Improve printing

martinnovaak · martinnovaak · commit 5ded834bf844 · 2024-05-14T15:17:37.000+02:00
diff --git a/trainer/model.py b/trainer/model.py
@@ -62,7 +62,7 @@ def eval(self, fen, device):
         hidden_features = torch.cat((stm_perspective, nstm_perspective))
         hidden_features = self.screlu(hidden_features)
 
-        print(int((torch.special.logit(torch.sigmoid(self.output_layer(hidden_features))) * 400).item()))
+        print(self.output_layer(hidden_features) * 400)
 
     def clamp_weights(self):
         self.feature_transformer.weight.data.clamp_(-1.27, 1.27)
diff --git a/trainer/train.py b/trainer/train.py
@@ -57,12 +57,12 @@ def train(model: torch.nn.Module, optimizer: torch.optim.Optimizer, dataloader:
             iterations = 0
             fens = 0
 
-            model.eval("rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR", device)
-
             quantize(model, f"network/nnue_{epoch}_scaled.bin")
 
             save_checkpoint(model, optimizer, epoch, running_loss, "checkpoint.pth")
 
+            model.eval("rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR", device)
+
         optimizer.zero_grad()
         prediction = model(batch)
 
@@ -79,7 +79,9 @@ def train(model: torch.nn.Module, optimizer: torch.optim.Optimizer, dataloader:
             epoch_time = time() - epoch_start_time
             formatted_fens = "{0:_}".format(fens)
             formatted_speed = "{0:_}".format(int(fens / epoch_time))
-            print("\rTotal fens parsed in this epoch: {}, Time: {:.2f} s, Speed: {} pos/s".format(formatted_fens,
-                                                                                                  epoch_time,
-                                                                                                  formatted_speed),
-                  end='', flush=True)
+            print("\rTotal fens parsed in this epoch: {}, Time: {:.2f} s, Speed: {} pos/s"
+                  .format(formatted_fens, epoch_time, formatted_speed), end='', flush=True)
+
+        if fens % 99_942_400 == 0:
+            print_epoch_stats(epoch, running_loss, iterations, fens, epoch_start_time, time())
+            model.eval("rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR", device)
