Super_Mario_Bot (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a4d530d",
   "metadata": {},
   "outputs": [
    {
     "ename": "",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31mRunning cells with 'c:\\msys64\\mingw64\\bin\\python.exe' requires the ipykernel package.\n",
      "\u001b[1;31mRun the following command to install 'ipykernel' into the Python environment. \n",
      "\u001b[1;31mCommand: 'c:/msys64/mingw64/bin/python.exe -m pip install ipykernel -U --user --force-reinstall'"
     ]
    }
   ],
   "source": [
    "import gym_super_mario_bros\n",
    "from nes_py.wrappers import JoypadSpace\n",
    "from gym_super_mario_bros.actions import SIMPLE_MOVEMENT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c896d1dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['NOOP'],\n",
       " ['right'],\n",
       " ['right', 'A'],\n",
       " ['right', 'B'],\n",
       " ['right', 'A', 'B'],\n",
       " ['A'],\n",
       " ['left']]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# SIMPLE_MOVEMENT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0b2b4069",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: gym in c:\\conda\\lib\\site-packages (0.26.2)\n",
      "Requirement already satisfied: numpy>=1.18.0 in c:\\conda\\lib\\site-packages (from gym) (1.24.3)\n",
      "Requirement already satisfied: cloudpickle>=1.2.0 in c:\\conda\\lib\\site-packages (from gym) (1.6.0)\n",
      "Requirement already satisfied: gym-notices>=0.0.4 in c:\\conda\\lib\\site-packages (from gym) (0.0.8)\n",
      "Requirement already satisfied: importlib-metadata>=4.8.0 in c:\\users\\krish\\appdata\\roaming\\python\\python38\\site-packages (from gym) (6.8.0)\n",
      "Requirement already satisfied: zipp>=0.5 in c:\\users\\krish\\appdata\\roaming\\python\\python38\\site-packages (from importlib-metadata>=4.8.0->gym) (3.16.2)\n"
     ]
    }
   ],
   "source": [
    "# !pip install gym\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a6ba3945",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\conda\\lib\\site-packages\\gym\\envs\\registration.py:555: UserWarning: \u001b[33mWARN: The environment SuperMarioBros-v0 is out of date. You should consider upgrading to version `v3`.\u001b[0m\n",
      "  logger.warn(\n",
      "C:\\conda\\lib\\site-packages\\gym\\envs\\registration.py:627: UserWarning: \u001b[33mWARN: The environment creator metadata doesn't include `render_modes`, contains: ['render.modes', 'video.frames_per_second']\u001b[0m\n",
      "  logger.warn(\n"
     ]
    }
   ],
   "source": [
    "env = gym_super_mario_bros.make('SuperMarioBros-v0',apply_api_compatibility=True,render_mode=\"human\" )\n",
    "env =JoypadSpace(env,SIMPLE_MOVEMENT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5e9114c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(240, 256, 3)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# env.observation_space.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bc6970bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Discrete(7)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# env.action_space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d6de75f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# state = env.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f36e270",
   "metadata": {},
   "outputs": [],
   "source": [
    "# env.step(1)[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f4ea60ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\conda\\lib\\site-packages\\gym\\utils\\passive_env_checker.py:233: DeprecationWarning: `np.bool8` is a deprecated alias for `np.bool_`.  (Deprecated NumPy 1.24)\n",
      "  if not isinstance(terminated, (bool, np.bool8)):\n",
      "C:\\conda\\lib\\site-packages\\gym_super_mario_bros\\smb_env.py:148: RuntimeWarning: overflow encountered in scalar subtract\n",
      "  return (self.ram[0x86] - self.ram[0x071c]) % 256\n"
     ]
    }
   ],
   "source": [
    "# done = True\n",
    "# env.reset()\n",
    "# for step in range(5000):\n",
    "#     action = env.action_space.sample()\n",
    "#     obs, reward, terminated, truncated, info = env.step(action)\n",
    "#     done = terminated or truncated\n",
    "\n",
    "#     if done:\n",
    "#        env.reset()\n",
    "\n",
    "# env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3e42fb64",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# state=env.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b9419562",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\conda\\lib\\site-packages\\gymnasium\\envs\\registration.py:604: UserWarning: \u001b[33mWARN: plugin: shimmy.registration:register_gymnasium_envs raised Traceback (most recent call last):\n",
      "  File \"C:\\conda\\lib\\site-packages\\gymnasium\\envs\\registration.py\", line 602, in load_plugin_envs\n",
