burn-onnx 0.21.0-pre.3

Library for importing ONNX models into the Burn framework
Documentation 
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use super::prelude::*;

impl NodeCodegen for onnx_ir::node::xor::XorNode {
    fn inputs(&self) -> &[Argument] {
        &self.inputs
    }

    fn outputs(&self) -> &[Argument] {
        &self.outputs
    }

    fn forward(&self, scope: &mut ScopeAtPosition<'_>) -> TokenStream {
        let lhs = self.inputs.first().unwrap();
        let rhs = self.inputs.get(1).unwrap();
        let output = arg_to_ident(self.outputs.first().unwrap());

        let lhs_value = scope.arg(lhs);

        let rhs_value = scope.arg(rhs);

        let function = match (&lhs.ty, &rhs.ty) {
            (lhs_ty, rhs_ty) if lhs_ty.is_on_device() && rhs_ty.is_on_device() => {
                let lhs_rank = lhs_ty.rank();
                let rhs_rank = rhs_ty.rank();
                let lhs_bc =
                    broadcast_helpers::leading_broadcast(quote! { #lhs_value }, lhs_rank, rhs_rank);
                let rhs_bc =
                    broadcast_helpers::leading_broadcast(quote! { #rhs_value }, rhs_rank, lhs_rank);
                // XOR is implemented as not_equal for boolean tensors
                quote! { #lhs_bc.not_equal(#rhs_bc) }
            }
            (ArgType::ScalarNative(_), rhs_ty) if rhs_ty.is_on_device() => quote! {
                if #lhs_value { #rhs_value.bool_not() } else { #rhs_value }
            },
            (lhs_ty, ArgType::ScalarNative(_)) if lhs_ty.is_on_device() => quote! {
                if #rhs_value { #lhs_value.bool_not() } else { #lhs_value }
            },
            (ArgType::ScalarNative(_), ArgType::ScalarNative(_)) => {
                quote! { #lhs_value ^ #rhs_value }
            }
            (ArgType::Shape(_), ArgType::Shape(_)) => quote! {
                {
                    let mut result = #lhs_value;
                    for (result_item, rhs_item) in result.iter_mut().zip(#rhs_value.iter()) {
                        *result_item = if (*result_item != 0) ^ (*rhs_item != 0) { 1i64 } else { 0i64 };
                    }
                    result
                }
            },
            _ => panic!("Xor operation requires tensor, scalar, or shape inputs"),
        };

        quote! {
            let #output = #function;
        }
    }
}

#[cfg(test)]
mod tests {
    use super::super::test_helpers::*;
    use burn::tensor::{BoolStore, DType};
    use insta::assert_snapshot;
    use onnx_ir::node::xor::XorNodeBuilder;

    #[test]
    fn test_xor_scalar_tensor_forward() {
        let node = XorNodeBuilder::new("xor1")
            .input_scalar("lhs", DType::Bool(BoolStore::Native))
            .input_tensor("rhs", 4, DType::Bool(BoolStore::Native))
            .output_tensor("output", 4, DType::Bool(BoolStore::Native))
            .build();
        let code = codegen_forward_default(&node);
        assert_snapshot!(code, @r"
        pub fn forward(&self, lhs: bool, rhs: Tensor<B, 4, Bool>) -> Tensor<B, 4, Bool> {
            let output = if lhs { rhs.bool_not() } else { rhs };
            output
        }
        ");
    }

    #[test]
    fn test_xor_tensor_scalar_forward() {
        let node = XorNodeBuilder::new("xor1")
            .input_tensor("lhs", 4, DType::Bool(BoolStore::Native))
            .input_scalar("rhs", DType::Bool(BoolStore::Native))
            .output_tensor("output", 4, DType::Bool(BoolStore::Native))
            .build();
        let code = codegen_forward_default(&node);
        assert_snapshot!(code, @r"
        pub fn forward(&self, lhs: Tensor<B, 4, Bool>, rhs: bool) -> Tensor<B, 4, Bool> {
            let output = if rhs { lhs.bool_not() } else { lhs };
            output
        }
        ");
    }

    #[test]
    fn test_xor_shape_forward() {
        let node = XorNodeBuilder::new("xor1")
            .input_shape("lhs", 3)
            .input_shape("rhs", 3)
            .output_shape("output", 3)
            .build();
        let code = codegen_forward_default(&node);
        assert_snapshot!(code, @r"
        pub fn forward(&self, lhs: [i64; 3], rhs: [i64; 3]) -> [i64; 3] {
            let output = {
                let mut result = lhs;
                for (result_item, rhs_item) in result.iter_mut().zip(rhs.iter()) {
                    *result_item = if (*result_item != 0) ^ (*rhs_item != 0) {
                        1i64
                    } else {
                        0i64
                    };
                }
                result
            };
            output
        }
        ");
    }

    #[test]
    fn test_xor_forward() {
        let node = XorNodeBuilder::new("xor1")
            .input_tensor("lhs", 2, DType::Bool(BoolStore::Native))
            .input_tensor("rhs", 2, DType::Bool(BoolStore::Native))
            .output_tensor("output", 2, DType::Bool(BoolStore::Native))
            .build();
        let code = codegen_forward_default(&node);
        assert_snapshot!(code, @r"
        pub fn forward(
            &self,
            lhs: Tensor<B, 2, Bool>,
            rhs: Tensor<B, 2, Bool>,
        ) -> Tensor<B, 2, Bool> {
            let output = lhs.not_equal(rhs);
            output
        }
        ");
    }
}