = ["dep:tract-onnx"]
 python-bindings = ["pyo3", "pyo3-log", "pyo3-asyncio"]
-ezkl = [
-    "onnx",
-    "serde",
-    "serde_json",
-    "log",
-    "colored",
-    "env_logger",
-    "tabled/color",
-    "colored_json",
-    "halo2_proofs/circuit-params",
-]
-mv-lookup = [
-    "halo2_proofs/mv-lookup",
-    "snark-verifier/mv-lookup",
-    "halo2_solidity_verifier/mv-lookup",
-]
+ezkl = ["onnx", "serde", "serde_json", "log", "colored", "env_logger", "tabled/color", "colored_json", "halo2_proofs/circuit-params"]
+mv-lookup = ["halo2_proofs/mv-lookup", "snark-verifier/mv-lookup", "halo2_solidity_verifier/mv-lookup"]
 det-prove = []
 icicle = ["halo2_proofs/icicle_gpu"]
 empty-cmd = []
-no-banner = []
 
 # icicle patch to 0.1.0 if feature icicle is enabled
 [patch.'https://github.com/ingonyama-zk/icicle']
-icicle = { git = "https://github.com/ingonyama-zk/icicle?rev=45b00fb", package = "icicle", branch = "fix/vhnat/ezkl-build-fix" }
-
-[patch.'https://github.com/zkonduit/halo2']
-halo2_proofs = { git = "https://github.com/zkonduit/halo2?branch=ac/optional-selector-poly#54f54453cf186aa5d89579c4e7663f9a27cfb89a", package = "halo2_proofs", branch = "ac/optional-selector-poly" }
-
+icicle = { git = "https://github.com/ingonyama-zk/icicle?rev=45b00fb", package = "icicle", branch = "fix/vhnat/ezkl-build-fix"}
 
 [profile.release]
-rustflags = ["-C", "relocation-model=pic"]
+rustflags = [ "-C", "relocation-model=pic" ]

README.md

@@ -31,9 +31,9 @@ EZKL
 
 [![Notebook](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/zkonduit/ezkl/blob/main/examples/notebooks/simple_demo_all_public.ipynb) 
 
-In the backend we use the collaboratively-developed [Halo2](https://github.com/privacy-scaling-explorations/halo2) as a proof system.
+In the backend we use [Halo2](https://github.com/privacy-scaling-explorations/halo2) as a proof system.
 
-The generated proofs can then be verified with much less computational resources, including on-chain (with the Ethereum Virtual Machine), in a browser, or on a device. 
+The generated proofs can then be used on-chain to verify computation, only the Ethereum Virtual Machine (EVM) is supported at the moment.
 
 - If you have any questions, we'd love for you to open up a discussion topic in [Discussions](https://github.com/zkonduit/ezkl/discussions). Alternatively, you can join the ✨[EZKL Community Telegram Group](https://t.me/+QRzaRvTPIthlYWMx)💫.
 
@@ -45,8 +45,6 @@ The generated proofs can then be verified with much less computational resources
 
 ### getting started ⚙️
 
-The easiest way to get started is to try out a notebook. 
-
 #### Python
 Install the python bindings by calling.
 
@@ -72,14 +70,10 @@ curl https://raw.githubusercontent.com/zkonduit/ezkl/main/install_ezkl_cli.sh |
 
 https://user-images.githubusercontent.com/45801863/236771676-5bbbbfd1-ba6f-418a-902e-20738ce0e9f0.mp4
 
-For more details visit the [docs](https://docs.ezkl.xyz). The CLI is faster than Python, as it has less overhead. For even more speed and convenience, check out the [remote proving service](https://ei40vx5x6j0.typeform.com/to/sFv1oxvb), which feels like the CLI but is backed by a tuned cluster.
+For more details visit the [docs](https://docs.ezkl.xyz).
 
 Build the auto-generated rust documentation and open the docs in your browser locally. `cargo doc --open`
 
-#### In-browser EVM verifier
-
-As an alternative to running the native Halo2 verifier as a WASM binding in the browser, you can use the in-browser EVM verifier. The source code of which you can find in the `in-browser-evm-verifier` directory and a README with instructions on how to use it.
-
 
 ### building the project 🔨
 
@@ -126,6 +120,17 @@ unset ENABLE_ICICLE_GPU
 
 **NOTE:** Even with the above environment variable set, icicle is disabled for circuits where k <= 8. To change the value of `k` where icicle is enabled, you can set the environment variable `ICICLE_SMALL_K`.
 
+### repos
+
+The EZKL project has several libraries and repos. 
+
+| Repo | Description |
+| --- | --- |
+| [@zkonduit/ezkl](https://github.com/zkonduit/ezkl) | the main ezkl repo in rust with wasm and python bindings |
+| [@zkonduit/ezkljs](https://github.com/zkonduit/ezkljs) | typescript and javascript tooling to help integrate ezkl into web apps |
+
+----------------------
+
 ### contributing 🌎
 
 If you're interested in contributing and are unsure where to start, reach out to one of the maintainers:
@@ -142,7 +147,7 @@ More broadly:
 - To report bugs or request new features [create a new issue within Issues](https://github.com/zkonduit/ezkl/issues) to inform the greater community.
 
 
-Any contribution intentionally submitted for inclusion in the work by you shall be licensed to Zkonduit Inc. under the terms and conditions specified in the [CLA](https://github.com/zkonduit/ezkl/blob/main/cla.md), which you agree to by intentionally submitting a contribution. In particular, you have the right to submit the contribution and we can distribute it, among other terms and conditions. 
+Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you shall be licensed to Zkonduit Inc. under the terms and conditions specified in the [CLA](https://github.com/zkonduit/ezkl/blob/main/cla.md), which you agree to by intentionally submitting a contribution. In particular, you have the right to submit the contribution and we can distribute it under the Apache 2.0 license, among other terms and conditions. 
 
 ### no security guarantees
 
@@ -150,7 +155,4 @@ Ezkl is unaudited, beta software undergoing rapid development. There may be bugs
 
 > NOTE: Because operations are quantized when they are converted from an onnx file to a zk-circuit, outputs in python and ezkl may differ slightly. 
 
-### no warranty
 
-Copyright (c) 2024 Zkonduit Inc. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

benches/accum_conv.rs

@@ -2,13 +2,11 @@ use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Through
 use ezkl::circuit::poly::PolyOp;
 use ezkl::circuit::*;
 use ezkl::pfsys::create_keys;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::srs::gen_srs;
 use ezkl::pfsys::TranscriptType;
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     arithmetic::Field,
@@ -17,7 +15,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::rngs::OsRng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 
 static mut KERNEL_HEIGHT: usize = 2;
 static mut KERNEL_WIDTH: usize = 2;
@@ -70,8 +67,8 @@ impl Circuit<Fr> for MyCircuit {
                         &mut region,
                         &[self.image.clone(), self.kernel.clone(), self.bias.clone()],
                         Box::new(PolyOp::Conv {
-                            padding: vec![(0, 0)],
-                            stride: vec![1; 2],
+                            padding: [(0, 0); 2],
+                            stride: (1, 1),
                         }),
                     )
                     .unwrap();
@@ -124,35 +121,28 @@ fn runcnvrl(c: &mut Criterion) {
             group.throughput(Throughput::Elements(*size as u64));
             group.bench_with_input(BenchmarkId::new("pk", size), &size, |b, &_| {
                 b.iter(|| {
-                    create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
-                        .unwrap();
+                    create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(
+                        &circuit, &params, true,
+                    )
+                    .unwrap();
                 });
             });
 
