dep(optimizer): remove derive_more dependency

concrete-optimizer/Cargo.toml

@@ -8,7 +8,6 @@ edition = "2021"
 [dependencies]
 concrete-commons = { git = "ssh://git@github.com/zama-ai/concrete-core.git", rev = "715d4a18a59d13a5a51fee14bc1f6578de665c20" }
 concrete-npe = { git = "ssh://git@github.com/zama-ai/concrete-core.git", rev = "715d4a18a59d13a5a51fee14bc1f6578de665c20" }
-derive_more = "0.99.17"
 file-lock = "2.1.6"
 static_init = "1.0.3"
 serde = { version = "1.0", features = ["derive"] }

concrete-optimizer/src/dag/operator/operator.rs

@@ -1,5 +1,4 @@
 use crate::dag::operator::tensor::{ClearTensor, Shape};
-use derive_more::{Add, AddAssign};
 
 pub type Weights = ClearTensor<i64>;
 
@@ -12,7 +11,7 @@ impl FunctionTable {
     pub const UNKWOWN: Self = Self { values: vec![] };
 }
 
-#[derive(Clone, Copy, PartialEq, Add, AddAssign, Debug)]
+#[derive(Clone, Copy, PartialEq, Debug)]
 pub struct LevelledComplexity {
     pub lwe_dim_cost_factor: f64,
     pub fixed_cost: f64,
@@ -35,6 +34,24 @@ impl LevelledComplexity {
     }
 }
 
+impl std::ops::Add for LevelledComplexity {
+    type Output = Self;
+
+    fn add(self, rhs: Self) -> Self::Output {
+        Self {
+            lwe_dim_cost_factor: self.lwe_dim_cost_factor + rhs.lwe_dim_cost_factor,
+            fixed_cost: self.fixed_cost + rhs.fixed_cost,
+        }
+    }
+}
+
+impl std::ops::AddAssign for LevelledComplexity {
+    fn add_assign(&mut self, rhs: Self) {
+        self.lwe_dim_cost_factor += rhs.lwe_dim_cost_factor;
+        self.fixed_cost += rhs.fixed_cost;
+    }
+}
+
 impl std::ops::Mul<u64> for LevelledComplexity {
     type Output = Self;
     fn mul(self, factor: u64) -> Self {

concrete-optimizer/src/optimization/dag/solo_key/symbolic_variance.rs

@@ -1,4 +1,5 @@
-use derive_more::{Add, AddAssign, Sum};
+use std::iter::Sum;
+
 /**
  * A variance that is represented as a linear combination of base variances.
  * Only the linear coefficient are known.
@@ -12,7 +13,7 @@ use derive_more::{Add, AddAssign, Sum};
  * Each linear coefficient is a variance factor.
  * There are homogenious to squared weight (or summed square weights or squared norm2).
  */
-#[derive(Clone, Copy, Add, AddAssign, Sum, Debug, PartialEq, PartialOrd)]
+#[derive(Clone, Copy, Debug, PartialEq, PartialOrd)]
 pub struct SymbolicVariance {
     pub lut_coeff: f64,
     pub input_coeff: f64,
@@ -31,6 +32,36 @@ pub enum VarianceOrigin {
     Mixed,
 }
 
+impl std::ops::Add for SymbolicVariance {
+    type Output = Self;
+
+    fn add(self, rhs: Self) -> Self::Output {
+        Self {
+            lut_coeff: self.lut_coeff + rhs.lut_coeff,
+            input_coeff: self.input_coeff + rhs.input_coeff,
+        }
+    }
+}
+
+impl std::ops::AddAssign for SymbolicVariance {
+    fn add_assign(&mut self, rhs: Self) {
+        self.lut_coeff += rhs.lut_coeff;
+        self.input_coeff += rhs.input_coeff;
+    }
+}
+
+impl Sum for SymbolicVariance {
+    fn sum<I: Iterator<Item = Self>>(iter: I) -> Self {
+        let mut accumulator = Self::ZERO;
+
+        for item in iter {
+            accumulator += item;
+        }
+
+        accumulator
+    }
+}
+
 impl std::ops::Mul<f64> for SymbolicVariance {
     type Output = Self;
     fn mul(self, sq_weight: f64) -> Self {