refactor: allow for negative stride downsample

chore: update docs and panics (#952 )
fix: handle [] shapes in sort (#954 )
2026-01-13 08:17:57 -05:00 · 2025-03-13 16:33:36 -04:00 · 2025-03-10 11:32:28 -04:00 · 2025-03-08 13:17:45 -05:00 · 2025-03-05 16:10:50 -05:00 · 2025-02-28 23:56:19 -05:00
49 changed files with 2317 additions and 975 deletions
--- a/.github/workflows/engine.yml
+++ b/.github/workflows/engine.yml
@@ -29,7 +29,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: jetli/wasm-pack-action@0d096b08b4e5a7de8c28de67e11e945404e9eefa  #v0.4.0
@@ -40,7 +40,7 @@ jobs:
        run: rustup target add wasm32-unknown-unknown

      - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2025-02-17-x86_64-unknown-linux-gnu
      - name: Install binaryen
        run: |
          set -e
--- a/.github/workflows/large-tests.yml
+++ b/.github/workflows/large-tests.yml
@@ -15,7 +15,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - name: nanoGPT Mock
--- a/.github/workflows/pypi.yml
+++ b/.github/workflows/pypi.yml
@@ -50,7 +50,7 @@ jobs:

      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy

@@ -115,7 +115,7 @@ jobs:

      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy

--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -51,7 +51,7 @@ jobs:
    steps:
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - name: Checkout repo
@@ -119,27 +119,27 @@ jobs:
        include:
          - build: windows-msvc
            os: windows-latest
-            rust: nightly-2024-07-18
+            rust: nightly-2025-02-17
            target: x86_64-pc-windows-msvc
          - build: macos
            os: macos-13
-            rust: nightly-2024-07-18
+            rust: nightly-2025-02-17
            target: x86_64-apple-darwin
          - build: macos-aarch64
            os: macos-13
-            rust: nightly-2024-07-18
+            rust: nightly-2025-02-17
            target: aarch64-apple-darwin
          - build: linux-musl
            os: ubuntu-22.04
-            rust: nightly-2024-07-18
+            rust: nightly-2025-02-17
            target: x86_64-unknown-linux-musl
          - build: linux-gnu
            os: ubuntu-22.04
-            rust: nightly-2024-07-18
+            rust: nightly-2025-02-17
            target: x86_64-unknown-linux-gnu
          - build: linux-aarch64
            os: ubuntu-22.04
-            rust: nightly-2024-07-18
+            rust: nightly-2025-02-17
            target: aarch64-unknown-linux-gnu

    steps:
--- a/.github/workflows/rust.yml
+++ b/.github/workflows/rust.yml
@@ -30,7 +30,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@v1
@@ -50,7 +50,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - name: Build
@@ -66,7 +66,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - name: Docs
@@ -82,7 +82,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -107,7 +107,7 @@ jobs:
  #   persist-credentials: false
  #     - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
  #       with:
-  #         toolchain: nightly-2024-07-18
+  #         toolchain: nightly-2025-02-17
  #         override: true
  #         components: rustfmt, clippy
  #     - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -117,10 +117,6 @@ jobs:
  #     - uses: mwilliamson/setup-wasmtime-action@bf814d7d8fc3c3a77dfe114bd9fb8a2c575f6ad6  #v2.0.0
  #       with:
  #         wasmtime-version: "3.0.1"
-  #     - name: Install wasm32-wasi
-  #       run: rustup target add wasm32-wasi
-  #     - name: Install cargo-wasi
-  #       run: cargo install cargo-wasi
  #     # - name: Matmul overflow (wasi)
  #     #   run: cargo wasi test matmul_col_ultra_overflow -- --include-ignored --nocapture
  #     # - name: Conv overflow (wasi)
@@ -144,7 +140,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -154,10 +150,6 @@ jobs:
      - uses: mwilliamson/setup-wasmtime-action@bf814d7d8fc3c3a77dfe114bd9fb8a2c575f6ad6  #v2.0.0
        with:
          wasmtime-version: "3.0.1"
-      - name: Install wasm32-wasi
-        run: rustup target add wasm32-wasi
-      - name: Install cargo-wasi
-        run: cargo install cargo-wasi
      # - name: Matmul overflow (wasi)
      #   run: cargo wasi test matmul_col_ultra_overflow -- --include-ignored --nocapture
      # - name: Conv overflow (wasi)
@@ -181,7 +173,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -191,10 +183,6 @@ jobs:
      - uses: mwilliamson/setup-wasmtime-action@bf814d7d8fc3c3a77dfe114bd9fb8a2c575f6ad6  #v2.0.0
        with:
          wasmtime-version: "3.0.1"
-      - name: Install wasm32-wasi
-        run: rustup target add wasm32-wasi
-      - name: Install cargo-wasi
-        run: cargo install cargo-wasi
      # - name: Matmul overflow (wasi)
      #   run: cargo wasi test matmul_col_ultra_overflow -- --include-ignored --nocapture
      # - name: Conv overflow (wasi)
@@ -218,7 +206,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -238,7 +226,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: jetli/wasm-pack-action@0d096b08b4e5a7de8c28de67e11e945404e9eefa  #v0.4.0
@@ -251,7 +239,7 @@ jobs:
      - name: Install wasm32-unknown-unknown
        run: rustup target add wasm32-unknown-unknown
      - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2025-02-17-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
@@ -267,7 +255,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -276,6 +264,8 @@ jobs:
          locked: true
      # - name: The Worm Mock
      #   run: cargo nextest run --verbose tests::large_mock_::large_tests_5_expects -- --include-ignored
+      - name: Large 1D Conv Mock
+        run: cargo nextest run --verbose tests::large_mock_::large_tests_7_expects -- --include-ignored
      - name: MNIST Gan Mock
        run: cargo nextest run --verbose tests::large_mock_::large_tests_4_expects -- --include-ignored
      - name: NanoGPT Mock
@@ -292,8 +282,6 @@ jobs:
        run: cargo nextest run --verbose tests::mock_fixed_params_ --test-threads 32
      - name: public outputs and bounded lookup log
        run: cargo nextest run --verbose tests::mock_bounded_lookup_log --test-threads 32
-      - name: public outputs and tolerance > 0
-        run: cargo nextest run --verbose tests::mock_tolerance_public_outputs_ --test-threads 32
      - name: public outputs + batch size == 10
        run: cargo nextest run --verbose tests::mock_large_batch_public_outputs_ --test-threads 16
      - name: kzg inputs
@@ -334,7 +322,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -354,7 +342,7 @@ jobs:
          node-version: "18.12.1"
          cache: "pnpm"
      - name: "Add rust-src"
-        run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2025-02-17-x86_64-unknown-linux-gnu
      - name: Install dependencies for js tests and in-browser-evm-verifier package
        run: |
          pnpm install --frozen-lockfile
@@ -419,7 +407,7 @@ jobs:
  #         persist-credentials: false
  #     - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
  #       with:
-  #         toolchain: nightly-2024-07-18
+  #         toolchain: nightly-2025-02-17
  #         override: true
  #         components: rustfmt, clippy
  #     - uses: jetli/wasm-pack-action@0d096b08b4e5a7de8c28de67e11e945404e9eefa  #v0.4.0
@@ -427,7 +415,7 @@ jobs:
  #         # Pin to version 0.12.1
  #         version: 'v0.12.1'
  #     - name: Add rust-src
-  #       run: rustup component add rust-src --toolchain nightly-2024-07-18
+  #       run: rustup component add rust-src --toolchain nightly-2025-02-17
  #     - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683  #v4.2.2
  #       with:
  #         persist-credentials: false
@@ -453,7 +441,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: jetli/wasm-pack-action@0d096b08b4e5a7de8c28de67e11e945404e9eefa  #v0.4.0
@@ -464,7 +452,7 @@ jobs:
        run: rustup target add wasm32-unknown-unknown

      - name: Add rust-src
-        run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
+        run: rustup component add rust-src --toolchain nightly-2025-02-17-x86_64-unknown-linux-gnu
      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683  #v4.2.2
        with:
          persist-credentials: false
@@ -534,11 +522,11 @@ jobs:
  #   persist-credentials: false
  #     - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
  #       with:
-  #         toolchain: nightly-2024-07-18
+  #         toolchain: nightly-2025-02-17
  #         override: true
  #         components: rustfmt, clippy
  #     - name: Add rust-src
-  #       run: rustup component add rust-src --toolchain nightly-2024-07-18-x86_64-unknown-linux-gnu
+  #       run: rustup component add rust-src --toolchain nightly-2025-02-17-x86_64-unknown-linux-gnu
  #     - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683  #v4.2.2
  #     - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
  #       with:
@@ -572,7 +560,7 @@ jobs:
          persist-credentials: false
      - uses: dtolnay/rust-toolchain@4f94fbe7e03939b0e674bcc9ca609a16088f63ff  #nightly branch, TODO: update when required
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -592,7 +580,7 @@ jobs:
  #   persist-credentials: false
  #     - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
  #       with:
-  #         toolchain: nightly-2024-07-18
+  #         toolchain: nightly-2025-02-17
  #         override: true
  #         components: rustfmt, clippy
  #     - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -613,7 +601,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -634,7 +622,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -659,7 +647,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -683,7 +671,7 @@ jobs:
          python-version: "3.12"
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - name: Install cmake
@@ -713,7 +701,7 @@ jobs:
          python-version: "3.12"
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -764,7 +752,7 @@ jobs:
          python-version: "3.11"
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -819,7 +807,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - uses: baptiste0928/cargo-install@91c5da15570085bcde6f4d7aed98cb82d6769fd3  #v3.3.0
@@ -827,7 +815,7 @@ jobs:
          crate: cargo-nextest
          locked: true
      - name: Run ios tests
-        run: CARGO_BUILD_TARGET=aarch64-apple-darwin RUSTUP_TOOLCHAIN=nightly-2024-07-18-aarch64-apple-darwin cargo test --test ios_integration_tests --features ios-bindings-test --no-default-features
+        run: CARGO_BUILD_TARGET=aarch64-apple-darwin RUSTUP_TOOLCHAIN=nightly-2025-02-17-aarch64-apple-darwin cargo test --test ios_integration_tests --features ios-bindings-test --no-default-features

  swift-package-tests:
    permissions:
@@ -841,7 +829,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy
      - name: Build EzklCoreBindings
--- a/.github/workflows/static-analysis.yml
+++ b/.github/workflows/static-analysis.yml
@@ -17,7 +17,7 @@ jobs:
          persist-credentials: false
      - uses: actions-rs/toolchain@b2417cde72dcf67f306c0ae8e0828a81bf0b189f  #v1.0.6
        with:
-          toolchain: nightly-2024-07-18
+          toolchain: nightly-2025-02-17
          override: true
          components: rustfmt, clippy

--- a/Cargo.lock
+++ b/Cargo.lock
@@ -1932,7 +1932,7 @@ dependencies = [
 ]

 [[package]]
-name = "ezkl-gpu"
+name = "ezkl"
 version = "0.0.0"
 dependencies = [
 "alloy",
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -3,7 +3,7 @@ cargo-features = ["profile-rustflags"]
 [package]
 name = "ezkl"
 version = "0.0.0"
-edition = "2021"
+edition = "2024"
 default-run = "ezkl"

 # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
--- a/benches/accum_conv.rs
+++ b/benches/accum_conv.rs
@@ -73,6 +73,8 @@ impl Circuit<Fr> for MyCircuit {
                            padding: vec![(0, 0)],
                            stride: vec![1; 2],
                            group: 1,
+                            data_format: DataFormat::NCHW,
+                            kernel_format: KernelFormat::OIHW,
                        }),
                    )
                    .unwrap();
--- a/benches/accum_sumpool.rs
+++ b/benches/accum_sumpool.rs
@@ -69,6 +69,7 @@ impl Circuit<Fr> for MyCircuit {
                            stride: vec![1, 1],
                            kernel_shape: vec![2, 2],
                            normalized: false,
+                            data_format: DataFormat::NCHW,
                        }),
                    )
                    .unwrap();
--- a/benches/zero_finder.rs
+++ b/benches/zero_finder.rs
@@ -22,7 +22,7 @@ fn generate_test_data(size: usize, zero_probability: f64) -> Vec<ValType> {
    let mut rng = rand::thread_rng();
    (0..size)
        .map(|_i| {
-            if rng.gen::<f64>() < zero_probability {
+            if rng.r#gen::<f64>() < zero_probability {
                ValType::Constant(F::ZERO)
            } else {
                ValType::Constant(F::ONE) // Or some other non-zero value
--- a/docs/advanced_security/quantization_backdoors.md
+++ b/docs/advanced_security/quantization_backdoors.md
@@ -1,20 +1,52 @@
-# EZKL Security Note: Quantization-Induced Model Backdoors
+# EZKL Security Note: Quantization-Activated Model Backdoors

-> Note: this only affects a situation where a party separate to an application's developer has access to the model's weights and can modify them. This is a common scenario in adversarial machine learning research, but can be less common in real-world applications. If you're building your models in house and deploying them yourself, this is less of a concern. If you're building a permisionless system where anyone can submit models, this is more of a concern.
+## Model backdoors and provenance

-Models processed through EZKL's quantization step can harbor backdoors that are dormant in the original full-precision model but activate during quantization. These backdoors force specific outputs when triggered, with impact varying by application.
+Machine learning models inherently suffer from robustness issues, which can lead to various
+kinds of attacks, from backdoors to evasion attacks. These vulnerabilities are a direct byproductof how machine learning models learn and cannot be remediated.

-Key Factors:
+We say a model has a backdoor whenever a specific attacker-chosen trigger in the input leads
+to the model misbehaving. For instance, if we have an image classifier discriminating cats from dogs, the ability to turn any image of a cat into an image classified as a dog by changing a specific pixel pattern constitutes a backdoor.

- Larger models increase attack feasibility through more parameter capacity
- Smaller quantization scales facilitate attacks by allowing greater weight modifications
- Rebase ratio of 1 enables exploitation of convolutional layer consistency
+Backdoors can be introduced using many different vectors. An attacker can introduce a
+backdoor using traditional security vulnerabilities. For instance, they could directly alter the file containing model weights or dynamically hack the Python code of the model. In addition, backdoors can be introduced by the training data through a process known as poisoning. In this case, an attacker adds malicious data points to the dataset before the model is trained so that the model learns to associate the backdoor trigger with the intended misbehavior.

-Limitations: 
+All these vectors constitute a whole range of provenance challenges, as any component of an
+AI system can virtually be an entrypoint for a backdoor. Although provenance is already a
+concern with traditional code, the issue is exacerbated with AI, as retraining a model is
+cost-prohibitive. It is thus impractical to translate the “recompile it yourself” thinking to AI.

- Attack effectiveness depends on calibration settings and internal rescaling operations. 
+## Quantization activated backdoors
+
+Backdoors are a generic concern in AI that is outside the scope of EZKL. However, EZKL may
+activate a specific subset of backdoors. Several academic papers have demonstrated the
+possibility, both in theory and in practice, of implanting undetectable and inactive backdoors in a full precision model that can be reactivated by quantization.
+
+An external attacker may trick the user of an application running EZKL into loading a model
+containing a quantization backdoor. This backdoor is active in the resulting model and circuit but not in the full-precision model supplied to EZKL, compromising the integrity of the target application and the resulting proof.
+
+### When is this a concern for me as a user?
+
+Any untrusted component in your AI stack may be a backdoor vector. In practice, the most
+sensitive parts include:
+
+- Datasets downloaded from the web or containing crowdsourced data
+- Models downloaded from the web even after finetuning
+- Untrusted software dependencies (well-known frameworks such as PyTorch can typically
+be considered trusted)
+- Any component loaded through an unsafe serialization format, such as Pickle.
+Because backdoors are inherent to ML and cannot be eliminated, reviewing the provenance of
+these sensitive components is especially important.
+
+### Responsibilities of the user and EZKL
+
+As EZKL cannot prevent backdoored models from being used, it is the responsibility of the user to review the provenance of all the components in their AI stack to ensure that no backdoor could have been implanted. EZKL shall not be held responsible for misleading prediction proofs resulting from using a backdoored model or for any harm caused to a system or its users due to a misbehaving model.
+
+### Limitations:
+
+- Attack effectiveness depends on calibration settings and internal rescaling operations.
 - Further research needed on backdoor persistence through witness/proof stages.
- Can be mitigated by evaluating the quantized model (using `ezkl gen-witness`), rather than relying on the evaluation of the original model. 
+- Can be mitigated by evaluating the quantized model (using `ezkl gen-witness`), rather than relying on the evaluation of the original model in pytorch or onnx-runtime as difference in evaluation could reveal a backdoor.

