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chess-gpt-eval/mainvs.py

@@ -0,0 +1,708 @@
+import openai
+import chess
+import chess.engine
+import os
+import csv
+import random
+import time
+import platform
+
+# NOTE: LLAMA AND NANOGPT ARE EXPERIMENTAL PLAYERS, if not using them, comment them out
+# from llama_module import BaseLlamaPlayer, LocalLlamaPlayer, LocalLoraLlamaPlayer
+from nanogpt.nanogpt_module import NanoGptPlayer
+from mamba_module import MambaPlayer
+import gpt_query
+from lczero.backends import Weights, Backend, GameState
+import numpy as np
+
+from typing import Optional, Tuple
+from dataclasses import dataclass
+
+
+@dataclass
+class LegalMoveResponse:
+    move_san: Optional[str] = None
+    move_uci: Optional[chess.Move] = None
+    attempts: int = 0
+    is_resignation: bool = False
+    is_illegal_move: bool = False
+
+
+# Define base Player class
+class Player:
+    def get_move(self, board: chess.Board, game_state: str, temperature: float) -> str:
+        raise NotImplementedError
+
+    def get_config(self) -> dict:
+        raise NotImplementedError
+
+
+class GPTPlayer(Player):
+    def __init__(self, model: str):
+        with open("gpt_inputs/api_key.txt", "r") as f:
+            openai.api_key = f.read().strip()
+        self.model = model
+
+    def get_move(
+        self, board: chess.Board, game_state: str, temperature: float
+    ) -> Optional[str]:
+        response = get_gpt_response(game_state, self.model, temperature)
+        return get_move_from_gpt_response(response)
+
+    def get_config(self) -> dict:
+        return {"model": self.model}
+        
+        
+class LC0PLayer(Player):
+    # "11258-32x4-se.pb.gz" = stockfish level 0- = skill 0
+    # "11258-48x5-se.pb.gz" = stockfish level 0+ = skill 1
+    # "11258-80x7-se.pb.gz" = stockfish level 1 = skill 2
+    # "11258-104x9-se.pb.gz" = stockfish level 2 = skill 3
+    # "TK-6430 aka 128x10-BPR-64M-6430000.pb.gz" = stockfish level 3 = skill 4
+    # "00af53b081e80147172e6f281c01daf5ca19ada173321438914c730370aa4267" = stockfish level 4 = skill 5
+    # "b2ec465d0fb5b5eb39d2e1e3f74041a5d2fc92d413b71aa7ea0b6fb082ccba9c" = stockfish level 5+ = skill 6
+    def __init__(self, skill):
+        self.skill = skill
+        network_paths = ["./lc0/build/release/11258-32x4-se.pb.gz", "./lc0/build/release/11258-48x5-se.pb.gz", "./lc0/build/release/11258-80x7-se.pb.gz", "./lc0/build/release/11258-104x9-se.pb.gz", "./lc0/build/release/TK-6430 aka 128x10-BPR-64M-6430000.pb.gz", "./lc0/build/release/00af53b081e80147172e6f281c01daf5ca19ada173321438914c730370aa4267", "./lc0/build/release/b2ec465d0fb5b5eb39d2e1e3f74041a5d2fc92d413b71aa7ea0b6fb082ccba9c"]
+        print(f"\n\nLoading lc0 network: {network_paths[skill]}\n\n")
+        self.weights = Weights(network_paths[skill])
+        self.backend = Backend(weights=self.weights)
+        self.gamestate = GameState()
+
+    def get_move(self, board: chess.Board, game_state: str, temperature: float):
+        self.gamestate = GameState(fen=board.fen())
+        input_planes = self.gamestate.as_input(self.backend)
+        result = self.backend.evaluate(input_planes)[0]
+        moves = self.gamestate.moves()
+        policy_indices = self.gamestate.policy_indices()
+        move_probs = np.array(result.p_softmax(*policy_indices))
+        best_move_idx = move_probs.argmax()
+        best_move = moves[best_move_idx]
+        return board.san(chess.Move.from_uci(best_move))
+        
+    def get_config(self) -> dict:
+        return {"network": self.weights, "skill_level": self.skill, "play_time": 0}
+
+
+class StockfishPlayer(Player):
+
+    @staticmethod
+    def get_stockfish_path() -> str:
+        """
+        Determines the operating system and returns the appropriate path for Stockfish.
