Dune_Q.ipynb

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            "Collecting wandb\n",
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            "\u001b[?25hRequirement already satisfied: click!=8.0.0,>=7.1 in /usr/local/lib/python3.10/dist-packages (from wandb) (8.1.7)\n",
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            "Collecting sentry-sdk>=1.0.0 (from wandb)\n",
            "  Downloading sentry_sdk-2.2.0-py2.py3-none-any.whl (281 kB)\n",
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            "\u001b[?25hCollecting setproctitle (from wandb)\n",
            "  Downloading setproctitle-1.3.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (30 kB)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from wandb) (67.7.2)\n",
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            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb) (2024.2.2)\n",
            "Collecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->gitpython!=3.1.29,>=1.0.0->wandb)\n",
            "  Downloading smmap-5.0.1-py3-none-any.whl (24 kB)\n",
            "Installing collected packages: smmap, setproctitle, sentry-sdk, docker-pycreds, gitdb, gitpython, wandb\n",
            "Successfully installed docker-pycreds-0.4.0 gitdb-4.0.11 gitpython-3.1.43 sentry-sdk-2.2.0 setproctitle-1.3.3 smmap-5.0.1 wandb-0.17.0\n"
          ]
        }
      ],
      "source": [
        "try:\n",
        "    import google.colab\n",
        "    COLAB = True\n",
        "except ModuleNotFoundError:\n",
        "    COLAB = False\n",
        "    pass\n",
        "\n",
        "if COLAB:\n",
        "    !pip -q install \"gymnasium[classic-control, atari, accept-rom-license]\"\n",
        "    !pip install -q gym matplotlib\n",
        "    !pip install wandb\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import wandb\n",
        "import random\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import time\n",
        "from gym import spaces\n",
        "import gymnasium as gym\n",
        "from functools import partial\n",
        "import matplotlib.pyplot as plt\n",
        "from IPython.display import clear_output\n",
        "\n",
        "%matplotlib inline\n"
      ],
      "metadata": {
        "id": "LmIkS0zQKXVJ"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import warnings\n",
        "\n",
        "# Бесят эти предупреждения об устаревании\n",
        "warnings.filterwarnings('ignore', category=DeprecationWarning)\n"
      ],
      "metadata": {
        "id": "7pHPetaZKold"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "wandb.init(project='Dune-Q', entity='Senich17')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 137
        },
        "id": "8s2HJ8M4OfDw",
        "outputId": "706ec081-ef20-42fe-fdbf-7122ceea5989"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33msenich17\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Tracking run with wandb version 0.17.0"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Run data is saved locally in <code>/content/wandb/run-20240520_085934-hpv5me37</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/hpv5me37' target=\"_blank\">olive-serenity-169</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/hpv5me37' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/hpv5me37</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<button onClick=\"this.nextSibling.style.display='block';this.style.display='none';\">Display W&B run</button><iframe src='https://wandb.ai/senich17/Dune-Q/runs/hpv5me37?jupyter=true' style='border:none;width:100%;height:420px;display:none;'></iframe>"
            ],
            "text/plain": [
              "<wandb.sdk.wandb_run.Run at 0x7e6d85c796f0>"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Детерминированная среда"
      ],
      "metadata": {
        "id": "myOAfZEmK48C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "Caladan = gym.make(\"Taxi-v3\", render_mode=\"rgb_array\")\n",
        "Caladan.reset()\n",
        "plt.imshow(Caladan.render())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 398
        },
        "id": "T2bCAqclLCIB",
        "outputId": "def60d4e-e30d-4683-a321-c8511a1ef29a"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x796cd9061090>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class Model:\n",
        "    def __init__(self, n_states, n_actions, seed):\n",
        "        self.n_states = n_states\n",
        "        self.n_actions = n_actions\n",
        "        self._rng = np.random.default_rng(seed)\n",
        "        self.data = []\n",
        "\n",
        "    def add(self, s: int, a: int, r: float, next_s: int) -> float:\n",
        "        self.data.append((s, a, r, next_s))\n",
        "        return r\n",
        "\n",
        "    def sample(self) -> tuple[int, int, float, int]:\n",
        "        idx = self._rng.integers(0, len(self.data))\n",
        "        return self.data[idx]\n",
        ""
      ],
      "metadata": {
        "id": "COFhFIih5Oyv"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "class PaulAtreides:\n",
        "    def __init__(self, n_states, n_actions, lr, gamma, eps, f_model, seed):\n",
        "        self.Q = np.zeros((n_states, n_actions))\n",
        "        self.model = f_model(n_states, n_actions, seed=seed)\n",
        "        self.lr = lr\n",
        "        self.gamma = gamma\n",
        "        self.eps = eps\n",
        "        self.n_actions = n_actions\n",
        "        self._rng = np.random.default_rng(seed)\n",
        "\n",
        "    def act(self, s):\n",
        "        if self._rng.random() < self.eps:\n",
        "            action = self._rng.choice(self.n_actions)\n",
        "        else:\n",
        "            action = np.argmax(self.Q[s])\n",
        "        return action\n",
        "\n",
        "    def update(self, s, a, r, s_n, update_model: bool):\n",
        "        max_next_action = np.argmax(self.Q[s_n])\n",
        "        td_target = r + self.gamma * self.Q[s_n][max_next_action]\n",
        "        td_error = td_target - self.Q[s][a]\n",
        "        self.Q[s][a] += self.lr * td_error\n",
        "\n",
        "        if update_model:\n",
        "            self.model.add(s, a, r, s_n)\n",
        "\n",
        "    def dream(self, max_steps, **_):\n",
        "        for _ in range(max_steps):\n",
        "            s, a, r, s_n = self.model.sample()\n",
        "            self.update(s, a, r, s_n, update_model=False)\n"
      ],
      "metadata": {
        "id": "uonsQunx5MWH"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def train(Caladan, agent, n_episodes, on_model_updates, seed, show_progress_schedule=50):\n",
        "    avg_returns, returns_batch = [], []\n",
        "    rng = np.random.default_rng(seed)\n",
        "\n",
        "    for i in range(1, n_episodes):\n",
        "        state, _ = Caladan.reset(seed=int(rng.integers(10000000)))\n",
        "        reward, episode_return = 0, 0\n",
        "\n",
        "        while True:\n",
        "            action = agent.act(state)\n",
        "\n",
        "            next_state, reward, terminated, truncated, info = Caladan.step(action)\n",
        "            agent.update(state, action, reward, next_state, update_model=True)\n",
        "            state = next_state\n",
        "            episode_return += reward\n",
        "            done = terminated or truncated\n",
        "            if done:\n",
        "                break\n",
        "            agent.dream(on_model_updates, state=state)\n",
        "\n",
        "            # Log episode data\n",
        "            wandb.log({'State': state, 'Action': action, 'Reward': reward, 'Next State': next_state})\n",
        "\n",
        "        returns_batch.append(episode_return)\n",
        "\n",
        "        if i % show_progress_schedule == 0:\n",
        "            avg_return = np.mean(returns_batch)\n",
        "            avg_returns.append((i, avg_return))\n",
        "            returns_batch = []\n",
        "\n",
        "            wandb.log({'Episode Return': episode_return, 'Average Return': avg_return})\n",
        "\n",
        "            print(\n",
        "                f\"Episode: {i}, Return: {episode_return}, \"\n",
        "                f\"AvgReturn[{show_progress_schedule}]: {avg_return:.0f}\"\n",
        "            )\n",
        "\n",
        "    return avg_returns\n",
        ""
      ],
      "metadata": {
        "id": "TKG7WX0-5JFs"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def main():\n",
        "    wandb.init(project=\"Dune-Q\")\n",
        "\n",
        "    n_states = Caladan.observation_space.n\n",
        "    n_actions = Caladan.action_space.n\n",
        "\n",
        "    print(f\"Observation space: {n_states}, Action space: {n_actions}\")\n",
        "\n",
        "    # Генерируем случайное значение seed на основе текущего времени\n",
        "    seed = int(time.time())\n",
        "\n",
        "    agent = PaulAtreides(\n",
        "        n_states,\n",
        "        n_actions,\n",
        "        f_model=Model,\n",
        "        lr=0.05,\n",
        "        gamma=0.975,\n",
        "        eps=0.1,\n",
        "        seed=seed\n",
        "    )\n",
        "\n",
        "    avg_returns = train(\n",
        "        Caladan,\n",
        "        agent,\n",
        "        on_model_updates=0,\n",
        "        seed=seed,\n",
        "        n_episodes=3001,\n",
        "    )\n"
      ],
      "metadata": {
        "id": "zlniSm1O5FwO"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Define the sweep configuration\n",
        "sweep_config = {\n",
        "    \"method\": \"grid\",\n",
        "    \"parameters\": {\n",
        "        \"n_planning_steps\": {\"values\": [1, 5, 10]},\n",
        "        \"n_dreaming_steps\": {\"values\": [1, 3, 5]}  # Add dreaming steps parameter\n",
        "    }\n",
        "}\n"
      ],
      "metadata": {
        "id": "P_c_2Xg0qVcX"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\"Процесс нельзя понять, остановив его. Постижение процесса развивается, следуя за ним, догоняя его, сливаясь с ним\" (с)\n",
        "\n",
        "Поэтому запустим алгоритм и будем перебирать параметры, анализируя их влияние."
