Updates

.cargo/config.toml

@@ -0,0 +1,8 @@
+# for Linux
+[target.x86_64-unknown-linux-gnu]
+linker = "clang"
+rustflags = ["-C", "link-arg=-fuse-ld=lld"]
+
+# for Windows
+[target.x86_64-pc-windows-msvc]
+linker = "rust-lld.exe"

Cargo.lock

@@ -2167,6 +2167,8 @@ dependencies = [
  "ctrlc",
  "rand 0.10.1",
  "rand_distr 0.6.0",
+ "serde",
+ "serde_json",
 ]
 
 [[package]]

engine/Cargo.toml

@@ -10,3 +10,5 @@ burn-ndarray = "0.21.0"
 rand_distr = "0.6.0"
 rand = "0.10.1"
 ctrlc = "3.5.2"
+serde_json = "1.0.150"
+serde = { version = "1.0.228", features = ["derive"] }

engine/src/main.rs

@@ -1,8 +1,7 @@
 #![recursion_limit = "256"]
 
-use burn::backend::Autodiff;
+use burn::backend::{Autodiff, Cuda};
 use burn::optim::AdamConfig;
-use burn_ndarray::NdArray;
 use engine::mcts::MctsConfig;
 use engine::training::train::{train, TrainingConfig};
 // fn main() {
@@ -16,14 +15,14 @@ use engine::training::train::{train, TrainingConfig};
 
 fn main() {
     // type MyBackend = Wgpu<f32, i32>;
-    // type MyBackend = Cuda<f32, i32>;
+    type MyBackend = Cuda<f32, i32>;
-    type MyBackend = NdArray<f32, i32>;
+    // type MyBackend = NdArray<f32, i32>;
     type MyAutodiffBackend = Autodiff<MyBackend>;
     // let device = burn::backend::wgpu::WgpuDevice::default();
-    let device = burn::backend::ndarray::NdArrayDevice::default();
+    // let device = burn::backend::ndarray::NdArrayDevice::default();
-    // let device = burn::backend::cuda::CudaDevice::default();
+    let device = burn::backend::cuda::CudaDevice::default();
 
-    let mcts_config = MctsConfig::new(100, 1.0, 0.05, 0.25);
+    let mcts_config = MctsConfig::new(400, 1.0, 0.05, 0.25, 128);
 
     let adam_config = AdamConfig::new();
 
@@ -41,6 +40,7 @@ fn main() {
         mcts_config,
         optimizer: adam_config,
         lr: 2e-4,
+        seed: None,
     };
 
     train::<MyAutodiffBackend>(training_config, device);

engine/src/mcts.rs

@@ -80,6 +80,7 @@ pub struct MctsConfig {
     pub c_puct: f32,
     pub dirichlet_alpha: f32,
     pub dirichlet_epsilon: f32,
+    pub batch_max: usize,
 }
 
 impl MctsConfig {
@@ -88,19 +89,21 @@ impl MctsConfig {
         c_puct: f32,
         dirichlet_alpha: f32,
         dirichlet_epsilon: f32,
+        batch_max: usize,
     ) -> MctsConfig {
         MctsConfig {
             num_simulations,
             c_puct,
             dirichlet_alpha,
             dirichlet_epsilon,
+            batch_max,
         }
     }
 }
 
 impl Default for MctsConfig {
     fn default() -> MctsConfig {
-        MctsConfig::new(400, 1.0, 0.05, 0.25)
+        MctsConfig::new(400, 1.0, 0.05, 0.25, 64)
     }
 }
 
@@ -128,10 +131,8 @@ impl<B: Backend> Mcts<B> {
         self.add_dirichlet_noise(root, &mut nodes);
 
         // We'll batch leaf evaluations to reduce per-leaf model calls and device-host syncs.
-        let mut sims_done = 0usize;
+        let mut sims_done: usize = 0;
         let num_sims = self.config.num_simulations;
-        // Tunable batch size for NN evaluation. Small value is safe; larger values increase throughput on GPU.
-        let batch_max = 32usize;
 
         while sims_done < num_sims {
             // Collect a batch of leaf nodes (and their selection paths)
@@ -139,7 +140,7 @@ impl<B: Backend> Mcts<B> {
             let mut leaf_paths: Vec<Vec<usize>> = Vec::new();
             let mut leaf_states: Vec<Tensor<B, 4>> = Vec::new();
 