+        
+        Returns:
+            str: Path to the Stockfish executable based on the operating system.
+        """
+        if platform.system() == 'Linux':
+            return "/usr/games/stockfish"
+        elif platform.system() == 'Darwin':  # Darwin is the system name for macOS
+            return "stockfish"
+        elif platform.system() == 'Windows':
+            return r"C:\Users\Haile\Downloads\stockfish\stockfish-windows-x86-64-avx2.exe"
+        else:
+            raise OSError("Unsupported operating system")
+    
+    def __init__(self, skill_level: int, play_time: float):
+        self._skill_level = skill_level
+        self._play_time = play_time
+        # If getting started, you need to run brew install stockfish
+        stockfish_path = StockfishPlayer.get_stockfish_path()
+        self._engine = chess.engine.SimpleEngine.popen_uci(stockfish_path)
+
+    def get_move(
+        self, board: chess.Board, game_state: str, temperature: float
+    ) -> Optional[str]:
+        if self._skill_level == -2:
+            legal_moves = list(board.legal_moves)
+            random_move = random.choice(legal_moves)
+            return board.san(random_move)
+        elif self._skill_level < 0:
+            self._engine.configure({"Skill Level": 0})
+            result = self._engine.play(
+                board, chess.engine.Limit(time=1e-8, depth=1, nodes=1)
+            )
+
+        else:
+            self._engine.configure({"Skill Level": self._skill_level})
+            result = self._engine.play(board, chess.engine.Limit(time=self._play_time))
+        if result.move is None:
+            return None
+        return board.san(result.move)
+
+    def get_config(self) -> dict:
+        return {"skill_level": self._skill_level, "play_time": self._play_time}
+
+    def close(self):
+        self._engine.quit()
+        
+        
+class HumanPlayer(Player):
+    def get_move(self, board: chess.Board, game_state: str, temperature: float) -> str:
+        # Print board for human player
+        print(board)  
+        while True:
+            move = input("Enter your move (SAN format): ")
+            try:
+                move_uci = board.parse_san(move) 
+                if move_uci in board.legal_moves:  
+                    return move
+            except:
+                print("Illegal move, try again.")
+
+    def get_config(self) -> dict:
+        return {"player": "human"}
+
+
+def get_gpt_response(game_state: str, model: str, temperature: float) -> Optional[str]:
+    # trying to prevent what I believe to be rate limit issues
+    if model == "gpt-4":
+        time.sleep(0.4)
+    response = gpt_query.get_gpt_response(game_state, model, temperature)
+    return response
+
+
+def get_move_from_gpt_response(response: Optional[str]) -> Optional[str]:
+    if response is None:
+        return None
+
+    # Parse the response to get only the first move
+    moves = response.split()
+    first_move = moves[0] if moves else None
+
+    return first_move
+
+
+def calculate_stats(csv_file_path):
+    data = []
+    with open(csv_file_path, "r") as csv_file:
+        reader = csv.DictReader(csv_file)
+        data = list(reader)
+
+    if not data:
+        return None
+
+    for i, v in enumerate(data):
+        data[i]["player_one_score"] = 0.5 if data[i]["player_one_score"] == "1/2" else float(data[i]["player_one_score"])
+        data[i]["player_two_score"] = 0.5 if data[i]["player_two_score"] == "1/2" else float(data[i]["player_two_score"])
+
+    stats = {
+        "wins": sum(row["player_one_score"] for row in data if row["player_one_score"] > 0.6),
+        "draws": len(data) - sum(row["player_two_score"] for row in data if row["player_two_score"] > 0.6) - sum(row["player_one_score"] for row in data if row["player_one_score"] > 0.6),
+        "illegal_attempts_ratio": sum(float(row["p1_illegal_attempts"]) for row in data) / (sum(float(row["p1_illegal_attempts"]) for row in data) + sum(float(row["player_one_legal_moves"]) for row in data)),
+        "illegal_moves_ratio": sum(float(row["player_one_illegal_moves"]) for row in data) / sum(float(row["player_one_illegal_moves"]) + float(row["player_one_legal_moves"]) for row in data),
+        "avg_attempts_per_illegal": sum(float(row["p1_avg_attempts_per_illegal"]) for row in data) / len(data),
+        "avg_first_illegal_move": sum(float(row["p1_first_illegal_move_num"]) for row in data if float(row["p1_first_illegal_move_num"]) > 0) / len([row for row in data if float(row["p1_first_illegal_move_num"]) > 0]),