      ],
      "metadata": {
        "id": "Gns212RaPb1V"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Start the sweep\n",
        "PaulTravel = wandb.sweep(sweep=sweep_config, project=\"Dune-Q\")\n",
        "\n",
        "# Run the sweep\n",
        "wandb.agent(PaulTravel, function=main, count=5)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
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            "74f752efb77d4a789f1489101b0cc8fc"
          ]
        },
        "id": "p59m9UXbXGye",
        "outputId": "fa04705b-a452-4120-d66c-e89cf540ecad"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Calling wandb.login() after wandb.init() has no effect.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Create sweep with ID: mh6e457x\n",
            "Sweep URL: https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: r251yh33 with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Tracking run with wandb version 0.17.0"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Run data is saved locally in <code>/content/wandb/run-20240520_081458-r251yh33</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/r251yh33' target=\"_blank\">sandy-sweep-1</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/r251yh33' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/r251yh33</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -220, AvgReturn[50]: -373\n",
            "Episode: 100, Return: -245, AvgReturn[50]: -274\n",
            "Episode: 150, Return: -308, AvgReturn[50]: -267\n",
            "Episode: 200, Return: -109, AvgReturn[50]: -235\n",
            "Episode: 250, Return: -45, AvgReturn[50]: -243\n",
            "Episode: 300, Return: -290, AvgReturn[50]: -219\n",
            "Episode: 350, Return: -299, AvgReturn[50]: -189\n",
            "Episode: 400, Return: -156, AvgReturn[50]: -210\n",
            "Episode: 450, Return: -236, AvgReturn[50]: -187\n",
            "Episode: 500, Return: -172, AvgReturn[50]: -173\n",
            "Episode: 550, Return: -150, AvgReturn[50]: -163\n",
            "Episode: 600, Return: -219, AvgReturn[50]: -144\n",
            "Episode: 650, Return: -63, AvgReturn[50]: -128\n",
            "Episode: 700, Return: -184, AvgReturn[50]: -124\n",
            "Episode: 750, Return: -137, AvgReturn[50]: -95\n",
            "Episode: 800, Return: -30, AvgReturn[50]: -108\n",
            "Episode: 850, Return: -139, AvgReturn[50]: -96\n",
            "Episode: 900, Return: -31, AvgReturn[50]: -93\n",
            "Episode: 950, Return: -140, AvgReturn[50]: -68\n",
            "Episode: 1000, Return: -109, AvgReturn[50]: -72\n",
            "Episode: 1050, Return: -98, AvgReturn[50]: -82\n",
            "Episode: 1100, Return: 13, AvgReturn[50]: -55\n",
            "Episode: 1150, Return: -8, AvgReturn[50]: -52\n",
            "Episode: 1200, Return: -40, AvgReturn[50]: -41\n",
            "Episode: 1250, Return: -122, AvgReturn[50]: -43\n",
            "Episode: 1300, Return: -9, AvgReturn[50]: -44\n",
            "Episode: 1350, Return: -54, AvgReturn[50]: -33\n",
            "Episode: 1400, Return: -57, AvgReturn[50]: -25\n",
            "Episode: 1450, Return: 2, AvgReturn[50]: -29\n",
            "Episode: 1500, Return: -47, AvgReturn[50]: -22\n",
            "Episode: 1550, Return: 12, AvgReturn[50]: -17\n",
            "Episode: 1600, Return: 3, AvgReturn[50]: -18\n",
            "Episode: 1650, Return: 12, AvgReturn[50]: -19\n",
            "Episode: 1700, Return: 5, AvgReturn[50]: -17\n",
            "Episode: 1750, Return: 1, AvgReturn[50]: -14\n",
            "Episode: 1800, Return: -8, AvgReturn[50]: -12\n",
            "Episode: 1850, Return: 0, AvgReturn[50]: -14\n",
            "Episode: 1900, Return: 8, AvgReturn[50]: -9\n",
            "Episode: 1950, Return: 8, AvgReturn[50]: -9\n",
            "Episode: 2000, Return: -49, AvgReturn[50]: -10\n",
            "Episode: 2050, Return: -15, AvgReturn[50]: -5\n",
            "Episode: 2100, Return: 6, AvgReturn[50]: -1\n",
            "Episode: 2150, Return: 9, AvgReturn[50]: -13\n",
            "Episode: 2200, Return: 0, AvgReturn[50]: -3\n",
            "Episode: 2250, Return: 8, AvgReturn[50]: -6\n",
            "Episode: 2300, Return: 8, AvgReturn[50]: 0\n",
            "Episode: 2350, Return: 7, AvgReturn[50]: -6\n",
            "Episode: 2400, Return: -25, AvgReturn[50]: -3\n",
            "Episode: 2450, Return: -12, AvgReturn[50]: -3\n",
            "Episode: 2500, Return: 10, AvgReturn[50]: -0\n",
            "Episode: 2550, Return: 11, AvgReturn[50]: -0\n",
            "Episode: 2600, Return: -45, AvgReturn[50]: -2\n",
            "Episode: 2650, Return: 8, AvgReturn[50]: -3\n",
            "Episode: 2700, Return: -5, AvgReturn[50]: -2\n",
            "Episode: 2750, Return: 6, AvgReturn[50]: -2\n",
            "Episode: 2800, Return: 9, AvgReturn[50]: -1\n",
            "Episode: 2850, Return: -1, AvgReturn[50]: 1\n",
            "Episode: 2900, Return: 5, AvgReturn[50]: 3\n",
            "Episode: 2950, Return: -1, AvgReturn[50]: 1\n",
            "Episode: 3000, Return: 10, AvgReturn[50]: 1\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(Label(value='0.001 MB of 0.001 MB uploaded\\r'), FloatProgress(value=1.0, max=1.0)))"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "065907e4041a437bbeae3ac44ea90ffc"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>▅▁▂▄▁▄▅▁▁▄▄▄▄▄▅▁▄▁▄▇▅▅▅▁▅▄▁▇▁▁▁▁█▄▂▄▁▅▂▅</td></tr><tr><td>Average Return</td><td>▁▃▄▃▄▄▅▅▆▆▆▆▇▇▇▇▇▇▇▇████████████████████</td></tr><tr><td>Episode Return</td><td>▃▂▅▇▁▄▄▄▆▄▇▅▅▅██▅█▆███████▇▇████▇█▇█████</td></tr><tr><td>Next State</td><td>▂▇▁▃█▁██▇▃▃▄▄▅▄▄▂▅▂▅▄▂▇▇▁▃▄▂▄▄▆▆▆█▁▅▇▂▅▄</td></tr><tr><td>Reward</td><td>███████████████████▁████████████▁███████</td></tr><tr><td>State</td><td>▂▇▁▃█▁██▇▃▃▄▄▅▄▄▂▅▂▅▄▂▇▇▁▃▄▂▄▄▆▆▆█▁▅▇▂▅▄</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>0</td></tr><tr><td>Average Return</td><td>1.22</td></tr><tr><td>Episode Return</td><td>10</td></tr><tr><td>Next State</td><td>479</td></tr><tr><td>Reward</td><td>-1</td></tr><tr><td>State</td><td>479</td></tr></table><br/></div></div>"
            ]
          },
          "metadata": {}
        },
        {
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          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run <strong style=\"color:#cdcd00\">sandy-sweep-1</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/r251yh33' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/r251yh33</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Find logs at: <code>./wandb/run-20240520_081458-r251yh33/logs</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: 519mz5bl with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 5\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33msenich17\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Tracking run with wandb version 0.17.0"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Run data is saved locally in <code>/content/wandb/run-20240520_081944-519mz5bl</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/519mz5bl' target=\"_blank\">classic-sweep-2</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/519mz5bl' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/519mz5bl</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -245, AvgReturn[50]: -371\n",
            "Episode: 100, Return: -254, AvgReturn[50]: -270\n",
            "Episode: 150, Return: -47, AvgReturn[50]: -245\n",
            "Episode: 200, Return: -290, AvgReturn[50]: -246\n",
            "Episode: 250, Return: -254, AvgReturn[50]: -223\n",
            "Episode: 300, Return: -249, AvgReturn[50]: -221\n",
            "Episode: 350, Return: -153, AvgReturn[50]: -205\n",
            "Episode: 400, Return: -141, AvgReturn[50]: -193\n",
            "Episode: 450, Return: -59, AvgReturn[50]: -182\n",
            "Episode: 500, Return: -152, AvgReturn[50]: -169\n",
            "Episode: 550, Return: -263, AvgReturn[50]: -146\n",
            "Episode: 600, Return: -272, AvgReturn[50]: -151\n",
            "Episode: 650, Return: -74, AvgReturn[50]: -147\n",
            "Episode: 700, Return: -53, AvgReturn[50]: -139\n",
            "Episode: 750, Return: -47, AvgReturn[50]: -112\n",
            "Episode: 800, Return: -11, AvgReturn[50]: -109\n",
            "Episode: 850, Return: -182, AvgReturn[50]: -100\n",
            "Episode: 900, Return: -150, AvgReturn[50]: -78\n",
            "Episode: 950, Return: -85, AvgReturn[50]: -77\n",
            "Episode: 1000, Return: -15, AvgReturn[50]: -74\n",
            "Episode: 1050, Return: -148, AvgReturn[50]: -63\n",
            "Episode: 1100, Return: -113, AvgReturn[50]: -54\n",
            "Episode: 1150, Return: -48, AvgReturn[50]: -50\n",
            "Episode: 1200, Return: -106, AvgReturn[50]: -61\n",
            "Episode: 1250, Return: -68, AvgReturn[50]: -34\n",
            "Episode: 1300, Return: -23, AvgReturn[50]: -40\n",
            "Episode: 1350, Return: -76, AvgReturn[50]: -45\n",
            "Episode: 1400, Return: -14, AvgReturn[50]: -34\n",
            "Episode: 1450, Return: -7, AvgReturn[50]: -27\n",
            "Episode: 1500, Return: 0, AvgReturn[50]: -23\n",
            "Episode: 1550, Return: -97, AvgReturn[50]: -23\n",
            "Episode: 1600, Return: 5, AvgReturn[50]: -20\n",
            "Episode: 1650, Return: 7, AvgReturn[50]: -18\n",
            "Episode: 1700, Return: -41, AvgReturn[50]: -14\n",
            "Episode: 1750, Return: -11, AvgReturn[50]: -16\n",
            "Episode: 1800, Return: -18, AvgReturn[50]: -17\n",
            "Episode: 1850, Return: 6, AvgReturn[50]: -9\n",
            "Episode: 1900, Return: 11, AvgReturn[50]: -9\n",
            "Episode: 1950, Return: 2, AvgReturn[50]: -7\n",
            "Episode: 2000, Return: -36, AvgReturn[50]: -12\n",
            "Episode: 2050, Return: 12, AvgReturn[50]: -9\n",
            "Episode: 2100, Return: -19, AvgReturn[50]: -11\n",
            "Episode: 2150, Return: -5, AvgReturn[50]: -8\n",
            "Episode: 2200, Return: 1, AvgReturn[50]: -6\n",
            "Episode: 2250, Return: 6, AvgReturn[50]: -5\n",
            "Episode: 2300, Return: 4, AvgReturn[50]: -2\n",
            "Episode: 2350, Return: -30, AvgReturn[50]: -2\n",
            "Episode: 2400, Return: 10, AvgReturn[50]: -4\n",
            "Episode: 2450, Return: 8, AvgReturn[50]: 1\n",
            "Episode: 2500, Return: 10, AvgReturn[50]: -3\n",
            "Episode: 2550, Return: -41, AvgReturn[50]: -3\n",
            "Episode: 2600, Return: -24, AvgReturn[50]: 1\n",
            "Episode: 2650, Return: 10, AvgReturn[50]: -1\n",
            "Episode: 2700, Return: 9, AvgReturn[50]: -0\n",
            "Episode: 2750, Return: -13, AvgReturn[50]: 0\n",
            "Episode: 2800, Return: 0, AvgReturn[50]: 1\n",
            "Episode: 2850, Return: 8, AvgReturn[50]: 1\n",
            "Episode: 2900, Return: 13, AvgReturn[50]: 3\n",
            "Episode: 2950, Return: 7, AvgReturn[50]: -2\n",
            "Episode: 3000, Return: 1, AvgReturn[50]: 2\n"
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              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>▁▅█▄▂▅▅▅▂▁▂▅▅▅▄▄▂▅▄▅▂▄▂▂▁▄▅▄▂▂▄▁▄▄▁▁▂▂▂▂</td></tr><tr><td>Average Return</td><td>▁▃▃▄▄▄▅▅▅▅▆▆▇▇▇▇▇▇▇▇████████████████████</td></tr><tr><td>Episode Return</td><td>▂▂▁▂▄▄▄▂▆▆▇▃▆▇▅▇▆▇▇█▅█▇▇██▇████▇██▇█▇███</td></tr><tr><td>Next State</td><td>▇▁▁▂▁▇▄▂▁▆▁▄▅▄▅▅▆▅▃▁▁▁▂▆▄██▃▃▆█▇▅▄▄▆▅▆▃▅</td></tr><tr><td>Reward</td><td>██▁█████████████████████████████████████</td></tr><tr><td>State</td><td>▇▁▁▂▁▇▄▂▁▆▁▄▅▄▅▅▆▅▃▁▁▁▂▆▄██▃▃▆█▇▅▄▄▆▅▆▃▅</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>3</td></tr><tr><td>Average Return</td><td>2.06</td></tr><tr><td>Episode Return</td><td>1</td></tr><tr><td>Next State</td><td>418</td></tr><tr><td>Reward</td><td>-1</td></tr><tr><td>State</td><td>418</td></tr></table><br/></div></div>"
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              " View run <strong style=\"color:#cdcd00\">classic-sweep-2</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/519mz5bl' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/519mz5bl</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
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            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: 8o54aboo with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 10\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
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        {
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              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/8o54aboo' target=\"_blank\">laced-sweep-3</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
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              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
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          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -263, AvgReturn[50]: -369\n",
            "Episode: 100, Return: -452, AvgReturn[50]: -255\n",
            "Episode: 150, Return: -290, AvgReturn[50]: -273\n",
            "Episode: 200, Return: -299, AvgReturn[50]: -253\n",
            "Episode: 250, Return: -75, AvgReturn[50]: -237\n",
            "Episode: 300, Return: -62, AvgReturn[50]: -213\n",
            "Episode: 350, Return: -172, AvgReturn[50]: -204\n",
            "Episode: 400, Return: -144, AvgReturn[50]: -190\n",
            "Episode: 450, Return: -281, AvgReturn[50]: -176\n",
            "Episode: 500, Return: -120, AvgReturn[50]: -174\n",
            "Episode: 550, Return: -244, AvgReturn[50]: -161\n",
            "Episode: 600, Return: -272, AvgReturn[50]: -157\n",
            "Episode: 650, Return: -78, AvgReturn[50]: -123\n",
            "Episode: 700, Return: 3, AvgReturn[50]: -125\n",
            "Episode: 750, Return: -78, AvgReturn[50]: -110\n",
            "Episode: 800, Return: -132, AvgReturn[50]: -76\n",
            "Episode: 850, Return: -185, AvgReturn[50]: -90\n",
            "Episode: 900, Return: -213, AvgReturn[50]: -87\n",
            "Episode: 950, Return: -39, AvgReturn[50]: -87\n",
            "Episode: 1000, Return: 4, AvgReturn[50]: -72\n",
            "Episode: 1050, Return: -58, AvgReturn[50]: -64\n",
            "Episode: 1100, Return: 11, AvgReturn[50]: -65\n",