 References:

--- a/docs/python/src/conf.py
+++ b/docs/python/src/conf.py
@@ -1,7 +1,7 @@
 import ezkl

 project = 'ezkl'
-release = '20.0.2'
+release = '0.0.0'
 version = release


--- a/examples/conv2d_mnist/main.rs
+++ b/examples/conv2d_mnist/main.rs
@@ -32,6 +32,7 @@ use mnist::*;
 use rand::rngs::OsRng;
 use std::marker::PhantomData;

+
 mod params;

 const K: usize = 20;
@@ -208,6 +209,8 @@ where
                        padding: vec![(PADDING, PADDING); 2],
                        stride: vec![STRIDE; 2],
                        group: 1,
+                        data_format: DataFormat::NCHW,
+                        kernel_format: KernelFormat::OIHW,
                    };
                    let x = config
                        .layer_config
--- a/examples/notebooks/cat_and_dog.ipynb
+++ b/examples/notebooks/cat_and_dog.ipynb
@@ -373,15 +373,19 @@
            "outputs": [],
            "source": [
                "# Set image size.\n",
-                "IMAGE_WIDTH = 112\n",
-                "IMAGE_HEIGHT = 112\n",
+                "IMAGE_WIDTH = 64\n",
+                "IMAGE_HEIGHT = 64\n",
                "IMAGE_SIZE=(IMAGE_WIDTH, IMAGE_HEIGHT)\n",
                "\n",
                "# Create training transform with TrivialAugment\n",
                "train_transform = transforms.Compose([\n",
                "    transforms.Resize(IMAGE_SIZE),\n",
                "    transforms.TrivialAugmentWide(),\n",
-                "    transforms.ToTensor()])\n",
+                "     transforms.RandomHorizontalFlip(),\n",
+                "    transforms.RandomRotation(10),\n",
+                "    transforms.ColorJitter(brightness=0.2, contrast=0.2),\n",
+                "    transforms.ToTensor(),\n",
+                "    ])\n",
                "\n",
                "# Create testing transform (no data augmentation)\n",
                "test_transform = transforms.Compose([\n",
@@ -424,7 +428,7 @@
        },
        {
            "cell_type": "code",
-            "execution_count": 26,
+            "execution_count": 74,
            "metadata": {},
            "outputs": [],
            "source": [
@@ -434,25 +438,55 @@
                "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
                "device\n",
                "\n",
-                "# # Creating a CNN-based image classifier.\n",
+                "#  Improved CNN-based image classifier\n",
                "class ImageClassifier(nn.Module):\n",
                "    def __init__(self):\n",
                "        super().__init__()\n",
+                "        \n",
+                "        # First convolutional block with batch normalization and LeakyReLU\n",
                "        self.conv_layer_1 = nn.Sequential(\n",
-                "          nn.Conv2d(3, 4, 3, padding=1),\n",
-                "          nn.ReLU(),\n",
-                "          nn.MaxPool2d(2))\n",
+                "            nn.Conv2d(3, 6, 3, padding=1),  # Moderate increase from 4 to 6\n",
+                "            nn.BatchNorm2d(6),\n",
+                "            nn.LeakyReLU(0.1),\n",
+                "            nn.MaxPool2d(2)\n",
+                "        )\n",
+                "        \n",
+                "        # Second convolutional block with batch normalization and LeakyReLU\n",
                "        self.conv_layer_2 = nn.Sequential(\n",
-                "          nn.Conv2d(4, 4, 3, padding=1),\n",
-                "          nn.ReLU(),\n",
-                "          nn.MaxPool2d(2))\n",
+                "            nn.Conv2d(6, 8, 3, padding=1),  # Moderate increase from 4 to 8\n",
+                "            nn.BatchNorm2d(8),\n",
+                "            nn.LeakyReLU(0.1),\n",
+                "            nn.MaxPool2d(2)\n",
+                "        )\n",
+                "        \n",
+                "        # For a 64x64 input, after 2 MaxPool2d(2) layers, the spatial dimensions are 16x16\n",
+                "        # With 8 channels, the flattened size is 16*16*8 = 2048\n",
+                "        \n",
+                "        # Classifier with dropout\n",
                "        self.classifier = nn.Sequential(\n",
-                "          nn.Flatten(),\n",
-                "          nn.Linear(in_features=3136, out_features=2))\n",
-                "    def forward(self, x: torch.Tensor):\n",
+                "            nn.Flatten(),\n",
+                "            nn.Dropout(0.25),  # Add dropout for regularization\n",
+                "            nn.Linear(in_features=16*16*8, out_features=2)\n",
+                "        )\n",
+                "        \n",
+                "        # For residual connection\n",
+                "        self.downsample = nn.Sequential(\n",
+                "            nn.Conv2d(3, 8, 1, stride=4),  # Match spatial dimensions (64x64 -> 16x16)\n",
+                "            nn.BatchNorm2d(8)\n",
+                "        )\n",
+                "        \n",
+                "    def forward(self, x):\n",
+                "        # Save input for residual connection\n",
+                "        identity = self.downsample(x)\n",
+                "        \n",
                "        x = self.conv_layer_1(x)\n",
                "        x = self.conv_layer_2(x)\n",
+                "        \n",
+                "        # Add residual connection\n",
+                "        x = x + identity\n",
+                "        \n",
                "        x = self.classifier(x)\n",
+                "        \n",
                "        return x\n",
                "# Instantiate an object.\n",
                "model = ImageClassifier().to(device)\n"
@@ -526,7 +560,7 @@
        },
        {
            "cell_type": "code",
-            "execution_count": 29,
+            "execution_count": 77,
            "metadata": {},
            "outputs": [],
            "source": [
@@ -662,15 +696,17 @@
                "torch.manual_seed(42) \n",
                "torch.cuda.manual_seed(42)\n",
                "\n",
-                "# Set number of epochs\n",
+                "# Set number of epochs (change to 1000 for better results)\n",
                "NUM_EPOCHS = 25\n",
+                "# NUM_EPOCHS = 1000\n",
+                "\n",
                "\n",
                "# Setup loss function and optimizer\n",
                "loss_fn = nn.CrossEntropyLoss()\n",
                "optimizer = torch.optim.Adam(params=model.parameters(), lr=1e-3)\n",
                "\n",
                "# Start the timer\n",
-                "from timeit import default_timer as timer \n",
+                "from timeit import default_timer as timer\n",
                "start_time = timer()\n",
                "\n",
                "# Train model_0\n",
@@ -695,7 +731,7 @@
        },
        {
            "cell_type": "code",
-            "execution_count": 78,
+            "execution_count": 94,
            "metadata": {},
            "outputs": [],
            "source": [
@@ -830,7 +866,7 @@
        },
        {
            "cell_type": "code",
-            "execution_count": 86,
+            "execution_count": 98,
            "metadata": {},
            "outputs": [],
            "source": [
@@ -1016,7 +1052,6 @@
            "source": [
                "import os\n",
                "\n",
-                "\n",
                "res = await ezkl.create_evm_verifier()\n",
                "\n",
                "assert res == True"
@@ -1102,7 +1137,7 @@
            "name": "python",
            "nbconvert_exporter": "python",
            "pygments_lexer": "ipython3",
-            "version": "3.12.7"
+            "version": "3.12.9"
        }
    },
    "nbformat": 4,
--- a/examples/onnx/1d_conv/input.json
+++ b/examples/onnx/1d_conv/input.json
@@ -0,0 +1,106 @@
+{
+  "input_data": [
+    [
+      8761,
+      7654,
+      8501,
+      2404,
+      6929,
+      8858,
+      5946,
+      3673,
+      4131,
+      3854,
+      8137,
+      8239,
+      9038,
+      6299,
+      1118,
+      9737,
+      208,
+      7954,
+      3691,
+      610,
+      3468,
+      3314,
+      8658,
+      8366,
+      2850,
+      477,
+      6114,
+      232,
+      4601,
+      7420,
+      5713,
+      2936,
+      6061,
+      2870,
+      8421,
+      177,
+      7107,
+      7382,
+      6115,
+      5487,
+      8502,
+      2559,
+      1875,
+      129,
+      8533,
+      8201,
+      8414,
+      4775,
+      9817,
+      3127,
+      8761,
+      7654,
+      8501,
+      2404,
+      6929,
+      8858,
+      5946,
+      3673,
+      4131,
+      3854,
+      8137,
+      8239,
+      9038,
+      6299,
+      1118,
+      9737,
+      208,
+      7954,
+      3691,
+      610,
+      3468,
+      3314,
+      8658,
+      8366,
+      2850,
+      477,
+      6114,
+      232,
+      4601,
+      7420,
+      5713,
+      2936,
+      6061,
+      2870,
+      8421,
+      177,
+      7107,
+      7382,
+      6115,
+      5487,
+      8502,
+      2559,
+      1875,
+      129,
+      8533,
+      8201,
+      8414,
+      4775,
+      9817,
+      3127
+    ]
+  ]
+}
--- a/examples/onnx/1d_conv/network.onnx
+++ b/examples/onnx/1d_conv/network.onnx
--- a/examples/onnx/1l_div/settings.json
+++ b/examples/onnx/1l_div/settings.json
@@ -0,0 +1 @@
+{"run_args":{"input_scale":7,"param_scale":7,"scale_rebase_multiplier":1,"lookup_range":[-32768,32768],"logrows":17,"num_inner_cols":2,"variables":[["batch_size",1]],"input_visibility":"Private","output_visibility":"Public","param_visibility":"Private","rebase_frac_zero_constants":false,"check_mode":"UNSAFE","commitment":"KZG","decomp_base":16384,"decomp_legs":2,"bounded_log_lookup":false,"ignore_range_check_inputs_outputs":false},"num_rows":54,"total_assignments":109,"total_const_size":4,"total_dynamic_col_size":0,"max_dynamic_input_len":0,"num_dynamic_lookups":0,"num_shuffles":0,"total_shuffle_col_size":0,"model_instance_shapes":[[1,1]],"model_output_scales":[7],"model_input_scales":[7],"module_sizes":{"polycommit":[],"poseidon":[0,[0]]},"required_lookups":[],"required_range_checks":[[-1,1],[0,16383]],"check_mode":"UNSAFE","version":"0.0.0","num_blinding_factors":null,"timestamp":1739396322131,"input_types":["F32"],"output_types":["F32"]}
--- a/examples/onnx/hierarchical_risk/input.json
+++ b/examples/onnx/hierarchical_risk/input.json
--- a/examples/onnx/hierarchical_risk/network.onnx
+++ b/examples/onnx/hierarchical_risk/network.onnx
--- a/2
+++ b/2
@@ -1,3 +1,3 @@
 [toolchain]
-channel = "nightly-2024-07-18"
+channel = "nightly-2025-02-17"
 components = ["rustfmt", "clippy"]
--- a/src/bin/ezkl.rs
+++ b/src/bin/ezkl.rs
@@ -28,6 +28,8 @@ use std::env;
 #[tokio::main(flavor = "current_thread")]
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 pub async fn main() {
+    use log::debug;
+
    let args = Cli::parse();

    if let Some(generator) = args.generator {
@@ -42,7 +44,7 @@ pub async fn main() {
        } else {
            info!("Running with CPU");
        }
-        info!(
+        debug!(
            "command: \n {}",
            &command.as_json().to_colored_json_auto().unwrap()
        );
--- a/src/bindings/python.rs
+++ b/src/bindings/python.rs
@@ -4,8 +4,8 @@ use crate::circuit::modules::poseidon::{
    PoseidonChip,
 };
 use crate::circuit::modules::Module;
+use crate::circuit::CheckMode;
 use crate::circuit::InputType;
-use crate::circuit::{CheckMode, Tolerance};
 use crate::commands::*;
 use crate::fieldutils::{felt_to_integer_rep, integer_rep_to_felt, IntegerRep};
 use crate::graph::TestDataSource;
@@ -155,9 +155,6 @@ impl pyo3::ToPyObject for PyG1Affine {
 #[derive(Clone)]
 #[gen_stub_pyclass]
 struct PyRunArgs {
-    #[pyo3(get, set)]
-    /// float: The tolerance for error on model outputs
-    pub tolerance: f32,
    #[pyo3(get, set)]
    /// int: The denominator in the fixed point representation used when quantizing inputs
    pub input_scale: crate::Scale,
@@ -225,7 +222,6 @@ impl From<PyRunArgs> for RunArgs {
    fn from(py_run_args: PyRunArgs) -> Self {
        RunArgs {
            bounded_log_lookup: py_run_args.bounded_log_lookup,
-            tolerance: Tolerance::from(py_run_args.tolerance),
            input_scale: py_run_args.input_scale,
            param_scale: py_run_args.param_scale,
            num_inner_cols: py_run_args.num_inner_cols,
@@ -250,7 +246,6 @@ impl Into<PyRunArgs> for RunArgs {
    fn into(self) -> PyRunArgs {
        PyRunArgs {
            bounded_log_lookup: self.bounded_log_lookup,
-            tolerance: self.tolerance.val,
            input_scale: self.input_scale,
            param_scale: self.param_scale,
            num_inner_cols: self.num_inner_cols,
@@ -597,7 +592,7 @@ fn poseidon_hash(message: Vec<PyFelt>) -> PyResult<Vec<PyFelt>> {
 /// Arguments
 /// -------
 /// message: list[str]
-///     List of field elements represnted as strings
+///     List of field elements represented as strings
 ///
 /// vk_path: str
 ///     Path to the verification key
@@ -656,7 +651,7 @@ fn kzg_commit(
 /// Arguments
 /// -------
 /// message: list[str]
-///     List of field elements represnted as strings
+///     List of field elements represented as strings
 ///
 /// vk_path: str
 ///     Path to the verification key
@@ -1014,7 +1009,7 @@ fn gen_random_data(
 /// bool
 ///
 #[pyfunction(signature = (
-    data = PathBuf::from(DEFAULT_CALIBRATION_FILE),
+    data = String::from(DEFAULT_CALIBRATION_FILE),
    model = PathBuf::from(DEFAULT_MODEL),
    settings = PathBuf::from(DEFAULT_SETTINGS),
    target = CalibrationTarget::default(), // default is "resources
@@ -1026,7 +1021,7 @@ fn gen_random_data(
 #[gen_stub_pyfunction]
 fn calibrate_settings(
    py: Python,
-    data: PathBuf,
+    data: String,
    model: PathBuf,
    settings: PathBuf,
    target: CalibrationTarget,
@@ -1081,7 +1076,7 @@ fn calibrate_settings(
 ///     Python object containing the witness values
 ///
 #[pyfunction(signature = (
-    data=PathBuf::from(DEFAULT_DATA),
+    data=String::from(DEFAULT_DATA),
    model=PathBuf::from(DEFAULT_COMPILED_CIRCUIT),
    output=PathBuf::from(DEFAULT_WITNESS),
    vk_path=None,
@@ -1090,7 +1085,7 @@ fn calibrate_settings(
 #[gen_stub_pyfunction]
 fn gen_witness(
    py: Python,
-    data: PathBuf,
+    data: String,
    model: PathBuf,
    output: Option<PathBuf>,
    vk_path: Option<PathBuf>,
@@ -1759,7 +1754,7 @@ fn create_evm_vka(
 /// bool
 ///
 #[pyfunction(signature = (
-    input_data=PathBuf::from(DEFAULT_DATA),
+    input_data=String::from(DEFAULT_DATA),
    settings_path=PathBuf::from(DEFAULT_SETTINGS),
    sol_code_path=PathBuf::from(DEFAULT_SOL_CODE_DA),
    abi_path=PathBuf::from(DEFAULT_VERIFIER_DA_ABI),
@@ -1768,7 +1763,7 @@ fn create_evm_vka(
 #[gen_stub_pyfunction]
 fn create_evm_data_attestation(
    py: Python,
-    input_data: PathBuf,
+    input_data: String,
    settings_path: PathBuf,
    sol_code_path: PathBuf,
    abi_path: PathBuf,
@@ -1829,7 +1824,7 @@ fn create_evm_data_attestation(
 #[gen_stub_pyfunction]
 fn setup_test_evm_witness(
    py: Python,
-    data_path: PathBuf,
+    data_path: String,
    compiled_circuit_path: PathBuf,
    test_data: PathBuf,
    input_source: PyTestDataSource,
@@ -1907,7 +1902,7 @@ fn deploy_evm(
 fn deploy_da_evm(
    py: Python,
    addr_path: PathBuf,
-    input_data: PathBuf,
+    input_data: String,
    settings_path: PathBuf,
    sol_code_path: PathBuf,
    rpc_url: Option<String>,
@@ -1950,7 +1945,7 @@ fn deploy_da_evm(
 ///     does the verifier use data attestation ?
 ///
 /// addr_vk: str
-///     The addess of the separate VK contract (if the verifier key is rendered as a separate contract)
+///     The address of the separate VK contract (if the verifier key is rendered as a separate contract)
 /// Returns
 /// -------
 /// bool
--- a/src/circuit/ops/base.rs
+++ b/src/circuit/ops/base.rs
@@ -21,7 +21,10 @@ pub enum BaseOp {