+        "avg_illegal_move_num": sum(float(row["p1_avg_illegal_move_num"]) for row in data if float(row["p1_avg_illegal_move_num"]) > 0) / len([row for row in data if float(row["p1_avg_illegal_move_num"]) > 0]),
+        "lost_to_illegal_ratio": len([row for row in data if row["player_one_failed_to_find_legal_move"] == "True"]) / len([row for row in data if float(row["number_of_moves"]) > 0]),
+        "avg_game_length": sum(float(row["number_of_moves"]) for row in data) / len(data),
+        "max_game_length": max(float(row["number_of_moves"]) for row in data),
+    }
+
+    return stats
+
+
+def record_results(
+    board: chess.Board,
+    player_one: Player,
+    player_two: Player,
+    game_state: str,
+    player_one_illegal_moves: int,
+    player_one_illegal_attempts: int,
+    player_two_illegal_moves: int,
+    player_two_illegal_attempts: int,
+    player_one_legal_moves: int,
+    player_two_legal_moves: int,
+    total_time: float,
+    player_one_resignation: bool,
+    player_two_resignation: bool,
+    player_one_failed_to_find_legal_move: bool,
+    player_two_failed_to_find_legal_move: bool,
+    total_moves: int,
+    illegal_moves: int,
+    opening_moves: int,
+    illegal_move_numbers: list[int],
+    illegal_move_numbers2: list[int],
+):
+    unique_game_id = generate_unique_game_id()
+
+    (
+        player_one_title,
+        player_two_title,
+        player_one_time,
+        player_two_time,
+    ) = get_player_titles_and_time(player_one, player_two)
+
+    if player_one_resignation or player_one_failed_to_find_legal_move:
+        result = "0-1"
+        player_one_score = 0
+        player_two_score = 1
+    elif player_two_resignation or player_two_failed_to_find_legal_move:
+        result = "1-0"
+        player_one_score = 1
+        player_two_score = 0
+    else:
+        result = board.result()
+        # Hmmm.... debating this one. Annoying if I leave it running and it fails here for some reason, probably involving some
+        # resignation / failed move situation I didn't think of
+        # -1e10 at least ensures it doesn't fail silently
+        if "-" in result:
+            player_one_score = result.split("-")[0]
+            player_one_score = 0.5 if player_one_score == "1/2" else player_one_score
+            player_two_score = result.split("-")[1]
+            player_two_score = 0.5 if player_two_score == "1/2" else player_two_score
+        elif result == "*": # Loss due to hitting max moves
+            player_one_score = 0
+            player_two_score = 1
+        else:
+            player_one_score = -1e10
+            player_two_score = -1e10
+
+    played_moves = player_one_illegal_moves + player_one_legal_moves
+    info_dict = {
+        "game_id": unique_game_id,
+        "transcript": game_state,
+        "result": result,
+        "player_one": player_one_title,
+        "player_two": player_two_title,
+        "player_one_time": player_one_time,
+        "player_two_time": player_two_time,
+        "player_one_score": player_one_score,
+        "player_two_score": player_two_score,
+        "player_one_illegal_moves": player_one_illegal_moves,
+        "player_two_illegal_moves": player_two_illegal_moves,
+        "player_one_legal_moves": player_one_legal_moves,
+        "player_two_legal_moves": player_two_legal_moves,
+        "player_one_resignation": player_one_resignation,
+        "player_two_resignation": player_two_resignation,
+        "player_one_failed_to_find_legal_move": player_one_failed_to_find_legal_move,
+        "player_two_failed_to_find_legal_move": player_two_failed_to_find_legal_move,
+        "game_title": f"{player_one_title} vs. {player_two_title}",
+        "number_of_moves": board.fullmove_number,
+        "p1_illegal_attempts": player_one_illegal_attempts,
+        "p1_avg_attempts_per_illegal": 0 if player_one_illegal_moves == 0 else player_one_illegal_attempts / float(player_one_illegal_moves),
+        "p1_illegal_attemtps_pct": 1.0 if played_moves == 0 else player_one_illegal_attempts / float(player_one_illegal_attempts + player_one_legal_moves),
+        "p1_illegal_moves_pct": 1.0 if played_moves == 0 else player_one_illegal_moves / float(played_moves),
+        "p1_first_illegal_move_num": illegal_move_numbers[0] if illegal_move_numbers else 0,
+        "p1_avg_illegal_move_num": np.average(illegal_move_numbers) if illegal_move_numbers else 0,
+        "p2_illegal_attempts": player_two_illegal_attempts,
+        "p2_avg_attempts_per_illegal": 0 if player_two_illegal_moves == 0 else player_two_illegal_attempts / float(player_two_illegal_moves),
+        "p2_illegal_attemtps_pct": 1.0 if played_moves == 0 else player_two_illegal_attempts / float(player_two_illegal_attempts + player_two_legal_moves),