            "Episode: 1150, Return: 10, AvgReturn[50]: -56\n",
            "Episode: 1200, Return: -74, AvgReturn[50]: -50\n",
            "Episode: 1250, Return: -5, AvgReturn[50]: -32\n",
            "Episode: 1300, Return: -1, AvgReturn[50]: -28\n",
            "Episode: 1350, Return: 0, AvgReturn[50]: -41\n",
            "Episode: 1400, Return: -6, AvgReturn[50]: -24\n",
            "Episode: 1450, Return: 2, AvgReturn[50]: -19\n",
            "Episode: 1500, Return: -18, AvgReturn[50]: -25\n",
            "Episode: 1550, Return: -51, AvgReturn[50]: -24\n",
            "Episode: 1600, Return: 2, AvgReturn[50]: -17\n",
            "Episode: 1650, Return: 7, AvgReturn[50]: -11\n",
            "Episode: 1700, Return: -11, AvgReturn[50]: -13\n",
            "Episode: 1750, Return: -64, AvgReturn[50]: -12\n",
            "Episode: 1800, Return: 13, AvgReturn[50]: -9\n",
            "Episode: 1850, Return: 1, AvgReturn[50]: -11\n",
            "Episode: 1900, Return: 7, AvgReturn[50]: -4\n",
            "Episode: 1950, Return: 4, AvgReturn[50]: -10\n",
            "Episode: 2000, Return: 4, AvgReturn[50]: -11\n",
            "Episode: 2050, Return: -41, AvgReturn[50]: -4\n",
            "Episode: 2100, Return: 6, AvgReturn[50]: -8\n",
            "Episode: 2150, Return: 7, AvgReturn[50]: -6\n",
            "Episode: 2200, Return: -18, AvgReturn[50]: -5\n",
            "Episode: 2250, Return: 2, AvgReturn[50]: -6\n",
            "Episode: 2300, Return: 10, AvgReturn[50]: -1\n",
            "Episode: 2350, Return: 8, AvgReturn[50]: -3\n",
            "Episode: 2400, Return: -13, AvgReturn[50]: -5\n",
            "Episode: 2450, Return: 0, AvgReturn[50]: -4\n",
            "Episode: 2500, Return: 3, AvgReturn[50]: 2\n",
            "Episode: 2550, Return: -3, AvgReturn[50]: -3\n",
            "Episode: 2600, Return: 9, AvgReturn[50]: 1\n",
            "Episode: 2650, Return: -22, AvgReturn[50]: 1\n",
            "Episode: 2700, Return: 9, AvgReturn[50]: -2\n",
            "Episode: 2750, Return: -39, AvgReturn[50]: 0\n",
            "Episode: 2800, Return: 9, AvgReturn[50]: 2\n",
            "Episode: 2850, Return: 9, AvgReturn[50]: 2\n",
            "Episode: 2900, Return: -6, AvgReturn[50]: 1\n",
            "Episode: 2950, Return: -7, AvgReturn[50]: -0\n",
            "Episode: 3000, Return: -6, AvgReturn[50]: 1\n"
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              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>▁▂▄▄▂▁▅▅▁▅▁▄▅▁█▂▂▄▄▁▄▅▄▁▄▅▄▂▁▁▁▅▅▅▄▇▄▁▁▁</td></tr><tr><td>Average Return</td><td>▁▃▃▃▄▄▅▅▆▆▇▆▆▇▇▇▇▇██████████████████████</td></tr><tr><td>Episode Return</td><td>▄▁▃▇▅▆▆▄▇█▆▅▇███████▇██▇███▇████████▇███</td></tr><tr><td>Next State</td><td>▆▁▇▅▁█▃▂█▂▇▃▆▄▄▆▄▃▆▂▆▇▃▅▄▄▁▅▅▅▅▃▄▁▅▁▁▄█▃</td></tr><tr><td>Reward</td><td>██████████████▁█████████████████████████</td></tr><tr><td>State</td><td>▆▁▇▅▁█▃▂█▂▇▃▆▄▄▆▄▃▆▂▆▇▃▅▄▄▁▅▅▅▅▃▄▁▅▁▁▄█▃</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>1</td></tr><tr><td>Average Return</td><td>0.74</td></tr><tr><td>Episode Return</td><td>-6</td></tr><tr><td>Next State</td><td>16</td></tr><tr><td>Reward</td><td>-1</td></tr><tr><td>State</td><td>16</td></tr></table><br/></div></div>"
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              " View run <strong style=\"color:#cdcd00\">laced-sweep-3</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/8o54aboo' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/8o54aboo</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
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              "Find logs at: <code>./wandb/run-20240520_082426-8o54aboo/logs</code>"
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          },
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        },
        {
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          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: izcibsa2 with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 3\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
          ]
        },
        {
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          "data": {
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              "<IPython.core.display.HTML object>"
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              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/izcibsa2' target=\"_blank\">hardy-sweep-4</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
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              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
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              "<IPython.core.display.HTML object>"
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              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
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        {
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          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -200, AvgReturn[50]: -377\n",
            "Episode: 100, Return: -272, AvgReturn[50]: -270\n",
            "Episode: 150, Return: -219, AvgReturn[50]: -253\n",
            "Episode: 200, Return: -254, AvgReturn[50]: -247\n",
            "Episode: 250, Return: -271, AvgReturn[50]: -232\n",
            "Episode: 300, Return: 6, AvgReturn[50]: -219\n",
            "Episode: 350, Return: -290, AvgReturn[50]: -220\n",
            "Episode: 400, Return: -272, AvgReturn[50]: -200\n",
            "Episode: 450, Return: -326, AvgReturn[50]: -175\n",
            "Episode: 500, Return: -259, AvgReturn[50]: -153\n",
            "Episode: 550, Return: -294, AvgReturn[50]: -160\n",
            "Episode: 600, Return: -371, AvgReturn[50]: -139\n",
            "Episode: 650, Return: -5, AvgReturn[50]: -146\n",
            "Episode: 700, Return: 10, AvgReturn[50]: -132\n",
            "Episode: 750, Return: -308, AvgReturn[50]: -102\n",
            "Episode: 800, Return: -43, AvgReturn[50]: -88\n",
            "Episode: 850, Return: -192, AvgReturn[50]: -92\n",
            "Episode: 900, Return: -94, AvgReturn[50]: -84\n",
            "Episode: 950, Return: -82, AvgReturn[50]: -80\n",
            "Episode: 1000, Return: -49, AvgReturn[50]: -79\n",
            "Episode: 1050, Return: -25, AvgReturn[50]: -58\n",
            "Episode: 1100, Return: 10, AvgReturn[50]: -73\n",
            "Episode: 1150, Return: -54, AvgReturn[50]: -54\n",
            "Episode: 1200, Return: -31, AvgReturn[50]: -52\n",
            "Episode: 1250, Return: -42, AvgReturn[50]: -42\n",
            "Episode: 1300, Return: -57, AvgReturn[50]: -29\n",
            "Episode: 1350, Return: 13, AvgReturn[50]: -29\n",
            "Episode: 1400, Return: -4, AvgReturn[50]: -22\n",
            "Episode: 1450, Return: -19, AvgReturn[50]: -29\n",
            "Episode: 1500, Return: -14, AvgReturn[50]: -17\n",
            "Episode: 1550, Return: -2, AvgReturn[50]: -23\n",
            "Episode: 1600, Return: 0, AvgReturn[50]: -16\n",
            "Episode: 1650, Return: 9, AvgReturn[50]: -24\n",
            "Episode: 1700, Return: -6, AvgReturn[50]: -13\n",
            "Episode: 1750, Return: 8, AvgReturn[50]: -15\n",
            "Episode: 1800, Return: -61, AvgReturn[50]: -13\n",
            "Episode: 1850, Return: 4, AvgReturn[50]: -10\n",
            "Episode: 1900, Return: -10, AvgReturn[50]: -6\n",
            "Episode: 1950, Return: 8, AvgReturn[50]: -14\n",
            "Episode: 2000, Return: 10, AvgReturn[50]: -4\n",
            "Episode: 2050, Return: -15, AvgReturn[50]: -6\n",
            "Episode: 2100, Return: 12, AvgReturn[50]: -9\n",
            "Episode: 2150, Return: 12, AvgReturn[50]: -2\n",
            "Episode: 2200, Return: -4, AvgReturn[50]: -4\n",
            "Episode: 2250, Return: 7, AvgReturn[50]: -4\n",
            "Episode: 2300, Return: -7, AvgReturn[50]: -1\n",
            "Episode: 2350, Return: -25, AvgReturn[50]: -3\n",
            "Episode: 2400, Return: 11, AvgReturn[50]: -6\n",
            "Episode: 2450, Return: 6, AvgReturn[50]: -0\n",
            "Episode: 2500, Return: 3, AvgReturn[50]: -6\n",
            "Episode: 2550, Return: 2, AvgReturn[50]: 0\n",
            "Episode: 2600, Return: 12, AvgReturn[50]: -1\n",
            "Episode: 2650, Return: 9, AvgReturn[50]: -1\n",
            "Episode: 2700, Return: 9, AvgReturn[50]: 1\n",
            "Episode: 2750, Return: -2, AvgReturn[50]: 1\n",
            "Episode: 2800, Return: 7, AvgReturn[50]: -1\n",
            "Episode: 2850, Return: -26, AvgReturn[50]: -1\n",
            "Episode: 2900, Return: 9, AvgReturn[50]: 5\n",
            "Episode: 2950, Return: -8, AvgReturn[50]: 1\n",
            "Episode: 3000, Return: 10, AvgReturn[50]: 3\n"
          ]
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              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>█▆▃▃█▆▅▃▃▅▅▆▃▅▃▁▆▆▃▃▃▃▁▅▅█▃▆▅▆█▃▆▃▅▃▆▆▅▆</td></tr><tr><td>Average Return</td><td>▁▃▃▄▄▄▅▅▅▅▆▆▆▆▇▇▇▇█▇▇███████████████████</td></tr><tr><td>Episode Return</td><td>▃▂▂▂▁▂▂▁██▇▃▆▇█▆▇▆█▇█████▇█▇███▇████████</td></tr><tr><td>Next State</td><td>▇▃▂▆▅▅▇▁▄█▁▂▂▂▇▃▄▅▁▃▄▆▃▃▂▅▆▇▁▆▂▇▇▇▆▆▅█▆▅</td></tr><tr><td>Reward</td><td>▁███▁████████████████████▁██████████████</td></tr><tr><td>State</td><td>▇▃▂▆▅▅▇▁▄█▁▂▂▂▇▃▄▅▁▃▄▆▃▃▂▅▆▇▁▆▂▇▇▇▆▆▅█▆▅</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>1</td></tr><tr><td>Average Return</td><td>2.58</td></tr><tr><td>Episode Return</td><td>10</td></tr><tr><td>Next State</td><td>97</td></tr><tr><td>Reward</td><td>-1</td></tr><tr><td>State</td><td>97</td></tr></table><br/></div></div>"
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              " View run <strong style=\"color:#cdcd00\">hardy-sweep-4</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/izcibsa2' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/izcibsa2</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
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              "<IPython.core.display.HTML object>"
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              "Find logs at: <code>./wandb/run-20240520_082908-izcibsa2/logs</code>"
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: n0x9fv9s with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 3\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 5\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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            "text/html": [
              "Tracking run with wandb version 0.17.0"
            ]
          },
          "metadata": {}
        },
        {
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          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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            "text/html": [
              "Run data is saved locally in <code>/content/wandb/run-20240520_083355-n0x9fv9s</code>"
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          },
          "metadata": {}
        },
        {
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          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/n0x9fv9s' target=\"_blank\">easy-sweep-5</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
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        {
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              "<IPython.core.display.HTML object>"
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            "text/html": [
              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/mh6e457x</a>"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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            "text/html": [
              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/n0x9fv9s' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/n0x9fv9s</a>"
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        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -380, AvgReturn[50]: -379\n",
            "Episode: 100, Return: -245, AvgReturn[50]: -265\n",
            "Episode: 150, Return: -22, AvgReturn[50]: -259\n",
            "Episode: 200, Return: -225, AvgReturn[50]: -245\n",
            "Episode: 250, Return: -272, AvgReturn[50]: -230\n",
            "Episode: 300, Return: -254, AvgReturn[50]: -209\n",
            "Episode: 350, Return: -24, AvgReturn[50]: -216\n",
            "Episode: 400, Return: -317, AvgReturn[50]: -204\n",
            "Episode: 450, Return: -281, AvgReturn[50]: -181\n",
            "Episode: 500, Return: -294, AvgReturn[50]: -184\n",
            "Episode: 550, Return: -265, AvgReturn[50]: -136\n",
            "Episode: 600, Return: -106, AvgReturn[50]: -129\n",
            "Episode: 650, Return: -34, AvgReturn[50]: -136\n",
            "Episode: 700, Return: -122, AvgReturn[50]: -125\n",
            "Episode: 750, Return: -33, AvgReturn[50]: -114\n",
            "Episode: 800, Return: -4, AvgReturn[50]: -128\n",
            "Episode: 850, Return: 13, AvgReturn[50]: -103\n",
            "Episode: 900, Return: -139, AvgReturn[50]: -60\n",
            "Episode: 950, Return: -158, AvgReturn[50]: -77\n",
            "Episode: 1000, Return: -35, AvgReturn[50]: -67\n",
            "Episode: 1050, Return: -21, AvgReturn[50]: -79\n",
            "Episode: 1100, Return: 1, AvgReturn[50]: -48\n",
            "Episode: 1150, Return: -108, AvgReturn[50]: -42\n",
            "Episode: 1200, Return: -22, AvgReturn[50]: -37\n",
            "Episode: 1250, Return: -227, AvgReturn[50]: -32\n",
            "Episode: 1300, Return: -37, AvgReturn[50]: -33\n",
            "Episode: 1350, Return: -33, AvgReturn[50]: -44\n",
            "Episode: 1400, Return: -55, AvgReturn[50]: -27\n",
            "Episode: 1450, Return: -105, AvgReturn[50]: -19\n",
            "Episode: 1500, Return: -50, AvgReturn[50]: -24\n",
            "Episode: 1550, Return: -59, AvgReturn[50]: -18\n",
            "Episode: 1600, Return: -49, AvgReturn[50]: -20\n",
            "Episode: 1650, Return: -27, AvgReturn[50]: -16\n",
            "Episode: 1700, Return: -62, AvgReturn[50]: -22\n",
            "Episode: 1750, Return: 2, AvgReturn[50]: -19\n",
            "Episode: 1800, Return: -15, AvgReturn[50]: -13\n",
            "Episode: 1850, Return: -7, AvgReturn[50]: -12\n",
            "Episode: 1900, Return: 3, AvgReturn[50]: -6\n",
            "Episode: 1950, Return: -12, AvgReturn[50]: -7\n",
