training_SOM.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import r2_score\n",
    "import pickle\n",
    "import gentrl\n",
    "import numpy as np\n",
    "\n",
    "import susi\n",
    "from susi.SOMPlots import plot_estimation_map, plot_som_histogram, plot_umatrix\n",
    "import gentrl\n",
    "import torch\n",
    "torch.cuda.set_device(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.cuda();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mored\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\torch\\nn\\modules\\container.py:434: UserWarning: Setting attributes on ParameterList is not supported.\n",
      "  warnings.warn(\"Setting attributes on ParameterList is not supported.\")\n"
     ]
    }
   ],
   "source": [
    "enc = gentrl.RNNEncoder(latent_size=50)\n",
    "dec = gentrl.DilConvDecoder(latent_input_size=50)\n",
    "model = gentrl.GENTRL(enc, dec, 50 * [('c', 20)], [('c', 20)], beta=0.001)\n",
    "model.cuda();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load from past\n",
    "model.load('ligase_gentrl/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "som_general = pickle.load(open(\"general_leish_som_500K.p\", \"rb\"))\n",
    "som_specific = pickle.load(open(\"specific_leish_som_800K_2.p\", \"rb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from moses.metrics import mol_passes_filters, SA, logP\n",
    "from moses.metrics.utils import get_n_rings, get_mol\n",
    "\n",
    "from moses.utils import disable_rdkit_log\n",
    "disable_rdkit_log()\n",
    "\n",
    "def get_num_rings_6(mol):\n",
    "    r = mol.GetRingInfo()\n",
    "    return len([x for x in r.AtomRings() if len(x) > 6])\n",
    "\n",
    "\n",
    "def penalized_logP(mol_or_smiles, masked=False, default=-5):\n",
    "    mol = get_mol(mol_or_smiles)\n",
    "    if mol is None:\n",
    "        return default\n",
    "    smiles_tokenized = gentrl.tokenizer.encode([mol_or_smiles])[0][0].tolist()\n",
    "    general_award = 0.015*som_general.predict([smiles_tokenized])[0]\n",
    "    specific_award = 1.4*som_specific.predict([smiles_tokenized])[0]\n",
    "    reward = logP(mol) - 1.2*SA(mol) - get_num_rings_6(mol) + specific_award + general_award\n",
    "    if masked and not mol_passes_filters(mol):\n",
    "        return default\n",
    "    return reward"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.143;valid_perc: 0.1784;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.105;valid_perc: 0.1832;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.092;valid_perc: 0.1845;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.061;valid_perc: 0.1901;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.033;valid_perc: 0.1953;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.998;valid_perc: 0.2024;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.999;valid_perc: 0.2024;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.971;valid_perc: 0.2074;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.904;valid_perc: 0.2178;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.902;valid_perc: 0.2191;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.888;valid_perc: 0.2178;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.882;valid_perc: 0.222;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.839;valid_perc: 0.229;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.713;valid_perc: 0.2503;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.75;valid_perc: 0.2428;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.749;valid_perc: 0.2422;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.697;valid_perc: 0.2544;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.715;valid_perc: 0.2472;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.634;valid_perc: 0.2632;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.626;valid_perc: 0.2617;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.596;valid_perc: 0.2672;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.551;valid_perc: 0.2735;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.556;valid_perc: 0.2736;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.485;valid_perc: 0.2834;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.462;valid_perc: 0.2884;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.44;valid_perc: 0.2914;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.346;valid_perc: 0.303;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.126;valid_perc: 0.3335;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.21;valid_perc: 0.3204;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.119;valid_perc: 0.3376;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.098;valid_perc: 0.3387;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.993;valid_perc: 0.3541;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.033;valid_perc: 0.3445;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.965;valid_perc: 0.358;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.925;valid_perc: 0.3598;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.87;valid_perc: 0.3728;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.726;valid_perc: 0.3918;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.524;valid_perc: 0.4191;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.469;valid_perc: 0.4271;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.448;valid_perc: 0.4267;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.399;valid_perc: 0.4338;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.505;valid_perc: 0.4172;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.141;valid_perc: 0.4676;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.165;valid_perc: 0.466;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.099;valid_perc: 0.4722;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.133;valid_perc: 0.4696;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.124;valid_perc: 0.4717;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.033;valid_perc: 0.4821;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.097;valid_perc: 0.4724;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.027;valid_perc: 0.4834;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.95;valid_perc: 0.4941;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.981;valid_perc: 0.4895;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.962;valid_perc: 0.4922;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.868;valid_perc: 0.5075;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.895;valid_perc: 0.5023;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.889;valid_perc: 0.5033;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.853;valid_perc: 0.5055;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.78;valid_perc: 0.5164;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.776;valid_perc: 0.5173;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.677;valid_perc: 0.5312;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.643;valid_perc: 0.5348;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.677;valid_perc: 0.5301;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.585;valid_perc: 0.54;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.32;valid_perc: 0.5758;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.265;valid_perc: 0.585;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9844;valid_perc: 0.623;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9499;valid_perc: 0.6264;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9003;valid_perc: 0.6352;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.8803;valid_perc: 0.637;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.866;valid_perc: 0.6389;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.4852;valid_perc: 0.6883;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.449;valid_perc: 0.6936;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3108;valid_perc: 0.7858;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3446;valid_perc: 0.7866;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3604;valid_perc: 0.7863;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4013;valid_perc: 0.7913;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4727;valid_perc: 0.8008;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5751;valid_perc: 0.8115;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5984;valid_perc: 0.81;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.798;valid_perc: 0.8328;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.8611;valid_perc: 0.835;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.9015;valid_perc: 0.8392;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.079;valid_perc: 0.8527;\n",
