Add Clone trait to the OptimizerAdaptor and Clone implementations to the optimizers (#1770)

Author: getumen

crates/burn-core/src/grad_clipping/base.rs

@@ -30,6 +30,7 @@ impl GradientClippingConfig {
 /// Gradient Clipping provides a way to mitigate exploding gradients
 /// by clipping every component of the gradient by value or by norm during
 /// backpropagation.
+#[derive(Clone)]
 pub enum GradientClipping {
     /// Clip the gradient by value.
     Value(f32),

crates/burn-core/src/optim/adagrad.rs

@@ -26,6 +26,7 @@ pub struct AdaGradConfig {
 }
 
 /// AdaGrad optimizer
+#[derive(Clone)]
 pub struct AdaGrad<B: Backend> {
     lr_decay: LrDecay,
     weight_decay: Option<WeightDecay<B>>,
@@ -105,6 +106,7 @@ pub struct LrDecayState<B: Backend, const D: usize> {
     sum: Tensor<B, D>,
 }
 
+#[derive(Clone)]
 struct LrDecay {
     lr_decay: f64,
     epsilon: f32,

crates/burn-core/src/optim/adam.rs

@@ -31,6 +31,7 @@ pub struct AdamConfig {
 }
 
 /// Adam optimizer as described in the paper [Adam: A Method for Stochastic Optimization](https://arxiv.org/pdf/1412.6980.pdf).
+#[derive(Clone)]
 pub struct Adam<B: Backend> {
     momentum: AdaptiveMomentum,
     weight_decay: Option<WeightDecay<B>>,
@@ -113,6 +114,7 @@ pub struct AdaptiveMomentumState<B: Backend, const D: usize> {
     moment_2: Tensor<B, D>,
 }
 
+#[derive(Clone)]
 struct AdaptiveMomentum {
     beta_1: f32,
     beta_2: f32,

crates/burn-core/src/optim/adamw.rs

@@ -30,6 +30,7 @@ pub struct AdamWConfig {
 }
 
 /// AdamW optimizer as described in the paper [Decoupled Weight Decay Regularization, Loshchilov and Hutter, 2019](https://arxiv.org/abs/1711.05101).
+#[derive(Clone)]
 pub struct AdamW<B: Backend> {
     momentum: AdaptiveMomentumW,
     weight_decay: f32,
@@ -112,6 +113,7 @@ pub struct AdaptiveMomentumWState<B: Backend, const D: usize> {
     moment_2: Tensor<B, D>,
 }
 
+#[derive(Clone)]
 struct AdaptiveMomentumW {
     beta_1: f32,
     beta_2: f32,

crates/burn-core/src/optim/decay.rs

@@ -20,6 +20,7 @@ pub struct WeightDecayState<B: Backend, const D: usize> {
 }
 
 /// Weight decay implementation that transforms gradients.
+#[derive(Clone)]
 pub struct WeightDecay<B: Backend> {
     penalty: B::FloatElem,
 }

crates/burn-core/src/optim/momentum.rs

@@ -27,6 +27,7 @@ pub struct MomentumState<B: Backend, const D: usize> {
 }
 
 /// Momemtum implementation that transforms gradients.
+#[derive(Clone)]
 pub struct Momentum<B: Backend> {
     momentum: B::FloatElem,
     dampening: f64,

crates/burn-core/src/optim/rmsprop.rs

@@ -64,6 +64,7 @@ impl RmsPropConfig {
 
 /// Optimizer that implements stochastic gradient descent with momentum.
 /// The optimizer can be configured with [RmsPropConfig](RmsPropConfig).
+#[derive(Clone)]
 pub struct RmsProp<B: Backend> {
     alpha: f32,
     // epsilon: f32,
@@ -251,6 +252,7 @@ impl<B: Backend, const D: usize> CenteredState<B, D> {
 
 /// [RmsPropMomentum](RmsPropMomentum) is to store config status for optimizer.
 /// (, which is stored in [optimizer](RmsProp) itself and not passed in during `step()` calculation)
+#[derive(Clone)]
 pub struct RmsPropMomentum {
     momentum: f32,
     epsilon: f32,

crates/burn-core/src/optim/sgd.rs

@@ -25,6 +25,7 @@ pub struct SgdConfig {
 /// Optimizer that implements stochastic gradient descent with momentum.
 ///
 /// The optimizer can be configured with [SgdConfig](SgdConfig).
+#[derive(Clone)]
 pub struct Sgd<B: Backend> {
     momentum: Option<Momentum<B>>,
     weight_decay: Option<WeightDecay<B>>,

crates/burn-core/src/optim/simple/adaptor.rs

@@ -11,6 +11,7 @@ use hashbrown::HashMap;
 
 /// Wrapper struct that adapts any [simple optimizer](SimpleOptimizer) into
 /// an [optimizer](Optimizer).
+#[derive(Clone)]
 pub struct OptimizerAdaptor<O, M, B>
 where
     O: SimpleOptimizer<B::InnerBackend>,

crates/burn-core/src/optim/simple/base.rs

@@ -6,7 +6,7 @@ use burn_tensor::{backend::Backend, Tensor};
 ///
 /// Implementations don't have to handle missing gradients, loading and exporting records, navigate the
 /// module parameter structure, handle tracked and untracked tensors, and the likes.
-pub trait SimpleOptimizer<B>: Send + Sync
+pub trait SimpleOptimizer<B>: Send + Sync + Clone
 where
     B: Backend,
 {