            "Episode: 2000, Return: 8, AvgReturn[50]: -6\n",
            "Episode: 2050, Return: -29, AvgReturn[50]: -7\n",
            "Episode: 2100, Return: 1, AvgReturn[50]: -8\n",
            "Episode: 2150, Return: 9, AvgReturn[50]: -3\n",
            "Episode: 2200, Return: 14, AvgReturn[50]: -2\n",
            "Episode: 2250, Return: 5, AvgReturn[50]: -2\n",
            "Episode: 2300, Return: -3, AvgReturn[50]: -3\n",
            "Episode: 2350, Return: 10, AvgReturn[50]: -1\n",
            "Episode: 2400, Return: 5, AvgReturn[50]: -2\n",
            "Episode: 2450, Return: 3, AvgReturn[50]: -3\n",
            "Episode: 2500, Return: 0, AvgReturn[50]: -3\n",
            "Episode: 2550, Return: 2, AvgReturn[50]: -1\n",
            "Episode: 2600, Return: -6, AvgReturn[50]: -2\n",
            "Episode: 2650, Return: 8, AvgReturn[50]: 2\n",
            "Episode: 2700, Return: 13, AvgReturn[50]: 3\n",
            "Episode: 2750, Return: 5, AvgReturn[50]: 2\n",
            "Episode: 2800, Return: -7, AvgReturn[50]: 3\n",
            "Episode: 2850, Return: -3, AvgReturn[50]: 0\n",
            "Episode: 2900, Return: 6, AvgReturn[50]: 1\n",
            "Episode: 2950, Return: 7, AvgReturn[50]: 2\n",
            "Episode: 3000, Return: 5, AvgReturn[50]: 2\n"
          ]
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            "text/html": [
              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>█▃▃▅▃▁▃▆▁▁▅▃▆▅▃▅▁▁▁▅▅▃▁▆█▅▆▅▆▃▆▅▁▆▅▅▅▆▃▆</td></tr><tr><td>Average Return</td><td>▁▃▃▄▄▄▅▅▅▆▆▆▇▇▇▇▇▇▇█████████████████████</td></tr><tr><td>Episode Return</td><td>▁▃▄▃▇▂▃▃▇▆██▅▇█▆▄▇▇▆▇▇▇████▇████████████</td></tr><tr><td>Next State</td><td>█▅▂▄▃▅▃▆▇█▂▆▅▂▂█▆█▇▅▄▅▇▆▂█▅▇▁▂▄▆▄▇▅▄▅▅▃▂</td></tr><tr><td>Reward</td><td>▁███████████████████████▁███████████████</td></tr><tr><td>State</td><td>█▅▂▄▃▅▃▆▇█▂▆▅▂▂█▆█▇▅▄▅▇▆▂█▅▇▁▂▄▆▄▇▅▄▅▅▃▂</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Action</td><td>1</td></tr><tr><td>Average Return</td><td>2.06</td></tr><tr><td>Episode Return</td><td>5</td></tr><tr><td>Next State</td><td>97</td></tr><tr><td>Reward</td><td>-1</td></tr><tr><td>State</td><td>97</td></tr></table><br/></div></div>"
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            "text/html": [
              " View run <strong style=\"color:#cdcd00\">easy-sweep-5</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/n0x9fv9s' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/n0x9fv9s</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
            ]
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        {
          "output_type": "display_data",
          "data": {
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              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Find logs at: <code>./wandb/run-20240520_083355-n0x9fv9s/logs</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Error in callback <bound method _WandbInit._pause_backend of <wandb.sdk.wandb_init._WandbInit object at 0x796d1e87a980>> (for post_run_cell):\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "BrokenPipeError",
          "evalue": "[Errno 32] Broken pipe",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mBrokenPipeError\u001b[0m                           Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_init.py\u001b[0m in \u001b[0;36m_pause_backend\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    430\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minterface\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    431\u001b[0m             \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"pausing backend\"\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 432\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minterface\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpublish_pause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    433\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    434\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_resume_backend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m#  noqa\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/interface/interface.py\u001b[0m in \u001b[0;36mpublish_pause\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    696\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mpublish_pause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    697\u001b[0m         \u001b[0mpause\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPauseRequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 698\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_publish_pause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpause\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    699\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    700\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mabstractmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/interface/interface_shared.py\u001b[0m in \u001b[0;36m_publish_pause\u001b[0;34m(self, pause)\u001b[0m\n\u001b[1;32m    357\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_publish_pause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpause\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mpb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPauseRequest\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    358\u001b[0m         \u001b[0mrec\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpause\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpause\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 359\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_publish\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrec\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    360\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    361\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_publish_resume\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresume\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mpb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mResumeRequest\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/interface/interface_sock.py\u001b[0m in \u001b[0;36m_publish\u001b[0;34m(self, record, local)\u001b[0m\n\u001b[1;32m     49\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_publish\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecord\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"pb.Record\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mbool\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_assign\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecord\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock_client\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend_record_publish\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecord\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     52\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m     def _communicate_async(\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/sock_client.py\u001b[0m in \u001b[0;36msend_record_publish\u001b[0;34m(self, record)\u001b[0m\n\u001b[1;32m    219\u001b[0m         \u001b[0mserver_req\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mspb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mServerRequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    220\u001b[0m         \u001b[0mserver_req\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecord_publish\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCopyFrom\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecord\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 221\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend_server_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mserver_req\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    222\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    223\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_extract_packet_bytes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mbytes\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/sock_client.py\u001b[0m in \u001b[0;36msend_server_request\u001b[0;34m(self, msg)\u001b[0m\n\u001b[1;32m    153\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    154\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msend_server_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 155\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_message\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    156\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    157\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msend_server_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/sock_client.py\u001b[0m in \u001b[0;36m_send_message\u001b[0;34m(self, msg)\u001b[0m\n\u001b[1;32m    150\u001b[0m         \u001b[0mheader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstruct\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"<BI\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mord\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"W\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mraw_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    151\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 152\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sendall_with_error_handle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheader\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    153\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    154\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msend_server_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/sock_client.py\u001b[0m in \u001b[0;36m_sendall_with_error_handle\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    128\u001b[0m             \u001b[0mstart_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmonotonic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    129\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 130\u001b[0;31m                 \u001b[0msent\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    131\u001b[0m                 \u001b[0;31m# sent equal to 0 indicates a closed socket\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    132\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0msent\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mBrokenPipeError\u001b[0m: [Errno 32] Broken pipe"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "WandB ссылка на отчет: https://wandb.ai/senich17/Dune-Q/reports/Paul-on-Caladan--Vmlldzo4MDIwNjUx?accessToken=oh7t2i45j5oucujri0noy3rofgqf7y1qe82mknrcnkaonur85xbsa4tebr2o01ma"
      ],
      "metadata": {
        "id": "p68uDHHSN5tw"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Выводы по гиперпараметрам\n",
        "\n",
        "В мире обучения с подкреплением, как в песках Арракиса, гиперпараметры играют важную роль, формируя путь к успеху или провалу...\n",
        "\n",
        "### 1. Пол Атрейдес на Каладане с n_dreaming_steps: 1 и n_planning_steps: 1\n",
        "\n",
        "Средний возврат составил 1.22, а возврат за эпизод был 10. Это свидетельствует о том, что модель, подобно молодому Полу Атрейдесу, имеет общую положительную тенденцию, но иногда может сталкиваться с вызовами. Хотя средний возврат высок, иногда возникают отдельные эпизоды с более низкими возвратами, что указывает на необходимость дальнейшего улучшения модели и ее стабилизацию.\n",
        "\n",
        "### 2. Лето Атрейдес – управляющий Каладаном с n_dreaming_steps: 1 и n_planning_steps: 5\n",
        "\n",
        "Средний возврат составил 2.06, а возврат за эпизод был 1. В этом случае модель, как и герцог Лето Атрейдес, проявляет стабильность и умение находить баланс. Хотя средний возврат немного выше, отдельные эпизоды могут быть менее успешными, что подчеркивает важность постоянного улучшения стратегии.\n",
        "\n",
        "### 3. Лето и Джессика с n_dreaming_steps: 1 и n_planning_steps: 10\n",
        "\n",
        "Средний возврат составил 0.74, а возврат за эпизод был -6. Это указывает на то, что модель стремится к идеалу, как Лето и Джессика, но её успехи неравномерны. при сочетании параметров таким образом, как в этом запуске, модель может столкнуться с тем, что застревает в минимумах (но это не точно). Чтобы точно определить причину отрицательного возврата за эпизоды, необходимо более глубокое анализировать обучение модели. Например, негативный возврат эпизодов может быть обусловлен недостаточным исследованием среды.\n",
        "\n",
        "### 4. Пол и его тренировки с Дунканом Айдахо с n_dreaming_steps: 3 и n_planning_steps: 1\n",
        "\n",
        "Средний возврат составил 2.58, а возврат за эпизод был 10. Модель, подобно Полу, получает ценный опыт и стремится к совершенству, ни смотря на скачки показателей за эпизоды. Высокие показатели указывают на то, что необходимо точно и детально анализировать параметры и шаг за шагом наблюдать за их влиянием на поведение модели. Что интересно в данном запуске, так это то, что при низком значении n_planning_steps и высоком n_dreaming_steps результат впечатляющий (на моей практике в 100500 раз, которые я переделывала эту работу, при таких значениях, особенно в стохаститческой среде, все выглядит совсем печально).\n",
        "\n",
        "### 5. Пол и его друг Гурни Халлек с n_dreaming_steps: 3 и n_planning_steps: 5\n",
        "\n",
        "Средний возврат составил 2.06, а возврат за эпизод был 5. Модель, подобно Полу и его другу Гурни Халлеку, находит радость и удовлетворение в своей стратегии. В целом, средний возврат положителен, и кажется, будто такие значения параметров неплохо сбалансированы. Это будет заметно и в дальнейших экспериментах. Важно четко понимать, что сильные перекосы в параметрах будут давать модели нестабильность и неустойчивость, которые в свою очередь приведут к низким показателям и не качественному обучению. В целом модели РЛ и так плохо обобщаются, поэтому не надо подливать масла в огонь :)\n",
        "\n",
        "### Общий вывод\n",
        "\n",
        "Модели с разными наборами гиперпараметров представляют собой различные эпизоды жизни героев на Каладане. Понимание и оптимизация этих параметров помогает модели достигать лучших результатов и преодолевать вызовы, создавая прочный фундамент для будущих достижений. Естественно, что такое небольшое количество эпизодов так же влияет на результаты, но тем не менее даже при таких игрушечных экспереметах заметна разница."