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      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.112;valid_perc: 0.8559;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  1.2;valid_perc: 0.8671;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.176;valid_perc: 0.8636;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.285;valid_perc: 0.8735;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.227;valid_perc: 0.8653;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.286;valid_perc: 0.8699;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.307;valid_perc: 0.8715;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.344;valid_perc: 0.8759;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.382;valid_perc: 0.8781;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.393;valid_perc: 0.8753;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.423;valid_perc: 0.8812;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.455;valid_perc: 0.8825;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.485;valid_perc: 0.8833;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.52;valid_perc: 0.8861;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.586;valid_perc: 0.8926;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.607;valid_perc: 0.8955;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.614;valid_perc: 0.8933;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.659;valid_perc: 0.8964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.652;valid_perc: 0.8941;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.728;valid_perc: 0.9022;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.726;valid_perc: 0.8973;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.813;valid_perc: 0.9093;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.759;valid_perc: 0.9002;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.827;valid_perc: 0.9067;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.876;valid_perc: 0.9084;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.849;valid_perc: 0.9038;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.872;valid_perc: 0.9053;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.874;valid_perc: 0.9041;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.943;valid_perc: 0.9097;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.952;valid_perc: 0.9086;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.004;valid_perc: 0.9139;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.028;valid_perc: 0.914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.048;valid_perc: 0.9151;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.079;valid_perc: 0.9173;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.135;valid_perc: 0.9212;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.146;valid_perc: 0.9212;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.22;valid_perc: 0.9273;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.183;valid_perc: 0.9222;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.251;valid_perc: 0.9279;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.256;valid_perc: 0.9252;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.301;valid_perc: 0.9283;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.315;valid_perc: 0.9278;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.379;valid_perc: 0.934;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.371;valid_perc: 0.9314;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.408;valid_perc: 0.9332;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.418;valid_perc: 0.9323;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.436;valid_perc: 0.9338;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.423;valid_perc: 0.9317;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.462;valid_perc: 0.9363;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.49;valid_perc: 0.9347;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.55;valid_perc: 0.9408;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.516;valid_perc: 0.9355;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.562;valid_perc: 0.938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.576;valid_perc: 0.938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.602;valid_perc: 0.9398;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.635;valid_perc: 0.9423;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.634;valid_perc: 0.9415;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.669;valid_perc: 0.9446;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.708;valid_perc: 0.9464;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.71;valid_perc: 0.9451;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.734;valid_perc: 0.9488;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.706;valid_perc: 0.9432;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.764;valid_perc: 0.9483;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.744;valid_perc: 0.9454;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.773;valid_perc: 0.9484;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.809;valid_perc: 0.9501;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.812;valid_perc: 0.9493;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.855;valid_perc: 0.9527;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.875;valid_perc: 0.954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.866;valid_perc: 0.9514;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.854;valid_perc: 0.9493;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.92;valid_perc: 0.9565;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.917;valid_perc: 0.9539;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.968;valid_perc: 0.9586;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.947;valid_perc: 0.9556;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.967;valid_perc: 0.9558;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.995;valid_perc: 0.9585;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.993;valid_perc: 0.9579;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.011;valid_perc: 0.9587;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.042;valid_perc: 0.9613;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.047;valid_perc: 0.9606;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.065;valid_perc: 0.9598;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.075;valid_perc: 0.9609;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  3.1;valid_perc: 0.9615;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.118;valid_perc: 0.9626;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.098;valid_perc: 0.9592;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.148;valid_perc: 