chess_transformers/play/human_play.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from chess_transformers.configs import import_config\n",
    "from chess_transformers.play.utils import write_pgns\n",
    "from chess_transformers.play.clocks import ChessClock\n",
    "from chess_transformers.play import human_v_model, warm_up, load_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load configuration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "config_name = \"CT-EFT-20\"\n",
    "CONFIG = import_config(config_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Cannot find model checkpoint on disk; will download.\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "averaged_CT-EFT-20.pt: 100%|██████████| 72.4M/72.4M [00:18<00:00, 4.00MB/s]  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Model loaded!\n",
      "\n"
     ]
    }
   ],
   "source": [
    "model = load_model(CONFIG)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Warm up model -- this runs the model for the first time (and then some), which triggers compilation. This may take up to a minute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Model warmed up!\n"
     ]
    }
   ],
   "source": [
    "warm_up(\n",
    "    model=model,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Play against the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "# I played ***c6b7***. I win! :)"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       ". Q . . . . . .\n",
       "B . . . . . . .\n",
       "p . p P . p p p\n",
       ". . . . . . . .\n",
       ". . . . . . . .\n",
       "P P P P . P P P\n",
       "R N B . K . . 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      ],
      "text/plain": [
       "Board('1k3bnr/1Q6/B7/p1pP1ppp/8/8/PPPP1PPP/RNB1K2R b KQ - 1 15')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "# Your final Score +0 | -1 | =0"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "wins, laws, draws, pgns = human_v_model(\n",
    "    human_color=\"b\",\n",
    "    model=model,\n",
    "    k=1,\n",
    "    use_amp=True,\n",
    "    rounds=1,\n",
    "    clock=None,\n",
    "    white_player_name=config_name,\n",
    "    black_player_name=\"Me\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write PGNs to file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "filepath = \"\"\n",
    "write_pgns(\n",
    "    pgns,\n",
    "    pgn_file=filepath,\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
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