      ],
      "metadata": {
        "id": "QytDeiyfnyPP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Стохастическая среда"
      ],
      "metadata": {
        "id": "AbmWuHLsMlM6"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\"Привычка к одним лишь победам сама по себе может стать слабостью.\" (С)\n",
        "\n",
        "Поэтому добавим нашему агенту препятствия на пути к его величию."
      ],
      "metadata": {
        "id": "XU7uiYoVDZpV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class SandStormArrakis(gym.Wrapper):\n",
        "    def __init__(self, env, wind_prob=0.2, wind_strength=1):\n",
        "        super().__init__(env)\n",
        "        self.wind_prob = wind_prob  # Вероятность воздействия ветра\n",
        "        self.wind_strength = wind_strength  # Сила воздействия ветра\n",
        "\n",
        "    def step(self, action):\n",
        "        # делаем шаг в оригинальной среде\n",
        "        next_state, reward, terminated, truncated, info = self.env.step(action)\n",
        "\n",
        "        # Определяем, будет ли воздействие ветра на текущем шаге\n",
        "        if np.random.rand() < self.wind_prob:\n",
        "            # применим ветер к среде\n",
        "            wind_action = np.random.choice([-self.wind_strength, 0, self.wind_strength])\n",
        "            next_state = (next_state + wind_action) % self.env.observation_space.n\n",
        "\n",
        "        return next_state, reward, terminated, truncated, info\n"
      ],
      "metadata": {
        "id": "Q5Uu3iTWrBH9"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Тут у нас будет моделька\n",
        "class Model:\n",
        "    def __init__(self, n_states, n_actions, seed):\n",
        "        self.n_states = n_states\n",
        "        self.n_actions = n_actions\n",
        "        self._rng = np.random.default_rng(seed)\n",
        "        self.data = []\n",
        "\n",
        "    def add(self, s, a, r, next_s):\n",
        "        self.data.append((s, a, r, next_s))\n",
        "        return r\n",
        "\n",
        "    def sample(self):\n",
        "        idx = self._rng.integers(0, len(self.data))\n",
        "        return self.data[idx]\n"
      ],
      "metadata": {
        "id": "D9_lt2gXVt8n"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\"— Ты должен выбрать себе имя, которым мы будем называть тебя открыто.\n",
        "— Как вы называете тень от второй луны?\n",
        "— Тень второй луны мы называем Муад’диб.\n",
        "— Можно ли мне называть себя Пол Муад’диб?\n",
        "— Отныне ты будешь Пол Муад’диб.\" (с)"
      ],
      "metadata": {
        "id": "c2Q1pHHUD58i"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# А тут у нас живет агент Пол Муад’диб\n",
        "class Muaddib:\n",
        "    def __init__(self, n_states, n_actions, lr, gamma, eps, f_model, seed):\n",
        "        self.Q = np.zeros((n_states, n_actions))\n",
        "        self.model = f_model(n_states, n_actions, seed=seed)\n",
        "        self.lr = lr\n",
        "        self.gamma = gamma\n",
        "        self.eps = eps\n",
        "        self.n_actions = n_actions\n",
        "        self.n_states = n_states\n",
        "        self._rng = np.random.default_rng(seed)\n",
        "\n",
        "    def act(self, s):\n",
        "        if s >= self.n_states:\n",
        "            raise ValueError(f\"State index {s} is out of bounds for Q-table with size {self.n_states}\")\n",
        "\n",
        "        if self._rng.random() < self.eps:\n",
        "            action = self._rng.choice(self.n_actions)\n",
        "        else:\n",
        "            action = np.argmax(self.Q[s])\n",
        "        return action\n",
        "\n",
        "    def update(self, s, a, r, s_n, update_model: bool):\n",
        "        if s >= self.n_states or s_n >= self.n_states:\n",
        "            raise ValueError(f\"State index {s} or next state index {s_n} is out of bounds for Q-table with size {self.n_states}\")\n",
        "\n",
        "        max_next_action = np.argmax(self.Q[s_n])\n",
        "        td_target = r + self.gamma * self.Q[s_n][max_next_action]\n",
        "        td_error = td_target - self.Q[s][a]\n",
        "        self.Q[s][a] += self.lr * td_error\n",
        "\n",
        "        if update_model:\n",
        "            self.model.add(s, a, r, s_n)\n",
        "\n",
        "    def dream(self, max_steps, **_):\n",
        "        for _ in range(max_steps):\n",
        "            s, a, r, s_n = self.model.sample()\n",
        "\n",
        "            if s >= self.n_states or s_n >= self.n_states:\n",
        "                print(f\"Sampled state index {s} or next state index {s_n} is out of bounds for Q-table with size {self.n_states}\")\n",
        "                continue\n",
        "\n",
        "            self.update(s, a, r, s_n, update_model=False)\n"
      ],
      "metadata": {
        "id": "xLMBpxKZA353"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Здесь творится магия\n",
        "def train(Arrakis, agent, n_episodes, on_model_updates, seed, show_progress_schedule=50):\n",
        "    returns_batch = []  # Инициализация списка для сбора возвратов\n",
        "    rng = np.random.default_rng(seed)\n",
        "    avg_returns = []  # Инициализация списка для средних возвратов\n",
        "\n",
        "    for i in range(1, n_episodes):\n",
        "        state, _ = Arrakis.reset(seed=int(rng.integers(10000000)))\n",
        "        reward, episode_return = 0, 0\n",
        "\n",
        "        while True:\n",
        "            action = agent.act(state)\n",
        "\n",
        "            # Выполним действия в среде\n",
        "            next_state, reward, terminated, truncated, info = Arrakis.step(action)\n",
        "            agent.update(state, action, reward, next_state, update_model=True)\n",
        "            state = next_state\n",
        "            episode_return += reward\n",
        "            done = terminated or truncated\n",
        "            if done:\n",
        "                break\n",
        "            agent.dream(on_model_updates, state=state)\n",
        "\n",
        "        returns_batch.append(episode_return)\n",
        "\n",
        "        if i % show_progress_schedule == 0:\n",
        "            avg_return = np.mean(returns_batch)\n",
        "\n",
        "            # про лргирование прогресса обучения и метрик с помощью wandb не забываем\n",
        "            wandb.log({'Episode Return': episode_return, 'Average Return': avg_return})\n",
        "\n",
        "            print(\n",
        "                f\"Episode: {i}, Return: {episode_return}, \"\n",
        "                f\"AvgReturn[{show_progress_schedule}]: {avg_return:.0f}\"\n",
        "            )\n",
        "\n",
        "            avg_returns.append(avg_return)  # Добавление среднего возврата в список\n",
        "\n",
        "    return avg_returns\n"
      ],
      "metadata": {
        "id": "gStmDt1PJ_AK"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def main():\n",
        "\n",
        "    wandb.init(project=\"Dune-Q\")\n",
        "\n",
        "    Arrakis = gym.make(\"Taxi-v3\")\n",
        "    Arrakis = SandStormArrakis(Arrakis)\n",
        "\n",
        "    # Проверка пространства наблюдений\n",
        "    n_states = Arrakis.observation_space.n\n",
        "    n_actions = Arrakis.action_space.n\n",
        "\n",
        "    print(f\"Observation space: {n_states}, Action space: {n_actions}\")\n",
        "\n",
        "    # Инициализация агента\n",
        "    agent = Muaddib(\n",
        "        n_states,\n",
        "        n_actions,\n",
        "        f_model=Model,\n",
        "        lr=0.05,\n",
        "        gamma=0.975,\n",
        "        eps=0.1,\n",
        "        seed=42,\n",
        "    )\n",
        "\n",
        "    # Обучения агента с текущими параметрами\n",
        "    avg_returns = train(\n",
        "        Arrakis,\n",
        "        agent,\n",
        "        on_model_updates=0,\n",
        "        seed=42,\n",
        "        n_episodes=3001,\n",
        "    )\n"
      ],
      "metadata": {
        "id": "Vxarp9rA4oia"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Define the sweep configuration\n",
        "sweep_config = {\n",
        "    \"method\": \"grid\",\n",
        "    \"parameters\": {\n",
        "        \"n_planning_steps\": {\"values\": [1, 5, 10]},\n",
        "        \"n_dreaming_steps\": {\"values\": [1, 3, 5]}  # Add dreaming steps parameter\n",
        "    }\n",
        "}\n"
      ],
      "metadata": {
        "id": "cR3dDaZO3vxQ"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\"Я не боюсь, я не должен бояться. Ибо страх убивает разум. Страх есть малая смерть, влекущая за собой полное уничтожение. Я встречу свой страх и приму его. Я позволю ему пройти надо мной и сквозь меня. И когда он пройдет через меня, я обращу свой внутренний взор на его путь; и там, где был страх, не останется ничего. Останусь лишь я, я сам.\" Muaddib\n",
        "\n",
        "Ну штош, теперь можно начать обучение с разными гиперпараметрами."