0.9643;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.119;valid_perc: 0.9593;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.165;valid_perc: 0.963;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.184;valid_perc: 0.964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.19;valid_perc: 0.9626;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.197;valid_perc: 0.9631;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.234;valid_perc: 0.9663;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.241;valid_perc: 0.9625;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.287;valid_perc: 0.966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.304;valid_perc: 0.9656;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.303;valid_perc: 0.9642;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.341;valid_perc: 0.9651;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.359;valid_perc: 0.9656;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.404;valid_perc: 0.9685;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.431;valid_perc: 0.9674;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.484;valid_perc: 0.9706;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.484;valid_perc: 0.9664;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.492;valid_perc: 0.9654;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.595;valid_perc: 0.9685;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.625;valid_perc: 0.9693;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.609;valid_perc: 0.9649;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.691;valid_perc: 0.967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.75;valid_perc: 0.9713;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.787;valid_perc: 0.9706;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.822;valid_perc: 0.9711;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.842;valid_perc: 0.9691;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.913;valid_perc: 0.9714;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.948;valid_perc: 0.9722;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.999;valid_perc: 0.9747;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.994;valid_perc: 0.9711;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.07;valid_perc: 0.9744;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.092;valid_perc: 0.9752;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.111;valid_perc: 0.9749;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.136;valid_perc: 0.9746;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.146;valid_perc: 0.9743;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.173;valid_perc: 0.9763;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.186;valid_perc: 0.9747;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.249;valid_perc: 0.9783;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.24;valid_perc: 0.9773;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.272;valid_perc: 0.9784;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.25;valid_perc: 0.9751;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.306;valid_perc: 0.98;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.308;valid_perc: 0.9793;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.333;valid_perc: 0.9802;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.367;valid_perc: 0.9823;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.383;valid_perc: 0.9824;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.379;valid_perc: 0.9829;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.387;valid_perc: 0.9815;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.422;valid_perc: 0.9837;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.41;valid_perc: 0.9822;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.401;valid_perc: 0.9812;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.431;valid_perc: 0.9825;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.439;valid_perc: 0.9826;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.449;valid_perc: 0.9836;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.463;valid_perc: 0.9853;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.469;valid_perc: 0.9839;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.488;valid_perc: 0.9849;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.481;valid_perc: 0.9837;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.486;valid_perc: 0.9844;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.54;valid_perc: 0.9886;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.534;valid_perc: 0.9872;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.529;valid_perc: 0.9868;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.534;valid_perc: 0.9872;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.538;valid_perc: 0.9873;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.547;valid_perc: 0.9868;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.554;valid_perc: 0.9876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.554;valid_perc: 0.9857;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.606;valid_perc: 0.9912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.588;valid_perc: 0.9881;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.601;valid_perc: 0.9893;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.608;valid_perc: 0.99;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.582;valid_perc: 0.9871;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.632;valid_perc: 0.9909;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.632;valid_perc: 0.9903;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.632;valid_perc: 0.9905;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.624;valid_perc: 0.9888;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.639;valid_perc: 0.9899;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.644;valid_perc: 0.9892;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.646;valid_perc: 0.9901;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.674;valid_perc: 0.9921;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.677;valid_perc: 0.991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.675;valid_perc: 0.9913;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.667;valid_perc: 0.9899;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.675;valid_perc: 0.9905;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.672;valid_perc: 0.9902;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.697;valid_perc: 0.9917;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.696;valid_perc: 0.992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.709;valid_perc: 0.9926;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.724;valid_perc: 0.9937;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.726;valid_perc: 0.9937;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.711;valid_perc: 0.9913;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.719;valid_perc: 0.9924;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.724;valid_perc: 0.9922;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.73;valid_perc: 0.9932;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.735;valid_perc: 0.9932;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.731;valid_perc: 0.9922;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.754;valid_perc: 0.9941;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.774;valid_perc: 0.9955;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.748;valid_perc: 0.9932;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.753;valid_perc: 0.9929;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.762;valid_perc: 