-            let pk = create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
-                .unwrap();
+            let pk =
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+                    .unwrap();
 
             group.throughput(Throughput::Elements(*size as u64));
             group.bench_with_input(BenchmarkId::new("prove", size), &size, |b, &_| {
                 b.iter(|| {
-                    let prover = create_proof_circuit::<
-                        KZGCommitmentScheme<_>,
-                        MyCircuit,
-                        ProverSHPLONK<_>,
-                        VerifierSHPLONK<_>,
-                        SingleStrategy<_>,
-                        _,
-                        EvmTranscript<_, _, _, _>,
-                        EvmTranscript<_, _, _, _>,
-                    >(
+                    let prover = create_proof_circuit_kzg(
                         circuit.clone(),
-                        vec![],
                         &params,
-                        &pk,
-                        CheckMode::UNSAFE,
-                        ezkl::Commitments::KZG,
-                        TranscriptType::EVM,
                         None,
+                        &pk,
+                        TranscriptType::EVM,
+                        SingleStrategy::new(&params),
+                        CheckMode::UNSAFE,
                         None,
                     );
                     prover.unwrap();

benches/accum_dot.rs

@@ -1,13 +1,11 @@
 use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
 use ezkl::circuit::poly::PolyOp;
 use ezkl::circuit::*;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     arithmetic::Field,
@@ -16,7 +14,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::rngs::OsRng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 use std::marker::PhantomData;
 
 static mut LEN: usize = 4;
@@ -93,35 +90,25 @@ fn rundot(c: &mut Criterion) {
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("pk", len), &len, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("prove", len), &len, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    MyCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
-                    &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
-                    TranscriptType::EVM,
                     None,
+                    &pk,
+                    TranscriptType::EVM,
+                    SingleStrategy::new(&params),
+                    CheckMode::UNSAFE,
                     None,
                 );
                 prover.unwrap();

benches/accum_einsum_matmul.rs

@@ -1,13 +1,11 @@
 use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
 use ezkl::circuit::poly::PolyOp;
 use ezkl::circuit::*;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     arithmetic::Field,
@@ -16,7 +14,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::rngs::OsRng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 use std::marker::PhantomData;
 
 static mut LEN: usize = 4;
@@ -97,35 +94,25 @@ fn runmatmul(c: &mut Criterion) {
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("pk", len), &len, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("prove", len), &len, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    MyCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
-                    &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
-                    TranscriptType::EVM,
                     None,
+                    &pk,
+                    TranscriptType::EVM,
+                    SingleStrategy::new(&params),
+                    CheckMode::UNSAFE,
                     None,
                 );
                 prover.unwrap();

benches/accum_matmul_relu.rs

@@ -4,20 +4,17 @@ use ezkl::circuit::*;
 
 use ezkl::circuit::lookup::LookupOp;
 use ezkl::circuit::poly::PolyOp;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     circuit::{Layouter, SimpleFloorPlanner, Value},
     plonk::{Circuit, ConstraintSystem, Error},
 };
 use halo2curves::bn256::{Bn256, Fr};
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 use std::marker::PhantomData;
 
 const BITS: Range = (-32768, 32768);
@@ -115,35 +112,25 @@ fn runmatmul(c: &mut Criterion) {
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("pk", len), &len, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("prove", len), &len, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    MyCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
-                    &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
-                    TranscriptType::EVM,
                     None,
+                    &pk,
+                    TranscriptType::EVM,
+                    SingleStrategy::new(&params),
+                    CheckMode::SAFE,
                     None,
                 );
                 prover.unwrap();

benches/accum_matmul_relu_overflow.rs

@@ -4,20 +4,17 @@ use ezkl::circuit::*;
 use ezkl::circuit::lookup::LookupOp;
 use ezkl::circuit::poly::PolyOp;
 use ezkl::circuit::table::Range;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     circuit::{Layouter, SimpleFloorPlanner, Value},
     plonk::{Circuit, ConstraintSystem, Error},
 };
 use halo2curves::bn256::{Bn256, Fr};
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 use std::marker::PhantomData;
 
 const BITS: Range = (-8180, 8180);
@@ -118,35 +115,25 @@ fn runmatmul(c: &mut Criterion) {
         group.throughput(Throughput::Elements(k as u64));
         group.bench_with_input(BenchmarkId::new("pk", k), &k, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(k as u64));
         group.bench_with_input(BenchmarkId::new("prove", k), &k, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    MyCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
-                    &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
-                    TranscriptType::EVM,
                     None,
+                    &pk,
+                    TranscriptType::EVM,
+                    SingleStrategy::new(&params),
+                    CheckMode::SAFE,
                     None,
                 );
                 prover.unwrap();

benches/accum_sum.rs

@@ -1,13 +1,11 @@
 use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
 use ezkl::circuit::poly::PolyOp;
 use ezkl::circuit::*;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     arithmetic::Field,
@@ -16,7 +14,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::rngs::OsRng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 use std::marker::PhantomData;
 
 static mut LEN: usize = 4;
@@ -89,35 +86,25 @@ fn runsum(c: &mut Criterion) {
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("pk", len), &len, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("prove", len), &len, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    MyCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
-                    &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
-                    TranscriptType::EVM,
                     None,
+                    &pk,
+                    TranscriptType::EVM,
+                    SingleStrategy::new(&params),
+                    CheckMode::UNSAFE,
                     None,
                 );
                 prover.unwrap();

benches/accum_sumpool.rs

@@ -2,13 +2,11 @@ use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Through
 use ezkl::circuit::hybrid::HybridOp;
 use ezkl::circuit::*;
 use ezkl::pfsys::create_keys;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::srs::gen_srs;
 use ezkl::pfsys::TranscriptType;
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     arithmetic::Field,
@@ -17,7 +15,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::rngs::OsRng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 
 static mut IMAGE_HEIGHT: usize = 2;
 static mut IMAGE_WIDTH: usize = 2;
@@ -65,9 +62,9 @@ impl Circuit<Fr> for MyCircuit {
                         &mut region,
                         &[self.image.clone()],
                         Box::new(HybridOp::SumPool {
-                            padding: vec![(0, 0); 2],
-                            stride: vec![1, 1],
-                            kernel_shape: vec![2, 2],
+                            padding: [(0, 0); 2],
+                            stride: (1, 1),
+                            kernel_shape: (2, 2),
                             normalized: false,
                         }),
                     )
@@ -104,35 +101,28 @@ fn runsumpool(c: &mut Criterion) {
             group.throughput(Throughput::Elements(*size as u64));
             group.bench_with_input(BenchmarkId::new("pk", size), &size, |b, &_| {
                 b.iter(|| {
-                    create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
-                        .unwrap();
+                    create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(
+                        &circuit, &params, true,
+                    )
+                    .unwrap();
                 });
             });
 
-            let pk = create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
-                .unwrap();
+            let pk =
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+                    .unwrap();
 
             group.throughput(Throughput::Elements(*size as u64));
             group.bench_with_input(BenchmarkId::new("prove", size), &size, |b, &_| {
                 b.iter(|| {
-                    let prover = create_proof_circuit::<
-                        KZGCommitmentScheme<_>,
-                        MyCircuit,
-                        ProverSHPLONK<_>,
-                        VerifierSHPLONK<_>,
-                        SingleStrategy<_>,
-                        _,
-                        EvmTranscript<_, _, _, _>,
-                        EvmTranscript<_, _, _, _>,
-                    >(
+                    let prover = create_proof_circuit_kzg(
                         circuit.clone(),
-                        vec![],
                         &params,
-                        &pk,
-                        CheckMode::UNSAFE,
-                        ezkl::Commitments::KZG,
-                        TranscriptType::EVM,
                         None,
+                        &pk,
+                        TranscriptType::EVM,
+                        SingleStrategy::new(&params),
+                        CheckMode::UNSAFE,
                         None,
                     );
                     prover.unwrap();

benches/pairwise_add.rs

@@ -1,13 +1,11 @@
 use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
 use ezkl::circuit::poly::PolyOp;
 use ezkl::circuit::*;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     arithmetic::Field,
@@ -16,7 +14,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::rngs::OsRng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 use std::marker::PhantomData;
 
 static mut LEN: usize = 4;
@@ -87,35 +84,25 @@ fn runadd(c: &mut Criterion) {
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("pk", len), &len, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("prove", len), &len, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    MyCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
-                    &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
-                    TranscriptType::EVM,
                     None,
+                    &pk,
+                    TranscriptType::EVM,
+                    SingleStrategy::new(&params),
+                    CheckMode::SAFE,
                     None,
                 );
                 prover.unwrap();