-            while leaf_nodes.len() < std::cmp::min(batch_max, num_sims - sims_done) {
+            while leaf_nodes.len() < std::cmp::min(self.config.batch_max, num_sims - sims_done) {
                 let mut path = vec![root];
                 let mut current = root;
 
@@ -153,7 +154,8 @@ impl<B: Backend> Mcts<B> {
                 leaf_paths.push(path.clone());
 
                 // Prepare state tensor for this leaf
-                let state: Tensor<B, 4> = encode_board_state_perspective(&nodes[current].board_state, device)
+                let state: Tensor<B, 4> =
+                    encode_board_state_perspective(&nodes[current].board_state, device)
                         .reshape([1, 18, 8, 8]);
                 leaf_states.push(state);
 
@@ -184,32 +186,51 @@ impl<B: Backend> Mcts<B> {
                 let logits = &policy_data[start..end];
 
                 // Convert logits to probabilities with a numerically-stable softmax on host
-                let mut max_logit = std::f32::NEG_INFINITY;
+                let mut max_logit = f32::NEG_INFINITY;
                 for &v in logits.iter() {
                     if v > max_logit {
                         max_logit = v;
                     }
                 }
-                let mut exps_sum = 0.0f32;
+                if logits.is_empty() {
-                // We'll build a Vec<f32> of probabilities lazily when needed
+                    println!("logits empty")
-                let mut probs: Vec<f32> = Vec::new();
-                probs.resize(num_moves, 0.0);
-                for (j, &v) in logits.iter().enumerate() {
-                    let e = (v - max_logit).exp();
-                    probs[j] = e;
-                    exps_sum += e;
                 }
-                if exps_sum > 0.0 {
+                if !max_logit.is_finite() {
-                    for p in probs.iter_mut() {
+                    println!("max logits not finite")
+                }
+
+                let mut exps_sum = 0.0f32;
+                let mut probs = vec![0.0f32; num_moves];
+
+                for (j, &v) in logits.iter().enumerate() {
+                    let x = (v - max_logit).exp();
+
+                    if !x.is_finite() {
+                        probs[j] = 0.0;
+                    } else {
+                        probs[j] = x;
+                        exps_sum += x;
+                    }
+                }
+
+                if exps_sum > 0.0 && exps_sum.is_finite() {
+                    for p in &mut probs {
                         *p /= exps_sum;
                     }
+                } else {
+                    // fallback: uniform or zero
+                    let uniform = 1.0 / num_moves as f32;
+                    for p in &mut probs {
+                        *p = uniform;
+                    }
                 }
 
                 // Expand: add legal moves as children with prior from probs
-                let legal_moves: Vec<ChessMove> = MoveGen::new_legal(&nodes[node_idx].board_state.board).collect();
+                let legal_moves: Vec<ChessMove> =
+                    MoveGen::new_legal(&nodes[node_idx].board_state.board).collect();
                 for mv in legal_moves {
                     let stm = nodes[node_idx].board_state.board.side_to_move();
-                    let idx = encode_move(mv, stm);
+                    let idx = encode_move(mv, stm).expect("Invalid move");
                     let prior = probs[idx];
 
                     let mut new_board = nodes[node_idx].board_state.clone();
@@ -233,7 +254,7 @@ impl<B: Backend> Mcts<B> {
         let denom = self.config.num_simulations as f32;
         for child_idx in nodes[root].children.iter() {
             let mv = nodes[*child_idx].last_move.expect("move didnt exist");
-            let enc = encode_move(mv, stm);
+            let enc = encode_move(mv, stm).expect("Invalid move");
             let prob = nodes[*child_idx].visit_count as f32 / denom;
             move_dist.push((enc, prob));
         }
@@ -280,7 +301,7 @@ impl<B: Backend> Mcts<B> {
 
             for mv in legal_moves {
                 let stm = arena[node_idx].board_state.board.side_to_move();
-                let idx = encode_move(mv, stm);
+                let idx = encode_move(mv, stm).expect("Invalid move");
                 let prior = policy[idx];
 
                 let mut new_board = arena[node_idx].board_state.clone();