 /// Matches a [BaseOp] to an operation over inputs
 impl BaseOp {
-    /// forward func
+    /// forward func for non-accumulating operations
+    /// # Panics
+    /// Panics if called on an accumulating operation
+    /// # Examples
    pub fn nonaccum_f<
        T: TensorType + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Neg<Output = T>,
    >(
@@ -37,7 +40,9 @@ impl BaseOp {
        }
    }

-    /// forward func
+    /// forward func for accumulating operations
+    /// # Panics
+    /// Panics if called on a non-accumulating operation
    pub fn accum_f<
        T: TensorType + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Neg<Output = T>,
    >(
--- a/src/circuit/ops/chip.rs
+++ b/src/circuit/ops/chip.rs
@@ -20,7 +20,6 @@ use crate::{
    circuit::{
        ops::base::BaseOp,
        table::{Range, RangeCheck, Table},
-        utils,
    },
    tensor::{Tensor, TensorType, ValTensor, VarTensor},
 };
@@ -85,55 +84,6 @@ impl CheckMode {
    }
 }

-#[allow(missing_docs)]
-/// An enum representing the tolerance we can accept for the accumulated arguments, either absolute or percentage
-#[derive(Clone, Default, Debug, PartialEq, PartialOrd, Serialize, Deserialize, Copy)]
-pub struct Tolerance {
-    pub val: f32,
-    pub scale: utils::F32,
-}
-
-impl std::fmt::Display for Tolerance {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        write!(f, "{:.2}", self.val)
-    }
-}
-
-#[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
-impl ToFlags for Tolerance {
-    /// Convert the struct to a subcommand string
-    fn to_flags(&self) -> Vec<String> {
-        vec![format!("{}", self)]
-    }
-}
-
-impl FromStr for Tolerance {
-    type Err = String;
-
-    fn from_str(s: &str) -> Result<Self, Self::Err> {
-        if let Ok(val) = s.parse::<f32>() {
-            Ok(Tolerance {
-                val,
-                scale: utils::F32(1.0),
-            })
-        } else {
-            Err(
-                "Invalid tolerance value provided. It should expressed as a percentage (f32)."
-                    .to_string(),
-            )
-        }
-    }
-}
-
-impl From<f32> for Tolerance {
-    fn from(value: f32) -> Self {
-        Tolerance {
-            val: value,
-            scale: utils::F32(1.0),
-        }
-    }
-}
-
 #[cfg(feature = "python-bindings")]
 /// Converts CheckMode into a PyObject (Required for CheckMode to be compatible with Python)
 impl IntoPy<PyObject> for CheckMode {
@@ -158,29 +108,6 @@ impl<'source> FromPyObject<'source> for CheckMode {
    }
 }

-#[cfg(feature = "python-bindings")]
-/// Converts Tolerance into a PyObject (Required for Tolerance to be compatible with Python)
-impl IntoPy<PyObject> for Tolerance {
-    fn into_py(self, py: Python) -> PyObject {
-        (self.val, self.scale.0).to_object(py)
-    }
-}
-
-#[cfg(feature = "python-bindings")]
-/// Obtains Tolerance from PyObject (Required for Tolerance to be compatible with Python)
-impl<'source> FromPyObject<'source> for Tolerance {
-    fn extract_bound(ob: &pyo3::Bound<'source, pyo3::PyAny>) -> PyResult<Self> {
-        if let Ok((val, scale)) = <(f32, f32)>::extract_bound(ob) {
-            Ok(Tolerance {
-                val,
-                scale: utils::F32(scale),
-            })
-        } else {
-            Err(PyValueError::new_err("Invalid tolerance value provided. "))
-        }
-    }
-}
-
 /// A struct representing the selectors for the dynamic lookup tables
 #[derive(Clone, Debug, Default)]
 pub struct DynamicLookups {
--- a/src/circuit/ops/hybrid.rs
+++ b/src/circuit/ops/hybrid.rs
@@ -1,9 +1,9 @@
 use super::*;
 use crate::{
-    circuit::{layouts, utils, Tolerance},
+    circuit::{layouts, utils},
    fieldutils::{integer_rep_to_felt, IntegerRep},
    graph::multiplier_to_scale,
-    tensor::{self, Tensor, TensorType, ValTensor},
+    tensor::{self, DataFormat, Tensor, TensorType, ValTensor},
 };
 use halo2curves::ff::PrimeField;
 use serde::{Deserialize, Serialize};
@@ -57,11 +57,13 @@ pub enum HybridOp {
        stride: Vec<usize>,
        kernel_shape: Vec<usize>,
        normalized: bool,
+        data_format: DataFormat,
    },
    MaxPool {
        padding: Vec<(usize, usize)>,
        stride: Vec<usize>,
        pool_dims: Vec<usize>,
+        data_format: DataFormat,
    },
    ReduceMin {
        axes: Vec<usize>,
@@ -77,7 +79,6 @@ pub enum HybridOp {
        axes: Vec<usize>,
    },
    Output {
-        tol: Tolerance,
        decomp: bool,
    },
    Greater,
@@ -154,10 +155,10 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Hybrid
                padding,
                stride,
                kernel_shape,
-                normalized,
+                normalized, data_format
            } => format!(
-                "SUMPOOL (padding={:?}, stride={:?}, kernel_shape={:?}, normalized={})",
-                padding, stride, kernel_shape, normalized
+                "SUMPOOL (padding={:?}, stride={:?}, kernel_shape={:?}, normalized={}, data_format={:?})",
+                padding, stride, kernel_shape, normalized, data_format
            ),
            HybridOp::ReduceMax { axes } => format!("REDUCEMAX (axes={:?})", axes),
            HybridOp::ReduceArgMax { dim } => format!("REDUCEARGMAX (dim={})", dim),
@@ -165,9 +166,10 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Hybrid
                padding,
                stride,
                pool_dims,
+                data_format,
            } => format!(
-                "MaxPool (padding={:?}, stride={:?}, pool_dims={:?})",
-                padding, stride, pool_dims
+                "MaxPool (padding={:?}, stride={:?}, pool_dims={:?}, data_format={:?})",
+                padding, stride, pool_dims, data_format
            ),
            HybridOp::ReduceMin { axes } => format!("REDUCEMIN (axes={:?})", axes),
            HybridOp::ReduceArgMin { dim } => format!("REDUCEARGMIN (dim={})", dim),
@@ -181,8 +183,8 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Hybrid
                    input_scale, output_scale, axes
                )
            }
-            HybridOp::Output { tol, decomp } => {
-                format!("OUTPUT (tol={:?}, decomp={})", tol, decomp)
+            HybridOp::Output { decomp } => {
+                format!("OUTPUT (decomp={})", decomp)
            }
            HybridOp::Greater => "GREATER".to_string(),
            HybridOp::GreaterEqual => "GREATEREQUAL".to_string(),
@@ -239,6 +241,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Hybrid
                stride,
                kernel_shape,
                normalized,
+                data_format,
            } => layouts::sumpool(
                config,
                region,
@@ -247,6 +250,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Hybrid
                stride,
                kernel_shape,
                *normalized,
+                *data_format,
            )?,
            HybridOp::Recip {
                input_scale,
@@ -287,6 +291,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Hybrid
                padding,
                stride,
                pool_dims,
+                data_format,
            } => layouts::max_pool(
                config,
                region,
@@ -294,6 +299,7 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Hybrid
                padding,
                stride,
                pool_dims,
+                *data_format,
            )?,
            HybridOp::ReduceMax { axes } => {
                layouts::max_axes(config, region, values[..].try_into()?, axes)?
@@ -319,14 +325,9 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Op<F> for Hybrid
                *output_scale,
                axes,
            )?,
-            HybridOp::Output { tol, decomp } => layouts::output(
-                config,
-                region,
-                values[..].try_into()?,
-                tol.scale,
-                tol.val,
-                *decomp,
-            )?,
+            HybridOp::Output { decomp } => {
+                layouts::output(config, region, values[..].try_into()?, *decomp)?
+            }
            HybridOp::Greater => layouts::greater(config, region, values[..].try_into()?)?,
            HybridOp::GreaterEqual => {
                layouts::greater_equal(config, region, values[..].try_into()?)?
--- a/src/circuit/ops/layouts.rs
+++ b/src/circuit/ops/layouts.rs
--- a/src/circuit/ops/mod.rs
+++ b/src/circuit/ops/mod.rs
@@ -159,6 +159,8 @@ impl std::str::FromStr for InputType {

 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 impl From<DatumType> for InputType {
+    /// # Panics
+    /// Panics if the datum type is not supported
    fn from(datum_type: DatumType) -> Self {
        match datum_type {
            DatumType::Bool => InputType::Bool,
@@ -317,13 +319,8 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> Constant<F> {
 }

 impl<
-        F: PrimeField
-            + TensorType
-            + PartialOrd
-            + std::hash::Hash
-            + Serialize
-            + for<'de> Deserialize<'de>,
-    > Op<F> for Constant<F>
+    F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Serialize + for<'de> Deserialize<'de>,
+> Op<F> for Constant<F>
 {
    fn as_any(&self) -> &dyn Any {
        self
--- a/src/circuit/ops/poly.rs
+++ b/src/circuit/ops/poly.rs
@@ -4,6 +4,7 @@ use crate::{
        utils::{self, F32},
    },
    tensor::{self, Tensor, TensorError},
+    tensor::{DataFormat, KernelFormat},
 };

 use super::{base::BaseOp, *};
@@ -43,10 +44,12 @@ pub enum PolyOp {
        padding: Vec<(usize, usize)>,
        stride: Vec<usize>,
        group: usize,
+        data_format: DataFormat,
+        kernel_format: KernelFormat,
    },
    Downsample {
        axis: usize,
-        stride: usize,
+        stride: isize,
        modulo: usize,
    },
    DeConv {
@@ -54,6 +57,8 @@ pub enum PolyOp {
        output_padding: Vec<usize>,
        stride: Vec<usize>,
        group: usize,
+        data_format: DataFormat,
+        kernel_format: KernelFormat,
    },
    Add,
    Sub,
@@ -103,13 +108,8 @@ pub enum PolyOp {
 }

 impl<
-        F: PrimeField
-            + TensorType
-            + PartialOrd
-            + std::hash::Hash
-            + Serialize
-            + for<'de> Deserialize<'de>,
-    > Op<F> for PolyOp
+    F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Serialize + for<'de> Deserialize<'de>,
+> Op<F> for PolyOp
 {
    /// Returns a reference to the Any trait.
    fn as_any(&self) -> &dyn Any {
@@ -165,10 +165,12 @@ impl<
                stride,
                padding,
                group,
+                data_format,
+                kernel_format,
            } => {
                format!(
-                    "CONV (stride={:?}, padding={:?}, group={})",
-                    stride, padding, group
+                    "CONV (stride={:?}, padding={:?}, group={}, data_format={:?}, kernel_format={:?})",
+                    stride, padding, group, data_format, kernel_format
                )
            }
            PolyOp::DeConv {
@@ -176,10 +178,12 @@ impl<
                padding,
                output_padding,
                group,
+                data_format,
+                kernel_format,
            } => {
                format!(
-                    "DECONV (stride={:?}, padding={:?}, output_padding={:?}, group={})",
-                    stride, padding, output_padding, group
+                    "DECONV (stride={:?}, padding={:?}, output_padding={:?}, group={}, data_format={:?}, kernel_format={:?})",
+                    stride, padding, output_padding, group, data_format, kernel_format
                )
            }
            PolyOp::Concat { axis } => format!("CONCAT (axis={})", axis),
@@ -242,6 +246,8 @@ impl<
                padding,
                stride,
                group,
+                data_format,
+                kernel_format,
            } => layouts::conv(
                config,
                region,
@@ -249,6 +255,8 @@ impl<
                padding,
                stride,
                *group,
+                *data_format,
+                *kernel_format,
            )?,
            PolyOp::GatherElements { dim, constant_idx } => {
                if let Some(idx) = constant_idx {
@@ -309,6 +317,8 @@ impl<
                output_padding,
                stride,
                group,
+                data_format,
+                kernel_format,
            } => layouts::deconv(
                config,
                region,
@@ -317,6 +327,8 @@ impl<
                output_padding,
                stride,
                *group,
+                *data_format,
+                *kernel_format,
            )?,
            PolyOp::Add => layouts::pairwise(config, region, values[..].try_into()?, BaseOp::Add)?,
            PolyOp::Sub => layouts::pairwise(config, region, values[..].try_into()?, BaseOp::Sub)?,
--- a/src/circuit/tests.rs
+++ b/src/circuit/tests.rs
@@ -1,5 +1,6 @@
 use crate::circuit::ops::poly::PolyOp;
 use crate::circuit::*;
+use crate::tensor::{DataFormat, KernelFormat};
 use crate::tensor::{Tensor, TensorType, ValTensor, VarTensor};
 use halo2_proofs::{
    circuit::{Layouter, SimpleFloorPlanner, Value},
@@ -1065,6 +1066,8 @@ mod conv {
                                    padding: vec![(1, 1); 2],
                                    stride: vec![2; 2],
                                    group: 1,
+                                    data_format: DataFormat::default(),
+                                    kernel_format: KernelFormat::default(),
                                }),
                            )
                            .map_err(|_| Error::Synthesis)
@@ -1220,6 +1223,8 @@ mod conv_col_ultra_overflow {
                                    padding: vec![(1, 1); 2],
                                    stride: vec![2; 2],
                                    group: 1,
+                                    data_format: DataFormat::default(),
+                                    kernel_format: KernelFormat::default(),
                                }),
                            )
                            .map_err(|_| Error::Synthesis)
@@ -1377,6 +1382,8 @@ mod conv_relu_col_ultra_overflow {
                                    padding: vec![(1, 1); 2],
                                    stride: vec![2; 2],
                                    group: 1,
+                                    data_format: DataFormat::default(),
+                                    kernel_format: KernelFormat::default(),
                                }),
                            )
                            .map_err(|_| Error::Synthesis);
--- a/src/commands.rs
+++ b/src/commands.rs
@@ -1,6 +1,6 @@
 use alloy::primitives::Address as H160;
 use clap::{Command, Parser, Subcommand};
-use clap_complete::{generate, Generator, Shell};
+use clap_complete::{Generator, Shell, generate};
 #[cfg(feature = "python-bindings")]
 use pyo3::{conversion::FromPyObject, exceptions::PyValueError, prelude::*};
 use serde::{Deserialize, Serialize};
@@ -8,7 +8,7 @@ use std::path::PathBuf;
 use std::str::FromStr;
 use tosubcommand::{ToFlags, ToSubcommand};