benches/pairwise_pow.rs

@@ -2,13 +2,11 @@ use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Through
 use ezkl::circuit::poly::PolyOp;
 use ezkl::circuit::region::RegionCtx;
 use ezkl::circuit::*;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::ProverSHPLONK;
-use halo2_proofs::poly::kzg::multiopen::VerifierSHPLONK;
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     arithmetic::Field,
@@ -17,7 +15,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::rngs::OsRng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 use std::marker::PhantomData;
 
 static mut LEN: usize = 4;
@@ -86,35 +83,25 @@ fn runpow(c: &mut Criterion) {
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("pk", len), &len, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("prove", len), &len, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    MyCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
-                    &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
-                    TranscriptType::EVM,
                     None,
+                    &pk,
+                    TranscriptType::EVM,
+                    SingleStrategy::new(&params),
+                    CheckMode::SAFE,
                     None,
                 );
                 prover.unwrap();

benches/poseidon.rs

@@ -1,18 +1,15 @@
-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};
 use ezkl::circuit::modules::Module;
 use ezkl::circuit::*;
 use ezkl::pfsys::create_keys;
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::srs::gen_srs;
 use ezkl::pfsys::TranscriptType;
 use ezkl::tensor::*;
 use halo2_proofs::circuit::Value;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::{ProverSHPLONK, VerifierSHPLONK};
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     arithmetic::Field,
@@ -21,7 +18,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::rngs::OsRng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 
 const L: usize = 10;
 
@@ -50,7 +46,7 @@ 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, &mut HashMap::new())?;
+        chip.layout(&mut layouter, &[self.image.clone()], 0)?;
         Ok(())
     }
 }
@@ -66,7 +62,7 @@ fn runposeidon(c: &mut Criterion) {
         let params = gen_srs::<KZGCommitmentScheme<_>>(k);
 
         let message = (0..*size).map(|_| Fr::random(OsRng)).collect::<Vec<_>>();
-        let _output =
+        let output =
             PoseidonChip::<PoseidonSpec, POSEIDON_WIDTH, POSEIDON_RATE, L>::run(message.to_vec())
                 .unwrap();
 
@@ -80,35 +76,25 @@ fn runposeidon(c: &mut Criterion) {
         group.throughput(Throughput::Elements(*size as u64));
         group.bench_with_input(BenchmarkId::new("pk", size), &size, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, MyCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, MyCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(*size as u64));
         group.bench_with_input(BenchmarkId::new("prove", size), &size, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    MyCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
+                    Some(output[0].clone()),
                     &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
                     TranscriptType::EVM,
-                    None,
+                    SingleStrategy::new(&params),
+                    CheckMode::UNSAFE,
                     None,
                 );
                 prover.unwrap();

benches/relu.rs

@@ -2,12 +2,11 @@ use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Through
 use ezkl::circuit::region::RegionCtx;
 use ezkl::circuit::table::Range;
 use ezkl::circuit::{ops::lookup::LookupOp, BaseConfig as Config, CheckMode};
-use ezkl::pfsys::create_proof_circuit;
+use ezkl::pfsys::create_proof_circuit_kzg;
 use ezkl::pfsys::TranscriptType;
 use ezkl::pfsys::{create_keys, srs::gen_srs};
 use ezkl::tensor::*;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::kzg::multiopen::{ProverSHPLONK, VerifierSHPLONK};
 use halo2_proofs::poly::kzg::strategy::SingleStrategy;
 use halo2_proofs::{
     circuit::{Layouter, SimpleFloorPlanner, Value},
@@ -15,7 +14,6 @@ use halo2_proofs::{
 };
 use halo2curves::bn256::{Bn256, Fr};
 use rand::Rng;
-use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
 
 const BITS: Range = (-32768, 32768);
 static mut LEN: usize = 4;
@@ -93,35 +91,25 @@ fn runrelu(c: &mut Criterion) {
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("pk", len), &len, |b, &_| {
             b.iter(|| {
-                create_keys::<KZGCommitmentScheme<Bn256>, NLCircuit>(&circuit, &params, true)
+                create_keys::<KZGCommitmentScheme<Bn256>, Fr, NLCircuit>(&circuit, &params, true)
                     .unwrap();
             });
         });
 
-        let pk =
-            create_keys::<KZGCommitmentScheme<Bn256>, NLCircuit>(&circuit, &params, true).unwrap();
+        let pk = create_keys::<KZGCommitmentScheme<Bn256>, Fr, NLCircuit>(&circuit, &params, true)
+            .unwrap();
 
         group.throughput(Throughput::Elements(len as u64));
         group.bench_with_input(BenchmarkId::new("prove", len), &len, |b, &_| {
             b.iter(|| {
-                let prover = create_proof_circuit::<
-                    KZGCommitmentScheme<_>,
-                    NLCircuit,
-                    ProverSHPLONK<_>,
-                    VerifierSHPLONK<_>,
-                    SingleStrategy<_>,
-                    _,
-                    EvmTranscript<_, _, _, _>,
-                    EvmTranscript<_, _, _, _>,
-                >(
+                let prover = create_proof_circuit_kzg(
                     circuit.clone(),
-                    vec![],
                     &params,
-                    &pk,
-                    CheckMode::UNSAFE,
-                    ezkl::Commitments::KZG,
-                    TranscriptType::EVM,
                     None,
+                    &pk,
+                    TranscriptType::EVM,
+                    SingleStrategy::new(&params),
+                    CheckMode::SAFE,
                     None,
                 );
                 prover.unwrap();

docs/python/build.sh

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

docs/python/requirements-docs.txt

@@ -1,4 +0,0 @@
-ezkl==10.3.1
-sphinx
-sphinx-rtd-theme
-sphinxcontrib-napoleon

docs/python/src/conf.py

@@ -1,29 +0,0 @@
-import ezkl
-
-project = 'ezkl'
-release = '10.3.1'
-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

@@ -1,11 +0,0 @@
-.. 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

@@ -6,7 +6,6 @@ use ezkl::fieldutils;
 use ezkl::fieldutils::i32_to_felt;
 use ezkl::tensor::*;
 use halo2_proofs::dev::MockProver;
-use halo2_proofs::poly::commitment::Params;
 use halo2_proofs::poly::kzg::multiopen::{ProverSHPLONK, VerifierSHPLONK};
 use halo2_proofs::{
     circuit::{Layouter, SimpleFloorPlanner, Value},
@@ -203,8 +202,8 @@ where
                     let mut region = RegionCtx::new(region, 0, NUM_INNER_COLS);
 
                     let op = PolyOp::Conv {
-                        padding: vec![(PADDING, PADDING); 2],
-                        stride: vec![STRIDE; 2],
+                        padding: [(PADDING, PADDING); 2],
+                        stride: (STRIDE, STRIDE),
                     };
                     let x = config
                         .layer_config
@@ -490,7 +489,6 @@ pub fn runconv() {
         strategy,
         pi_for_real_prover,
         &mut transcript,
-        params.n(),
     );
     assert!(verify.is_ok());
 

examples/notebooks/applications/data_attest_hashed.ipynb

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

examples/notebooks/applications/ezkl_demo.ipynb

@@ -695,19 +695,17 @@
         "formatted_output = \"[\"\n",
         "for i, value in enumerate(proof[\"instances\"]):\n",
         "    for j, field_element in enumerate(value):\n",
-        "        onchain_input_array.append(ezkl.felt_to_big_endian(field_element))\n",
-        "        formatted_output += '\"' + str(onchain_input_array[-1]) + '\"'\n",
+        "        onchain_input_array.append(ezkl.string_to_felt(field_element))\n",
+        "        formatted_output += str(onchain_input_array[-1])\n",
         "        if j != len(value) - 1:\n",
         "            formatted_output += \", \"\n",
-        "    if i != len(proof[\"instances\"]) - 1:\n",
-        "        formatted_output += \", \"\n",
-        "formatted_output += \"]\"\n",
+        "    formatted_output += \"]\"\n",
         "\n",
         "# This will be the values you use onchain\n",
         "# copy them over to remix and see if they verify\n",
         "# What happens when you change a value?\n",
         "print(\"pubInputs: \", formatted_output)\n",
-        "print(\"proof: \", proof[\"proof\"])"
+        "print(\"proof: \", \"0x\" + proof[\"proof\"])"
       ]
     },
     {