      "    fn()\n",
      "  File \"C:\\conda\\lib\\site-packages\\shimmy\\registration.py\", line 262, in register_gymnasium_envs\n",
      "    _register_dm_control_envs()\n",
      "  File \"C:\\conda\\lib\\site-packages\\shimmy\\registration.py\", line 26, in _register_dm_control_envs\n",
      "    from shimmy.dm_control_compatibility import DmControlCompatibilityV0\n",
      "  File \"C:\\conda\\lib\\site-packages\\shimmy\\dm_control_compatibility.py\", line 15, in <module>\n",
      "    from dm_control import composer\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\composer\\__init__.py\", line 18, in <module>\n",
      "    from dm_control.composer.arena import Arena\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\composer\\arena.py\", line 20, in <module>\n",
      "    from dm_control import mjcf\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\mjcf\\__init__.py\", line 18, in <module>\n",
      "    from dm_control.mjcf.attribute import Asset\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\mjcf\\attribute.py\", line 28, in <module>\n",
      "    from dm_control.mujoco.wrapper import util\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\mujoco\\__init__.py\", line 18, in <module>\n",
      "    from dm_control.mujoco.engine import action_spec\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\mujoco\\engine.py\", line 42, in <module>\n",
      "    from dm_control.mujoco import index\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\mujoco\\index.py\", line 88, in <module>\n",
      "    from dm_control.mujoco.wrapper import util\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\mujoco\\wrapper\\__init__.py\", line 18, in <module>\n",
      "    from dm_control.mujoco.wrapper import mjbindings\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\mujoco\\wrapper\\mjbindings\\__init__.py\", line 29, in <module>\n",
      "    from dm_control.mujoco.wrapper.mjbindings import functions\n",
      "  File \"C:\\conda\\lib\\site-packages\\dm_control\\mujoco\\wrapper\\mjbindings\\functions.py\", line 21, in <module>\n",
      "    import mujoco\n",
      "  File \"C:\\conda\\lib\\site-packages\\mujoco\\__init__.py\", line 40, in <module>\n",
      "    from mujoco._callbacks import *\n",
      "ModuleNotFoundError: No module named 'mujoco._callbacks'\n",
      "\u001b[0m\n",
      "  logger.warn(f\"plugin: {plugin.value} raised {traceback.format_exc()}\")\n"
     ]
    }
   ],
   "source": [
    "from gym.wrappers import GrayScaleObservation\n",
    "from stable_baselines3.common.vec_env import VecFrameStack, DummyVecEnv\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "71ea4332",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\conda\\lib\\site-packages\\gym\\envs\\registration.py:555: UserWarning: \u001b[33mWARN: The environment SuperMarioBros-v0 is out of date. You should consider upgrading to version `v3`.\u001b[0m\n",
      "  logger.warn(\n",
      "C:\\conda\\lib\\site-packages\\gym\\envs\\registration.py:627: UserWarning: \u001b[33mWARN: The environment creator metadata doesn't include `render_modes`, contains: ['render.modes', 'video.frames_per_second']\u001b[0m\n",
      "  logger.warn(\n",
      "C:\\conda\\lib\\site-packages\\stable_baselines3\\common\\vec_env\\patch_gym.py:49: UserWarning: You provided an OpenAI Gym environment. We strongly recommend transitioning to Gymnasium environments. Stable-Baselines3 is automatically wrapping your environments in a compatibility layer, which could potentially cause issues.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "env = gym_super_mario_bros.make('SuperMarioBros-v0',apply_api_compatibility=True,render_mode=\"human\" )\n",
    "env =JoypadSpace(env,SIMPLE_MOVEMENT)\n",
    "env = GrayScaleObservation(env, keep_dim=True)\n",
    "env = DummyVecEnv([lambda: env])\n",
    "env = VecFrameStack(env , 4 , channels_order='last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cc39ac7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "state = JoypadSpace.reset = lambda self, **kwargs: self.env.reset(**kwargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "55bbbd8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# obs, reward, terminated, truncated, info = env.step([5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "176e393b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from stable_baselines3 import PPO\n",
    "from stable_baselines3.common.callbacks import BaseCallback"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "189512c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "class TrainAndLoggingCallback(BaseCallback):\n",
    "\n",
    "    def __init__(self, check_freq, save_path, verbose=1):\n",
    "        super(TrainAndLoggingCallback, self).__init__(verbose)\n",
    "        self.check_freq = check_freq\n",