      ],
      "metadata": {
        "id": "xR4Q_ZrtC2yY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Start the sweep\n",
        "MuaddibTravel = wandb.sweep(sweep=sweep_config, project=\"Dune-Q\")\n",
        "\n",
        "# Run the sweep\n",
        "wandb.agent(MuaddibTravel, function=main, count=5)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "43c122760e5d46f689a0875f5075a9fd",
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        },
        "id": "96Tpgbei4Ai9",
        "outputId": "f875c68d-5058-4197-b5c2-137a4c795ff4"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Calling wandb.login() after wandb.init() has no effect.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Create sweep with ID: ai15t1kj\n",
            "Sweep URL: https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: lqp5viqo with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Tracking run with wandb version 0.17.0"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Run data is saved locally in <code>/content/wandb/run-20240520_090050-lqp5viqo</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/lqp5viqo' target=\"_blank\">fancy-sweep-1</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/lqp5viqo' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/lqp5viqo</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -272, AvgReturn[50]: -368\n",
            "Episode: 100, Return: -261, AvgReturn[50]: -336\n",
            "Episode: 150, Return: -192, AvgReturn[50]: -316\n",
            "Episode: 200, Return: -335, AvgReturn[50]: -302\n",
            "Episode: 250, Return: -254, AvgReturn[50]: -290\n",
            "Episode: 300, Return: -299, AvgReturn[50]: -284\n",
            "Episode: 350, Return: -120, AvgReturn[50]: -277\n",
            "Episode: 400, Return: -262, AvgReturn[50]: -271\n",
            "Episode: 450, Return: -108, AvgReturn[50]: -265\n",
            "Episode: 500, Return: -281, AvgReturn[50]: -263\n",
            "Episode: 550, Return: -90, AvgReturn[50]: -261\n",
            "Episode: 600, Return: -272, AvgReturn[50]: -260\n",
            "Episode: 650, Return: -272, AvgReturn[50]: -255\n",
            "Episode: 700, Return: -208, AvgReturn[50]: -251\n",
            "Episode: 750, Return: -74, AvgReturn[50]: -248\n",
            "Episode: 800, Return: -281, AvgReturn[50]: -245\n",
            "Episode: 850, Return: -102, AvgReturn[50]: -243\n",
            "Episode: 900, Return: -206, AvgReturn[50]: -239\n",
            "Episode: 950, Return: -74, AvgReturn[50]: -236\n",
            "Episode: 1000, Return: -299, AvgReturn[50]: -233\n",
            "Episode: 1050, Return: -308, AvgReturn[50]: -229\n",
            "Episode: 1100, Return: -326, AvgReturn[50]: -228\n",
            "Episode: 1150, Return: -131, AvgReturn[50]: -225\n",
            "Episode: 1200, Return: -281, AvgReturn[50]: -222\n",
            "Episode: 1250, Return: -230, AvgReturn[50]: -220\n",
            "Episode: 1300, Return: -181, AvgReturn[50]: -217\n",
            "Episode: 1350, Return: -15, AvgReturn[50]: -215\n",
            "Episode: 1400, Return: -254, AvgReturn[50]: -212\n",
            "Episode: 1450, Return: -169, AvgReturn[50]: -210\n",
            "Episode: 1500, Return: -263, AvgReturn[50]: -207\n",
            "Episode: 1550, Return: -245, AvgReturn[50]: -205\n",
            "Episode: 1600, Return: -28, AvgReturn[50]: -202\n",
            "Episode: 1650, Return: -79, AvgReturn[50]: -199\n",
            "Episode: 1700, Return: -263, AvgReturn[50]: -196\n",
            "Episode: 1750, Return: -234, AvgReturn[50]: -193\n",
            "Episode: 1800, Return: -52, AvgReturn[50]: -191\n",
            "Episode: 1850, Return: -59, AvgReturn[50]: -188\n",
            "Episode: 1900, Return: -3, AvgReturn[50]: -185\n",
            "Episode: 1950, Return: -42, AvgReturn[50]: -183\n",
            "Episode: 2000, Return: -91, AvgReturn[50]: -181\n",
            "Episode: 2050, Return: -2, AvgReturn[50]: -178\n",
            "Episode: 2100, Return: 8, AvgReturn[50]: -176\n",
            "Episode: 2150, Return: -3, AvgReturn[50]: -173\n",
            "Episode: 2200, Return: 13, AvgReturn[50]: -171\n",
            "Episode: 2250, Return: 10, AvgReturn[50]: -168\n",
            "Episode: 2300, Return: -43, AvgReturn[50]: -166\n",
            "Episode: 2350, Return: -19, AvgReturn[50]: -164\n",
            "Episode: 2400, Return: -16, AvgReturn[50]: -162\n",
            "Episode: 2450, Return: -281, AvgReturn[50]: -160\n",
            "Episode: 2500, Return: -24, AvgReturn[50]: -158\n",
            "Episode: 2550, Return: -35, AvgReturn[50]: -155\n",
            "Episode: 2600, Return: -47, AvgReturn[50]: -153\n",
            "Episode: 2650, Return: -21, AvgReturn[50]: -151\n",
            "Episode: 2700, Return: 7, AvgReturn[50]: -149\n",
            "Episode: 2750, Return: -273, AvgReturn[50]: -147\n",
            "Episode: 2800, Return: -48, AvgReturn[50]: -145\n",
            "Episode: 2850, Return: 2, AvgReturn[50]: -143\n",
            "Episode: 2900, Return: 8, AvgReturn[50]: -141\n",
            "Episode: 2950, Return: -28, AvgReturn[50]: -140\n",
            "Episode: 3000, Return: 0, AvgReturn[50]: -138\n"
          ]
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              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>▁▂▃▃▄▄▄▄▄▅▅▅▅▅▅▅▅▆▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇██████</td></tr><tr><td>Episode Return</td><td>▂▂▁▃▅▂▂▆▂▄▂▆▆▂▁▅▃▄▃▄▃▇▂▃▇█▆███▇▇▂▇▇▇▂▇██</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>-138.19733</td></tr><tr><td>Episode Return</td><td>0</td></tr></table><br/></div></div>"
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              " View run <strong style=\"color:#cdcd00\">fancy-sweep-1</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/lqp5viqo' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/lqp5viqo</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
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            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: c54p7p81 with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 5\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/c54p7p81' target=\"_blank\">clear-sweep-2</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
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              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
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          },
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          "data": {
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              "<IPython.core.display.HTML object>"
            ],
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              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
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        {
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              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/c54p7p81' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/c54p7p81</a>"
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          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -281, AvgReturn[50]: -379\n",
            "Episode: 100, Return: -416, AvgReturn[50]: -345\n",
            "Episode: 150, Return: -290, AvgReturn[50]: -325\n",
            "Episode: 200, Return: -308, AvgReturn[50]: -311\n",
            "Episode: 250, Return: -272, AvgReturn[50]: -299\n",
            "Episode: 300, Return: -272, AvgReturn[50]: -290\n",
            "Episode: 350, Return: -290, AvgReturn[50]: -283\n",
            "Episode: 400, Return: -165, AvgReturn[50]: -277\n",
            "Episode: 450, Return: -299, AvgReturn[50]: -273\n",
            "Episode: 500, Return: -141, AvgReturn[50]: -268\n",
            "Episode: 550, Return: -290, AvgReturn[50]: -265\n",
            "Episode: 600, Return: -281, AvgReturn[50]: -262\n",
            "Episode: 650, Return: -127, AvgReturn[50]: -257\n",
            "Episode: 700, Return: -189, AvgReturn[50]: -253\n",
            "Episode: 750, Return: -91, AvgReturn[50]: -248\n",
            "Episode: 800, Return: -43, AvgReturn[50]: -244\n",
            "Episode: 850, Return: -245, AvgReturn[50]: -240\n",
            "Episode: 900, Return: -254, AvgReturn[50]: -237\n",
            "Episode: 950, Return: -290, AvgReturn[50]: -234\n",
            "Episode: 1000, Return: -263, AvgReturn[50]: -231\n",
            "Episode: 1050, Return: -236, AvgReturn[50]: -229\n",
            "Episode: 1100, Return: -272, AvgReturn[50]: -226\n",
            "Episode: 1150, Return: -80, AvgReturn[50]: -223\n",
            "Episode: 1200, Return: -185, AvgReturn[50]: -219\n",
            "Episode: 1250, Return: -95, AvgReturn[50]: -217\n",
            "Episode: 1300, Return: -249, AvgReturn[50]: -214\n",
            "Episode: 1350, Return: -37, AvgReturn[50]: -212\n",
            "Episode: 1400, Return: -62, AvgReturn[50]: -209\n",
            "Episode: 1450, Return: -53, AvgReturn[50]: -206\n",
            "Episode: 1500, Return: -112, AvgReturn[50]: -204\n",
            "Episode: 1550, Return: -66, AvgReturn[50]: -201\n",
            "Episode: 1600, Return: -106, AvgReturn[50]: -198\n",
            "Episode: 1650, Return: -43, AvgReturn[50]: -195\n",
            "Episode: 1700, Return: -71, AvgReturn[50]: -192\n",
            "Episode: 1750, Return: -36, AvgReturn[50]: -190\n",
            "Episode: 1800, Return: -36, AvgReturn[50]: -187\n",
            "Episode: 1850, Return: 2, AvgReturn[50]: -184\n",
            "Episode: 1900, Return: 3, AvgReturn[50]: -181\n",
            "Episode: 1950, Return: -181, AvgReturn[50]: -178\n",
            "Episode: 2000, Return: -74, AvgReturn[50]: -176\n",
            "Episode: 2050, Return: -16, AvgReturn[50]: -173\n",
            "Episode: 2100, Return: -48, AvgReturn[50]: -171\n",
            "Episode: 2150, Return: 8, AvgReturn[50]: -168\n",
            "Episode: 2200, Return: 14, AvgReturn[50]: -165\n",
            "Episode: 2250, Return: 12, AvgReturn[50]: -162\n",
            "Episode: 2300, Return: -119, AvgReturn[50]: -160\n",
            "Episode: 2350, Return: -23, AvgReturn[50]: -157\n",
            "Episode: 2400, Return: -95, AvgReturn[50]: -155\n",
            "Episode: 2450, Return: -56, AvgReturn[50]: -153\n",
            "Episode: 2500, Return: 6, AvgReturn[50]: -151\n",
            "Episode: 2550, Return: -79, AvgReturn[50]: -148\n",
            "Episode: 2600, Return: -49, AvgReturn[50]: -146\n",
            "Episode: 2650, Return: 5, AvgReturn[50]: -144\n",
            "Episode: 2700, Return: -17, AvgReturn[50]: -142\n",
            "Episode: 2750, Return: -48, AvgReturn[50]: -140\n",
            "Episode: 2800, Return: -19, AvgReturn[50]: -138\n",
            "Episode: 2850, Return: 10, AvgReturn[50]: -136\n",
            "Episode: 2900, Return: 10, AvgReturn[50]: -134\n",
            "Episode: 2950, Return: -32, AvgReturn[50]: -133\n",
            "Episode: 3000, Return: -56, AvgReturn[50]: -131\n"
          ]
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              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>▁▂▃▃▄▄▄▄▄▅▅▅▅▅▅▅▆▆▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇██████</td></tr><tr><td>Episode Return</td><td>▃▁▃▃▃▅▅▃▆▅▇▄▃▃▃▆▆▄▇▇▇▆▇▇██▇███▆▇▇█▇█▇▇█▇</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>-130.76467</td></tr><tr><td>Episode Return</td><td>-56</td></tr></table><br/></div></div>"
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              " View run <strong style=\"color:#cdcd00\">clear-sweep-2</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/c54p7p81' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/c54p7p81</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
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              "<IPython.core.display.HTML object>"
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              "Find logs at: <code>./wandb/run-20240520_090125-c54p7p81/logs</code>"
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        },
        {
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          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: qty3chx5 with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 10\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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              "Tracking run with wandb version 0.17.0"
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              "Run data is saved locally in <code>/content/wandb/run-20240520_090155-qty3chx5</code>"
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              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/qty3chx5' target=\"_blank\">golden-sweep-3</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
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              "<IPython.core.display.HTML object>"
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              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
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          "data": {
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              "<IPython.core.display.HTML object>"
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            "text/html": [
              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
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              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/qty3chx5' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/qty3chx5</a>"
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          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -272, AvgReturn[50]: -373\n",
            "Episode: 100, Return: -308, AvgReturn[50]: -338\n",
            "Episode: 150, Return: -317, AvgReturn[50]: -319\n",
            "Episode: 200, Return: -272, AvgReturn[50]: -309\n",
            "Episode: 250, Return: -263, AvgReturn[50]: -298\n",
            "Episode: 300, Return: -299, AvgReturn[50]: -292\n",
            "Episode: 350, Return: -106, AvgReturn[50]: -285\n",
            "Episode: 400, Return: -254, AvgReturn[50]: -274\n",
            "Episode: 450, Return: -150, AvgReturn[50]: -271\n",
            "Episode: 500, Return: -254, AvgReturn[50]: -266\n",
            "Episode: 550, Return: -353, AvgReturn[50]: -261\n",
            "Episode: 600, Return: -135, AvgReturn[50]: -259\n",
            "Episode: 650, Return: -60, AvgReturn[50]: -254\n",
            "Episode: 700, Return: -62, AvgReturn[50]: -250\n",
            "Episode: 750, Return: -19, AvgReturn[50]: -245\n",
            "Episode: 800, Return: -227, AvgReturn[50]: -242\n",
            "Episode: 850, Return: -125, AvgReturn[50]: -239\n",
            "Episode: 900, Return: -317, AvgReturn[50]: -236\n",
            "Episode: 950, Return: -308, AvgReturn[50]: -233\n",
            "Episode: 1000, Return: -254, AvgReturn[50]: -232\n",
