Fen token.

chess_classification/chess_classification.py

@@ -42,7 +42,8 @@ def train_and_eval(self, train_json, eval_json):
 
     def predict_fen(self, fen):
         # Make predictions with the model
-        prediction, raw_outputs = self.model.predict([fen])
+        fen_token = fen.replace("/", " ")
+        # fen_token = ' '.join(list(fen))
+        prediction, raw_outputs = self.model.predict([fen_token])
         # print(prediction, raw_outputs)
         return prediction, raw_outputs
-

chess_classification/genPgn.py

@@ -18,7 +18,10 @@ async def main(path="train-pgn", loop=1, time=20, fen=None) -> None:
     os.makedirs(path, exist_ok=True)
 
     for i in range(loop):
-        board = chess.Board(fen)
+        if fen:
+            board = chess.Board(fen)
+        else:
+            board = chess.Board()
         game = chess.pgn.Game()
         game.headers["Event"]
         game.setup(board)

chess_classification/importPgn.py

@@ -12,7 +12,9 @@ def readPgn(path):
     for file in os.listdir(path):
         if file.endswith(".pgn"):
             file_path = os.path.join(path, file)
-            train_df = train_df.append(importPgn(file_path), ignore_index=True)
+            # train_df = train_df.append(importPgn(file_path), ignore_index=True)
+            df = pd.DataFrame(importPgn(file_path), columns=["text", "labels"])
+            train_df = pd.concat([train_df, df], ignore_index=True)
     train_df.to_json(os.path.join(path, "fen.json"))
 
 def importPgn(pgn_file):
@@ -35,7 +37,11 @@ def importPgn(pgn_file):
             board = game.board()
             for move in game.mainline_moves():
                 board.push(move)
-                train_df = train_df.append({"text": board.fen(), "labels": result_label}, ignore_index=True)
+                fen_token = board.fen().replace("/", " ")
+                # fen_token = ' '.join(list(board.fen()))
+                # train_df = train_df.append({"text": fen_token, "labels": result_label}, ignore_index=True)
+                df = pd.DataFrame([{"text": fen_token, "labels": result_label}], columns=["text", "labels"])
+                train_df = pd.concat([train_df, df], ignore_index=True)
         except:
             break
     return train_df

setup.py

@@ -5,7 +5,7 @@
 
 setup(
     name='chess_classification',
-    version='0.0.3',
+    version='0.0.4',
     url='https://github.com/akuroiwa/chess-classification',
     # # PyPI url
     # download_url='',