use super::prelude::*;

impl NodeCodegen for onnx_ir::comparison::EqualNode {
    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) {
            (ArgType::Tensor(lhs_tensor), ArgType::Tensor(rhs_tensor)) => {
                let lhs_rank = lhs_tensor.rank;
                let rhs_rank = rhs_tensor.rank;

                if lhs_rank == rhs_rank {
                    quote! { #lhs_value.equal(#rhs_value) }
                } else if lhs_rank > rhs_rank {
                    let num_dims = lhs_rank - rhs_rank;
                    let dims: Vec<isize> = (0..num_dims).map(|i| i as isize).collect();
                    quote! { #lhs_value.equal(#rhs_value.unsqueeze_dims(&[#(#dims),*])) }
                } else {
                    let num_dims = rhs_rank - lhs_rank;
                    let dims: Vec<isize> = (0..num_dims).map(|i| i as isize).collect();
                    quote! { #lhs_value.unsqueeze_dims(&[#(#dims),*]).equal(#rhs_value) }
                }
            }
            (ArgType::Scalar(_), ArgType::Scalar(_)) => 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 == rhs_item { 1i64 } else { 0i64 };
                    }
                    result
                }
            },
            (ArgType::Shape(_), ArgType::Tensor(tensor_type)) => {
                let dtype_tokens = tensor_type.dtype.to_tokens();
                quote! {
                    {
                        let shape_tensor = Tensor::<B, 1, Int>::from_data_dtype(
                            burn::tensor::TensorData::from(#lhs_value.as_slice()),
                            &*self.device,
                            #dtype_tokens
                        );
                        shape_tensor.equal(#rhs_value)
                    }
                }
            }
            (ArgType::Tensor(tensor_type), ArgType::Shape(_)) => {
                let dtype_tokens = tensor_type.dtype.to_tokens();
                quote! {
                    {
                        let shape_tensor = Tensor::<B, 1, Int>::from_data_dtype(
                            burn::tensor::TensorData::from(#rhs_value.as_slice()),
                            &*self.device,
                            #dtype_tokens
                        );
                        #lhs_value.equal(shape_tensor)
                    }
                }
            }
            _ => panic!(
                "Comparison is supported for tensor to tensor, scalar to scalar, shape to shape, and shape to tensor only"
            ),
        };

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

#[cfg(test)]
mod tests {
    use super::super::test_helpers::*;
    use burn::tensor::DType;
    use insta::assert_snapshot;
    use onnx_ir::comparison::EqualNodeBuilder;

    #[test]
    fn test_equal_forward() {
        let node = EqualNodeBuilder::new("equal1")
            .input_tensor("lhs", 2, DType::F32)
            .input_tensor("rhs", 2, DType::F32)
            .output_tensor("output", 2, DType::Bool)
            .build();
        let code = codegen_forward_default(&node);
        assert_snapshot!(code, @r"
        pub fn forward(&self, lhs: Tensor<B, 2>, rhs: Tensor<B, 2>) -> Tensor<B, 2, Bool> {
            let output = lhs.equal(rhs);
            output
        }
        ");
    }
}