examples/notebooks/applications/proof_splitting.ipynb

@@ -208,7 +208,7 @@
                 "- `private`: known only to the prover\n",
                 "- `hashed`: the hash pre-image is known to the prover, the prover and verifier know the hash. The prover proves that the they know the pre-image to the hash. \n",
                 "- `encrypted`: the non-encrypted element and the secret key used for decryption are known to the prover. The prover and the verifier know the encrypted element, the public key used to encrypt, and the hash of the decryption hey. The prover proves that they know the pre-image of the hashed decryption key and that this key can in fact decrypt the encrypted message.\n",
-                "- `polycommit`: unblinded advice column which generates a kzg commitment. This doesn't appear in the instances of the circuit and must instead be modified directly within the proof bytes.  \n",
+                "- `kzgcommit`: unblinded advice column which generates a kzg commitment. This doesn't appear in the instances of the circuit and must instead be modified directly within the proof bytes.  \n",
                 "\n",
                 "Here we create the following setup:\n",
                 "- `input_visibility`: \"public\"\n",
@@ -234,7 +234,7 @@
                 "run_args.input_scale = 2\n",
                 "run_args.logrows = 8\n",
                 "\n",
-                "ezkl.get_srs(logrows=run_args.logrows, commitment=ezkl.PyCommitments.KZG)"
+                "ezkl.get_srs(logrows=run_args.logrows)"
             ]
         },
         {
@@ -385,9 +385,9 @@
                 "###  KZG commitment intermediate calculations\n",
                 "\n",
                 "This time the visibility parameters are:\n",
-                "- `input_visibility`: \"polycommit\"\n",
+                "- `input_visibility`: \"kzgcommit\"\n",
                 "- `param_visibility`: \"public\"\n",
-                "- `output_visibility`: polycommit"
+                "- `output_visibility`: kzgcommit"
             ]
         },
         {
@@ -399,9 +399,9 @@
                 "import ezkl\n",
                 "\n",
                 "run_args = ezkl.PyRunArgs()\n",
-                "run_args.input_visibility = \"polycommit\"\n",
+                "run_args.input_visibility = \"kzgcommit\"\n",
                 "run_args.param_visibility = \"fixed\"\n",
-                "run_args.output_visibility = \"polycommit\"\n",
+                "run_args.output_visibility = \"kzgcommit\"\n",
                 "run_args.variables = [(\"batch_size\", 1)]\n",
                 "run_args.input_scale = 2\n",
                 "run_args.logrows = 8\n"

examples/notebooks/applications/simple_demo_aggregated_proofs.ipynb

@@ -275,6 +275,7 @@
                 "        proof_path,\n",
                 "        settings_path,\n",
                 "        vk_path,\n",
+                "        \n",
                 "    )\n",
                 "\n",
                 "assert res == True\n",
@@ -290,7 +291,7 @@
             "source": [
                 "# Generate a larger SRS. This is needed for the aggregated proof\n",
                 "\n",
-                "res = ezkl.get_srs(settings_path=None, logrows=21, commitment=ezkl.PyCommitments.KZG)"
+                "res = ezkl.get_srs(settings_path=None, logrows=21)"
             ]
         },
         {

examples/notebooks/applications/solvency.ipynb

@@ -9,7 +9,7 @@
       "source": [
         "## Solvency demo\n",
         "\n",
-        "Here we create a demo of a solvency calculation in the manner of [summa-solvency](https://github.com/summa-dev/summa-solvency). The aim here is to demonstrate the use of the new polycommit method detailed [here](https://blog.ezkl.xyz/post/commits/). \n",
+        "Here we create a demo of a solvency calculation in the manner of [summa-solvency](https://github.com/summa-dev/summa-solvency). The aim here is to demonstrate the use of the new kzgcommit method detailed [here](https://blog.ezkl.xyz/post/commits/). \n",
         "\n",
         "In this setup:\n",
         "- the commitments to users, respective balances, and total balance are known are publicly known to the prover and verifier. \n",
@@ -126,7 +126,7 @@
         "# Loop through each element in the y tensor\n",
         "for e in user_preimages:\n",
         "    # Apply the custom function and append the result to the list\n",
-        "    users.append(ezkl.poseidon_hash([ezkl.float_to_felt(e, 0)])[0])\n",
+        "    users.append(ezkl.poseidon_hash([ezkl.float_to_string(e, 0)])[0])\n",
         "\n",
         "users_t = torch.tensor(user_preimages)\n",
         "users_t = users_t.reshape(1, 6)\n",
@@ -177,10 +177,10 @@
         "- `private`: known only to the prover\n",
         "- `hashed`: the hash pre-image is known to the prover, the prover and verifier know the hash. The prover proves that the they know the pre-image to the hash. \n",
         "- `encrypted`: the non-encrypted element and the secret key used for decryption are known to the prover. The prover and the verifier know the encrypted element, the public key used to encrypt, and the hash of the decryption hey. The prover proves that they know the pre-image of the hashed decryption key and that this key can in fact decrypt the encrypted message.\n",
-        "- `polycommit`: unblinded advice column which generates a kzg commitment. This doesn't appear in the instances of the circuit and must instead be modified directly within the proof bytes.  \n",
+        "- `kzgcommit`: unblinded advice column which generates a kzg commitment. This doesn't appear in the instances of the circuit and must instead be modified directly within the proof bytes.  \n",
         "\n",
         "Here we create the following setup:\n",
-        "- `input_visibility`: \"polycommit\"\n",
+        "- `input_visibility`: \"kzgcommit\"\n",
         "- `param_visibility`: \"public\"\n",
         "- `output_visibility`: public\n",
         "\n",
@@ -202,8 +202,8 @@
       "outputs": [],
       "source": [
         "run_args = ezkl.PyRunArgs()\n",
-        "# \"polycommit\" means that the output of the hashing is not visible to the verifier and is instead fed into the computational graph\n",
-        "run_args.input_visibility = \"polycommit\"\n",
+        "# \"kzgcommit\" means that the output of the hashing is not visible to the verifier and is instead fed into the computational graph\n",
+        "run_args.input_visibility = \"kzgcommit\"\n",
         "# the parameters are public\n",
         "run_args.param_visibility = \"fixed\"\n",
         "# the output is public (this is the inequality test)\n",
@@ -303,7 +303,7 @@
         "# we force the output to be 1 this corresponds to the solvency test being true -- and we set this to a fixed vis output\n",
         "# this means that the output is fixed and the verifier can see it but that if the input is not in the set the output will not be 0 and the verifier will reject\n",
         "witness = json.load(open(witness_path, \"r\"))\n",
-        "witness[\"outputs\"][0] = [ezkl.float_to_felt(1.0, 0)]\n",
+        "witness[\"outputs\"][0] = [ezkl.float_to_string(1.0, 0)]\n",
         "json.dump(witness, open(witness_path, \"w\"))"
       ]
     },
@@ -417,7 +417,7 @@
         "# we force the output to be 1 this corresponds to the solvency test being true -- and we set this to a fixed vis output\n",
         "# this means that the output is fixed and the verifier can see it but that if the input is not in the set the output will not be 0 and the verifier will reject\n",
         "witness = json.load(open(witness_path, \"r\"))\n",
-        "witness[\"outputs\"][0] = [ezkl.float_to_felt(1.0, 0)]\n",
+        "witness[\"outputs\"][0] = [ezkl.float_to_string(1.0, 0)]\n",
         "json.dump(witness, open(witness_path, \"w\"))\n"
       ]
     },
@@ -510,9 +510,9 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.15"
+      "version": "3.9.13"
     }
   },
   "nbformat": 4,
   "nbformat_minor": 5
-}
+}