-use crate::{pfsys::ProofType, Commitments, RunArgs};
+use crate::{Commitments, RunArgs, pfsys::ProofType};

 use crate::circuit::CheckMode;
 use crate::graph::TestDataSource;
@@ -360,8 +360,13 @@ pub fn get_styles() -> clap::builder::Styles {
 }

 /// Print completions for the given generator
-pub fn print_completions<G: Generator>(gen: G, cmd: &mut Command) {
-    generate(gen, cmd, cmd.get_name().to_string(), &mut std::io::stdout());
+pub fn print_completions<G: Generator>(r#gen: G, cmd: &mut Command) {
+    generate(
+        r#gen,
+        cmd,
+        cmd.get_name().to_string(),
+        &mut std::io::stdout(),
+    );
 }

 #[allow(missing_docs)]
@@ -396,8 +401,9 @@ pub enum Commands {
    /// Generates the witness from an input file.
    GenWitness {
        /// The path to the .json data file
+        /// You can also pass the input data as a string, eg. --data '{"input_data": [1.0,2.0,3.0]}' directly and skip the file
        #[arg(short = 'D', long, default_value = DEFAULT_DATA, value_hint = clap::ValueHint::FilePath)]
-        data: Option<PathBuf>,
+        data: Option<String>,
        /// The path to the compiled model file (generated using the compile-circuit command)
        #[arg(short = 'M', long, default_value = DEFAULT_COMPILED_CIRCUIT, value_hint = clap::ValueHint::FilePath)]
        compiled_circuit: Option<PathBuf>,
@@ -429,7 +435,7 @@ pub enum Commands {
        /// The path to the .onnx model file
        #[arg(short = 'M', long, default_value = DEFAULT_MODEL, value_hint = clap::ValueHint::FilePath)]
        model: Option<PathBuf>,
-        /// The path to the .json data file
+        /// The path to the .json data file to output
        #[arg(short = 'D', long, default_value = DEFAULT_DATA, value_hint = clap::ValueHint::FilePath)]
        data: Option<PathBuf>,
        /// Hand-written parser for graph variables, eg. batch_size=1
@@ -442,8 +448,9 @@ pub enum Commands {
    /// Calibrates the proving scale, lookup bits and logrows from a circuit settings file.
    CalibrateSettings {
        /// The path to the .json calibration data file.
+        /// You can also pass the input data as a string, eg. --data '{"input_data": [1.0,2.0,3.0]}' directly and skip the file
        #[arg(short = 'D', long, default_value = DEFAULT_CALIBRATION_FILE, value_hint = clap::ValueHint::FilePath)]
-        data: Option<PathBuf>,
+        data: Option<String>,
        /// The path to the .onnx model file
        #[arg(short = 'M', long, default_value = DEFAULT_MODEL, value_hint = clap::ValueHint::FilePath)]
        model: Option<PathBuf>,
@@ -626,8 +633,9 @@ pub enum Commands {
    #[command(arg_required_else_help = true)]
    SetupTestEvmData {
        /// The path to the .json data file, which should include both the network input (possibly private) and the network output (public input to the proof)
+        /// You can also pass the input data as a string, eg. --data '{"input_data": [1.0,2.0,3.0]}' directly and skip the file
        #[arg(short = 'D', long, value_hint = clap::ValueHint::FilePath)]
-        data: Option<PathBuf>,
+        data: Option<String>,
        /// The path to the compiled model file (generated using the compile-circuit command)
        #[arg(short = 'M', long, value_hint = clap::ValueHint::FilePath)]
        compiled_circuit: Option<PathBuf>,
@@ -653,8 +661,9 @@ pub enum Commands {
        #[arg(long, value_hint = clap::ValueHint::Other)]
        addr: H160Flag,
        /// The path to the .json data file.
+        /// You can also pass the input data as a string, eg. --data '{"input_data": [1.0,2.0,3.0]}' directly and skip the file
        #[arg(short = 'D', long, value_hint = clap::ValueHint::FilePath)]
-        data: Option<PathBuf>,
+        data: Option<String>,
        /// RPC URL for an Ethereum node, if None will use Anvil but WON'T persist state
        #[arg(short = 'U', long, value_hint = clap::ValueHint::Url)]
        rpc_url: Option<String>,
@@ -771,7 +780,7 @@ pub enum Commands {
        /// view functions that return the data that the network
        /// ingests as inputs.
        #[arg(short = 'D', long, default_value = DEFAULT_DATA, value_hint = clap::ValueHint::FilePath)]
-        data: Option<PathBuf>,
+        data: Option<String>,
        /// The path to the witness file. This is needed for proof swapping for kzg commitments.
        #[arg(short = 'W', long, default_value = DEFAULT_WITNESS, value_hint = clap::ValueHint::FilePath)]
        witness: Option<PathBuf>,
@@ -866,8 +875,9 @@ pub enum Commands {
    #[command(name = "deploy-evm-da")]
    DeployEvmDataAttestation {
        /// The path to the .json data file, which should include both the network input (possibly private) and the network output (public input to the proof)
+        /// You can also pass the input data as a string, eg. --data '{"input_data": [1.0,2.0,3.0]}' directly and skip the file
        #[arg(short = 'D', long, default_value = DEFAULT_DATA, value_hint = clap::ValueHint::FilePath)]
-        data: Option<PathBuf>,
+        data: Option<String>,
        /// The path to load circuit settings .json file from (generated using the gen-settings command)
        #[arg(long, default_value = DEFAULT_SETTINGS, value_hint = clap::ValueHint::FilePath)]
        settings_path: Option<PathBuf>,
--- a/src/eth.rs
+++ b/src/eth.rs
@@ -383,7 +383,7 @@ pub async fn deploy_contract_via_solidity(
 ///
 pub async fn deploy_da_verifier_via_solidity(
    settings_path: PathBuf,
-    input: PathBuf,
+    input: String,
    sol_code_path: PathBuf,
    rpc_url: Option<&str>,
    runs: usize,
@@ -391,7 +391,7 @@ pub async fn deploy_da_verifier_via_solidity(
 ) -> Result<H160, EthError> {
    let (client, client_address) = setup_eth_backend(rpc_url, private_key).await?;

-    let input = GraphData::from_path(input).map_err(|_| EthError::GraphData)?;
+    let input = GraphData::from_str(&input).map_err(|_| EthError::GraphData)?;

    let settings = GraphSettings::load(&settings_path).map_err(|_| EthError::GraphSettings)?;

@@ -688,10 +688,10 @@ fn parse_call_to_account(call_to_account: CallToAccount) -> Result<ParsedCallToA

 pub async fn update_account_calls(
    addr: H160,
-    input: PathBuf,
+    input: String,
    rpc_url: Option<&str>,
 ) -> Result<(), EthError> {
-    let input = GraphData::from_path(input).map_err(|_| EthError::GraphData)?;
+    let input = GraphData::from_str(&input).map_err(|_| EthError::GraphData)?;

    // The data that will be stored in the test contracts that will eventually be read from.
    let mut calls_to_accounts = vec![];
--- a/src/execute.rs
+++ b/src/execute.rs
@@ -1,5 +1,6 @@
-use crate::circuit::region::RegionSettings;
+use crate::EZKL_BUF_CAPACITY;
 use crate::circuit::CheckMode;
+use crate::circuit::region::RegionSettings;
 use crate::commands::CalibrationTarget;
 use crate::eth::{
    deploy_contract_via_solidity, deploy_da_verifier_via_solidity, fix_da_multi_sol,
@@ -12,21 +13,21 @@ use crate::graph::{GraphCircuit, GraphSettings, GraphWitness, Model};
 use crate::graph::{TestDataSource, TestSources};
 use crate::pfsys::evm::aggregation_kzg::{AggregationCircuit, PoseidonTranscript};
 use crate::pfsys::{
-    create_keys, load_pk, load_vk, save_params, save_pk, Snark, StrategyType, TranscriptType,
+    ProofSplitCommit, create_proof_circuit, swap_proof_commitments_polycommit, verify_proof_circuit,
 };
 use crate::pfsys::{
-    create_proof_circuit, swap_proof_commitments_polycommit, verify_proof_circuit, ProofSplitCommit,
+    Snark, StrategyType, TranscriptType, create_keys, load_pk, load_vk, save_params, save_pk,
 };
 use crate::pfsys::{save_vk, srs::*};
 use crate::tensor::TensorError;
-use crate::EZKL_BUF_CAPACITY;
-use crate::{commands::*, EZKLError};
 use crate::{Commitments, RunArgs};
+use crate::{EZKLError, commands::*};
 use colored::Colorize;
 #[cfg(unix)]
 use gag::Gag;
 use halo2_proofs::dev::VerifyFailure;
 use halo2_proofs::plonk::{self, Circuit};
+use halo2_proofs::poly::VerificationStrategy;
 use halo2_proofs::poly::commitment::{CommitmentScheme, Params};
 use halo2_proofs::poly::commitment::{ParamsProver, Verifier};
 use halo2_proofs::poly::ipa::commitment::{IPACommitmentScheme, ParamsIPA};
@@ -39,7 +40,6 @@ use halo2_proofs::poly::kzg::strategy::AccumulatorStrategy as KZGAccumulatorStra
 use halo2_proofs::poly::kzg::{
    commitment::ParamsKZG, strategy::SingleStrategy as KZGSingleStrategy,
 };
-use halo2_proofs::poly::VerificationStrategy;
 use halo2_proofs::transcript::{EncodedChallenge, TranscriptReadBuffer};
 use halo2_solidity_verifier;
 use halo2curves::bn256::{Bn256, Fr, G1Affine};
@@ -50,12 +50,12 @@ use instant::Instant;
 use itertools::Itertools;
 use log::debug;
 use log::{info, trace, warn};
-use serde::de::DeserializeOwned;
 use serde::Serialize;
+use serde::de::DeserializeOwned;
 use snark_verifier::loader::native::NativeLoader;
+use snark_verifier::system::halo2::Config;
 use snark_verifier::system::halo2::compile;
 use snark_verifier::system::halo2::transcript::evm::EvmTranscript;
-use snark_verifier::system::halo2::Config;
 use std::fs::File;
 use std::io::BufWriter;
 use std::io::{Cursor, Write};
@@ -516,7 +516,9 @@ fn update_ezkl_binary(version: &Option<String>) -> Result<String, EZKLError> {
        .status()
        .is_err()
    {
-        log::warn!("bash is not installed on this system, trying to run the install script with sh (may fail)");
+        log::warn!(
+            "bash is not installed on this system, trying to run the install script with sh (may fail)"
+        );
        "sh"
    } else {
        "bash"
@@ -725,7 +727,7 @@ pub(crate) fn table(model: PathBuf, run_args: RunArgs) -> Result<String, EZKLErr

 pub(crate) async fn gen_witness(
    compiled_circuit_path: PathBuf,
-    data: PathBuf,
+    data: String,
    output: Option<PathBuf>,
    vk_path: Option<PathBuf>,
    srs_path: Option<PathBuf>,
@@ -733,7 +735,7 @@ pub(crate) async fn gen_witness(
    // these aren't real values so the sanity checks are mostly meaningless

    let mut circuit = GraphCircuit::load(compiled_circuit_path)?;
-    let data: GraphData = GraphData::from_path(data)?;
+    let data = GraphData::from_str(&data)?;
    let settings = circuit.settings().clone();

    let vk = if let Some(vk) = vk_path {
@@ -876,7 +878,7 @@ pub(crate) fn gen_random_data(

        let mut tensor = TractTensor::zero::<f32>(sizes).unwrap();
        let slice = tensor.as_slice_mut::<f32>().unwrap();
-        slice.iter_mut().for_each(|x| *x = rng.gen());
+        slice.iter_mut().for_each(|x| *x = rng.r#gen());
        tensor.cast_to_dt(datum_type).unwrap().into_owned()
    }

@@ -1044,7 +1046,7 @@ impl AccuracyResults {
 #[allow(clippy::too_many_arguments)]
 pub(crate) async fn calibrate(
    model_path: PathBuf,
-    data: PathBuf,
+    data: String,
    settings_path: PathBuf,
    target: CalibrationTarget,
    lookup_safety_margin: f64,
@@ -1058,7 +1060,7 @@ pub(crate) async fn calibrate(

    use crate::fieldutils::IntegerRep;

-    let data = GraphData::from_path(data)?;
+    let data = GraphData::from_str(&data)?;
    // load the pre-generated settings
    let settings = GraphSettings::load(&settings_path)?;
    // now retrieve the run args
@@ -1522,7 +1524,7 @@ pub(crate) async fn create_evm_data_attestation(
    settings_path: PathBuf,
    sol_code_path: PathBuf,
    abi_path: PathBuf,
-    input: PathBuf,
+    input: String,
    witness: Option<PathBuf>,
 ) -> Result<String, EZKLError> {
    #[allow(unused_imports)]
@@ -1536,7 +1538,7 @@ pub(crate) async fn create_evm_data_attestation(

    // if input is not provided, we just instantiate dummy input data
    let data =
-        GraphData::from_path(input).unwrap_or_else(|_| GraphData::new(DataSource::File(vec![])));
+        GraphData::from_str(&input).unwrap_or_else(|_| GraphData::new(DataSource::File(vec![])));

    // The number of input and output instances we attest to for the single call data attestation
    let mut input_len = None;
@@ -1625,7 +1627,7 @@ pub(crate) async fn create_evm_data_attestation(
 }

 pub(crate) async fn deploy_da_evm(
-    data: PathBuf,
+    data: String,
    settings_path: PathBuf,
    sol_code_path: PathBuf,
    rpc_url: Option<String>,
@@ -1868,7 +1870,7 @@ pub(crate) fn setup(
 }

 pub(crate) async fn setup_test_evm_witness(
-    data_path: PathBuf,
+    data_path: String,
    compiled_circuit_path: PathBuf,
    test_data: PathBuf,
    rpc_url: Option<String>,
@@ -1877,7 +1879,7 @@ pub(crate) async fn setup_test_evm_witness(
 ) -> Result<String, EZKLError> {
    use crate::graph::TestOnChainData;

-    let mut data = GraphData::from_path(data_path)?;
+    let mut data = GraphData::from_str(&data_path)?;
    let mut circuit = GraphCircuit::load(compiled_circuit_path)?;

    // if both input and output are from files fail
@@ -1905,7 +1907,7 @@ pub(crate) async fn setup_test_evm_witness(
 use crate::pfsys::ProofType;
 pub(crate) async fn test_update_account_calls(
    addr: H160Flag,
-    data: PathBuf,
+    data: String,
    rpc_url: Option<String>,
 ) -> Result<String, EZKLError> {
    use crate::eth::update_account_calls;
--- a/src/graph/errors.rs
+++ b/src/graph/errors.rs
@@ -33,7 +33,7 @@ pub enum GraphError {
    #[error("a node is missing required params: {0}")]
    MissingParams(String),
    /// A node has missing parameters
-    #[error("a node is has misformed params: {0}")]
+    #[error("a node has misformed params: {0}")]
    MisformedParams(String),
    /// Error in the configuration of the visibility of variables
    #[error("there should be at least one set of public variables")]
--- a/src/graph/input.rs
+++ b/src/graph/input.rs
@@ -528,6 +528,27 @@ impl GraphData {
        }
    }