engine/src/net/encoding.rs

@@ -20,6 +20,38 @@ Output:
 65-73: underpromotions
 */
 
+const PLANES_PER_SQUARE: usize = 73;
+
+const SLIDING_DIRS: [(i8, i8); 8] = [
+    (0, 1),   // N
+    (1, 1),   // NE
+    (1, 0),   // E
+    (1, -1),  // SE
+    (0, -1),  // S
+    (-1, -1), // SW
+    (-1, 0),  // W
+    (-1, 1),  // NW
+];
+
+const KNIGHT_DIRS: [(i8, i8); 8] = [
+    (1, 2),
+    (2, 1),
+    (2, -1),
+    (1, -2),
+    (-1, -2),
+    (-2, -1),
+    (-2, 1),
+    (-1, 2),
+];
+
+const UNDERPROMO_DIRS: [(i8, i8); 3] = [
+    (-1, 1), // capture left
+    (0, 1),  // forward
+    (1, 1),  // capture right
+];
+
+const UNDERPROMO_PIECES: [Piece; 3] = [Piece::Knight, Piece::Bishop, Piece::Rook];
+
 pub fn encode_board_state_perspective<B: Backend>(
     state: &BoardState,
     device: &B::Device,
@@ -120,180 +152,163 @@ fn fill_plane(buffer: &mut [f32], plane: usize) {
     }
 }
 
-pub fn encode_move(mv: ChessMove, side_to_move: Color) -> usize {
+/// Rotate a square into the side-to-move perspective.
-    let from = mv.get_source().to_index();
+fn orient_square(sq: Square, stm: Color) -> (i8, i8) {
-    let to = mv.get_dest().to_index();
+    let file = sq.get_file().to_index() as i8;
+    let rank = sq.get_rank().to_index() as i8;
 
-    let mut from_rank = from / 8;
+    match stm {
-    let mut from_file = from % 8;
+        Color::White => (file, rank),
-    let mut to_rank = to / 8;
+        Color::Black => (7 - file, 7 - rank),
-    let mut to_file = to % 8;
-
-    if side_to_move == Color::Black {
-        from_rank = 7 - from_rank;
-        from_file = 7 - from_file;
-
-        to_rank = 7 - to_rank;
-        to_file = 7 - to_file;
-    }
-
-    let delta_rank = to_rank as i32 - from_rank as i32;
-    let delta_file = to_file as i32 - from_file as i32;
-
-    let plane = encode_move_type(delta_rank, delta_file, mv.get_promotion());
-
-    plane * 64 + (from_rank * 8 + from_file)
-}
-
-fn encode_move_type(dr: i32, df: i32, promotion: Option<Piece>) -> usize {
-    // Knight moves
-    const KNIGHT_DELTAS: [(i32, i32); 8] = [
-        (2, 1),
-        (1, 2),
-        (-1, 2),
-        (-2, 1),
-        (-2, -1),
-        (-1, -2),
-        (1, -2),
-        (2, -1),
-    ];
-
-    for (i, (r, f)) in KNIGHT_DELTAS.iter().enumerate() {
-        if dr == *r && df == *f {
-            return 56 + i;
     }
 }
 
-    // UNDERPromotions
+/// Convert a perspective-space coordinate back into a real square.
-    if let Some(promo) = promotion {
+fn deorient_square(file: i8, rank: i8, stm: Color) -> Square {
+    let (file, rank) = match stm {
+        Color::White => (file, rank),
+        Color::Black => (7 - file, 7 - rank),
+    };
+
+    Square::make_square(
+        Rank::from_index(rank as usize),
+        File::from_index(file as usize),
+    )
+}
+
+/// Encode a move into [0, 4672).
+pub fn encode_move(mv: ChessMove, stm: Color) -> Option<usize> {
+    let (ff, fr) = orient_square(mv.get_source(), stm);
+    let (tf, tr) = orient_square(mv.get_dest(), stm);
+
+    let dx = tf - ff;
+    let dy = tr - fr;
+
+    let plane = if let Some(promo) = mv.get_promotion() {
         if promo != Piece::Queen {
-            let dir = if df == 0 {
+            let dir = UNDERPROMO_DIRS
-                0
+                .iter()
-            } else if df < 0 {
+                .position(|&(x, y)| x == dx && y == dy)?;
-                1
+
+            let piece = UNDERPROMO_PIECES.iter().position(|&p| p == promo)?;
+
+            64 + piece * 3 + dir
         } else {
-                2
+            encode_non_underpromo(dx, dy)?
+        }
+    } else {
+        encode_non_underpromo(dx, dy)?
     };
 