examples/notebooks/applications/tictactoe_autoencoder.ipynb

@@ -13,7 +13,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 1,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -57,7 +57,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 2,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -119,7 +119,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 3,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -163,7 +163,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 4,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -217,7 +217,7 @@
         },
         {
             "cell_type": "code",
-            "execution_count": 6,
+            "execution_count": null,
             "metadata": {},
             "outputs": [],
             "source": [
@@ -227,10 +227,6 @@
                 "        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",
@@ -637,7 +633,7 @@
                 "json.dump(data, open(cal_path, 'w'))\n",
                 "\n",
                 "\n",
-                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales = [11])"
+                "ezkl.calibrate_settings(cal_path, model_path, settings_path, \"resources\", scales = [4])"
             ]
         },
         {
@@ -668,6 +664,7 @@
                 "    compiled_model_path,\n",
                 "    vk_path,\n",
                 "    pk_path,\n",
+                "    \n",
                 ")"
             ]
         },
@@ -753,7 +750,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.12.2"
+            "version": "3.9.15"
         }
     },
     "nbformat": 4,

examples/notebooks/applications/tictactoe_binary_classification.ipynb

@@ -209,11 +209,6 @@
                 "        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",
@@ -642,7 +637,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.12.2"
+            "version": "3.9.15"
         }
     },
     "nbformat": 4,

examples/notebooks/applications/world_rotation.ipynb

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

examples/notebooks/data_science/generalized_inverse.ipynb

@@ -10,7 +10,7 @@
         "\n",
         "## Generalized Inverse\n",
         "\n",
-        "We show how to use EZKL to prove that we know matrices $A$ and its generalized inverse $B$. Since these are large we deal with the KZG commitments, with $a$ the polycommit of $A$, $b$ the polycommit of $B$, and $ABA = A$.\n"
+        "We show how to use EZKL to prove that we know matrices $A$ and its generalized inverse $B$. Since these are large we deal with the KZG commitments, with $a$ the kzgcommit of $A$, $b$ the kzgcommit of $B$, and $ABA = A$.\n"
       ]
     },
     {
@@ -77,7 +77,7 @@
       "outputs": [],
       "source": [
         "gip_run_args = ezkl.PyRunArgs()\n",
-        "gip_run_args.input_visibility = \"polycommit\"  # matrix and generalized inverse commitments\n",
+        "gip_run_args.input_visibility = \"kzgcommit\"  # matrix and generalized inverse commitments\n",
         "gip_run_args.output_visibility = \"fixed\"   # no parameters used\n",
         "gip_run_args.param_visibility = \"fixed\" # should be Tensor(True)"
       ]
@@ -340,4 +340,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 5
-}
+}

examples/notebooks/data_science/hashed_vis.ipynb

@@ -161,7 +161,7 @@
                 "- `fixed`: known to the prover and verifier (as a commit), but not modifiable by the prover.\n",
                 "- `hashed`: the hash pre-image is known to the prover, the prover and verifier know the hash. The prover proves that the they know the pre-image to the hash. \n",
                 "- `encrypted`: the non-encrypted element and the secret key used for decryption are known to the prover. The prover and the verifier know the encrypted element, the public key used to encrypt, and the hash of the decryption hey. The prover proves that they know the pre-image of the hashed decryption key and that this key can in fact decrypt the encrypted message.\n",
-                "- `polycommit`: unblinded advice column which generates a kzg commitment. This doesn't appear in the instances of the circuit and must instead be inserted directly within the proof bytes.  \n",
+                "- `kzgcommit`: unblinded advice column which generates a kzg commitment. This doesn't appear in the instances of the circuit and must instead be inserted directly within the proof bytes.  \n",
                 "\n",
                 "\n",
                 "Here we create the following setup:\n",
@@ -510,4 +510,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 2
-}
+}

examples/notebooks/data_science/kzg_vis.ipynb

@@ -154,11 +154,11 @@
                 "- `fixed`: known to the prover and verifier (as a commit), but not modifiable by the prover.\n",
                 "- `hashed`: the hash pre-image is known to the prover, the prover and verifier know the hash. The prover proves that the they know the pre-image to the hash. \n",
                 "- `encrypted`: the non-encrypted element and the secret key used for decryption are known to the prover. The prover and the verifier know the encrypted element, the public key used to encrypt, and the hash of the decryption hey. The prover proves that they know the pre-image of the hashed decryption key and that this key can in fact decrypt the encrypted message.\n",
-                "- `polycommit`: unblinded advice column which generates a kzg commitment. This doesn't appear in the instances of the circuit and must instead be modified directly within the proof bytes.  \n",
+                "- `kzgcommit`: unblinded advice column which generates a kzg commitment. This doesn't appear in the instances of the circuit and must instead be modified directly within the proof bytes.  \n",
                 "\n",
                 "Here we create the following setup:\n",
-                "- `input_visibility`: \"polycommit\"\n",
-                "- `param_visibility`: \"polycommit\"\n",
+                "- `input_visibility`: \"kzgcommit\"\n",
+                "- `param_visibility`: \"kzgcommit\"\n",
                 "- `output_visibility`: public\n",
                 "\n",
                 "We encourage you to play around with other setups :) \n",
@@ -186,8 +186,8 @@
                 "data_path = os.path.join('input.json')\n",
                 "\n",
                 "run_args = ezkl.PyRunArgs()\n",
-                "run_args.input_visibility = \"polycommit\"\n",
-                "run_args.param_visibility = \"polycommit\"\n",
+                "run_args.input_visibility = \"kzgcommit\"\n",
+                "run_args.param_visibility = \"kzgcommit\"\n",
                 "run_args.output_visibility = \"public\"\n",
                 "run_args.variables = [(\"batch_size\", 1)]\n",
                 "\n",
@@ -512,4 +512,4 @@
     },
     "nbformat": 4,
     "nbformat_minor": 2
-}
+}

examples/notebooks/data_science/set_membership.ipynb

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

examples/notebooks/deep_learning/keras_simple_demo.ipynb

@@ -67,7 +67,6 @@
                 "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/deep_learning/mnist_gan.ipynb

@@ -38,7 +38,7 @@
                 "import logging\n",
                 "\n",
                 "import tensorflow as tf\n",
-                "from tensorflow.keras.optimizers import Adam\n",
+                "from tensorflow.keras.optimizers.legacy import Adam\n",
                 "from tensorflow.keras.layers import *\n",
                 "from tensorflow.keras.models import Model\n",
                 "from tensorflow.keras.datasets import mnist\n",
@@ -71,10 +71,8 @@
             },
             "outputs": [],
             "source": [
-                "ZDIM = 100\n",
-                "\n",
                 "opt = Adam()\n",
-                "\n",
+                "ZDIM = 100\n",
                 "\n",
                 "# discriminator\n",
                 "# 0 if it's fake, 1 if it's real\n",
@@ -116,11 +114,8 @@
                 "\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",
@@ -420,7 +415,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.12.2"
+            "version": "3.9.15"
         }
     },
     "nbformat": 4,