+        "p2_illegal_moves_pct": 1.0 if played_moves == 0 else player_two_illegal_moves / float(played_moves),
+        "p2_first_illegal_move_num": illegal_move_numbers2[0] if illegal_move_numbers2 else 0,
+        "p2_avg_illegal_move_num": np.average(illegal_move_numbers2) if illegal_move_numbers2 else 0,
+
+
+        "time_taken": total_time,
+        "total_moves": total_moves,
+        "illegal_moves": illegal_moves,
+    }
+
+    if RUN_FOR_ANALYSIS:
+        csv_file_path = f"logs/{player_one_recording_name}_vs_{player_two_recording_name}"
+        csv_file_path = csv_file_path.replace(".", "_") # Because I'm using ckpt filenames for nanogpt models 
+        csv_file_path += ".csv"
+    else:
+        csv_file_path = recording_file
+
+
+
+    # Determine if we need to write headers (in case the file doesn't exist yet)
+    write_headers = not os.path.exists(csv_file_path)
+
+    # Append the results to the CSV file
+    os.makedirs(os.path.dirname(csv_file_path), exist_ok=True)
+    with open(csv_file_path, "a", newline="") as csv_file: 
+        writer = csv.DictWriter(csv_file, fieldnames=info_dict.keys())
+        if write_headers:
+            writer.writeheader()
+        writer.writerow(info_dict)
+
+    with open("game.txt", "w") as f:
+        f.write(game_state)
+
+
+def generate_unique_game_id() -> str:
+    timestamp = int(time.time())
+    random_num = random.randint(1000, 9999)  # 4-digit random number
+    return f"{timestamp}-{random_num}"
+
+
+def get_player_titles_and_time(
+    player_one: Player, player_two: Player
+) -> Tuple[str, str, Optional[float], Optional[float]]:
+    player_one_config = player_one.get_config()
+    player_two_config = player_two.get_config()
+
+    # For player one
+    if "model" in player_one_config:
+        player_one_title = player_one_config["model"]
+        player_one_time = None
+    else:
+        player_one_title = f"Stockfish {player_one_config['skill_level']}"
+        player_one_time = player_one_config["play_time"]
+
+    # For player two
+    if "model" in player_two_config:
+        player_two_title = player_two_config["model"]
+        player_two_time = None
+    else:
+        player_two_title = f"Stockfish {player_two_config['skill_level']}"
+        player_two_time = player_two_config["play_time"]
+
+    return (player_one_title, player_two_title, player_one_time, player_two_time)
+
+
+used_openings = []
+def random_book_opening(
+    game_state: str, board: chess.Board
+) -> Tuple[str, chess.Board]:
+    global used_openings
+    with open("openings.csv", "r") as file:
+        lines = file.readlines()[1:]  # Skip header
+    moves_string = random.choice(lines)
+    while moves_string in used_openings:
+        moves_string = random.choice(lines)
+    used_openings.append(moves_string)
+    if move_num_in_gamestate:
+        game_state = moves_string.rstrip() + " "
+    else:
+        game_state = ' '.join(['.' + m.split(".")[-1] if "." in m else m for m in moves_string.split()])
+        game_state = game_state.rstrip() + " "
+    # Splitting the moves string on spaces
+    tokens = moves_string.split()
+
+    for token in tokens:
+        # If the token contains a period, it's a move number + move combination
+        if "." in token:
+            move = token.split(".")[-1]  # Take the move part after the period
+        else:
+            move = token
+
+        board.push_san(move)
+    return game_state.rstrip(), board, len(tokens) // 2
+
+
+def add_random_moves(
+    game_state: str, board: chess.Board, num_moves: int = 20
+) -> Tuple[str, chess.Board, int]:
+    for i in range(num_moves * 2):  # Full moves to half moves
+        legal_moves = list(board.legal_moves)
+        if not legal_moves:
+            return None, None, 0  # Game over, discard the game
+
+        move = board.san(random.choice(legal_moves))
+        board.push(board.parse_san(move))
+
+        if board.turn == chess.BLACK:
+            game_state += f" {i//2 + 1}.{move}" if move_num_in_gamestate else f" .{move}"
+        else:
+            game_state += f" {move}"
+
+        if board.is_game_over():
+            return None, None, 0  # Game over, discard the game
+
+    game_state = game_state.strip()
+    return game_state, board, num_moves
+
+
+# Return is (move_san, move_uci, attempts, is_resignation, is_illegal_move)
+def get_legal_move(
+    player: Player,
+    board: chess.Board,
+    game_state: str,
+    player_one: bool,
+    max_attempts: int = 5,
+) -> LegalMoveResponse:
+    """Request a move from the player and ensure it's legal."""