-            let piece_index = match promo {
+    let from_sq = (fr as usize) * 8 + (ff as usize);
-                // Piece::Queen => 0,
+    Some(from_sq * PLANES_PER_SQUARE + plane)
-                Piece::Rook => 0,
+}
-                Piece::Bishop => 1,
+
-                Piece::Knight => 2,
+fn encode_non_underpromo(dx: i8, dy: i8) -> Option<usize> {
-                _ => unreachable!(),
+    // Knight planes: 56..63
+    if let Some(idx) = KNIGHT_DIRS.iter().position(|&(x, y)| x == dx && y == dy) {
+        return Some(56 + idx);
+    }
+
+    // Sliding planes: 0..55
+    for (dir_idx, &(sx, sy)) in SLIDING_DIRS.iter().enumerate() {
+        for dist in 1..=7 {
+            if dx == sx * dist && dy == sy * dist {
+                return Some(dir_idx * 7 + (dist as usize - 1));
+            }
+        }
+    }
+
+    None
+}
+
+/// Decode an index in [0, 4672) back into a ChessMove.
+pub fn decode_move(idx: usize, stm: Color) -> Option<ChessMove> {
+    if idx >= 4672 {
+        return None;
+    }
+
+    let from_idx = idx / PLANES_PER_SQUARE;
+    let plane = idx % PLANES_PER_SQUARE;
+
+    let ff = (from_idx % 8) as i8;
+    let fr = (from_idx / 8) as i8;
+
+    let (dx, dy, promo) = if plane < 56 {
+        let dir = plane / 7;
+        let dist = (plane % 7 + 1) as i8;
+
+        let (sx, sy) = SLIDING_DIRS[dir];
+        (sx * dist, sy * dist, None)
+    } else if plane < 64 {
+        let k = plane - 56;
+        let (dx, dy) = KNIGHT_DIRS[k];
+        (dx, dy, None)
+    } else {
+        let p = plane - 64;
+
+        let piece = UNDERPROMO_PIECES[p / 3];
+        let (dx, dy) = UNDERPROMO_DIRS[p % 3];
+
+        (dx, dy, Some(piece))
     };
 
-            return 64 + dir * 3 + piece_index;
+    let tf = ff + dx;
-        }
+    let tr = fr + dy;
+
+    if !(0..8).contains(&tf) || !(0..8).contains(&tr) {
+        return None;
     }
 
-    // Sliding
+    let from = deorient_square(ff, fr, stm);
-    let direction_index = match (dr.signum(), df.signum()) {
+    let to = deorient_square(tf, tr, stm);
-        (1, 0) => 0, // N
-        (1, 1) => 1,
-        (0, 1) => 2,
-        (-1, 1) => 3,
-        (-1, 0) => 4,
-        (-1, -1) => 5,
-        (0, -1) => 6,
-        (1, -1) => 7,
-        _ => panic!("Invalid move delta"),
-    };
 
-    let distance = dr.abs().max(df.abs()) as usize - 1;
+    Some(ChessMove::new(from, to, promo))
-
-    direction_index * 7 + distance
 }
 
-pub fn decode_move(index: usize, side_to_move: Color) -> ChessMove {
+#[cfg(test)]
-    let from_index = index % 64;
+mod tests {
-    let plane = index / 64;
+    use super::*;
+    use chess::ALL_COLORS;
 