+    /// Loads graph input data from a string, first seeing if it is a file path or JSON data
+    /// If it is a file path, it will load the data from the file
+    /// Otherwise, it will attempt to parse the string as JSON data
+    /// 
+    /// # Arguments
+    /// * `data` - String containing the input data
+    /// # Returns
+    /// A new GraphData instance containing the loaded data
+    pub fn from_str(data: &str) -> Result<Self, GraphError> {
+        let graph_input = serde_json::from_str(data); 
+        match graph_input {
+            Ok(graph_input) => {
+                return Ok(graph_input);
+            }
+            Err(_) => {
+                let path = std::path::PathBuf::from(data);
+                GraphData::from_path(path)
+            }
+        }
+    }
+
    /// Loads graph input data from a file
    ///
    /// # Arguments
@@ -609,8 +630,12 @@ impl GraphData {
            if input.len() % input_size != 0 {
                return Err(GraphError::InvalidDims(
                    0,
-                    "calibration data length must be evenly divisible by the original input_size"
-                        .to_string(),
+                    format!(
+                        "calibration data length (={}) must be evenly divisible by the original input_size(={})",
+                        input.len(),
+                        input_size
+                    ),
+                    
                ));
            }

--- a/src/graph/model.rs
+++ b/src/graph/model.rs
@@ -1,7 +1,6 @@
 use super::errors::GraphError;
 use super::extract_const_quantized_values;
 use super::node::*;
-use super::scale_to_multiplier;
 use super::vars::*;
 use super::GraphSettings;
 use crate::circuit::hybrid::HybridOp;
@@ -1173,17 +1172,10 @@ impl Model {
                    })?;

                if run_args.output_visibility.is_public() || run_args.output_visibility.is_fixed() {
-                    let output_scales = self.graph.get_output_scales().map_err(|e| {
-                        error!("{}", e);
-                        halo2_proofs::plonk::Error::Synthesis
-                    })?;
                    let res = outputs
                        .iter()
                        .enumerate()
                        .map(|(i, output)| {
-                            let mut tol: crate::circuit::Tolerance = run_args.tolerance;
-                            tol.scale = scale_to_multiplier(output_scales[i]).into();
-
                            let comparators = if run_args.output_visibility == Visibility::Public {
                                let res = vars
                                    .instance
@@ -1206,7 +1198,6 @@ impl Model {
                                    &mut thread_safe_region,
                                    &[output.clone(), comparators],
                                    Box::new(HybridOp::Output {
-                                        tol,
                                        decomp: !run_args.ignore_range_check_inputs_outputs,
                                    }),
                                )
@@ -1468,11 +1459,9 @@ impl Model {
        let outputs = self.layout_nodes(&mut model_config, &mut region, &mut results)?;

        if self.visibility.output.is_public() || self.visibility.output.is_fixed() {
-            let output_scales = self.graph.get_output_scales()?;
            let res = outputs
                .iter()
-                .enumerate()
-                .map(|(i, output)| {
+                .map(|output| {
                    let mut comparator: ValTensor<Fp> = (0..output.len())
                        .map(|_| {
                            if !self.visibility.output.is_fixed() {
@@ -1485,14 +1474,10 @@ impl Model {
                        .into();
                    comparator.reshape(output.dims())?;

-                    let mut tol = run_args.tolerance;
-                    tol.scale = scale_to_multiplier(output_scales[i]).into();
-
                    dummy_config.layout(
                        &mut region,
                        &[output.clone(), comparator],
                        Box::new(HybridOp::Output {
-                            tol,
                            decomp: !run_args.ignore_range_check_inputs_outputs,
                        }),
                    )
--- a/src/graph/utilities.rs
+++ b/src/graph/utilities.rs
@@ -1,14 +1,14 @@
-use super::errors::GraphError;
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 use super::VarScales;
+use super::errors::GraphError;
 use super::{Rescaled, SupportedOp, Visibility};
+use crate::circuit::Op;
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 use crate::circuit::hybrid::HybridOp;
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 use crate::circuit::lookup::LookupOp;
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 use crate::circuit::poly::PolyOp;
-use crate::circuit::Op;
 use crate::fieldutils::IntegerRep;
 use crate::tensor::{Tensor, TensorError, TensorType};
 use halo2curves::bn256::Fr as Fp;
@@ -22,6 +22,7 @@ use std::sync::Arc;
 use tract_onnx::prelude::{DatumType, Node as OnnxNode, TypedFact, TypedOp};
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 use tract_onnx::tract_core::ops::{
+    Downsample,
    array::{
        Gather, GatherElements, GatherNd, MultiBroadcastTo, OneHot, ScatterElements, ScatterNd,
        Slice, Topk,
@@ -31,7 +32,6 @@ use tract_onnx::tract_core::ops::{
    einsum::EinSum,
    element_wise::ElementWiseOp,
    nn::{LeakyRelu, Reduce, Softmax},
-    Downsample,
 };
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 use tract_onnx::tract_hir::{
@@ -39,9 +39,8 @@ use tract_onnx::tract_hir::{
    ops::array::{Pad, PadMode, TypedConcat},
    ops::cnn::PoolSpec,
    ops::konst::Const,
-    ops::nn::DataFormat,
    tract_core::ops::cast::Cast,
-    tract_core::ops::cnn::{conv::KernelFormat, MaxPool, SumPool},
+    tract_core::ops::cnn::{MaxPool, SumPool},
 };

 /// Quantizes an iterable of f64 to a [Tensor] of IntegerRep using a fixed point representation.
@@ -1146,13 +1145,6 @@ pub fn new_op_from_onnx(

            let pool_spec: &PoolSpec = &sumpool_node.pool_spec;

-            // only support pytorch type formatting for now
-            if pool_spec.data_format != DataFormat::NCHW {
-                return Err(GraphError::MissingParams(
-                    "data in wrong format".to_string(),
-                ));
-            }
-
            let stride = extract_strides(pool_spec)?;
            let padding = extract_padding(pool_spec, &input_dims[0])?;
            let kernel_shape = &pool_spec.kernel_shape;
@@ -1161,6 +1153,7 @@ pub fn new_op_from_onnx(
                padding,
                stride: stride.to_vec(),
                pool_dims: kernel_shape.to_vec(),
+                data_format: pool_spec.data_format.into(),
            })
        }
        "Ceil" => {
@@ -1314,15 +1307,6 @@ pub fn new_op_from_onnx(
                }
            }

-            if ((conv_node.pool_spec.data_format != DataFormat::NCHW)
-                && (conv_node.pool_spec.data_format != DataFormat::CHW))
-                || (conv_node.kernel_fmt != KernelFormat::OIHW)
-            {
-                return Err(GraphError::MisformedParams(
-                    "data or kernel in wrong format".to_string(),
-                ));
-            }
-
            let pool_spec = &conv_node.pool_spec;

            let stride = extract_strides(pool_spec)?;
@@ -1350,6 +1334,8 @@ pub fn new_op_from_onnx(
                padding,
                stride,
                group,
+                data_format: conv_node.pool_spec.data_format.into(),
+                kernel_format: conv_node.kernel_fmt.into(),
            })
        }
        "Not" => SupportedOp::Linear(PolyOp::Not),
@@ -1373,14 +1359,6 @@ pub fn new_op_from_onnx(
                }
            }

-            if (deconv_node.pool_spec.data_format != DataFormat::NCHW)
-                || (deconv_node.kernel_format != KernelFormat::OIHW)
-            {
-                return Err(GraphError::MisformedParams(
-                    "data or kernel in wrong format".to_string(),
-                ));
-            }
-
            let pool_spec = &deconv_node.pool_spec;

            let stride = extract_strides(pool_spec)?;
@@ -1406,6 +1384,8 @@ pub fn new_op_from_onnx(
                output_padding: deconv_node.adjustments.to_vec(),
                stride,
                group: deconv_node.group,
+                data_format: deconv_node.pool_spec.data_format.into(),
+                kernel_format: deconv_node.kernel_format.into(),
            })
        }
        "Downsample" => {
@@ -1418,7 +1398,7 @@ pub fn new_op_from_onnx(

            SupportedOp::Linear(PolyOp::Downsample {
                axis: downsample_node.axis,
-                stride: downsample_node.stride as usize,
+                stride: downsample_node.stride,
                modulo: downsample_node.modulo,
            })
        }
@@ -1489,13 +1469,6 @@ pub fn new_op_from_onnx(

            let pool_spec: &PoolSpec = &sumpool_node.pool_spec;

-            // only support pytorch type formatting for now
-            if pool_spec.data_format != DataFormat::NCHW {
-                return Err(GraphError::MissingParams(
-                    "data in wrong format".to_string(),
-                ));
-            }
-
            let stride = extract_strides(pool_spec)?;
            let padding = extract_padding(pool_spec, &input_dims[0])?;

@@ -1504,6 +1477,7 @@ pub fn new_op_from_onnx(
                stride: stride.to_vec(),
                kernel_shape: pool_spec.kernel_shape.to_vec(),
                normalized: sumpool_node.normalize,
+                data_format: pool_spec.data_format.into(),
            })
        }
        "Pad" => {
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -97,10 +97,9 @@ impl From<String> for EZKLError {

 use std::str::FromStr;

-use circuit::{table::Range, CheckMode, Tolerance};
+use circuit::{table::Range, CheckMode};
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 use clap::Args;
-#[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 use fieldutils::IntegerRep;
 use graph::{Visibility, MAX_PUBLIC_SRS};
 use halo2_proofs::poly::{
@@ -275,10 +274,6 @@ impl From<String> for Commitments {
    derive(Args, ToFlags)
 )]
 pub struct RunArgs {
-    /// Error tolerance for model outputs
-    /// Only applicable when outputs are public
-    #[cfg_attr(all(feature = "ezkl", not(target_arch = "wasm32")), arg(short = 'T', long, default_value = "0", value_hint = clap::ValueHint::Other))]
-    pub tolerance: Tolerance,
    /// Fixed point scaling factor for quantizing inputs
    /// Higher values provide more precision but increase circuit complexity
    #[cfg_attr(all(feature = "ezkl", not(target_arch = "wasm32")), arg(short = 'S', long, default_value = "7", value_hint = clap::ValueHint::Other))]
@@ -365,7 +360,6 @@ impl Default for RunArgs {
    fn default() -> Self {
        Self {
            bounded_log_lookup: false,
-            tolerance: Tolerance::default(),
            input_scale: 7,
            param_scale: 7,
            scale_rebase_multiplier: 1,
@@ -399,6 +393,16 @@ impl RunArgs {
    pub fn validate(&self) -> Result<(), String> {
        let mut errors = Vec::new();

+        // check if the largest represented integer in the decomposed form overflows IntegerRep
+        //  try it with the largest possible value
+        let max_decomp = (self.decomp_base as IntegerRep).checked_pow(self.decomp_legs as u32);
+        if max_decomp.is_none() {
+            errors.push(format!(
+                "decomp_base^decomp_legs overflows IntegerRep: {}^{}",
+                self.decomp_base, self.decomp_legs
+            ));
+        }
+
        // Visibility validations
        if self.param_visibility == Visibility::Public {
            errors.push(
@@ -407,10 +411,6 @@ impl RunArgs {
            );
        }

-        if self.tolerance.val > 0.0 && self.output_visibility != Visibility::Public {
-            errors.push("Non-zero tolerance requires output_visibility to be public".to_string());
-        }
-
        // Scale validations
        if self.scale_rebase_multiplier < 1 {
            errors.push("scale_rebase_multiplier must be >= 1".to_string());
@@ -459,11 +459,6 @@ impl RunArgs {
            warn!("logrows exceeds maximum public SRS size");
        }

-        // Validate tolerance is non-negative
-        if self.tolerance.val < 0.0 {
-            errors.push("tolerance cannot be negative".to_string());
-        }
-
        // Performance warnings
        if self.input_scale > 20 || self.param_scale > 20 {
            warn!("High scale values (>20) may impact performance");
@@ -610,23 +605,6 @@ mod tests {
        assert!(err.contains("num_inner_cols must be >= 1"));
    }

-    #[test]
-    fn test_invalid_tolerance() {
-        let mut args = RunArgs::default();
-        args.tolerance.val = 1.0;
-        args.output_visibility = Visibility::Private;
-        let err = args.validate().unwrap_err();
-        assert!(err.contains("Non-zero tolerance requires output_visibility to be public"));
-    }
-
-    #[test]
-    fn test_negative_tolerance() {
-        let mut args = RunArgs::default();
-        args.tolerance.val = -1.0;
-        let err = args.validate().unwrap_err();
-        assert!(err.contains("tolerance cannot be negative"));
-    }
-
    #[test]
    fn test_zero_batch_size() {
        let mut args = RunArgs::default();
--- a/src/pfsys/mod.rs
+++ b/src/pfsys/mod.rs
@@ -17,16 +17,16 @@ use crate::{Commitments, EZKL_BUF_CAPACITY, EZKL_KEY_FORMAT};
 use clap::ValueEnum;
 use halo2_proofs::circuit::Value;
 use halo2_proofs::plonk::{
-    create_proof, keygen_pk, keygen_vk_custom, verify_proof, Circuit, ProvingKey, VerifyingKey,
+    Circuit, ProvingKey, VerifyingKey, create_proof, keygen_pk, keygen_vk_custom, verify_proof,
 };
+use halo2_proofs::poly::VerificationStrategy;
 use halo2_proofs::poly::commitment::{CommitmentScheme, Params, ParamsProver, Prover, Verifier};
 use halo2_proofs::poly::ipa::commitment::IPACommitmentScheme;
 use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
-use halo2_proofs::poly::VerificationStrategy;
 use halo2_proofs::transcript::{EncodedChallenge, TranscriptReadBuffer, TranscriptWriterBuffer};
+use halo2curves::CurveAffine;
 use halo2curves::ff::{FromUniformBytes, PrimeField, WithSmallOrderMulGroup};
 use halo2curves::serde::SerdeObject;
-use halo2curves::CurveAffine;
 use instant::Instant;
 use log::{debug, info, trace};
 #[cfg(not(feature = "det-prove"))]
@@ -51,6 +51,9 @@ use pyo3::types::PyDictMethods;

 use halo2curves::bn256::{Bn256, Fr, G1Affine};

+/// Converts a string to a `SerdeFormat`.
+/// # Panics
+/// Panics if the provided `s` is not a valid `SerdeFormat` (i.e. not one of "processed", "raw-bytes-unchecked", or "raw-bytes").
 fn serde_format_from_str(s: &str) -> halo2_proofs::SerdeFormat {
    match s {
        "processed" => halo2_proofs::SerdeFormat::Processed,
@@ -321,7 +324,7 @@ where
 }

 #[cfg(feature = "python-bindings")]
-use pyo3::{types::PyDict, PyObject, Python, ToPyObject};
+use pyo3::{PyObject, Python, ToPyObject, types::PyDict};
 #[cfg(feature = "python-bindings")]
 impl<F: PrimeField + SerdeObject + Serialize, C: CurveAffine + Serialize> ToPyObject for Snark<F, C>
 where
@@ -345,9 +348,9 @@ where
 }

 impl<
-        F: PrimeField + SerdeObject + Serialize + FromUniformBytes<64> + DeserializeOwned,
-        C: CurveAffine + Serialize + DeserializeOwned,
-    > Snark<F, C>
+    F: PrimeField + SerdeObject + Serialize + FromUniformBytes<64> + DeserializeOwned,
+    C: CurveAffine + Serialize + DeserializeOwned,
+> Snark<F, C>
 where
    C::Scalar: Serialize + DeserializeOwned,
    C::ScalarExt: Serialize + DeserializeOwned,
--- a/src/tensor/errors.rs
+++ b/src/tensor/errors.rs
@@ -1,6 +1,6 @@
 use thiserror::Error;

-use super::ops::DecompositionError;
+use super::{ops::DecompositionError, DataFormat};

 /// A wrapper for tensor related errors.
 #[derive(Debug, Error)]
@@ -44,4 +44,7 @@ pub enum TensorError {
    /// Index out of bounds
    #[error("index {0} out of bounds for dimension {1}")]
    IndexOutOfBounds(usize, usize),
+    /// Invalid data conversion
+    #[error("invalid data conversion from format {0} to {1}")]
+    InvalidDataConversion(DataFormat, DataFormat),
 }
--- a/src/tensor/mod.rs
+++ b/src/tensor/mod.rs
@@ -9,6 +9,7 @@ pub mod var;

 pub use errors::TensorError;

