Merge pull request #609 from gizatechxyz/develop

Merge Develop into Main

.github/workflows/test.yaml

@@ -9,5 +9,5 @@ jobs:
       - uses: actions/checkout@v3
       - uses: software-mansion/setup-scarb@v1
         with:
-          scarb-version: "2.5.3"
+          scarb-version: "2.6.4"
       - run: scarb test --workspace && scarb fmt --workspace

.tool-versions

@@ -1 +1 @@
-scarb 2.5.3
+scarb 2.6.4

Scarb.toml

@@ -1,7 +1,7 @@
 [package]
 name = "orion"
-version = "0.2.4"
-cairo-version = "2.5.3"
+version = "0.2.5"
+cairo-version = "2.6.3"
 edition = "2023_10"
 description = "ONNX Runtime in Cairo for verifiable ML inference using STARK"
 homepage = "https://github.com/gizatechxyz/orion"

docs/framework/operators/tensor/README.md

@@ -55,7 +55,8 @@ use orion::operators::tensor::TensorTrait;
 | [`tensor.min_in_tensor`](tensor.min\_in\_tensor.md) | Returns the minimum value in the tensor. |
 | [`tensor.min`](tensor.min.md) | Returns the minimum value in the tensor. |
 | [`tensor.max`](tensor.max.md) | Returns the maximum value in the tensor. |
-| [`tensor.reduce_sum`](tensor.reduce\_sum.md) | Reduces a tensor by summing its elements along a specified axis. |
+| [`tensor.reduce_sum`](tensor.reduce\_sum.md) | Computes the sum of the input tensor's elements along the provided axes. |
+| [`tensor.reduce_sum_single_axis`](tensor.reduce\_sum\_single\_axis.md) | Reduces a tensor by summing its elements along a specified axis. |
 | [`tensor.reduce_prod`](tensor.reduce\_prod.md) | Reduces a tensor to its products along specified axis. |
 | [`tensor.argmax`](tensor.argmax.md) | Returns the index of the maximum value along the specified axis. |
 | [`tensor.argmin`](tensor.argmin.md) | Returns the index of the minimum value along the specified axis. |

docs/framework/operators/tensor/tensor.reduce_sum.md

@@ -4,13 +4,14 @@
    fn reduce_sum(self: @Tensor<T>, axis: usize, keepdims: bool) -> Tensor<T>;
 ```
 
-Reduces a tensor by summing its elements along a specified axis.
+Computes the sum of the input tensor's elements along the provided axes
 
 ## Args
 
 * `self`(`@Tensor<T>`) - The input tensor.
-* `axis`(`usize`) - The dimension to reduce.
-* `keepdims`(`bool`) - If true, retains reduced dimensions with length 1.
+* `axes`(`Option<Span<usize>>`) - Optional input list of integers, along which to reduce.
+* `keepdims`(`Option<bool>`) - If true, retains reduced dimensions with length 1.
+* `noop_with_empty_axes`(`Option<bool>`) - Defines behavior if 'axes' is empty. Default behavior with 'false' is to reduce all axes. When axes is empty and this attribute is set to true, input tensor will not be reduced,and the output tensor would be equivalent to input tensor.
 
 ## Panics 
 
@@ -29,11 +30,11 @@ use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
 
 fn reduce_sum_example() -> Tensor<u32> {
     let tensor = TensorTrait::<u32>::new(
-        shape: array![2, 2, 2].span(), data: array![0, 1, 2, 3, 4, 5, 6, 7].span(),
+        shape: array![3, 2, 2].span(), data: array![1, 2, 3, 4, 5, 6, 7, 8 ,9, 10, 11, 12].span(),
     );
 
     // We can call `reduce_sum` function as follows.
-    return tensor.reduce_sum(axis: 0, keepdims: false);
+    return tensor.reduce_sum(Option::Some(array![1].span()), Option::Some(false), Option::None);
 }
->>> [[4,6],[8,10]]
+>>> [[4, 6] [12, 14] [20, 22]]
 ```

docs/framework/operators/tensor/tensor.reduce_sum_single_axis.md

@@ -0,0 +1,39 @@
+## tensor.reduce_sum_single_axis
+
+```rust 
+   fn reduce_sum_single_axis(self: @Tensor<T>, axis: usize, keepdims: bool) -> Tensor<T>;
+```
+
+Reduces a tensor by summing its elements along a specified axis.
+
+## Args
+
+* `self`(`@Tensor<T>`) - The input tensor.
+* `axis`(`usize`) - The dimension to reduce.
+* `keepdims`(`bool`) - If true, retains reduced dimensions with length 1.
+
+## Panics 
+
+* Panics if axis is not in the range of the input tensor's dimensions.
+
+## Returns
+
+A new `Tensor<T>` instance with the specified axis reduced by summing its elements.
+
+## Examples
+
+```rust
+use core::array::{ArrayTrait, SpanTrait};
+
+use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor};
+
+fn reduce_sum_single_axis_example() -> Tensor<u32> {
+    let tensor = TensorTrait::<u32>::new(
+        shape: array![2, 2, 2].span(), data: array![0, 1, 2, 3, 4, 5, 6, 7].span(),
+    );
+
+    // We can call `reduce_sum_single_axis` function as follows.
+    return tensor.reduce_sum_single_axis(axis: 0, keepdims: false);
+}
+>>> [[4,6],[8,10]]
+```

nodegen/file_manager.py

@@ -91,25 +91,36 @@ def base_template(
         This method generates a list of strings that form the template of a Cairo test function,
         including module imports, function definition, and assertions.
         """
-        return [
+        template = [
             *[f"mod input_{i};" for i in range(arg_cnt)],
             *[f"mod output_{i};" for i in range(out_cnt)],
-            *[""],
-            *[""],
+            "",
+            "",
             *[f"use {ref};" for ref in refs],
-            *[""],
-            *["#[test]"],
-            *["#[available_gas(2000000000)]"],
-            *[f"fn test_{name}()" + " {"],
+            "",
+            "#[test]",
+            "#[available_gas(2000000000)]",
+            f"fn test_{name}()" + " {",
             *[f"    let input_{i} = input_{i}::input_{i}();" for i in range(arg_cnt)],
             *[f"    let z_{i} = output_{i}::output_{i}();" for i in range(out_cnt)],
-            *[""],
-            *[f"    let ({', '.join(f'y_{i}' for i in range(out_cnt))}) = {func_sig};"],
-            *[""],
-            *[f"    assert_eq(y_{i}, z_{i});" for i in range(out_cnt)],
-            *["}"],
+            ""
         ]
 
+        # Handling conditional function signature based on the number of outputs
+        if out_cnt > 1:
+            template.append(f"    let ({', '.join(f'y_{i}' for i in range(out_cnt))}) = {func_sig};")
+        else:
+            template.append(f"    let y_0 = {func_sig};")
+
+        # Continue appending to the template
+        template.extend([
+            "",
+            *[f"    assert_eq(y_{i}, z_{i});" for i in range(out_cnt)],
+            "}"
+        ])
+
+        return template
+
     @classmethod
     def sequence_template(cls, name: str, arg_cnt: int, refs: list[str], func_sig: str) -> list[str]:
         """