-    // Perspective-space coordinates
+    #[test]
-    let mut from_rank = from_index / 8;
+    fn encoding_roundtrips() {
-    let mut from_file = from_index % 8;
+        for color in ALL_COLORS {
-
+            for action in 0..4672 {
-    let (mut dr, mut df, promotion) = decode_move_type(plane);
+                let decoded = decode_move(action, color);
-
+                if decoded.is_none() {
-    // Convert from perspective coordinates back to absolute board coordinates
+                    continue;
-    if side_to_move == Color::Black {
-        from_rank = 7 - from_rank;
-        from_file = 7 - from_file;
-
-        dr = -dr;
-        df = -df;
                 }
-
+                let decoded = decoded.unwrap();
-    let to_rank = (from_rank as i32 + dr) as usize;
+                let encoded = encode_move(decoded, color).unwrap();
-    let to_file = (from_file as i32 + df) as usize;
+                // eprintln!(
-
+                //     "orig idx = {}, plane={}, from_idx={}",
-    let from = Square::make_square(Rank::from_index(from_rank), File::from_index(from_file));
+                //     action,
-
+                //     action / 64,
-    let to = Square::make_square(Rank::from_index(to_rank), File::from_index(to_file));
+                //     action % 64
-
+                // );
-    ChessMove::new(from, to, promotion)
+                // eprintln!(
+                //     "move = {}, from={}, to={}, promo={:?}",
+                //     decoded,
+                //     decoded.get_source(),
+                //     decoded.get_dest(),
+                //     decoded.get_promotion()
+                // );
+                // eprintln!(
+                //     "decoded = {}, from={}, to={}, promo={:?}",
+                //     decoded,
+                //     decoded.get_source(),
+                //     decoded.get_dest(),
+                //     decoded.get_promotion()
+                // );
+                // eprintln!(
+                //     "re-encoded idx = {}, plane={}, from_idx={}",
+                //     encoded,
+                //     encoded / 64,
+                //     encoded % 64
+                // );
+                assert_eq!(action, encoded);
             }
-
-fn decode_move_type(plane: usize) -> (i32, i32, Option<Piece>) {
-    // Knight moves
-    const KNIGHT_DELTAS: [(i32, i32); 8] = [
-        (2, 1),
-        (1, 2),
-        (-1, 2),
-        (-2, 1),
-        (-2, -1),
-        (-1, -2),
-        (1, -2),
-        (2, -1),
-    ];
-
-    // 0–55: sliding moves
-    if plane < 56 {
-        let direction = plane / 7;
-        let distance = (plane % 7) + 1;
-
-        let (dr, df) = match direction {
-            0 => (1, 0),
-            1 => (1, 1),
-            2 => (0, 1),
-            3 => (-1, 1),
-            4 => (-1, 0),
-            5 => (-1, -1),
-            6 => (0, -1),
-            7 => (1, -1),
-            _ => unreachable!(),
-        };
-
-        return (dr * distance as i32, df * distance as i32, None);
         }
-
-    // 56–63: knight moves
-    if plane < 64 {
-        let (dr, df) = KNIGHT_DELTAS[plane - 56];
-        return (dr, df, None);
     }
-
-    // 64–72: underpromotions
-    let promo_plane = plane - 64;
-
-    let dir = promo_plane / 3;
-    let piece_index = promo_plane % 3;
-
-    let df = match dir {
-        0 => 0,
-        1 => -1,
-        2 => 1,
-        _ => unreachable!(),
-    };
-
-    let dr = 1; // always forward (important: assumes white perspective)
-
-    let promotion = Some(match piece_index {
-        0 => Piece::Rook,
-        1 => Piece::Bishop,
-        2 => Piece::Knight,
-        _ => unreachable!(),
-    });
-
-    (dr, df, promotion)
 }

engine/src/net/model.rs

@@ -32,6 +32,12 @@ Output:
 65-73: underpromotions
 */
 
+#[derive(serde::Serialize, serde::Deserialize)]
+pub struct ModelMetadata {
+    pub(crate) name: String,
+    pub(crate) iterations: usize,
+}
+
 #[derive(Module, Debug)]
 pub struct ResidualBlock<B: Backend> {
     conv1: Conv2d<B>,

engine/src/training/train.rs

@@ -1,6 +1,8 @@
 use crate::mcts::{BoardState, BoardStateStatus, Mcts, MctsConfig, MctsResults};
 use crate::net::encoding::decode_move;
-use crate::net::model::{ChessBatcher, ChessModel, ChessModelConfig, TrainingSample};
+use crate::net::model::{
+    ChessBatcher, ChessModel, ChessModelConfig, ModelMetadata, TrainingSample,
+};
 use burn::data::dataloader::batcher::Batcher;
 use burn::module::{AutodiffModule, Module};
 use burn::optim::{AdamConfig, GradientsParams, Optimizer};
@@ -11,6 +13,8 @@ use rand::rngs::SmallRng;
 use rand::seq::SliceRandom;
 use rand::{RngExt, SeedableRng};
 use std::collections::VecDeque;
+use std::fs::File;
+use std::io::BufReader;
 use std::marker::PhantomData;
 use std::sync::atomic::{AtomicBool, Ordering};
 use std::sync::Arc;
@@ -19,7 +23,7 @@ use std::time::{SystemTime, UNIX_EPOCH};
 
 pub struct TrainingConfig {
     pub max_time_s: Option<u64>,
-    pub num_iters: Option<u32>,
+    pub num_iters: Option<usize>,
     pub max_depth: u16, // unused
     pub model_name: String,
     pub load_model: bool,
@@ -31,10 +35,12 @@ pub struct TrainingConfig {
     pub mcts_config: MctsConfig,
     pub optimizer: AdamConfig,
     pub lr: f64,
+    pub seed: Option<u64>,
 }
 
 pub fn train<B: AutodiffBackend>(training_config: TrainingConfig, device: B::Device) {
     let model_path = format!("artifacts/{}", training_config.model_name.as_str());
+    let metadata_path = format!("{}.json", model_path);
     println!("Creating model...");
     let mut model: ChessModel<B> = ChessModelConfig::init(
         training_config.num_blocks,
@@ -53,7 +59,20 @@ pub fn train<B: AutodiffBackend>(training_config: TrainingConfig, device: B::Dev
     let train = Arc::new(AtomicBool::new(true));
     let train_signal = Arc::clone(&train);
 