+use core::hash::Hash;
 use halo2curves::ff::PrimeField;
 use maybe_rayon::{
    prelude::{
@@ -26,7 +27,7 @@ pub use var::*;

 use crate::{
    circuit::utils,
-    fieldutils::{integer_rep_to_felt, IntegerRep},
+    fieldutils::{IntegerRep, integer_rep_to_felt},
    graph::Visibility,
 };

@@ -61,7 +62,7 @@ pub trait TensorType: Clone + Debug + 'static {
 }

 macro_rules! tensor_type {
-    ($rust_type:ty, $tensor_type:ident, $zero:expr, $one:expr) => {
+    ($rust_type:ty, $tensor_type:ident, $zero:expr_2021, $one:expr_2021) => {
        impl TensorType for $rust_type {
            fn zero() -> Option<Self> {
                Some($zero)
@@ -414,7 +415,7 @@ impl<T: Clone + TensorType + PrimeField> Tensor<T> {
                Err(_) => {
                    return Err(TensorError::FileLoadError(
                        "Failed to read tensor".to_string(),
-                    ))
+                    ));
                }
            }
        }
@@ -925,6 +926,9 @@ impl<T: Clone + TensorType> Tensor<T> {
                ));
            }
            self.dims = vec![];
+        }
+        if self.dims() == &[0] && new_dims.iter().product::<usize>() == 1 {
+            self.dims = Vec::from(new_dims);
        } else {
            let product = if new_dims != [0] {
                new_dims.iter().product::<usize>()
@@ -1103,6 +1107,10 @@ impl<T: Clone + TensorType> Tensor<T> {
            let mut output = self.clone();
            output.reshape(shape)?;
            return Ok(output);
+        } else if self.dims() == &[0] && shape.iter().product::<usize>() == 1 {
+            let mut output = self.clone();
+            output.reshape(shape)?;
+            return Ok(output);
        }

        if self.dims().len() > shape.len() {
@@ -1253,7 +1261,7 @@ impl<T: Clone + TensorType> Tensor<T> {
            None => {
                return Err(TensorError::DimError(
                    "Cannot get last element of empty tensor".to_string(),
-                ))
+                ));
            }
        };

@@ -1278,7 +1286,7 @@ impl<T: Clone + TensorType> Tensor<T> {
            None => {
                return Err(TensorError::DimError(
                    "Cannot get first element of empty tensor".to_string(),
-                ))
+                ));
            }
        };

@@ -1691,8 +1699,8 @@ impl<T: TensorType + Rem<Output = T> + std::marker::Send + std::marker::Sync + P

        lhs.par_iter_mut()
            .zip(rhs)
-            .map(|(o, r)| {
-                if let Some(zero) = T::zero() {
+            .map(|(o, r)| match T::zero() {
+                Some(zero) => {
                    if r != zero {
                        *o = o.clone() % r;
                        Ok(())
@@ -1701,11 +1709,10 @@ impl<T: TensorType + Rem<Output = T> + std::marker::Send + std::marker::Sync + P
                            "Cannot divide by zero in remainder".to_string(),
                        ))
                    }
-                } else {
-                    Err(TensorError::InvalidArgument(
-                        "Undefined zero value".to_string(),
-                    ))
                }
+                _ => Err(TensorError::InvalidArgument(
+                    "Undefined zero value".to_string(),
+                )),
            })
            .collect::<Result<Vec<_>, _>>()?;

@@ -1767,6 +1774,229 @@ pub fn get_broadcasted_shape(
    }
 }
 ////////////////////////
+///
+
+/// The shape of data for some operations
+#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, Default, Copy)]
+pub enum DataFormat {
+    /// NCHW
+    #[default]
+    NCHW,
+    /// NHWC
+    NHWC,
+    /// CHW
+    CHW,
+    /// HWC
+    HWC,
+}
+
+// as str
+impl core::fmt::Display for DataFormat {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        match self {
+            DataFormat::NCHW => write!(f, "NCHW"),
+            DataFormat::NHWC => write!(f, "NHWC"),
+            DataFormat::CHW => write!(f, "CHW"),
+            DataFormat::HWC => write!(f, "HWC"),
+        }
+    }
+}
+
+impl DataFormat {
+    /// Get the format's canonical form
+    pub fn canonical(&self) -> DataFormat {
+        match self {
+            DataFormat::NHWC => DataFormat::NCHW,
+            DataFormat::HWC => DataFormat::CHW,
+            _ => self.clone(),
+        }
+    }
+
+    /// no batch dim
+    pub fn has_no_batch(&self) -> bool {
+        match self {
+            DataFormat::CHW | DataFormat::HWC => true,
+            _ => false,
+        }
+    }
+
+    /// Convert tensor to canonical format (NCHW or CHW)
+    pub fn to_canonical<F: PrimeField + TensorType + PartialOrd + Hash>(
+        &self,
+        tensor: &mut ValTensor<F>,
+    ) -> Result<(), TensorError> {
+        match self {
+            DataFormat::NHWC => {
+                // For ND: Move channels from last axis to position after batch
+                let ndims = tensor.dims().len();
+                if ndims > 2 {
+                    tensor.move_axis(ndims - 1, 1)?;
+                }
+            }
+            DataFormat::HWC => {
+                // For ND: Move channels from last axis to first position
+                let ndims = tensor.dims().len();
+                if ndims > 1 {
+                    tensor.move_axis(ndims - 1, 0)?;
+                }
+            }
+            _ => {} // NCHW/CHW are already in canonical format
+        }
+        Ok(())
+    }
+
+    /// Convert tensor from canonical format to target format
+    pub fn from_canonical<F: PrimeField + TensorType + PartialOrd + Hash>(
+        &self,
+        tensor: &mut ValTensor<F>,
+    ) -> Result<(), TensorError> {
+        match self {
+            DataFormat::NHWC => {
+                // Move channels from position 1 to end
+                let ndims = tensor.dims().len();
+                if ndims > 2 {
+                    tensor.move_axis(1, ndims - 1)?;
+                }
+            }
+            DataFormat::HWC => {
+                // Move channels from position 0 to end
+                let ndims = tensor.dims().len();
+                if ndims > 1 {
+                    tensor.move_axis(0, ndims - 1)?;
+                }
+            }
+            _ => {} // NCHW/CHW don't need conversion
+        }
+        Ok(())
+    }
+
+    /// Get the position of the channel dimension
+    pub fn get_channel_dim(&self, ndims: usize) -> usize {
+        match self {
+            DataFormat::NCHW => 1,
+            DataFormat::NHWC => ndims - 1,
+            DataFormat::CHW => 0,
+            DataFormat::HWC => ndims - 1,
+        }
+    }
+}
+/// The shape of the kernel for some operations
+#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, Default, Copy)]
+pub enum KernelFormat {
+    /// HWIO
+    HWIO,
+    /// OIHW
+    #[default]
+    OIHW,
+    /// OHWI
+    OHWI,
+}
+
+impl core::fmt::Display for KernelFormat {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        match self {
+            KernelFormat::HWIO => write!(f, "HWIO"),
+            KernelFormat::OIHW => write!(f, "OIHW"),
+            KernelFormat::OHWI => write!(f, "OHWI"),
+        }
+    }
+}
+
+impl KernelFormat {
+    /// Get the format's canonical form
+    pub fn canonical(&self) -> KernelFormat {
+        match self {
+            KernelFormat::HWIO => KernelFormat::OIHW,
+            KernelFormat::OHWI => KernelFormat::OIHW,
+            _ => self.clone(),
+        }
+    }
+
+    /// Convert kernel to canonical format (OIHW)
+    pub fn to_canonical<F: PrimeField + TensorType + PartialOrd + Hash>(
+        &self,
+        kernel: &mut ValTensor<F>,
+    ) -> Result<(), TensorError> {
+        match self {
+            KernelFormat::HWIO => {
+                let kdims = kernel.dims().len();
+                // Move output channels from last to first
+                kernel.move_axis(kdims - 1, 0)?;
+                // Move input channels from new last to second position
+                kernel.move_axis(kdims - 1, 1)?;
+            }
+            KernelFormat::OHWI => {
+                let kdims = kernel.dims().len();
+                // Move input channels from last to second position
+                kernel.move_axis(kdims - 1, 1)?;
+            }
+            _ => {} // OIHW is already canonical
+        }
+        Ok(())
+    }
+
+    /// Convert kernel from canonical format to target format
+    pub fn from_canonical<F: PrimeField + TensorType + PartialOrd + Hash>(
+        &self,
+        kernel: &mut ValTensor<F>,
+    ) -> Result<(), TensorError> {
+        match self {
+            KernelFormat::HWIO => {
+                let kdims = kernel.dims().len();
+                // Move input channels from second position to last
+                kernel.move_axis(1, kdims - 1)?;
+                // Move output channels from first to last
+                kernel.move_axis(0, kdims - 1)?;
+            }
+            KernelFormat::OHWI => {
+                let kdims = kernel.dims().len();
+                // Move input channels from second position to last
+                kernel.move_axis(1, kdims - 1)?;
+            }
+            _ => {} // OIHW doesn't need conversion
+        }
+        Ok(())
+    }
+
+    /// Get the position of input and output channel dimensions
+    pub fn get_channel_dims(&self, ndims: usize) -> (usize, usize) {
+        // (input_ch, output_ch)
+        match self {
+            KernelFormat::OIHW => (1, 0),
+            KernelFormat::HWIO => (ndims - 2, ndims - 1),
+            KernelFormat::OHWI => (ndims - 1, 0),
+        }
+    }
+}
+
+#[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
+impl From<tract_onnx::tract_hir::ops::nn::DataFormat> for DataFormat {
+    fn from(fmt: tract_onnx::tract_hir::ops::nn::DataFormat) -> Self {
+        match fmt {
+            tract_onnx::tract_hir::ops::nn::DataFormat::NCHW => DataFormat::NCHW,
+            tract_onnx::tract_hir::ops::nn::DataFormat::NHWC => DataFormat::NHWC,
+            tract_onnx::tract_hir::ops::nn::DataFormat::CHW => DataFormat::CHW,
+            tract_onnx::tract_hir::ops::nn::DataFormat::HWC => DataFormat::HWC,
+        }
+    }
+}
+
+#[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
+impl From<tract_onnx::tract_hir::tract_core::ops::cnn::conv::KernelFormat> for KernelFormat {
+    fn from(fmt: tract_onnx::tract_hir::tract_core::ops::cnn::conv::KernelFormat) -> Self {
+        match fmt {
+            tract_onnx::tract_hir::tract_core::ops::cnn::conv::KernelFormat::HWIO => {
+                KernelFormat::HWIO
+            }
+            tract_onnx::tract_hir::tract_core::ops::cnn::conv::KernelFormat::OIHW => {
+                KernelFormat::OIHW
+            }
+            tract_onnx::tract_hir::tract_core::ops::cnn::conv::KernelFormat::OHWI => {
+                KernelFormat::OHWI
+            }
+        }
+    }
+}

 #[cfg(test)]
 mod tests {
--- a/src/tensor/ops.rs
+++ b/src/tensor/ops.rs
@@ -535,30 +535,101 @@ pub fn mult<T: TensorType + Mul<Output = T> + std::marker::Send + std::marker::S
 /// let result = downsample(&x, 1, 2, 2).unwrap();
 /// let expected = Tensor::<IntegerRep>::new(Some(&[3, 6]), &[2, 1]).unwrap();
 /// assert_eq!(result, expected);
+/// let x = Tensor::<IntegerRep>::new(
+///     Some(&[1, 2, 3, 4, 5, 6]),
+///     &[2, 3],
+/// ).unwrap();
+///
+/// // Test case 1: Negative stride along dimension 0
+/// // This should flip the order along dimension 0
+/// let result = downsample(&x, 0, -1, 0).unwrap();
+/// let expected = Tensor::<IntegerRep>::new(
+///     Some(&[4, 5, 6, 1, 2, 3]), // Flipped order of rows
+///     &[2, 3]
+/// ).unwrap();
+/// assert_eq!(result, expected);
+///
+/// // Test case 2: Negative stride along dimension 1
+/// // This should flip the order along dimension 1
+/// let result = downsample(&x, 1, -1, 0).unwrap();
+/// let expected = Tensor::<IntegerRep>::new(
+///     Some(&[3, 2, 1, 6, 5, 4]), // Flipped order of columns
+///     &[2, 3]
+/// ).unwrap();
+/// assert_eq!(result, expected);
+///
+/// // Test case 3: Negative stride with stride magnitude > 1
+/// // This should both skip and flip
+/// let result = downsample(&x, 1, -2, 0).unwrap();
+/// let expected = Tensor::<IntegerRep>::new(
+///     Some(&[3, 1, 6, 4]), // Take every 2nd element in reverse
+///     &[2, 2]
+/// ).unwrap();
+/// assert_eq!(result, expected);
+///
+/// // Test case 4: Negative stride with non-zero modulo
+/// // This should start at (size - 1 - modulo) and reverse
+/// let result = downsample(&x, 1, -2, 1).unwrap();
+/// let expected = Tensor::<IntegerRep>::new(
+///     Some(&[2, 5]), // Start at second element from end, take every 2nd in reverse
+///     &[2, 1]
+/// ).unwrap();
+/// assert_eq!(result, expected);
+///
+/// // Create a larger test case for more complex downsampling
+/// let y = Tensor::<IntegerRep>::new(
+///     Some(&[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]),
+///     &[3, 4],
+/// ).unwrap();
+///
+/// // Test case 5: Negative stride with modulo on larger tensor
+/// let result = downsample(&y, 1, -2, 1).unwrap();
+/// let expected = Tensor::<IntegerRep>::new(
+///     Some(&[3, 1, 7, 5, 11, 9]), // Start at one after reverse, take every 2nd
+///     &[3, 2]
+/// ).unwrap();
+/// assert_eq!(result, expected);
+/// ```
 pub fn downsample<T: TensorType + Send + Sync>(
    input: &Tensor<T>,
    dim: usize,
-    stride: usize,
+    stride: isize, // Changed from usize to isize to support negative strides
    modulo: usize,
 ) -> Result<Tensor<T>, TensorError> {
-    let mut output_shape = input.dims().to_vec();
-    // now downsample along axis dim offset by modulo, rounding up (+1 if remaidner is non-zero)
-    let remainder = (input.dims()[dim] - modulo) % stride;
-    let div = (input.dims()[dim] - modulo) / stride;
-    output_shape[dim] = div + (remainder > 0) as usize;
-    let mut output = Tensor::<T>::new(None, &output_shape)?;
+    // Handle negative stride case
+    if stride == 0 {
+        return Err(TensorError::DimMismatch(
+            "downsample stride cannot be zero".to_string(),
+        ));
+    }

-    if modulo > input.dims()[dim] {
+    let stride_abs = stride.unsigned_abs();
+    let mut output_shape = input.dims().to_vec();
+
+    if modulo >= input.dims()[dim] {
        return Err(TensorError::DimMismatch("downsample".to_string()));
    }

-    // now downsample along axis dim offset by modulo
+    // Calculate output shape based on the absolute value of stride
+    let remainder = (input.dims()[dim] - modulo) % stride_abs;
+    let div = (input.dims()[dim] - modulo) / stride_abs;
+    output_shape[dim] = div + (remainder > 0) as usize;
+
+    let mut output = Tensor::<T>::new(None, &output_shape)?;
+
+    // Calculate indices based on stride direction
    let indices = (0..output_shape.len())
        .map(|i| {
            if i == dim {
                let mut index = vec![0; output_shape[i]];
-                for (i, idx) in index.iter_mut().enumerate() {
-                    *idx = i * stride + modulo;
+                for (j, idx) in index.iter_mut().enumerate() {
+                    if stride > 0 {
+                        // Positive stride: move forward from modulo
+                        *idx = j * stride_abs + modulo;
+                    } else {
+                        // Negative stride: move backward from (size - 1 - modulo)
+                        *idx = (input.dims()[dim] - 1 - modulo) - j * stride_abs;
+                    }
                }
                index
            } else {
--- a/src/tensor/val.rs
+++ b/src/tensor/val.rs
@@ -1342,9 +1342,11 @@ impl<F: PrimeField + TensorType + PartialOrd + std::hash::Hash> ValTensor<F> {
    /// Gets the total number of elements in the tensor
    pub fn len(&self) -> usize {
        match self {
-            ValTensor::Value { dims, .. } => {
+            ValTensor::Value { dims, inner, .. } => {
                if !dims.is_empty() && (dims != &[0]) {
                    dims.iter().product::<usize>()
+                } else if dims.is_empty() {
+                    inner.inner.len()
                } else {
                    0
                }
--- a/src/tensor/var.rs
+++ b/src/tensor/var.rs
@@ -2,7 +2,7 @@ use std::collections::HashSet;

 use log::{debug, error, warn};