examples/notebooks/deep_learning/mnist_gan_proof_splitting.ipynb

@@ -0,0 +1,470 @@
+{
+    "cells": [
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "# Proof splitting\n",
+                "\n",
+                "Here we showcase how to split a larger circuit into multiple smaller proofs. This is useful if you want to prove over multiple machines, or if you want to split a proof into multiple parts to reduce the memory requirements.\n",
+                "\n",
+                "We showcase how to do this in the case where:\n",
+                "- intermediate calculations need to be kept secret (but not blinded !) and we need to use the low overhead kzg commitment scheme detailed [here](https://blog.ezkl.xyz/post/commits/) to stitch the circuits together.\n"
+            ]
+        },
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "First we import the necessary dependencies and set up logging to be as informative as possible. "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# check if notebook is in colab\n",
+                "try:\n",
+                "    # install ezkl\n",
+                "    import google.colab\n",
+                "    import subprocess\n",
+                "    import sys\n",
+                "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"ezkl\"])\n",
+                "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"tf2onnx\"])\n",
+                "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", \"onnx\"])\n",
+                "\n",
+                "# rely on local installation of ezkl if the notebook is not in colab\n",
+                "except:\n",
+                "    pass\n",
+                "\n",
+                "# make sure you have the dependencies required here already installed\n",
+                "import ezkl\n",
+                "import os\n",
+                "import json\n",
+                "import time\n",
+                "import random\n",
+                "import logging\n",
+                "\n",
+                "import tensorflow as tf\n",
+                "from tensorflow.keras.optimizers.legacy import Adam\n",
+                "from tensorflow.keras.layers import *\n",
+                "from tensorflow.keras.models import Model\n",
+                "from tensorflow.keras.datasets import mnist\n",
+                "\n",
+                "# uncomment for more descriptive logging \n",
+                "# FORMAT = '%(levelname)s %(name)s %(asctime)-15s %(filename)s:%(lineno)d %(message)s'\n",
+                "# logging.basicConfig(format=FORMAT)\n",
+                "# logging.getLogger().setLevel(logging.INFO)\n",
+                "\n",
+                "# Can we build a simple GAN that can produce all 10 mnist digits?"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "\n",
+                "(x_train, y_train), (x_test, y_test) = mnist.load_data()\n",
+                "x_train, x_test = [x/255.0 for x in [x_train, x_test]]\n",
+                "y_train, y_test = [tf.keras.utils.to_categorical(x) for x in [y_train, y_test]]"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "opt = Adam()\n",
+                "ZDIM = 100\n",
+                "\n",
+                "# discriminator\n",
+                "# 0 if it's fake, 1 if it's real\n",
+                "x = in1 = Input((28,28))\n",
+                "x = Reshape((28,28,1))(x)\n",
+                "\n",
+                "x = Conv2D(64, (5,5), padding='same', strides=(2,2))(x)\n",
+                "x = BatchNormalization()(x)\n",
+                "x = ELU()(x)\n",
+                "\n",
+                "x = Conv2D(128, (5,5), padding='same', strides=(2,2))(x)\n",
+                "x = BatchNormalization()(x)\n",
+                "x = ELU()(x)\n",
+                "\n",
+                "x = Flatten()(x)\n",
+                "x = Dense(128)(x)\n",
+                "x = BatchNormalization()(x)\n",
+                "x = ELU()(x)\n",
+                "x = Dense(1, activation='sigmoid')(x)\n",
+                "dm = Model(in1, x)\n",
+                "dm.compile(opt, 'binary_crossentropy')\n",
+                "dm.summary()\n",
+                "\n",
+                "# generator, output digits\n",
+                "x = in1 = Input((ZDIM,))\n",
+                "\n",
+                "x = Dense(7*7*64)(x)\n",
+                "x = BatchNormalization()(x)\n",
+                "x = ELU()(x)\n",
+                "x = Reshape((7,7,64))(x)\n",
+                "\n",
+                "x = Conv2DTranspose(128, (5,5), strides=(2,2), padding='same')(x)\n",
+                "x = BatchNormalization()(x)\n",
+                "x = ELU()(x)\n",
+                "\n",
+                "x = Conv2DTranspose(1, (5,5), strides=(2,2), padding='same')(x)\n",
+                "x = Activation('sigmoid')(x)\n",
+                "x = Reshape((28,28))(x)\n",
+                "\n",
+                "gm = Model(in1, x)\n",
+                "gm.compile('adam', 'mse')\n",
+                "gm.summary()\n",
+                "\n",
+                "# GAN\n",
+                "dm.trainable = False\n",
+                "x = dm(gm.output)\n",
+                "tm = Model(gm.input, x)\n",
+                "tm.compile(opt, 'binary_crossentropy')\n",
+                "\n",
+                "dlosses, glosses = [], []"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import numpy as np\n",
+                "from matplotlib.pyplot import figure, imshow, show\n",
+                "\n",
+                "BS = 256\n",
+                "\n",
+                "# GAN training loop\n",
+                "# make larger if you want it to look better\n",
+                "for i in range(1):\n",
+                "  # train discriminator\n",
+                "  dm.trainable = True\n",
+                "  real_i = x_train[np.random.choice(x_train.shape[0], BS)]\n",
+                "  fake_i = gm.predict_on_batch(np.random.normal(0,1,size=(BS,ZDIM)))\n",
+                "  dloss_r = dm.train_on_batch(real_i, np.ones(BS))\n",
+                "  dloss_f = dm.train_on_batch(fake_i, np.zeros(BS))\n",
+                "  dloss = (dloss_r + dloss_f)/2\n",
+                "\n",
+                "  # train generator\n",
+                "  dm.trainable = False\n",
+                "  gloss_0 = tm.train_on_batch(np.random.normal(0,1,size=(BS,ZDIM)), np.ones(BS))\n",
+                "  gloss_1 = tm.train_on_batch(np.random.normal(0,1,size=(BS,ZDIM)), np.ones(BS))\n",
+                "  gloss = (gloss_0 + gloss_1)/2\n",
+                "\n",
+                "  if i%50 == 0:\n",
+                "    print(\"%4d: dloss:%8.4f   gloss:%8.4f\" % (i, dloss, gloss))\n",
+                "  dlosses.append(dloss)\n",
+                "  glosses.append(gloss)\n",
+                "    \n",
+                "  if i%250 == 0:\n",
+                "    \n",
+                "    figure(figsize=(16,16))\n",
+                "    imshow(np.concatenate(gm.predict(np.random.normal(size=(10,ZDIM))), axis=1))\n",
+                "    show()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from matplotlib.pyplot import plot, legend\n",
+                "figure(figsize=(8,8))\n",
+                "plot(dlosses[100:], label=\"Discriminator Loss\")\n",
+                "plot(glosses[100:], label=\"Generator Loss\")\n",
+                "legend()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "x = []\n",
+                "for i in range(10):\n",
+                "  x.append(np.concatenate(gm.predict(np.random.normal(size=(10,ZDIM))), axis=1))\n",
+                "imshow(np.concatenate(x, axis=0))"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "Now we export the _generator_ to onnx"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "\n",
+                "import numpy as np\n",
+                "import tf2onnx\n",
+                "import tensorflow as tf\n",
+                "import json\n",
+                "\n",
+                "# split the model into 3 parts\n",
+                "gm2 = tf.keras.models.Sequential(gm.layers[0:4])\n",
+                "gm3 = tf.keras.models.Sequential(gm.layers[4:11])\n",
+                "gm4 = tf.keras.models.Sequential(gm.layers[11:])\n",
+                "\n",
+                "# After training, export to onnx (network.onnx) and create a data file (input.json)\n",
+                "x = 0.1*np.random.rand(1,*[1, ZDIM])\n",
+                "inter_x1 = gm2(x[0])\n",
+                "inter_x2 = gm3(inter_x1)\n",
+                "\n",
+                "output_path = \"network_split_0.onnx\"\n",
+                "spec = tf.TensorSpec([1, ZDIM], tf.float32, name='input_0')\n",
+                "tf2onnx.convert.from_keras(gm2, input_signature=[spec], inputs_as_nchw=['input_0'], opset=12, output_path=output_path)\n",
+                "output_path = \"network_split_1.onnx\"\n",
+                "spec = tf.TensorSpec(inter_x1.shape, tf.float32, name='elu1')\n",
+                "tf2onnx.convert.from_keras(gm3, input_signature=[spec], inputs_as_nchw=['input_1'], opset=12, output_path=output_path)\n",