+    move_san = None
+    move_uci = None
+
+    for attempt in range(max_attempts):
+        #print(f"get_legal_move: |{game_state}|")
+        move_san = player.get_move(
+            board, game_state, min(((attempt / max_attempts) * 1) + 0.001, 0.75)
+        )
+
+        # Sometimes when GPT thinks it's the end of the game, it will just output the result
+        # Like "1-0". If so, this really isn't an illegal move, so we'll add a check for that.
+        if move_san is not None:
+            if move_san == "1-0" or move_san == "0-1" or move_san == "1/2-1/2":
+                print(f"{move_san}, player has resigned")
+                return LegalMoveResponse(
+                    move_san=None,
+                    move_uci=None,
+                    attempts=attempt,
+                    is_resignation=True,
+                )
+
+        try:
+            move_uci = board.parse_san(move_san)
+        except Exception as e:
+            print(f"Error parsing move {move_san}: {e}")
+            # check if player is gpt-3.5-turbo-instruct
+            # only recording errors for gpt-3.5-turbo-instruct because it's errors are so rare
+            if player.get_config()["model"] == "gpt-3.5-turbo-instruct":
+                with open("gpt-3.5-turbo-instruct-illegal-moves.txt", "a") as f:
+                    f.write(f"{game_state}\n{move_san}\n")
+            continue
+
+        if move_uci in board.legal_moves:
+            if player_one == False:
+                if not move_san.startswith(" "):
+                    move_san = " " + move_san
+            else:
+                if move_san.startswith(" "):
+                    move_san = move_san[1:]
+            return LegalMoveResponse(move_san, move_uci, attempt)
+        print(f"Illegal move: {move_san}")
+
+    # If we reach here, the player has made illegal moves for all attempts.
+    print(f"{player} provided illegal moves for {max_attempts} attempts.")