-use crate::circuit::{region::ConstantsMap, CheckMode};
+use crate::circuit::{CheckMode, region::ConstantsMap};

 use super::*;
 /// A wrapper around Halo2's Column types that represents a tensor of variables in the circuit.
@@ -403,7 +403,10 @@ impl VarTensor {
        let mut assigned_coord = 0;
        let mut res: ValTensor<F> = match values {
            ValTensor::Instance { .. } => {
-                unimplemented!("cannot assign instance to advice columns with omissions")
+                error!(
+                    "assignment with omissions is not supported on instance columns. increase K if you require more rows."
+                );
+                Err(halo2_proofs::plonk::Error::Synthesis)
            }
            ValTensor::Value { inner: v, .. } => Ok::<ValTensor<F>, halo2_proofs::plonk::Error>(
                v.enum_map(|coord, k| {
@@ -569,8 +572,13 @@ impl VarTensor {
        constants: &mut ConstantsMap<F>,
    ) -> Result<(ValTensor<F>, usize), halo2_proofs::plonk::Error> {
        match values {
-            ValTensor::Instance { .. } => unimplemented!("duplication is not supported on instance columns. increase K if you require more rows."),
-            ValTensor::Value { inner: v, dims , ..} => {
+            ValTensor::Instance { .. } => {
+                error!(
+                    "duplication is not supported on instance columns. increase K if you require more rows."
+                );
+                Err(halo2_proofs::plonk::Error::Synthesis)
+            }
+            ValTensor::Value { inner: v, dims, .. } => {
                let duplication_freq = if single_inner_col {
                    self.col_size()
                } else {
@@ -583,21 +591,20 @@ impl VarTensor {
                    self.num_inner_cols()
                };

-                let duplication_offset = if single_inner_col {
-                    row
-                } else {
-                    offset
-                };
-
+                let duplication_offset = if single_inner_col { row } else { offset };

                // duplicates every nth element to adjust for column overflow
-                let mut res: ValTensor<F> = v.duplicate_every_n(duplication_freq, num_repeats, duplication_offset).unwrap().into();
+                let mut res: ValTensor<F> = v
+                    .duplicate_every_n(duplication_freq, num_repeats, duplication_offset)
+                    .unwrap()
+                    .into();

                let constants_map = res.create_constants_map();
                constants.extend(constants_map);

                let total_used_len = res.len();
-                res.remove_every_n(duplication_freq, num_repeats, duplication_offset).unwrap();
+                res.remove_every_n(duplication_freq, num_repeats, duplication_offset)
+                    .unwrap();

                res.reshape(dims).unwrap();
                res.set_scale(values.scale());
@@ -627,9 +634,13 @@ impl VarTensor {
        constants: &mut ConstantsMap<F>,
    ) -> Result<(ValTensor<F>, usize), halo2_proofs::plonk::Error> {
        match values {
-            ValTensor::Instance { .. } => unimplemented!("duplication is not supported on instance columns. increase K if you require more rows."),
-            ValTensor::Value { inner: v, dims , ..} => {
-
+            ValTensor::Instance { .. } => {
+                error!(
+                    "duplication is not supported on instance columns. increase K if you require more rows."
+                );
+                Err(halo2_proofs::plonk::Error::Synthesis)
+            }
+            ValTensor::Value { inner: v, dims, .. } => {
                let duplication_freq = self.block_size();

                let num_repeats = self.num_inner_cols();
@@ -637,17 +648,31 @@ impl VarTensor {
                let duplication_offset = offset;

                // duplicates every nth element to adjust for column overflow
-                let v = v.duplicate_every_n(duplication_freq, num_repeats, duplication_offset).unwrap();
+                let v = v
+                    .duplicate_every_n(duplication_freq, num_repeats, duplication_offset)
+                    .map_err(|e| {
+                        error!("Error duplicating values: {:?}", e);
+                        halo2_proofs::plonk::Error::Synthesis
+                    })?;
                let mut res: ValTensor<F> = {
                    v.enum_map(|coord, k| {
-                    let cell = self.assign_value(region, offset, k.clone(), coord, constants)?;
-                    Ok::<_, halo2_proofs::plonk::Error>(cell)
-
-                })?.into()};
+                        let cell =
+                            self.assign_value(region, offset, k.clone(), coord, constants)?;
+                        Ok::<_, halo2_proofs::plonk::Error>(cell)
+                    })?
+                    .into()
+                };
                let total_used_len = res.len();
-                res.remove_every_n(duplication_freq, num_repeats, duplication_offset).unwrap();
+                res.remove_every_n(duplication_freq, num_repeats, duplication_offset)
+                    .map_err(|e| {
+                        error!("Error duplicating values: {:?}", e);
+                        halo2_proofs::plonk::Error::Synthesis
+                    })?;

-                res.reshape(dims).unwrap();
+                res.reshape(dims).map_err(|e| {
+                    error!("Error duplicating values: {:?}", e);
+                    halo2_proofs::plonk::Error::Synthesis
+                })?;
                res.set_scale(values.scale());

                Ok((res, total_used_len))
@@ -681,61 +706,71 @@ impl VarTensor {
        let mut prev_cell = None;

        match values {
-            ValTensor::Instance { .. } => unimplemented!("duplication is not supported on instance columns. increase K if you require more rows."),
-            ValTensor::Value { inner: v, dims , ..} => {
-
+            ValTensor::Instance { .. } => {
+                error!(
+                    "duplication is not supported on instance columns. increase K if you require more rows."
+                );
+                Err(halo2_proofs::plonk::Error::Synthesis)
+            }
+            ValTensor::Value { inner: v, dims, .. } => {
                let duplication_freq = self.col_size();
                let num_repeats = 1;
                let duplication_offset = row;

                // duplicates every nth element to adjust for column overflow
-                let v = v.duplicate_every_n(duplication_freq, num_repeats, duplication_offset).unwrap();
-                let mut res: ValTensor<F> =
-                    v.enum_map(|coord, k| {
+                let v = v
+                    .duplicate_every_n(duplication_freq, num_repeats, duplication_offset)
+                    .unwrap();
+                let mut res: ValTensor<F> = v
+                    .enum_map(|coord, k| {
+                        let step = self.num_inner_cols();

-                    let step = self.num_inner_cols();
+                        let (x, y, z) = self.cartesian_coord(offset + coord * step);
+                        if matches!(check_mode, CheckMode::SAFE) && coord > 0 && z == 0 && y == 0 {
+                            // assert that duplication occurred correctly
+                            assert_eq!(
+                                Into::<IntegerRep>::into(k.clone()),
+                                Into::<IntegerRep>::into(v[coord - 1].clone())
+                            );
+                        };

-                    let (x, y, z) = self.cartesian_coord(offset + coord * step);
-                    if matches!(check_mode, CheckMode::SAFE) && coord > 0 && z == 0 && y == 0 {
-                        // assert that duplication occurred correctly
-                        assert_eq!(Into::<IntegerRep>::into(k.clone()), Into::<IntegerRep>::into(v[coord - 1].clone()));
-                    };
+                        let cell =
+                            self.assign_value(region, offset, k.clone(), coord * step, constants)?;

-                    let cell = self.assign_value(region, offset, k.clone(), coord * step, constants)?;
+                        let at_end_of_column = z == duplication_freq - 1;
+                        let at_beginning_of_column = z == 0;

-                    let at_end_of_column = z == duplication_freq - 1;
-                    let at_beginning_of_column = z == 0;
-
-                    if at_end_of_column {
-                        // if we are at the end of the column, we need to copy the cell to the next column
-                        prev_cell = Some(cell.clone());
-                    } else if coord > 0 && at_beginning_of_column  {
-                        if let Some(prev_cell) = prev_cell.as_ref() {
-                            let cell = if let Some(cell) = cell.cell() {
-                                cell
+                        if at_end_of_column {
+                            // if we are at the end of the column, we need to copy the cell to the next column
+                            prev_cell = Some(cell.clone());
+                        } else if coord > 0 && at_beginning_of_column {
+                            if let Some(prev_cell) = prev_cell.as_ref() {
+                                let cell = if let Some(cell) = cell.cell() {
+                                    cell
+                                } else {
+                                    error!("Error getting cell: {:?}", (x, y));
+                                    return Err(halo2_proofs::plonk::Error::Synthesis);
+                                };
+                                let prev_cell = if let Some(prev_cell) = prev_cell.cell() {
+                                    prev_cell
+                                } else {
+                                    error!("Error getting prev cell: {:?}", (x, y));
+                                    return Err(halo2_proofs::plonk::Error::Synthesis);
+                                };
+                                region.constrain_equal(prev_cell, cell)?;
                            } else {
-                                error!("Error getting cell: {:?}", (x,y));
+                                error!("Previous cell was not set");
                                return Err(halo2_proofs::plonk::Error::Synthesis);
-                            };
-                            let prev_cell = if let Some(prev_cell) = prev_cell.cell() {
-                                prev_cell
-                            } else {
-                                error!("Error getting prev cell: {:?}", (x,y));
-                                return Err(halo2_proofs::plonk::Error::Synthesis);
-                            };
-                            region.constrain_equal(prev_cell,cell)?;
-                        } else {
-                            error!("Previous cell was not set");
-                            return Err(halo2_proofs::plonk::Error::Synthesis);
+                            }
                        }
-                    }

-                    Ok(cell)
-
-                })?.into();
+                        Ok(cell)
+                    })?
+                    .into();

                let total_used_len = res.len();
-                res.remove_every_n(duplication_freq, num_repeats, duplication_offset).unwrap();
+                res.remove_every_n(duplication_freq, num_repeats, duplication_offset)
+                    .unwrap();

                res.reshape(dims).unwrap();
                res.set_scale(values.scale());
@@ -771,21 +806,30 @@ impl VarTensor {
                VarTensor::Advice { inner: advices, .. } => {
                    ValType::PrevAssigned(region.assign_advice(|| "k", advices[x][y], z, || v)?)
                }
-                _ => unimplemented!(),
+                _ => {
+                    error!("VarTensor was not initialized");
+                    return Err(halo2_proofs::plonk::Error::Synthesis);
+                }
            },
            // Handle copying previously assigned value
            ValType::PrevAssigned(v) => match &self {
                VarTensor::Advice { inner: advices, .. } => {
                    ValType::PrevAssigned(v.copy_advice(|| "k", region, advices[x][y], z)?)
                }
-                _ => unimplemented!(),
+                _ => {
+                    error!("VarTensor was not initialized");
+                    return Err(halo2_proofs::plonk::Error::Synthesis);
+                }
            },
            // Handle copying previously assigned constant
            ValType::AssignedConstant(v, val) => match &self {
                VarTensor::Advice { inner: advices, .. } => {
                    ValType::AssignedConstant(v.copy_advice(|| "k", region, advices[x][y], z)?, val)
                }
-                _ => unimplemented!(),
+                _ => {
+                    error!("VarTensor was not initialized");
+                    return Err(halo2_proofs::plonk::Error::Synthesis);
+                }
            },
            // Handle assigning evaluated value
            ValType::AssignedValue(v) => match &self {
@@ -794,7 +838,10 @@ impl VarTensor {
                        .assign_advice(|| "k", advices[x][y], z, || v)?
                        .evaluate(),
                ),
-                _ => unimplemented!(),
+                _ => {
+                    error!("VarTensor was not initialized");
+                    return Err(halo2_proofs::plonk::Error::Synthesis);
+                }
            },
            // Handle constant value assignment with caching
            ValType::Constant(v) => {
--- a/tests/assets/model.compiled
+++ b/tests/assets/model.compiled
--- a/tests/integration_tests.rs
+++ b/tests/integration_tests.rs
@@ -1,13 +1,12 @@
 #[cfg(all(feature = "ezkl", not(target_arch = "wasm32")))]
 #[cfg(test)]
 mod native_tests {
-    use ezkl::circuit::Tolerance;
-    use ezkl::fieldutils::{felt_to_integer_rep, integer_rep_to_felt, IntegerRep};
+
    // use ezkl::circuit::table::RESERVED_BLINDING_ROWS_PAD;
+    use ezkl::Commitments;
    use ezkl::graph::input::{FileSource, FileSourceInner, GraphData};
    use ezkl::graph::{DataSource, GraphSettings, GraphWitness};
    use ezkl::pfsys::Snark;
-    use ezkl::Commitments;
    use halo2_proofs::poly::kzg::commitment::KZGCommitmentScheme;
    use halo2curves::bn256::Bn256;
    use lazy_static::lazy_static;
@@ -187,7 +186,7 @@ mod native_tests {

    const PF_FAILURE_AGGR: &str = "examples/test_failure_aggr_proof.json";

-    const LARGE_TESTS: [&str; 7] = [
+    const LARGE_TESTS: [&str; 8] = [
        "self_attention",
        "nanoGPT",
        "multihead_attention",
@@ -195,6 +194,7 @@ mod native_tests {
        "mnist_gan",
        "smallworm",
        "fr_age",
+        "1d_conv",
    ];

    const ACCURACY_CAL_TESTS: [&str; 6] = [
@@ -522,7 +522,7 @@ mod native_tests {
            use crate::native_tests::run_js_tests;
            use crate::native_tests::render_circuit;
            use crate::native_tests::model_serialization_different_binaries;
-            use rand::Rng;
+
            use tempdir::TempDir;
            use ezkl::Commitments;

@@ -543,7 +543,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "public", "fixed", "public", 1, "accuracy", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "public", "fixed", "public", 1, "accuracy", None, false, None, None);
                test_dir.close().unwrap();
            }
        });
@@ -608,7 +608,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "private", "private", "public", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "private", "private", "public", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -618,22 +618,10 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "private", "private", "public", 1, "resources", None, 0.0, true, Some(8194), Some(4));
+                mock(path, test.to_string(), "private", "private", "public", 1, "resources", None, true, Some(8194), Some(4));
                test_dir.close().unwrap();
            }

-            #(#[test_case(TESTS[N])])*
-            fn mock_tolerance_public_outputs_(test: &str) {
-                crate::native_tests::init_binary();
-                let test_dir = TempDir::new(test).unwrap();
-                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                // gen random number between 0.0 and 1.0
-                let tolerance = rand::thread_rng().gen_range(0.0..1.0) * 100.0;
-                mock(path, test.to_string(), "private", "private", "public", 1, "resources", None, tolerance, false, Some(32776), Some(5));
-                test_dir.close().unwrap();
-            }
-
-

