foo bar

2026-06-12 18:02:09 -06:00
parent 743c395e11
commit f09ca60315
23 changed files with 1286 additions and 61 deletions
@@ -0,0 +1,64 @@
+using JoshHeaps.Net.Models;
+using JoshHeaps.Net.Services.Interfaces;
+
+namespace JoshHeaps.Net.Services.Implementations;
+
+/// <summary>
+/// Managed facade over the native learned-weights model (see <see cref="ILearnedWeightsStore"/>).
+/// On construction it points the native engine at the weights file; everything else delegates
+/// to the shared native ABI in <see cref="CustomChessEngine"/>.
+/// </summary>
+public sealed class LearnedWeightsStore : ILearnedWeightsStore
+{
+    private const int Pieces = 6;       // Pawn..King
+    private const int Squares = 64;
+    private const int Features = 8;     // mobility N/B/R/Q, passed, isolated, doubled, king safety
+
+    public string WeightsFilePath { get; }
+
+    public LearnedWeightsStore(IHostEnvironment env)
+    {
+        WeightsFilePath = Path.Combine(env.ContentRootPath, "chess-data", "learned-weights.txt");
+        Directory.CreateDirectory(Path.GetDirectoryName(WeightsFilePath)!);
+        CustomChessEngine.NativeMethods.learned_load(WeightsFilePath);
+    }
+
+    public nint CreateTrainer() => CustomChessEngine.NativeMethods.trainer_create();
+
+    public void Record(nint trainer, string fen) =>
+        CustomChessEngine.NativeMethods.trainer_record(trainer, fen);
+
+    public void ApplyResult(nint trainer, PieceColor winner, double weight) =>
+        CustomChessEngine.NativeMethods.trainer_apply(trainer, winner == PieceColor.White ? 0 : 1, weight);
+
+    public void DestroyTrainer(nint trainer) =>
+        CustomChessEngine.NativeMethods.trainer_destroy(trainer);
+
+    public LearnedWeightsSnapshot Snapshot()
+    {
+        const int total = Pieces * Squares * 2 + Features;
+        var buffer = new int[total];
+
+        unsafe
+        {
+            fixed (int* p = buffer)
+                CustomChessEngine.NativeMethods.weights_snapshot(p, total);
+        }
+
+        var mg = new int[Pieces][];
+        var eg = new int[Pieces][];
+
+        for (int piece = 0; piece < Pieces; piece++)
+        {
+            mg[piece] = new int[Squares];
+            eg[piece] = new int[Squares];
+            Array.Copy(buffer, piece * Squares, mg[piece], 0, Squares);
+            Array.Copy(buffer, Pieces * Squares + piece * Squares, eg[piece], 0, Squares);
+        }
+
+        var features = new int[Features];
+        Array.Copy(buffer, Pieces * Squares * 2, features, 0, Features);
+
+        return new LearnedWeightsSnapshot(mg, eg, features);
+    }
+}