+                "output_path = \"network_split_2.onnx\"\n",
+                "spec = tf.TensorSpec(inter_x2.shape, tf.float32, name='elu2')\n",
+                "tf2onnx.convert.from_keras(gm4, input_signature=[spec], inputs_as_nchw=['input_2'], opset=12, output_path=output_path)\n",
+                "\n",
+                "data_array = x.reshape([-1]).tolist()\n",
+                "\n",
+                "data = dict(input_data = [data_array])\n",
+                "inter_x1 = inter_x1.numpy().reshape([-1]).tolist()\n",
+                "inter_x2 = inter_x2.numpy().reshape([-1]).tolist()\n",
+                "data_2 = dict(input_data = [inter_x1])\n",
+                "data_3 = dict(input_data = [inter_x2])\n",
+                "\n",
+                "    # Serialize data into file:\n",
+                "data_path = os.path.join('gan_input_0.json')\n",
+                "json.dump( data, open(data_path, 'w' ))\n",
+                "data_path = os.path.join('gan_input_1.json')\n",
+                "json.dump( data_2, open(data_path, 'w' ))\n",
+                "data_path = os.path.join('gan_input_2.json')\n",
+                "json.dump( data_3, open(data_path, 'w' ))\n",
+                "\n"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "###  KZG commitment intermediate calculations\n",
+                "\n",
+                "the visibility parameters are:\n",
+                "- `input_visibility`: \"kzgcommit\"\n",
+                "- `param_visibility`: \"public\"\n",
+                "- `output_visibility`: kzgcommit"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import ezkl\n",
+                "\n",
+                "srs_path = os.path.join('kzg.srs')\n",
+                "\n",
+                "run_args = ezkl.PyRunArgs()\n",
+                "run_args.input_visibility = \"kzgcommit\"\n",
+                "run_args.param_visibility = \"fixed\"\n",
+                "run_args.output_visibility = \"kzgcommit\"\n",
+                "run_args.variables = [(\"batch_size\", 1)]\n",
+                "run_args.input_scale = 0\n",
+                "run_args.param_scale = 0\n",
+                "run_args.logrows = 18\n",
+                "\n",
+                "ezkl.get_srs(logrows=run_args.logrows)\n"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## Circuit compilation"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 20,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# iterate over each submodel gen-settings, compile circuit and setup zkSNARK\n",
+                "\n",
+                "def setup(i):\n",
+                "    print(\"Setting up split model \"+str(i))\n",
+                "    # file names\n",
+                "    model_path = os.path.join('network_split_'+str(i)+'.onnx')\n",
+                "    settings_path = os.path.join('settings_split_'+str(i)+'.json')\n",
+                "    data_path =  os.path.join('gan_input_'+str(i)+'.json')\n",
+                "    compiled_model_path = os.path.join('network_split_'+str(i)+'.compiled')\n",
+                "    pk_path = os.path.join('test_split_'+str(i)+'.pk')\n",
+                "    vk_path = os.path.join('test_split_'+str(i)+'.vk')\n",
+                "    witness_path = os.path.join('witness_split_'+str(i)+'.json')\n",
+                "\n",
+                "    if i > 0:\n",
+                "         prev_witness_path = os.path.join('witness_split_'+str(i-1)+'.json')\n",
+                "         witness = json.load(open(prev_witness_path, 'r'))\n",
+                "         data = dict(input_data = witness['outputs'])\n",
+                "         # Serialize data into file:\n",
+                "         json.dump(data, open(data_path, 'w' ))\n",
+                "    else:\n",
+                "         data_path = os.path.join('gan_input_0.json')\n",
+                "\n",
+                "    # generate settings for the current model\n",
+                "    res = ezkl.gen_settings(model_path, settings_path, py_run_args=run_args)\n",
+                "    res = ezkl.calibrate_settings(data_path, model_path, settings_path, \"resources\", scales=[run_args.input_scale], max_logrows=run_args.logrows)\n",
+                "    assert res == True\n",
+                "\n",
+                "    # load settings and print them to the console\n",
+                "    settings = json.load(open(settings_path, 'r'))\n",
+                "    settings['run_args']['logrows'] = run_args.logrows\n",
+                "    json.dump(settings, open(settings_path, 'w' ))\n",
+                "\n",
+                "    res = ezkl.compile_circuit(model_path, compiled_model_path, settings_path)\n",
+                "\n",
+                "\n",
+                "    res = ezkl.setup(\n",
+                "         compiled_model_path,\n",
+                "         vk_path,\n",
+                "         pk_path,\n",
+                "         compress_selectors=True,\n",
+                "      )\n",
+                "\n",
+                "    assert res == True\n",
+                "    assert os.path.isfile(vk_path)\n",
+                "    assert os.path.isfile(pk_path)\n",
+                "    res = ezkl.gen_witness(data_path, compiled_model_path, witness_path, vk_path)\n",
+                "    run_args.input_scale = settings[\"model_output_scales\"][0]\n",
+                "\n",
+                "for i in range(3):\n",
+                "    setup(i)\n"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## Proof generation"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# GENERATE A PROOF\n",
+                "\n",
+                "def prove_model(i): \n",
+                "    proof_path = os.path.join('proof_split_'+str(i)+'.json')\n",
+                "    witness_path = os.path.join('witness_split_'+str(i)+'.json')\n",
+                "    compiled_model_path = os.path.join('network_split_'+str(i)+'.compiled')\n",
+                "    pk_path = os.path.join('test_split_'+str(i)+'.pk')\n",
+                "    vk_path = os.path.join('test_split_'+str(i)+'.vk')\n",
+                "    settings_path = os.path.join('settings_split_'+str(i)+'.json')\n",
+                "\n",
+                "    res = ezkl.prove(\n",
+                "            witness_path,\n",
+                "            compiled_model_path,\n",
+                "            pk_path,\n",
+                "            proof_path,\n",
+                "            \"for-aggr\",\n",
+                "        )\n",
+                "\n",
+                "    print(res)\n",
+                "    assert os.path.isfile(proof_path)\n",
+                "\n",
+                "    # Verify the proof\n",
+                "    if i > 0:\n",
+                "        # swap the proof commitments if we are not the first model\n",
+                "        prev_witness_path = os.path.join('witness_split_'+str(i-1)+'.json')\n",
+                "        prev_witness = json.load(open(prev_witness_path, 'r'))\n",
+                "\n",
+                "        witness = json.load(open(witness_path, 'r'))\n",
+                "\n",
+                "        print(prev_witness[\"processed_outputs\"])\n",
+                "        print(witness[\"processed_inputs\"])\n",
+                "\n",
+                "        witness[\"processed_inputs\"] = prev_witness[\"processed_outputs\"]\n",
+                "\n",
+                "        # now save the witness\n",
+                "        with open(witness_path, \"w\") as f:\n",
+                "            json.dump(witness, f)\n",
+                "\n",
+                "        res = ezkl.swap_proof_commitments(proof_path, witness_path)\n",
+                "\n",
+                "    res = ezkl.verify(\n",
+                "            proof_path,\n",
+                "            settings_path,\n",
+                "            vk_path,\n",
+                "        )\n",
+                "\n",
+                "    assert res == True\n",
+                "    print(\"verified\")\n",
+                "\n",
+                "for i in range(3):\n",
+                "    prove_model(i)"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "You can also mock aggregate the split proofs into a single proof. This is useful if you want to verify the proof on chain at a lower cost. Here we mock aggregate the proofs to save time. You can use other notebooks to see how to aggregate in full ! "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# now mock aggregate the proofs\n",
+                "proofs = []\n",
+                "for i in range(3):\n",
+                "    proof_path = os.path.join('proof_split_'+str(i)+'.json')\n",
+                "    proofs.append(proof_path)\n",
+                "\n",
+                "ezkl.mock_aggregate(proofs, logrows=22, split_proofs = True)"
+            ]
+        }
+    ],
+    "metadata": {
+        "kernelspec": {
+            "display_name": "ezkl",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.9.15"
+        },
+        "orig_nbformat": 4
+    },
+    "nbformat": 4,
+    "nbformat_minor": 2
+}