            #(#[test_case(TESTS[N])])*
            fn mock_large_batch_public_outputs_(test: &str) {
@@ -644,7 +632,7 @@ mod native_tests {
                    let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
                    let large_batch_dir = &format!("large_batches_{}", test);
                    crate::native_tests::mk_data_batches_(path, test, &large_batch_dir, 10);
-                    mock(path, large_batch_dir.to_string(), "private", "private", "public", 10, "resources", None, 0.0, false, None, None);
+                    mock(path, large_batch_dir.to_string(), "private", "private", "public", 10, "resources", None, false, None, None);
                    test_dir.close().unwrap();
                }
            }
@@ -654,7 +642,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "public", "private", "private", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "public", "private", "private", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -663,7 +651,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "public", "hashed", "private", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "public", "hashed", "private", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -672,7 +660,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "fixed", "private", "private", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "fixed", "private", "private", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -681,7 +669,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "private", "private", "fixed", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "private", "private", "fixed", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -690,7 +678,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "private", "fixed", "private", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "private", "fixed", "private", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -699,7 +687,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "hashed", "private", "public", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "hashed", "private", "public", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -708,7 +696,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "polycommit", "private", "public", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "polycommit", "private", "public", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -718,7 +706,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "private", "hashed", "public", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "private", "hashed", "public", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -728,7 +716,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "private", "polycommit", "public", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "private", "polycommit", "public", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -737,7 +725,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "public", "private", "hashed", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "public", "private", "hashed", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -747,7 +735,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "public", "private", "polycommit", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "public", "private", "polycommit", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -756,7 +744,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "public", "fixed", "hashed", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "public", "fixed", "hashed", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -766,7 +754,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "public", "polycommit", "hashed", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "public", "polycommit", "hashed", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -776,7 +764,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "polycommit", "polycommit", "polycommit", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "polycommit", "polycommit", "polycommit", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -786,7 +774,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "hashed", "private", "hashed", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(), "hashed", "private", "hashed", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -796,7 +784,7 @@ mod native_tests {
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
                // needs an extra row for the large model
-                mock(path, test.to_string(),"hashed", "hashed", "public", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(),"hashed", "hashed", "public", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -806,7 +794,7 @@ mod native_tests {
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
                // needs an extra row for the large model
-                mock(path, test.to_string(),"hashed", "hashed", "hashed", 1, "resources", None, 0.0, false, None, None);
+                mock(path, test.to_string(),"hashed", "hashed", "hashed", 1, "resources", None, false, None, None);
                test_dir.close().unwrap();
            }

@@ -965,7 +953,7 @@ mod native_tests {

            });

-            seq!(N in 0..=6 {
+            seq!(N in 0..=7 {

            #(#[test_case(LARGE_TESTS[N])])*
            #[ignore]
@@ -983,7 +971,7 @@ mod native_tests {
                crate::native_tests::init_binary();
                let test_dir = TempDir::new(test).unwrap();
                let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                mock(path, test.to_string(), "private", "fixed", "public", 1, "resources", None, 0.0, false, None, Some(5));
+                mock(path, test.to_string(), "private", "fixed", "public", 1, "resources", None, false, None, Some(5));
                test_dir.close().unwrap();
            }
        });
@@ -1459,12 +1447,10 @@ mod native_tests {
        batch_size: usize,
        cal_target: &str,
        scales_to_use: Option<Vec<u32>>,
-        tolerance: f32,
        bounded_lookup_log: bool,
        decomp_base: Option<usize>,
        decomp_legs: Option<usize>,
    ) {
-        let mut tolerance = tolerance;
        gen_circuit_settings_and_witness(
            test_dir,
            example_name.clone(),
@@ -1475,7 +1461,6 @@ mod native_tests {
            cal_target,
            scales_to_use,
            2,
-            &mut tolerance,
            Commitments::KZG,
            2,
            bounded_lookup_log,
@@ -1483,128 +1468,17 @@ mod native_tests {
            decomp_legs,
        );

-        if tolerance > 0.0 {
-            // load witness and shift the output by a small amount that is less than tolerance percent
-            let witness = GraphWitness::from_path(
-                format!("{}/{}/witness.json", test_dir, example_name).into(),
-            )
-            .unwrap();
-            let witness = witness.clone();
-            let outputs = witness.outputs.clone();
-
-            // get values as i64
-            let output_perturbed_safe: Vec<Vec<halo2curves::bn256::Fr>> = outputs
-                .iter()
-                .map(|sv| {
-                    sv.iter()
-                        .map(|v| {
-                            // randomly perturb by a small amount less than tolerance
-                            let perturbation = if v == &halo2curves::bn256::Fr::zero() {
-                                halo2curves::bn256::Fr::zero()
-                            } else {
-                                integer_rep_to_felt(
-                                    (felt_to_integer_rep(*v) as f32
-                                        * (rand::thread_rng().gen_range(-0.01..0.01) * tolerance))
-                                        as IntegerRep,
-                                )
-                            };
-
-                            *v + perturbation
-                        })
-                        .collect::<Vec<_>>()
-                })
-                .collect::<Vec<_>>();
-
-            // get values as i64
-            let output_perturbed_bad: Vec<Vec<halo2curves::bn256::Fr>> = outputs
-                .iter()
-                .map(|sv| {
-                    sv.iter()
-                        .map(|v| {
-                            // randomly perturb by a small amount less than tolerance
-                            let perturbation = if v == &halo2curves::bn256::Fr::zero() {
-                                halo2curves::bn256::Fr::from(2)
-                            } else {
-                                integer_rep_to_felt(
-                                    (felt_to_integer_rep(*v) as f32
-                                        * (rand::thread_rng().gen_range(0.02..0.1) * tolerance))
-                                        as IntegerRep,
-                                )
-                            };
-                            *v + perturbation
-                        })
-                        .collect::<Vec<_>>()
-                })
-                .collect::<Vec<_>>();
-
-            let good_witness = GraphWitness {
-                outputs: output_perturbed_safe,
-                ..witness.clone()
-            };
-
-            // save
-            good_witness
-                .save(format!("{}/{}/witness_ok.json", test_dir, example_name).into())
-                .unwrap();
-
-            let bad_witness = GraphWitness {
-                outputs: output_perturbed_bad,
-                ..witness.clone()
-            };
-
-            // save
-            bad_witness
-                .save(format!("{}/{}/witness_bad.json", test_dir, example_name).into())
-                .unwrap();
-
-            let status = Command::new(format!("{}/{}", *CARGO_TARGET_DIR, TEST_BINARY))
-                .args([
-                    "mock",
-                    "-W",
-                    format!("{}/{}/witness.json", test_dir, example_name).as_str(),
-                    "-M",
-                    format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
-                ])
-                .status()
-                .expect("failed to execute process");
-            assert!(status.success());
-
-            let status = Command::new(format!("{}/{}", *CARGO_TARGET_DIR, TEST_BINARY))
-                .args([
-                    "mock",
-                    "-W",
-                    format!("{}/{}/witness_ok.json", test_dir, example_name).as_str(),
-                    "-M",
-                    format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
-                ])
-                .status()
-                .expect("failed to execute process");
-            assert!(status.success());
-
-            let status = Command::new(format!("{}/{}", *CARGO_TARGET_DIR, TEST_BINARY))
-                .args([
-                    "mock",
-                    "-W",
-                    format!("{}/{}/witness_bad.json", test_dir, example_name).as_str(),
-                    "-M",
-                    format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
-                ])
-                .status()
-                .expect("failed to execute process");
-            assert!(!status.success());
-        } else {
-            let status = Command::new(format!("{}/{}", *CARGO_TARGET_DIR, TEST_BINARY))
-                .args([
-                    "mock",
-                    "-W",
-                    format!("{}/{}/witness.json", test_dir, example_name).as_str(),
-                    "-M",
-                    format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
-                ])
-                .status()
-                .expect("failed to execute process");
-            assert!(status.success());
-        }
+        let status = Command::new(format!("{}/{}", *CARGO_TARGET_DIR, TEST_BINARY))
+            .args([
+                "mock",
+                "-W",
+                format!("{}/{}/witness.json", test_dir, example_name).as_str(),
+                "-M",
+                format!("{}/{}/network.compiled", test_dir, example_name).as_str(),
+            ])
+            .status()
+            .expect("failed to execute process");
+        assert!(status.success());
    }

    #[allow(clippy::too_many_arguments)]
@@ -1618,7 +1492,6 @@ mod native_tests {
        cal_target: &str,
        scales_to_use: Option<Vec<u32>>,
        num_inner_columns: usize,
-        tolerance: &mut f32,
        commitment: Commitments,
        lookup_safety_margin: usize,
        bounded_lookup_log: bool,
@@ -1633,13 +1506,16 @@ mod native_tests {
                "--settings-path={}/{}/settings.json",
                test_dir, example_name
            ),
-            format!("--variables=batch_size->{}", batch_size),
+            format!(
+                "--variables=batch_size->{},sequence_length->100,<Sym1>->1",
+                batch_size
+            ),
            format!("--input-visibility={}", input_visibility),
            format!("--param-visibility={}", param_visibility),
            format!("--output-visibility={}", output_visibility),
            format!("--num-inner-cols={}", num_inner_columns),
-            format!("--tolerance={}", tolerance),
            format!("--commitment={}", commitment),
+            format!("--logrows={}", 22),
        ];

        // if output-visibility is fixed set --range-check-inputs-outputs to False
@@ -1695,24 +1571,6 @@ mod native_tests {
            .expect("failed to execute process");
        assert!(status.success());

-        let mut settings =
-            GraphSettings::load(&format!("{}/{}/settings.json", test_dir, example_name).into())
-                .unwrap();
-
-        let any_output_scales_smol = settings.model_output_scales.iter().any(|s| *s <= 0);
-
-        if any_output_scales_smol {
-            // set the tolerance to 0.0
-            settings.run_args.tolerance = Tolerance {
-                val: 0.0,
-                scale: 0.0.into(),
-            };
-            settings
-                .save(&format!("{}/{}/settings.json", test_dir, example_name).into())
-                .unwrap();
-            *tolerance = 0.0;
-        }
-
        let status = Command::new(format!("{}/{}", *CARGO_TARGET_DIR, TEST_BINARY))
            .args([
                "compile-circuit",
@@ -1725,7 +1583,6 @@ mod native_tests {
                    test_dir, example_name
                ),
            ])
-            .stdout(std::process::Stdio::null())
            .status()
            .expect("failed to execute process");
        assert!(status.success());
@@ -1768,7 +1625,6 @@ mod native_tests {
            cal_target,
            None,
            2,
-            &mut 0.0,
            Commitments::KZG,
            2,
            false,
@@ -2054,7 +1910,6 @@ mod native_tests {
            target_str,
            scales_to_use,
            num_inner_columns,
-            &mut 0.0,
            commitment,
            lookup_safety_margin,
            false,
@@ -2438,7 +2293,12 @@ mod native_tests {
                .expect("failed to execute process");

            if status.success() {
-                log::error!("Verification unexpectedly succeeded for modified proof {}. Flipped bit {} in byte {}", i, random_bit, random_byte);
+                log::error!(
+                    "Verification unexpectedly succeeded for modified proof {}. Flipped bit {} in byte {}",
+                    i,
+                    random_bit,
+                    random_byte
+                );
            }

            assert!(
@@ -2489,7 +2349,6 @@ mod native_tests {
            // we need the accuracy
            Some(vec![4]),
            1,
-            &mut 0.0,
            Commitments::KZG,
            2,
            false,
--- a/tests/py_integration_tests.rs
+++ b/tests/py_integration_tests.rs
@@ -46,7 +46,9 @@ mod py_tests {
            assert!(status.success());
        });
        // set VOICE_DATA_DIR environment variable
-        std::env::set_var("VOICE_DATA_DIR", format!("{}", voice_data_dir));
+        unsafe {
+            std::env::set_var("VOICE_DATA_DIR", format!("{}", voice_data_dir));
+        }
    }

    fn download_catdog_data() {
@@ -63,7 +65,9 @@ mod py_tests {
            assert!(status.success());
        });
        // set VOICE_DATA_DIR environment variable
-        std::env::set_var("CATDOG_DATA_DIR", format!("{}", cat_and_dog_data_dir));
+        unsafe {
+            std::env::set_var("CATDOG_DATA_DIR", format!("{}", cat_and_dog_data_dir));
+        }
    }

    fn setup_py_env() {
--- a/tests/python/binding_tests.py
+++ b/tests/python/binding_tests.py
@@ -48,7 +48,6 @@ def test_py_run_args():
    run_args = ezkl.PyRunArgs()
    run_args.input_visibility = "hashed"
    run_args.output_visibility = "hashed"
-    run_args.tolerance = 1.5


 def test_poseidon_hash():
@@ -873,7 +872,8 @@ def get_examples():
        'linear_regression',
        "mnist_gan",
        "smallworm",
-        "fr_age"
+        "fr_age",
+        "1d_conv",
    ]
    examples = []
    for subdir, _, _ in os.walk(os.path.join(examples_path, "onnx")):
@@ -900,7 +900,12 @@ async def test_all_examples(model_file, input_file):
    proof_path = os.path.join(folder_path, 'proof.json')

    print("Testing example: ", model_file)
-    res = ezkl.gen_settings(model_file, settings_path)
+
+    run_args = ezkl.PyRunArgs()
+    run_args.variables = [("batch_size", 1), ("sequence_length", 100), ("<Sym1>", 1)]
+    run_args.logrows = 22
+
+    res = ezkl.gen_settings(model_file, settings_path, py_run_args=run_args)
    assert res

    res = await ezkl.calibrate_settings(
--- a/tests/wasm.rs
+++ b/tests/wasm.rs
@@ -337,7 +337,7 @@ mod wasm32 {
        // Run compiled circuit validation on onnx network (should fail)
        let circuit = compiledCircuitValidation(wasm_bindgen::Clamped(NETWORK.to_vec()));
        assert!(circuit.is_err());
-        // Run compiled circuit validation on comiled network (should pass)
+        // Run compiled circuit validation on compiled network (should pass)
        let circuit = compiledCircuitValidation(wasm_bindgen::Clamped(NETWORK_COMPILED.to_vec()));
        assert!(circuit.is_ok());
        // Run input validation on witness (should fail)
Author	SHA1	Message	Date
dante	ca354f9261	refactor: allow for negative stride downsample	2025-03-13 16:33:36 -04:00
dante	ab4997d0c2	chore: update docs and panics (#952 )	2025-03-10 11:32:28 -04:00
dante	701e69dd2f	fix: handle [] shapes in sort (#954 )	2025-03-08 13:17:45 -05:00
dante	f631445e26	docs: document arguments better (#950 )	2025-03-05 16:10:50 -05:00
dante	fcbb27677f	fix: empty dim len can be 1 (#949 )	2025-02-28 23:56:19 -05:00
dante	bc26691bd5	chore: smaller cat dog example (#947 )	2025-02-28 10:37:08 -05:00
dante	73c813a81d	feat: pass data directly in cli (#939 )	2025-02-13 12:35:13 -05:00
dante	ae076aef09	refactor: rm tolerance parameter (#937 )	2025-02-11 12:57:18 -05:00
dante	a7544f4060	feat: generalize conv mem layout and ND (#935 )	2025-02-10 09:11:58 -05:00
dante	c19fa5218a	refactor: enforce max decomp base/legs in args (#936 )	2025-02-09 16:15:40 -05:00
rebustron	eb205d0c73	chore: fix typos in comments and docs (#934 )	2025-02-08 19:13:17 -05:00
				`@@ -0,0 +1 @@`
				{"run_args":{"input_scale":7,"param_scale":7,"scale_rebase_multiplier":1,"lookup_range":[-32768,32768],"logrows":17,"num_inner_cols":2,"variables":[["batch_size",1]],"input_visibility":"Private","output_visibility":"Public","param_visibility":"Private","rebase_frac_zero_constants":false,"check_mode":"UNSAFE","commitment":"KZG","decomp_base":16384,"decomp_legs":2,"bounded_log_lookup":false,"ignore_range_check_inputs_outputs":false},"num_rows":54,"total_assignments":109,"total_const_size":4,"total_dynamic_col_size":0,"max_dynamic_input_len":0,"num_dynamic_lookups":0,"num_shuffles":0,"total_shuffle_col_size":0,"model_instance_shapes":[[1,1]],"model_output_scales":[7],"model_input_scales":[7],"module_sizes":{"polycommit":[],"poseidon":[0,[0]]},"required_lookups":[],"required_range_checks":[[-1,1],[0,16383]],"check_mode":"UNSAFE","version":"0.0.0","num_blinding_factors":null,"timestamp":1739396322131,"input_types":["F32"],"output_types":["F32"]}