0.9942;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.767;valid_perc: 0.9936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.775;valid_perc: 0.994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.784;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.773;valid_perc: 0.9941;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.781;valid_perc: 0.9945;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.794;valid_perc: 0.9949;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.789;valid_perc: 0.9947;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.792;valid_perc: 0.9948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.791;valid_perc: 0.9942;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.786;valid_perc: 0.9936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.793;valid_perc: 0.994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.807;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.81;valid_perc: 0.9951;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.818;valid_perc: 0.9953;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.816;valid_perc: 0.9948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.816;valid_perc: 0.9948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.819;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.811;valid_perc: 0.9949;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.81;valid_perc: 0.994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.82;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.823;valid_perc: 0.9951;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.842;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.841;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.834;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.833;valid_perc: 0.9951;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.842;valid_perc: 0.9955;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.843;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.839;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.839;valid_perc: 0.9953;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.855;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.861;valid_perc: 0.9969;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.856;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.854;valid_perc: 0.9963;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.865;valid_perc: 0.9963;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.865;valid_perc: 0.9963;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.846;valid_perc: 0.9945;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.875;valid_perc: 0.9969;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.871;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.862;valid_perc: 0.9959;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.865;valid_perc: 0.9957;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.868;valid_perc: 0.9956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.872;valid_perc: 0.9959;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.88;valid_perc: 0.9963;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.88;valid_perc: 0.9963;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.889;valid_perc: 0.9971;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.897;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.902;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.893;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.902;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.918;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.916;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.918;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.93;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.931;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.952;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.964;valid_perc: 0.9967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.986;valid_perc: 0.9969;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.007;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.027;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.081;valid_perc: 0.9969;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.122;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.171;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.201;valid_perc: 0.9937;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.253;valid_perc: 0.9953;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.29;valid_perc: 0.9956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.306;valid_perc: 0.9945;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.351;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.371;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.366;valid_perc: 0.9943;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.401;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.42;valid_perc: 0.9967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.441;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.447;valid_perc: 0.9965;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.449;valid_perc: 0.9961;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.471;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.478;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.483;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.489;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.499;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.502;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.512;valid_perc: 0.9975;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.51;valid_perc: 0.9967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.514;valid_perc: 0.9969;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.527;valid_perc: 0.9973;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.531;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.545;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.536;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.549;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.552;valid_perc: 0.9979;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.545;valid_perc: 0.9967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.546;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.552;valid_perc: 0.9975;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.561;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.573;valid_perc: 0.9981;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.562;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.575;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.576;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.576;valid_perc: 0.9975;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.587;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.581;valid_perc: 0.9979;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.594;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.595;valid_perc: 0.9985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.594;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.601;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.596;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  5.6;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.604;valid_perc: 0.9979;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.601;valid_perc: 0.9979;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.61;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.613;valid_perc: 0.9985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.614;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.614;valid_perc: 0.9981;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.616;valid_perc: 0.9981;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.616;valid_perc: 