examples/notebooks/deep_learning/mnist_vae.ipynb

@@ -349,8 +349,6 @@
                 "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/tree_models/random_forest.ipynb

@@ -61,10 +61,11 @@
                 "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 hummingbird.ml import convert\n",
+                "from torch import nn\n",
                 "\n",
                 "\n",
                 "\n",
@@ -76,12 +77,28 @@
                 "clr.fit(X_train, y_train)\n",
                 "\n",
                 "\n",
+                "trees = []\n",
+                "for tree in clr.estimators_:\n",
+                "    trees.append(sk2torch.wrap(tree))\n",
                 "\n",
-                "torch_rf = convert(clr, 'torch')\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",
                 "# assert predictions from torch are = to sklearn \n",
                 "diffs = []\n",
                 "for i in range(len(X_test)):\n",
-                "    torch_pred = torch_rf.predict(torch.tensor(X_test[i].reshape(1, -1)))\n",
+                "    torch_pred = torch_rf(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",
@@ -117,12 +134,14 @@
                 "\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.predict(x)\n",
+                "torch_out = torch_rf(x)\n",
                 "# Export the model\n",
-                "torch.onnx.export(torch_rf.model,               # model being run\n",
+                "torch.onnx.export(torch_rf,               # 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",
@@ -139,7 +158,7 @@
                 "\n",
                 "data = dict(input_shapes=[shape],\n",
                 "            input_data=[d],\n",
-                "            output_data=[o.reshape([-1]).tolist() for o in torch_out])\n",
+                "            output_data=[((o).detach().numpy()).reshape([-1]).tolist() for o in torch_out])\n",
                 "\n",
                 "# Serialize data into file:\n",
                 "json.dump(data, open(\"input.json\", 'w'))\n"
@@ -302,7 +321,7 @@
             "name": "python",
             "nbconvert_exporter": "python",
             "pygments_lexer": "ipython3",
-            "version": "3.12.2"
+            "version": "3.9.15"
         }
     },
     "nbformat": 4,

examples/onnx/1l_lppool/gen.py

@@ -1,40 +0,0 @@
-from torch import nn
-import torch
-import json
-
-class Model(nn.Module):
-    def __init__(self):
-        super(Model, self).__init__()
-        self.layer = nn.LPPool2d(2, 1, (1, 1))
-
-    def forward(self, x):
-        return self.layer(x)[0]
-
-
-circuit = Model()
-
-x = torch.empty(1, 3, 2, 2).uniform_(0, 1)
-
-out = circuit(x)
-
-print(out)
-
-torch.onnx.export(circuit, x, "network.onnx",
-                  export_params=True,        # store the trained parameter weights inside the model file
-                  opset_version=17,          # the ONNX version to export the model to
-                  do_constant_folding=True,  # whether to execute constant folding for optimization
-                  input_names=['input'],   # the model's input names
-                  output_names=['output'],  # the model's output names
-                  dynamic_axes={'input': {0: 'batch_size'},  # variable length axes
-                                'output': {0: 'batch_size'}})
-
-
-d1 = ((x).detach().numpy()).reshape([-1]).tolist()
-
-data = dict(
-    input_data=[d1],
-)
-
-# Serialize data into file:
-json.dump(data, open("input.json", 'w'))
-

examples/onnx/1l_lppool/input.json

@@ -1 +0,0 @@
-{"input_data": [[0.7549541592597961, 0.990360677242279, 0.9473411440849304, 0.3951031565666199, 0.8500555753707886, 0.9352139830589294, 0.11867779493331909, 0.9493132829666138, 0.6588345766067505, 0.1933223009109497, 0.12139874696731567, 0.8547163605690002]]}

examples/onnx/celu/gen.py

@@ -1,42 +0,0 @@
-from torch import nn
-import torch
-import json
-import numpy as np
-
-
-class MyModel(nn.Module):
-    def __init__(self):
-        super(MyModel, self).__init__()
-
-    def forward(self, x):          
-        m = nn.CELU()(x)
-        
-        return m 
-
-
-circuit = MyModel()
-
-x = torch.empty(1, 8).uniform_(0, 1)
-
-out = circuit(x)
-
-print(out)
-
-torch.onnx.export(circuit, x, "network.onnx",
-                  export_params=True,        # store the trained parameter weights inside the model file
-                  opset_version=17,          # the ONNX version to export the model to
-                  do_constant_folding=True,  # whether to execute constant folding for optimization
-                  input_names=['input'],   # the model's input names
-                  output_names=['output'],  # the model's output names
-                  dynamic_axes={'input': {0: 'batch_size'},  # variable length axes
-                                'output': {0: 'batch_size'}})
-
-
-d1 = ((x).detach().numpy()).reshape([-1]).tolist()
-
-data = dict(
-    input_data=[d1],
-)
-
-# Serialize data into file:
-json.dump(data, open("input.json", 'w'))

examples/onnx/celu/input.json

@@ -1 +0,0 @@
-{"input_data": [[0.35387128591537476, 0.030473172664642334, 0.08707714080810547, 0.2429301142692566, 0.45228832960128784, 0.496021032333374, 0.13245105743408203, 0.8497090339660645]]}

examples/onnx/clip/gen.py

@@ -1,41 +0,0 @@
-from torch import nn
-import torch
-import json
-import numpy as np
-
-
-class MyModel(nn.Module):
-    def __init__(self):
-        super(MyModel, self).__init__()
-
-    def forward(self, x):          
-        m = torch.clamp(x, min=0.4, max=0.8)
-        return m
-
-
-circuit = MyModel()
-
-x = torch.empty(1, 2, 2, 8).uniform_(0, 1)
-
-out = circuit(x)
-
-print(out)
-
-torch.onnx.export(circuit, x, "network.onnx",
-                  export_params=True,        # store the trained parameter weights inside the model file
-                  opset_version=17,          # the ONNX version to export the model to
-                  do_constant_folding=True,  # whether to execute constant folding for optimization
-                  input_names=['input'],   # the model's input names
-                  output_names=['output'],  # the model's output names
-                  dynamic_axes={'input': {0: 'batch_size'},  # variable length axes
-                                'output': {0: 'batch_size'}})
-
-
-d1 = ((x).detach().numpy()).reshape([-1]).tolist()
-
-data = dict(
-    input_data=[d1],
-)
-
-# Serialize data into file:
-json.dump(data, open("input.json", 'w'))

examples/onnx/clip/input.json

@@ -1 +0,0 @@
-{"input_data": [[0.03297048807144165, 0.46362626552581787, 0.6044231057167053, 0.4949902892112732, 0.48823297023773193, 0.6798646450042725, 0.6824942231178284, 0.03491640090942383, 0.19608813524246216, 0.24129939079284668, 0.9769315123558044, 0.6306831240653992, 0.7690497636795044, 0.252221941947937, 0.9167693853378296, 0.3882681131362915, 0.9307044148445129, 0.33559417724609375, 0.7815426588058472, 0.3435332179069519, 0.7871478796005249, 0.12240773439407349, 0.5295405983924866, 0.4874419569969177, 0.08262640237808228, 0.1124718189239502, 0.5834914445877075, 0.30927878618240356, 0.48899340629577637, 0.9376634955406189, 0.21893149614334106, 0.526070773601532]]}

examples/onnx/clip/network.onnx

@@ -1,24 +0,0 @@
-pytorch2.2.1:±
-?/Constant_output_0	/Constant"Constant*
-value*
JÍÌÌ> 

-C/Constant_1_output_0/Constant_1"Constant*
-value*
JÍÌL? 

-F
-input
-/Constant_output_0
-/Constant_1_output_0output/Clip"Clip
-main_graphZ)
-input 
-

-
-batch_size
-
-
-b*
-output 
-

-
-batch_size
-
-
-B

examples/onnx/gather_nd/gen.py

@@ -1,48 +0,0 @@
-from torch import nn
-import json
-import numpy as np
-import tf2onnx
-
-
-import tensorflow as tf
-from tensorflow.keras.layers import *
-from tensorflow.keras.models import Model
-
-
-# gather_nd in tf then export to onnx
-
-
-
-
-x = in1 = Input((15, 18,))
-w = in2 = Input((15, 1), dtype=tf.int32)
-x = tf.gather_nd(x, w, batch_dims=1)
-tm = Model((in1, in2), x )
-tm.summary()
-tm.compile(optimizer='adam', loss='mse')
-
-shape = [1, 15, 18]
-index_shape = [1, 15, 1]
-# After training, export to onnx (network.onnx) and create a data file (input.json)
-x = 0.1*np.random.rand(1,*shape)
-# w = random int tensor
-w = np.random.randint(0, 10, index_shape)
-
-spec = tf.TensorSpec(shape, tf.float32, name='input_0')
-index_spec = tf.TensorSpec(index_shape, tf.int32, name='input_1')
-
-model_path = "network.onnx"
-
-tf2onnx.convert.from_keras(tm, input_signature=[spec, index_spec], inputs_as_nchw=['input_0', 'input_1'], opset=12, output_path=model_path)
-
-
-d = x.reshape([-1]).tolist()
-d1 = w.reshape([-1]).tolist()
-
-
-data = dict(
-    input_data=[d, d1],
-)
-
-# Serialize data into file:
-json.dump(data, open("input.json", 'w'))