+    return LegalMoveResponse(
+        move_san=None, move_uci=None, attempts=max_attempts, is_illegal_move=True
+    )
+
+
+def play_turn(
+    player: Player, board: chess.Board, game_state: str, player_one: bool
+) -> Tuple[str, bool, bool, int]:
+    result = get_legal_move(player, board, game_state, player_one, 5)
+    illegal_moves = result.attempts
+    move_san = result.move_san
+    move_uci = result.move_uci
+    resignation = result.is_resignation
+    failed_to_find_legal_move = result.is_illegal_move
+
+    if resignation:
+        print(f"{player} resigned with result: {board.result()}")
+    elif failed_to_find_legal_move:
+        print(f"Game over: 5 consecutive illegal moves from {player}")
+    elif move_san is None or move_uci is None:
+        print(f"Game over: {player} failed to find a legal move")
+    else:
+        board.push(move_uci)
+        game_state += move_san
+        print(move_san, end=" ")
+
+    return game_state, resignation, failed_to_find_legal_move, illegal_moves
+
+
+def play_games(
+    player_one: Player,
+    player_two: Player,
+    max_games: int = 10,
+    book_opening: bool = False,
+    random_opening: bool = False,
+    random_opening_moves: int = 20,
+):
+    unique_games = set()
+    games_saved = 0
+    while games_saved < max_games:
+        print(f"\nGame {games_saved} of {max_games}\n")
+    
+        with open("gpt_inputs/prompt.txt", "r") as f:
+            game_state = f.read()
+        board = chess.Board()
+
+        if book_opening:
+            game_state, board, opening_moves = random_book_opening(game_state, board)
+        elif random_opening:
+            while True:
+                game_state, board, opening_moves = add_random_moves(game_state, board, random_opening_moves)
+                if game_state is not None:
+                    break
+        else:
+            opening_moves = 0
+        player_one_illegal_moves = 0
+        player_one_illegal_attempts = 0
+        player_two_illegal_moves = 0
+        player_two_illegal_attempts = 0
+        player_one_legal_moves = 0
+        player_two_legal_moves = 0
+        player_one_resignation = False
+        player_two_resignation = False
+        player_one_failed_to_find_legal_move = False
+        player_two_failed_to_find_legal_move = False
+        start_time = time.time()
+
+        total_moves = 0
+        illegal_moves = 0
+        illegal_move_numbers = []
+        illegal_move_numbers2 = []
+        print_for_human = isinstance(player_one, HumanPlayer) or isinstance(player_two, HumanPlayer)
+
+        while not board.is_game_over():
+            if print_for_human:
+                print(board)
+
+            with open("game.txt", "w") as f:
+                f.write(game_state)
+            current_move_num = f"{board.fullmove_number if move_num_in_gamestate else ''}."
+            total_moves += 1
+            # I increment legal moves here so player_two isn't penalized for the game ending before its turn
+            player_one_legal_moves += 1
+            player_two_legal_moves += 1
+
+            # this if statement may be overkill, just trying to get format to exactly match PGN notation
+            if board.fullmove_number != 1:
+                game_state += " "
+            game_state += current_move_num
+            #print(f"|{game_state}|")
+            #print(f"{current_move_num}", end=" ")
+
+            (
+                game_state,
+                player_one_resignation,
+                player_one_failed_to_find_legal_move,
+                illegal_moves_one,
+            ) = play_turn(player_one, board, game_state, player_one=True)
+            player_one_illegal_moves  += 1 if illegal_moves_one > 0 else 0
+            player_one_illegal_attempts += illegal_moves_one
+            if illegal_moves_one != 0:
+                player_one_legal_moves -= 1
+                illegal_move_numbers.append(board.fullmove_number)
+            if (
+                board.is_game_over()
+                or player_one_resignation
+                or player_one_failed_to_find_legal_move
+            ):
+                break
+
+            (
+                game_state,
+                player_two_resignation,
+                player_two_failed_to_find_legal_move,
+                illegal_moves_two,
+            ) = play_turn(player_two, board, game_state, player_one=False)
+            player_two_illegal_moves  += 1 if illegal_moves_two > 0 else 0
+            player_two_illegal_attempts += illegal_moves_two
+            if illegal_moves_two != 0:
+                player_two_legal_moves -= 1
+                illegal_move_numbers2.append(board.fullmove_number)
+            if (
+                board.is_game_over()
+                or player_two_resignation
+                or player_two_failed_to_find_legal_move
+            ):
+                break
+
+            print("\n", end="")
+
+            if total_moves > MAX_MOVES:
+                break
+
+        end_time = time.time()
+        total_time = end_time - start_time
+        print(f"\nGame over. Total time: {total_time} seconds")
+        print(f"Result: {board.result()}")
+        print(board)
+        print()
+        game_transcript = game_state.strip()
+        if game_transcript not in unique_games:
+            unique_games.add(game_transcript)
+            record_results(
+                board,
+                player_one,
+                player_two,
+                game_state,
+                player_one_illegal_moves,
+                player_one_illegal_attempts,
+                player_two_illegal_moves,
+                player_two_illegal_attempts,
+                player_one_legal_moves,
+                player_two_legal_moves,
+                total_time,
+                player_one_resignation,
+                player_two_resignation,
+                player_one_failed_to_find_legal_move,
+                player_two_failed_to_find_legal_move,
+                total_moves,
+                illegal_moves,
+                opening_moves,
+                illegal_move_numbers,
+                illegal_move_numbers2
+            )
+            games_saved += 1
+        else:
+            print("Duplicate game; not saved.")