0.9981;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.617;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.625;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.619;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.626;valid_perc: 0.9981;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.639;valid_perc: 0.9991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.628;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.638;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.64;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.633;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.646;valid_perc: 0.9991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.639;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.641;valid_perc: 0.9985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.645;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.65;valid_perc: 0.9985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.645;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.647;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.651;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.65;valid_perc: 0.9985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.661;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.658;valid_perc: 0.9989;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.664;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.667;valid_perc: 0.9995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.661;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.661;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.673;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.668;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.668;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.674;valid_perc: 0.9989;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.675;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.67;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.672;valid_perc: 0.9983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.682;valid_perc: 0.9989;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.679;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.675;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.691;valid_perc: 0.9989;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.695;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.689;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.692;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.697;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.703;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.709;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.719;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.719;valid_perc: 0.9985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.727;valid_perc: 0.9987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.738;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.749;valid_perc: 0.9985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.761;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.781;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.798;valid_perc: 0.9981;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.816;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.846;valid_perc: 0.9979;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.876;valid_perc: 0.9981;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.89;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.929;valid_perc: 0.9979;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.945;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.967;valid_perc: 0.9969;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.988;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.989;valid_perc: 0.9956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.019;valid_perc: 0.9967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.03;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.049;valid_perc: 0.9957;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.054;valid_perc: 0.995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.068;valid_perc: 0.9953;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.115;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.117;valid_perc: 0.9936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.148;valid_perc: 0.9929;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.186;valid_perc: 0.9927;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.224;valid_perc: 0.9932;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.259;valid_perc: 0.9922;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.29;valid_perc: 0.9925;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.351;valid_perc: 0.9933;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.413;valid_perc: 0.9915;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.479;valid_perc: 0.9902;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.55;valid_perc: 0.9889;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.603;valid_perc: 0.986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.763;valid_perc: 0.9869;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.828;valid_perc: 0.9838;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.924;valid_perc: 0.981;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.004;valid_perc: 0.9763;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.096;valid_perc: 0.9778;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.164;valid_perc: 0.9776;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.219;valid_perc: 0.9764;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.311;valid_perc: 0.9796;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.334;valid_perc: 0.9748;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.38;valid_perc: 0.9727;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.434;valid_perc: 0.9729;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.456;valid_perc: 0.9691;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.478;valid_perc: 0.9686;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.533;valid_perc: 0.972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.567;valid_perc: 0.9692;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.582;valid_perc: 0.9653;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.565;valid_perc: 0.9585;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.654;valid_perc: 0.9588;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.65;valid_perc: 0.9551;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.666;valid_perc: 0.9542;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.703;valid_perc: 0.9528;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.641;valid_perc: 0.9473;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.693;valid_perc: 0.9497;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.751;valid_perc: 0.9494;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.665;valid_perc: 0.9426;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.651;valid_perc: 0.9406;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.69;valid_perc: 0.9428;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.683;valid_perc: 0.943;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.665;valid_perc: 0.9411;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.678;valid_perc: 0.9429;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.644;valid_perc: 0.9413;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.67;valid_perc: 0.9451;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.671;valid_perc: 0.9442;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.646;valid_perc: 0.9419;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.629;valid_perc: 