            "Episode: 1050, Return: -158, AvgReturn[50]: -230\n",
            "Episode: 1100, Return: -95, AvgReturn[50]: -225\n",
            "Episode: 1150, Return: -236, AvgReturn[50]: -222\n",
            "Episode: 1200, Return: -244, AvgReturn[50]: -218\n",
            "Episode: 1250, Return: -108, AvgReturn[50]: -214\n",
            "Episode: 1300, Return: -254, AvgReturn[50]: -210\n",
            "Episode: 1350, Return: -32, AvgReturn[50]: -206\n",
            "Episode: 1400, Return: -13, AvgReturn[50]: -202\n",
            "Episode: 1450, Return: -192, AvgReturn[50]: -200\n",
            "Episode: 1500, Return: -50, AvgReturn[50]: -196\n",
            "Episode: 1550, Return: -35, AvgReturn[50]: -193\n",
            "Episode: 1600, Return: -73, AvgReturn[50]: -189\n",
            "Episode: 1650, Return: -79, AvgReturn[50]: -186\n",
            "Episode: 1700, Return: -281, AvgReturn[50]: -183\n",
            "Episode: 1750, Return: -14, AvgReturn[50]: -180\n",
            "Episode: 1800, Return: -231, AvgReturn[50]: -178\n",
            "Episode: 1850, Return: -13, AvgReturn[50]: -174\n",
            "Episode: 1900, Return: 7, AvgReturn[50]: -171\n",
            "Episode: 1950, Return: -149, AvgReturn[50]: -169\n",
            "Episode: 2000, Return: -38, AvgReturn[50]: -166\n",
            "Episode: 2050, Return: -17, AvgReturn[50]: -164\n",
            "Episode: 2100, Return: 6, AvgReturn[50]: -161\n",
            "Episode: 2150, Return: -4, AvgReturn[50]: -158\n",
            "Episode: 2200, Return: 14, AvgReturn[50]: -156\n",
            "Episode: 2250, Return: -14, AvgReturn[50]: -153\n",
            "Episode: 2300, Return: -14, AvgReturn[50]: -151\n",
            "Episode: 2350, Return: -127, AvgReturn[50]: -149\n",
            "Episode: 2400, Return: -1, AvgReturn[50]: -147\n",
            "Episode: 2450, Return: -72, AvgReturn[50]: -144\n",
            "Episode: 2500, Return: -39, AvgReturn[50]: -142\n",
            "Episode: 2550, Return: -90, AvgReturn[50]: -140\n",
            "Episode: 2600, Return: -80, AvgReturn[50]: -137\n",
            "Episode: 2650, Return: -6, AvgReturn[50]: -135\n",
            "Episode: 2700, Return: 7, AvgReturn[50]: -133\n",
            "Episode: 2750, Return: -47, AvgReturn[50]: -131\n",
            "Episode: 2800, Return: -77, AvgReturn[50]: -129\n",
            "Episode: 2850, Return: 9, AvgReturn[50]: -127\n",
            "Episode: 2900, Return: 10, AvgReturn[50]: -125\n",
            "Episode: 2950, Return: -32, AvgReturn[50]: -124\n",
            "Episode: 3000, Return: -12, AvgReturn[50]: -122\n"
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              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>▁▂▃▃▃▄▄▄▄▄▅▅▅▅▅▅▅▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇██████</td></tr><tr><td>Episode Return</td><td>▃▂▃▃▆▃▃▁▇▇▃▅▂▃▆▃▆▃▇▄▇▆▂▇▇█▇▇██▇▅▆▇▆█▇▆██</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>-121.96233</td></tr><tr><td>Episode Return</td><td>-12</td></tr></table><br/></div></div>"
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              " View run <strong style=\"color:#cdcd00\">golden-sweep-3</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/qty3chx5' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/qty3chx5</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
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            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: 8uu697sg with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 3\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 1\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
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        {
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              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/8uu697sg' target=\"_blank\">sleek-sweep-4</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
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              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
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              "<IPython.core.display.HTML object>"
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              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
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              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/8uu697sg' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/8uu697sg</a>"
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          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -299, AvgReturn[50]: -377\n",
            "Episode: 100, Return: -335, AvgReturn[50]: -343\n",
            "Episode: 150, Return: -272, AvgReturn[50]: -322\n",
            "Episode: 200, Return: -208, AvgReturn[50]: -309\n",
            "Episode: 250, Return: -299, AvgReturn[50]: -296\n",
            "Episode: 300, Return: -263, AvgReturn[50]: -289\n",
            "Episode: 350, Return: -308, AvgReturn[50]: -280\n",
            "Episode: 400, Return: -299, AvgReturn[50]: -274\n",
            "Episode: 450, Return: -281, AvgReturn[50]: -269\n",
            "Episode: 500, Return: -299, AvgReturn[50]: -266\n",
            "Episode: 550, Return: -130, AvgReturn[50]: -263\n",
            "Episode: 600, Return: -308, AvgReturn[50]: -259\n",
            "Episode: 650, Return: -89, AvgReturn[50]: -255\n",
            "Episode: 700, Return: -362, AvgReturn[50]: -252\n",
            "Episode: 750, Return: -62, AvgReturn[50]: -247\n",
            "Episode: 800, Return: -86, AvgReturn[50]: -243\n",
            "Episode: 850, Return: -263, AvgReturn[50]: -240\n",
            "Episode: 900, Return: -192, AvgReturn[50]: -237\n",
            "Episode: 950, Return: -263, AvgReturn[50]: -234\n",
            "Episode: 1000, Return: -245, AvgReturn[50]: -231\n",
            "Episode: 1050, Return: -272, AvgReturn[50]: -228\n",
            "Episode: 1100, Return: -135, AvgReturn[50]: -225\n",
            "Episode: 1150, Return: -100, AvgReturn[50]: -222\n",
            "Episode: 1200, Return: -164, AvgReturn[50]: -218\n",
            "Episode: 1250, Return: -93, AvgReturn[50]: -215\n",
            "Episode: 1300, Return: -55, AvgReturn[50]: -212\n",
            "Episode: 1350, Return: -11, AvgReturn[50]: -209\n",
            "Episode: 1400, Return: -184, AvgReturn[50]: -208\n",
            "Episode: 1450, Return: -272, AvgReturn[50]: -206\n",
            "Episode: 1500, Return: -110, AvgReturn[50]: -204\n",
            "Episode: 1550, Return: -2, AvgReturn[50]: -202\n",
            "Episode: 1600, Return: -128, AvgReturn[50]: -200\n",
            "Episode: 1650, Return: -272, AvgReturn[50]: -197\n",
            "Episode: 1700, Return: -290, AvgReturn[50]: -195\n",
            "Episode: 1750, Return: -53, AvgReturn[50]: -192\n",
            "Episode: 1800, Return: -33, AvgReturn[50]: -190\n",
            "Episode: 1850, Return: 5, AvgReturn[50]: -187\n",
            "Episode: 1900, Return: 1, AvgReturn[50]: -184\n",
            "Episode: 1950, Return: -239, AvgReturn[50]: -183\n",
            "Episode: 2000, Return: -209, AvgReturn[50]: -180\n",
            "Episode: 2050, Return: -30, AvgReturn[50]: -177\n",
            "Episode: 2100, Return: -29, AvgReturn[50]: -174\n",
            "Episode: 2150, Return: 7, AvgReturn[50]: -171\n",
            "Episode: 2200, Return: -11, AvgReturn[50]: -169\n",
            "Episode: 2250, Return: 12, AvgReturn[50]: -167\n",
            "Episode: 2300, Return: -128, AvgReturn[50]: -165\n",
            "Episode: 2350, Return: -36, AvgReturn[50]: -163\n",
            "Episode: 2400, Return: -128, AvgReturn[50]: -161\n",
            "Episode: 2450, Return: -133, AvgReturn[50]: -159\n",
            "Episode: 2500, Return: -102, AvgReturn[50]: -158\n",
            "Episode: 2550, Return: -204, AvgReturn[50]: -155\n",
            "Episode: 2600, Return: -7, AvgReturn[50]: -153\n",
            "Episode: 2650, Return: 8, AvgReturn[50]: -152\n",
            "Episode: 2700, Return: 5, AvgReturn[50]: -150\n",
            "Episode: 2750, Return: -19, AvgReturn[50]: -148\n",
            "Episode: 2800, Return: -6, AvgReturn[50]: -145\n",
            "Episode: 2850, Return: 1, AvgReturn[50]: -143\n",
            "Episode: 2900, Return: 6, AvgReturn[50]: -142\n",
            "Episode: 2950, Return: -60, AvgReturn[50]: -140\n",
            "Episode: 3000, Return: -79, AvgReturn[50]: -138\n"
          ]
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              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>▁▂▃▃▄▄▄▄▅▅▅▅▅▅▅▆▆▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇██████</td></tr><tr><td>Episode Return</td><td>▂▂▄▂▂▂▂▅▆▁▆▃▃▃▅▆▆▇▄▃█▅▂▇██▄▇██▅▇▅▆██▇██▆</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>-138.01267</td></tr><tr><td>Episode Return</td><td>-79</td></tr></table><br/></div></div>"
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              " View run <strong style=\"color:#cdcd00\">sleek-sweep-4</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/8uu697sg' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/8uu697sg</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
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              "Find logs at: <code>./wandb/run-20240520_090227-8uu697sg/logs</code>"
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          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Agent Starting Run: lbr4hiyt with config:\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_dreaming_steps: 3\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \tn_planning_steps: 5\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Ignored wandb.init() arg project when running a sweep.\n"
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        },
        {
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          "data": {
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              "<IPython.core.display.HTML object>"
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              "Tracking run with wandb version 0.17.0"
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              "Run data is saved locally in <code>/content/wandb/run-20240520_090302-lbr4hiyt</code>"
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              "Syncing run <strong><a href='https://wandb.ai/senich17/Dune-Q/runs/lbr4hiyt' target=\"_blank\">major-sweep-5</a></strong> to <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>Sweep page: <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
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              " View project at <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a>"
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          },
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              "<IPython.core.display.HTML object>"
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            "text/html": [
              " View sweep at <a href='https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/sweeps/ai15t1kj</a>"
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              " View run at <a href='https://wandb.ai/senich17/Dune-Q/runs/lbr4hiyt' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/lbr4hiyt</a>"
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          "text": [
            "Observation space: 500, Action space: 6\n",
            "Episode: 50, Return: -443, AvgReturn[50]: -366\n",
            "Episode: 100, Return: -425, AvgReturn[50]: -338\n",
            "Episode: 150, Return: -299, AvgReturn[50]: -312\n",
            "Episode: 200, Return: -290, AvgReturn[50]: -300\n",
            "Episode: 250, Return: -107, AvgReturn[50]: -288\n",
            "Episode: 300, Return: -308, AvgReturn[50]: -283\n",
            "Episode: 350, Return: -236, AvgReturn[50]: -276\n",
            "Episode: 400, Return: -183, AvgReturn[50]: -270\n",
            "Episode: 450, Return: -61, AvgReturn[50]: -267\n",
            "Episode: 500, Return: -263, AvgReturn[50]: -263\n",
            "Episode: 550, Return: -198, AvgReturn[50]: -260\n",
            "Episode: 600, Return: -254, AvgReturn[50]: -257\n",
            "Episode: 650, Return: -237, AvgReturn[50]: -252\n",
            "Episode: 700, Return: -254, AvgReturn[50]: -249\n",
            "Episode: 750, Return: -272, AvgReturn[50]: -247\n",
            "Episode: 800, Return: -301, AvgReturn[50]: -244\n",
            "Episode: 850, Return: -102, AvgReturn[50]: -241\n",
            "Episode: 900, Return: -239, AvgReturn[50]: -237\n",
            "Episode: 950, Return: -168, AvgReturn[50]: -233\n",
            "Episode: 1000, Return: -254, AvgReturn[50]: -231\n",
            "Episode: 1050, Return: -127, AvgReturn[50]: -228\n",
            "Episode: 1100, Return: -59, AvgReturn[50]: -226\n",
            "Episode: 1150, Return: -19, AvgReturn[50]: -222\n",
            "Episode: 1200, Return: -156, AvgReturn[50]: -220\n",
            "Episode: 1250, Return: -272, AvgReturn[50]: -218\n",
            "Episode: 1300, Return: -98, AvgReturn[50]: -215\n",
            "Episode: 1350, Return: -245, AvgReturn[50]: -213\n",
            "Episode: 1400, Return: -308, AvgReturn[50]: -210\n",
            "Episode: 1450, Return: -31, AvgReturn[50]: -206\n",
            "Episode: 1500, Return: -115, AvgReturn[50]: -204\n",
            "Episode: 1550, Return: -193, AvgReturn[50]: -201\n",
            "Episode: 1600, Return: -69, AvgReturn[50]: -198\n",
            "Episode: 1650, Return: -206, AvgReturn[50]: -194\n",
            "Episode: 1700, Return: -147, AvgReturn[50]: -192\n",
            "Episode: 1750, Return: -16, AvgReturn[50]: -188\n",
            "Episode: 1800, Return: -207, AvgReturn[50]: -186\n",
            "Episode: 1850, Return: -5, AvgReturn[50]: -183\n",
            "Episode: 1900, Return: 9, AvgReturn[50]: -181\n",
            "Episode: 1950, Return: -73, AvgReturn[50]: -178\n",
            "Episode: 2000, Return: -90, AvgReturn[50]: -176\n",
            "Episode: 2050, Return: -28, AvgReturn[50]: -173\n",
            "Episode: 2100, Return: -99, AvgReturn[50]: -171\n",
            "Episode: 2150, Return: -124, AvgReturn[50]: -169\n",
            "Episode: 2200, Return: 8, AvgReturn[50]: -167\n",
            "Episode: 2250, Return: -130, AvgReturn[50]: -165\n",
            "Episode: 2300, Return: -5, AvgReturn[50]: -163\n",
            "Episode: 2350, Return: -85, AvgReturn[50]: -160\n",
            "Episode: 2400, Return: -78, AvgReturn[50]: -158\n",
            "Episode: 2450, Return: -36, AvgReturn[50]: -156\n",
            "Episode: 2500, Return: 6, AvgReturn[50]: -154\n",
            "Episode: 2550, Return: -133, AvgReturn[50]: -152\n",
            "Episode: 2600, Return: -186, AvgReturn[50]: -150\n",
            "Episode: 2650, Return: 7, AvgReturn[50]: -148\n",
            "Episode: 2700, Return: 9, AvgReturn[50]: -146\n",