+    if isinstance(player_one, StockfishPlayer):
+        player_one.close()
+    if isinstance(player_two, StockfishPlayer):
+        player_two.close()
+
+    if RUN_FOR_ANALYSIS:
+        csv_file_path = f"logs/{player_one_recording_name}_vs_{player_two_recording_name}"
+        csv_file_path = csv_file_path.replace(".", "_") # Because I'm using ckpt filenames for nanogpt models 
+        csv_file_path += ".csv"
+    else:
+        csv_file_path = recording_file
+    stats = calculate_stats(csv_file_path)
+    if stats:
+        print("\nStatistics:")
+        for key, value in stats.items():
+            print(f"{key}: {value}")
+        
+        with open(csv_file_path, "a") as csv_file:
+            writer = csv.writer(csv_file)
+            writer.writerow([""] * 19)  # Add empty cells for existing columns
+            writer.writerow(list(stats.keys()))
+            writer.writerow(list(stats.values()))
+
+
+RUN_FOR_ANALYSIS = True
+MAX_MOVES = 999 # Due to nanogpt max input length of 1024
+recording_file = "logs/determine.csv" # default recording file. Because we are using list [player_ones], recording_file is overwritten
+player_ones = ["50M/adams.pt"]
+player_two_recording_name = "lc0_sweep" #"stockfish_sweep"
+move_num_in_gamestate = False
+book_opening = True
+random_opening = False
+random_opening_moves = 20
+if __name__ == "__main__":
+    for nanogpt_player in player_ones:
+        for i in [0]: # [3] #range(11):
+            num_games = 500
+            # player_one = GPTPlayer(model="gpt-3.5-turbo-instruct")
+            # player_one = LocalLlamaPlayer(model_name="meta-llama/Llama-2-7b-hf")
+            # player_one = LocalLoraLlamaPlayer("meta-llama/Llama-2-7b-hf", "/workspace/axolotl/lora2-out")
+            # player_one = GPTPlayer(model="gpt-4")
+            # player_one = StockfishPlayer(skill_level=-1, play_time=0.1)
+            
+            player_one_recording_name = nanogpt_player
+  #          player_one = NanoGptPlayer(model_name=player_one_recording_name, move_num_in_gamestate=move_num_in_gamestate)
+#            player_one_recording_name = "xformer_" + nanogpt_player
+            player_one_recording_name = "mamba"
+            player_one = MambaPlayer(model_name="50M/anneal/anneal_complete_round3.pt", move_num_in_gamestate=move_num_in_gamestate)
+            #player_two = StockfishPlayer(skill_level=i, play_time=0.1)
+#            player_two = LC0PLayer(skill=i)
+            
+            player_two = NanoGptPlayer(model_name="50M/stockfish_16layers_ckpt_with_optimizer.pt", move_num_in_gamestate=True)
+            player_two_recording_name = "adam"
+            # player_two = GPTPlayer(model="gpt-4")
+            # player_two = GPTPlayer(model="gpt-3.5-turbo-instruct")
+            
+            #print(f"\n\nSTARTING GAMES AGAINST STOCKFISH LEVEL {i}\n\n")
+            print(f"\n\nSTARTING GAMES AGAINST LC0 LEVEL {i}\n\n")
+
+            play_games(player_one, player_two, num_games, book_opening=book_opening, random_opening=random_opening, random_opening_moves=random_opening_moves)
+            
+print("\n\n\n********\nFinal Statistics:\n********\n")
+for nanogpt_player in player_ones:
+    #player_one_recording_name = "xformer_" + nanogpt_player
+    if RUN_FOR_ANALYSIS:
+        csv_file_path = f"logs/{player_one_recording_name}_vs_{player_two_recording_name}"
+        csv_file_path = csv_file_path.replace(".", "_") # Because I'm using ckpt filenames for nanogpt models 
+        csv_file_path += ".csv"
+    else:
+        csv_file_path = recording_file
+    
+    try:
+        stats = calculate_stats(csv_file_path)
+        if stats:
+            print(f"\nStatistics for {nanogpt_player}:")
+            for key, value in stats.items():
+                print(f"{key}: {value}")
+    except:
+        print(f"Couldn't get stats for {csv_file_path}")
+print("\n\n\n********\nDONE!\n********\n\n\n")