    "        self.save_path = save_path\n",
    "\n",
    "    def _init_callback(self):\n",
    "        if self.save_path is not None:\n",
    "            os.makedirs(self.save_path, exist_ok=True)\n",
    "\n",
    "    def _on_step(self):\n",
    "        if self.n_calls % self.check_freq == 0:\n",
    "            model_path = os.path.join(self.save_path, 'best_model_{}'.format(self.n_calls))\n",
    "            self.model.save(model_path)\n",
    "\n",
    "        return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7b389dd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "CHECKPOINT_DIR = './train/'\n",
    "LOG_DIR = './logs/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bdfe39ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setup model saving callback\n",
    "callback = TrainAndLoggingCallback(check_freq=10000, save_path=CHECKPOINT_DIR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "48ff612f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cpu device\n",
      "Wrapping the env in a VecTransposeImage.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\conda\\lib\\site-packages\\stable_baselines3\\ppo\\ppo.py:148: UserWarning: You have specified a mini-batch size of 64, but because the `RolloutBuffer` is of size `n_steps * n_envs = 400`, after every 6 untruncated mini-batches, there will be a truncated mini-batch of size 16\n",
      "We recommend using a `batch_size` that is a factor of `n_steps * n_envs`.\n",
      "Info: (n_steps=400 and n_envs=1)\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "model = PPO('CnnPolicy', env, verbose=1, tensorboard_log=LOG_DIR, learning_rate=0.0001, \n",
    "            n_steps=400) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bbea2a58",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Train the AI model, this is where the AI model starts to learn\n",
    "# model.learn(total_timesteps=100, callback=callback)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e6b4c1b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# model.save('thisisatestmodel')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "87cd3084",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\conda\\lib\\site-packages\\stable_baselines3\\common\\save_util.py:166: UserWarning: Could not deserialize object clip_range. Consider using `custom_objects` argument to replace this object.\n",
      "Exception: Can't get attribute '_make_function' on <module 'cloudpickle.cloudpickle' from 'C:\\\\conda\\\\lib\\\\site-packages\\\\cloudpickle\\\\cloudpickle.py'>\n",
      "  warnings.warn(\n",
      "C:\\conda\\lib\\site-packages\\stable_baselines3\\common\\save_util.py:166: UserWarning: Could not deserialize object lr_schedule. Consider using `custom_objects` argument to replace this object.\n",
      "Exception: Can't get attribute '_make_function' on <module 'cloudpickle.cloudpickle' from 'C:\\\\conda\\\\lib\\\\site-packages\\\\cloudpickle\\\\cloudpickle.py'>\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "model = PPO.load('./train/best_model_100000')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4e8fc57e",
   "metadata": {},
   "outputs": [],
   "source": [
    "state = env.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9db79c9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['right']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# SIMPLE_MOVEMENT[model.predict(state)[0][0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7babc644",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\conda\\lib\\site-packages\\gym\\utils\\passive_env_checker.py:233: DeprecationWarning: `np.bool8` is a deprecated alias for `np.bool_`.  (Deprecated NumPy 1.24)\n",
      "  if not isinstance(terminated, (bool, np.bool8)):\n",
      "C:\\conda\\lib\\site-packages\\gym\\utils\\passive_env_checker.py:272: UserWarning: \u001b[33mWARN: No render modes was declared in the environment (env.metadata['render_modes'] is None or not defined), you may have trouble when calling `.render()`.\u001b[0m\n",
      "  logger.warn(\n",
      "C:\\conda\\lib\\site-packages\\gym_super_mario_bros\\smb_env.py:148: RuntimeWarning: overflow encountered in scalar subtract\n",
      "  return (self.ram[0x86] - self.ram[0x071c]) % 256\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Start the game \n",
    "state = env.reset()\n",
    "# Loop through the game\n",
    "while True:     \n",
    "    action, _ = model.predict(state)\n",
    "    state, reward, done, info = env.step(action)\n",
    "    env.render()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38168858",
   "metadata": {},
   "outputs": [],
   "source": [
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ab7a1f26",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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