-    let mut iter: u32 = 0;
+    let mut iter: usize = 0;
+
+    if training_config.load_model {
+        let file = File::open(&metadata_path).unwrap();
+
+        // 2. Use a buffered reader for efficiency
+        let reader = BufReader::new(file);
+
+        // 3. Deserialize JSON directly from the file reader
+        let metadata: ModelMetadata = serde_json::from_reader(reader).unwrap();
+        iter = metadata.iterations;
+        println!("Loaded model had {} iters", iter);
+    }
+
     let start_time = Instant::now();
 
     ctrlc::set_handler(move || {
@@ -72,7 +91,8 @@ pub fn train<B: AutodiffBackend>(training_config: TrainingConfig, device: B::Dev
     // Create RNG once and reuse it for sampling and shuffling
     // Seed from system time (platform default entropy may be unavailable in some contexts)
     let now = SystemTime::now().duration_since(UNIX_EPOCH).unwrap();
-    let seed = now.as_nanos() as u64;
+    let seed = training_config.seed.unwrap_or(now.as_nanos() as u64);
+    println!("using seed: {}", seed);
     let mut rng = SmallRng::seed_from_u64(seed);
 
     // Initialize optimizer once so state (moments) persist across steps
@@ -80,6 +100,7 @@ pub fn train<B: AutodiffBackend>(training_config: TrainingConfig, device: B::Dev
 
     println!("Starting training...");
     while train.load(Ordering::Relaxed) {
+        println!("Iteration: {}", iter);
         let infer_model = model.valid();
         // Gen samples
         println!("Generating {} games...", training_config.num_episodes);
@@ -88,8 +109,12 @@ pub fn train<B: AutodiffBackend>(training_config: TrainingConfig, device: B::Dev
             let mut board_state = BoardState::default();
             let mut episode_buffer: Vec<MctsResults> = vec![];
 
+            let mut game_hist = String::new();
+
             while board_state.status == BoardStateStatus::Ongoing {
+                // let before = Instant::now();
                 let results = mcts.search(&board_state, &infer_model, &device);
+                // println!("{}", before.elapsed().as_millis());
                 episode_buffer.push(results);
 
                 let temp = if board_state.halfmove_clock < 30 {
@@ -102,9 +127,17 @@ pub fn train<B: AutodiffBackend>(training_config: TrainingConfig, device: B::Dev
 
                 let stm = board_state.board.side_to_move();
                 let mv = sample_move(&adjusted, &mut rng, stm).unwrap();
-                println!("playing move: {}", mv);
+                // println!("playing move: {}", mv);
+                if episode == 0 {
+                    game_hist.push_str(mv.to_string().as_str());
+                    game_hist.push(' ');
+                }
+
                 board_state.apply_move(mv)
             }
+            if episode == 0 {
+                println!("Game history of first game of iteration: {}", game_hist);
+            }
 
             for result in episode_buffer.iter().enumerate() {
                 if board_state.status == BoardStateStatus::Stalemate
@@ -180,6 +213,19 @@ pub fn train<B: AutodiffBackend>(training_config: TrainingConfig, device: B::Dev
     }
 
     println!("Saving model...");
+
+    let metadata = ModelMetadata {
+        name: training_config.model_name,
+        iterations: iter,
+    };
+
+    std::fs::write(
+        metadata_path,
+        serde_json::to_string_pretty(&metadata)
+            .expect("Should be able to convert metadata to JSON string"),
+    )
+    .expect("Should be able to write metadata");
+
     // Save model in MessagePack format with full precision
     let recorder = NamedMpkFileRecorder::<FullPrecisionSettings>::new();
     model
@@ -235,10 +281,12 @@ fn sample_move(
     for (idx, p) in dist {
         r -= *p;
         if r <= 0.0 {
-            return Some(decode_move(*idx, side_to_move));
+            return Some(decode_move(*idx, side_to_move).expect("Invalid move"));
         }
     }
 
     // fallback due to floating point drift
-    dist.get(0).map(|(idx, _)| decode_move(*idx, side_to_move))
+    dist.get(0)
+        .map(|(idx, _)| decode_move(*idx, side_to_move).expect("Invalid move"))
 }
+