            "Episode: 2750, Return: -51, AvgReturn[50]: -144\n",
            "Episode: 2800, Return: -31, AvgReturn[50]: -142\n",
            "Episode: 2850, Return: 8, AvgReturn[50]: -140\n",
            "Episode: 2900, Return: 9, AvgReturn[50]: -138\n",
            "Episode: 2950, Return: 2, AvgReturn[50]: -136\n",
            "Episode: 3000, Return: -51, AvgReturn[50]: -134\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(Label(value='0.001 MB of 0.001 MB uploaded\\r'), FloatProgress(value=1.0, max=1.0)))"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "17b781d64a834fb1b62ad3846608a222"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>▁▂▃▃▄▄▄▄▄▅▅▅▅▅▅▅▅▆▆▆▆▆▆▆▇▇▇▇▇▇▇▇▇▇██████</td></tr><tr><td>Episode Return</td><td>▁▁▃▆▄▅▄▅▄▄▃▆▅▄▇█▄▆▃▇▅▇▆███▆▇▆██▇▇█▅█▇▇█▇</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Average Return</td><td>-134.04933</td></tr><tr><td>Episode Return</td><td>-51</td></tr></table><br/></div></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run <strong style=\"color:#cdcd00\">major-sweep-5</strong> at: <a href='https://wandb.ai/senich17/Dune-Q/runs/lbr4hiyt' target=\"_blank\">https://wandb.ai/senich17/Dune-Q/runs/lbr4hiyt</a><br/> View project at: <a href='https://wandb.ai/senich17/Dune-Q' target=\"_blank\">https://wandb.ai/senich17/Dune-Q</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Find logs at: <code>./wandb/run-20240520_090302-lbr4hiyt/logs</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Error in callback <bound method _WandbInit._pause_backend of <wandb.sdk.wandb_init._WandbInit object at 0x7e6dca43db40>> (for post_run_cell):\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "BrokenPipeError",
          "evalue": "[Errno 32] Broken pipe",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mBrokenPipeError\u001b[0m                           Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/wandb_init.py\u001b[0m in \u001b[0;36m_pause_backend\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    430\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minterface\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    431\u001b[0m             \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"pausing backend\"\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 432\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minterface\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpublish_pause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    433\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    434\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_resume_backend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m#  noqa\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/interface/interface.py\u001b[0m in \u001b[0;36mpublish_pause\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    696\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mpublish_pause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    697\u001b[0m         \u001b[0mpause\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPauseRequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 698\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_publish_pause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpause\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    699\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    700\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mabstractmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/interface/interface_shared.py\u001b[0m in \u001b[0;36m_publish_pause\u001b[0;34m(self, pause)\u001b[0m\n\u001b[1;32m    357\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_publish_pause\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpause\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mpb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPauseRequest\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    358\u001b[0m         \u001b[0mrec\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpause\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpause\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 359\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_publish\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrec\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    360\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    361\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_publish_resume\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresume\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mpb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mResumeRequest\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/interface/interface_sock.py\u001b[0m in \u001b[0;36m_publish\u001b[0;34m(self, record, local)\u001b[0m\n\u001b[1;32m     49\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_publish\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecord\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"pb.Record\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mbool\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_assign\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecord\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock_client\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend_record_publish\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecord\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     52\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m     def _communicate_async(\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/sock_client.py\u001b[0m in \u001b[0;36msend_record_publish\u001b[0;34m(self, record)\u001b[0m\n\u001b[1;32m    219\u001b[0m         \u001b[0mserver_req\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mspb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mServerRequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    220\u001b[0m         \u001b[0mserver_req\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecord_publish\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCopyFrom\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecord\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 221\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend_server_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mserver_req\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    222\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    223\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_extract_packet_bytes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mbytes\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/sock_client.py\u001b[0m in \u001b[0;36msend_server_request\u001b[0;34m(self, msg)\u001b[0m\n\u001b[1;32m    153\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    154\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msend_server_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 155\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_send_message\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    156\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    157\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msend_server_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/sock_client.py\u001b[0m in \u001b[0;36m_send_message\u001b[0;34m(self, msg)\u001b[0m\n\u001b[1;32m    150\u001b[0m         \u001b[0mheader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstruct\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"<BI\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mord\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"W\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mraw_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    151\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 152\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sendall_with_error_handle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheader\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    153\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    154\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msend_server_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/wandb/sdk/lib/sock_client.py\u001b[0m in \u001b[0;36m_sendall_with_error_handle\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    128\u001b[0m             \u001b[0mstart_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmonotonic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    129\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 130\u001b[0;31m                 \u001b[0msent\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    131\u001b[0m                 \u001b[0;31m# sent equal to 0 indicates a closed socket\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    132\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0msent\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mBrokenPipeError\u001b[0m: [Errno 32] Broken pipe"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Прилагаю ссылку на WandB, чтобы посмотреть на параметры и результаты https://api.wandb.ai/links/senich17/ky83q8g3"
      ],
      "metadata": {
        "id": "E9BWjMuKCQ6R"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Выводы по гиперпараметрам\n",
        "\n",
        "### 1. Прибытие Пола на Арракис с n_dreaming_steps: 1, n_planning_steps: 1\n",
        "\n",
        "Средний возврат составил -138.19733, а возврат за эпизод был 0. В начале своего пути модель, как молодой Пол Атрейдес, только что прибывший на Арракис. Неопытная и неосведомленная о суровых реалиях загадочной планеты, она сталкивается с многочисленными трудностями, такими как песчаные бури, засуха, и нападения на спайс-майнеры. Она ещё не обрела достаточного опыта и планирования, чтобы успешно противостоять вызовам планеты.\n",
        "\n",
        "### 2. Прозрение в пустыне с n_dreaming_steps: 1, n_planning_steps: 5\n",
        "\n",
        "Повышение n_planning_steps до 5 позволило модели лучше планировать свои действия, что улучшило средний возврат до -130.76467 (по сравнению с -138.19733 в предыдущем запуске), но возврат за эпизод стал тревожно низким (-56). На Арракисе, где вода ценится дороже золота, а спайс правит судьбами, Пол учился балансировать между видениями и реальностью, между мечтами о свободе и жестокой борьбой за выживание. Планета учила его, что истинная сила заключается не только в умениях и знаниях, но и в умении видеть то, что скрыто от глаз.\n",
        "\n",
        "\n",
        "### 3. Фримены и их предводитель с n_dreaming_steps: 1, n_planning_steps: 10\n",
        "\n",
        "По мере того, как средний возврат и возврат за эпизод растут -121.96233 и -12 соответственно (в сравнении в предыдущим запуском), в результате увеличения n_planning_steps, модель становится подобной Стилгару, опытному лидеру фрименов. Ее стратегия позволяет ей справляться с трудностями, находить оптимальные решения и в результате чего она демонстрирует значительные успехи... Но, увы, переменчивая природа планеты иногда все еще чинит препятствия.\n",
        "\n",
        "### 4. Видения Алии в пустыне с n_dreaming_steps: 3, n_planning_steps: 1\n",
        "\n",
        "Увеличение n_dreaming_steps до 3 позволило модели лучше улавливать возможности и вероятности, подобно видениям Алии Атрейдес, но с n_planning_steps, равным 1, модель не всегда могла воплотить пророчества в реальность. Это отражалось на результатах: средний возврат составил -138.01267, а возврат за эпизод -79. Алия, обладая силой и мудростью не по возрасту, часто оказывалась обузой для самой себя, так как её видения не всегда могли компенсировать недостаток опыта и стратегического планирования, что показало модели, что одни только видения не гарант успеха.\n",
        "\n",
        "### 5. Гости с Салусы Секундус с n_dreaming_steps: 3, n_planning_steps: 5\n",
        "\n",
        "В данном запуске модель произвела впечатление, аналогичное эффекту, который производили Сардаукары в мире. Средний возврат (-134.04933) демонстрировал ее внушительный потенциал. Но вот возврат за эпизод (-51) не вызывал у Пола и Фрименов такого же ужаса, как у всех остальных подданых императора. В итоге, несмотря на впечатляющий потенциал модели в данном запуске, она оказалась на стороне проигравших.\n",
        "\n",
        "## Общий вывод\n",
        "\n",
        "Проведенный анализ различных комбинаций гиперпараметров n_dreaming_steps и n_planning_steps позволяет сделать следующие выводы:\n",
        "\n",
        "Мы установили, что увеличение значения n_planning_steps способствует улучшению среднего возврата модели. Это свидетельствует о том, что эффективное стратегическое планирование играет ключевую роль в успешной адаптации модели к условиям планеты.\n",
        "\n",
        "Однако при использовании слишком высоких значений n_planning_steps наблюдается снижение возврата за эпизод, что указывает на необходимость баланса между планированием и эффективной реализацией стратегии. Иначе никакие Фриманы не помогут.\n",
        "\n",
        "Увеличение значения n_dreaming_steps также может способствовать улучшению среднего возврата модели, позволяя ей лучше распознавать возможности и вероятности. Однако необходимо учитывать, что слишком высокие значения этого параметра могут привести к потере фокуса и недостаточной концентрации на планировании стратегии (собственно, что происходило в предыдущих работах, при высоких показателях эпсилона).\n",
        "\n",
        "Таким образом, оптимальный выбор гиперпараметров зависит от конкретных условий задачи и требует баланса между способностью модели к стратегическому планированию и ее способностью адаптироваться к изменяющимся условиям. Будь как Пол, адаптируйся и выживай!\n",
        "\n",
        "P.S.: Так же очень заметно, что модели нужно больше времени для обучения в стохастической среде(ну в нашем случае это не прям стохастичность, это так, ерунда), поэтому и результаты разительно отличаются от результатов, которые были показаны в оригинальной среде."
      ],
      "metadata": {
        "id": "Z3C0yvg6ngt2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jNYCxz4VoDpd",
        "outputId": "049e9a4b-e61f-4db3-f477-28aacc44c757"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import Image\n"
      ],
      "metadata": {
        "id": "0yrBl4TtrMFQ"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fname = '/content/drive/MyDrive/Игры.gif'\n",
        "Image(open(fname, 'rb').read())  # local\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "id": "clcUlM0prHHk",
        "outputId": "bd53fc68-7c35-4506-c92b-71209ab55411"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "P.S.: В процессе работы над этой домашкой ни один Шаи'хулуд не пострадал.\n",
        "По какому-то закону Мерфи всю дорогу у меня ломался пайп, решить эту проблему так и не удалось, но в целом это не повлияло на логирование показателей и работу моделей."
      ],
      "metadata": {
        "id": "rD5g3GFY1zbh"
      }
    }
  ]
}