0.9396;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.534;valid_perc: 0.9309;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.383;valid_perc: 0.9166;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.222;valid_perc: 0.9024;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.023;valid_perc: 0.8862;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.674;valid_perc: 0.8591;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.556;valid_perc: 0.8492;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.23;valid_perc: 0.8254;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.009;valid_perc: 0.8061;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.514;valid_perc: 0.7674;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.96;valid_perc: 0.7209;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.81;valid_perc: 0.7034;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.633;valid_perc: 0.6843;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.762;valid_perc: 0.6831;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.81;valid_perc: 0.6824;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.929;valid_perc: 0.6825;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.944;valid_perc: 0.6804;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.396;valid_perc: 0.6416;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.204;valid_perc: 0.6251;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  3.4;valid_perc: 0.5778;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.69;valid_perc: 0.5311;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.318;valid_perc: 0.5156;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.89;valid_perc: 0.4885;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.381;valid_perc: 0.4545;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.104;valid_perc: 0.4304;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.64;valid_perc: 0.4049;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.272;valid_perc: 0.3853;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.03948;valid_perc: 0.3649;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.198;valid_perc: 0.3553;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.5702;valid_perc: 0.3282;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7216;valid_perc: 0.3152;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.419;valid_perc: 0.2642;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.784;valid_perc: 0.2357;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.139;valid_perc: 0.2033;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.537;valid_perc: 0.1671;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.815;valid_perc: 0.1399;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.183;valid_perc: 0.1103;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.31;valid_perc: 0.0967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.169;valid_perc: 0.0996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.392;valid_perc: 0.1268;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.1307;valid_perc: 0.2285;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.103;valid_perc: 0.4296;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.74;valid_perc: 0.5385;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 9.278;valid_perc: 0.6015;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 10.65;valid_perc: 0.6588;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 11.53;valid_perc: 0.695;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.28;valid_perc: 0.7262;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.58;valid_perc: 0.738;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.09;valid_perc: 0.7589;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.64;valid_perc: 0.7822;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.09;valid_perc: 0.8011;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.33;valid_perc: 0.8116;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.49;valid_perc: 0.8176;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.55;valid_perc: 0.8204;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.71;valid_perc: 0.8268;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.04;valid_perc: 0.8402;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.01;valid_perc: 0.8392;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.27;valid_perc: 0.8497;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.54;valid_perc: 0.8616;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.59;valid_perc: 0.8635;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.9;valid_perc: 0.876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.9;valid_perc: 0.8761;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.05;valid_perc: 0.8826;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.12;valid_perc: 0.8853;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.97;valid_perc: 0.879;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.19;valid_perc: 0.8885;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.26;valid_perc: 0.8908;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.4;valid_perc: 0.8963;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.35;valid_perc: 0.8949;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.23;valid_perc: 0.8894;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.48;valid_perc: 0.8999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.67;valid_perc: 0.9077;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.69;valid_perc: 0.9082;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.81;valid_perc: 0.9133;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 17.01;valid_perc: 0.9213;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 17.09;valid_perc: 0.9248;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.9;valid_perc: 0.9173;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.85;valid_perc: 0.9149;\n",
      "!!"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-49-82512d4ed78b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mmodel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtrain_as_rl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpenalized_logP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\gentrl-0.1-py3.8.egg\\gentrl\\gentrl.py\u001b[0m in \u001b[0;36mtrain_as_rl\u001b[1;34m(self, reward_fn, num_iterations, verbose_step, batch_size, cond_lb, cond_rb, lr_lp, lr_dec)\u001b[0m\n\u001b[0;32m    222\u001b[0m             \u001b[0mzc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdevice\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    223\u001b[0m             \u001b[0mconc_zy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mzc\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdim\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 224\u001b[1;33m             \u001b[0mlog_probs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlog_prob\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mconc_zy\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmarg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m50\u001b[0m \u001b[1;33m*\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    225\u001b[0m             \u001b[0mlog_probs\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdec\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mweighted_forward\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msmiles\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mz\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    226\u001b[0m             \u001b[0mr_list\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mreward_fn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0msmiles\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\gentrl-0.1-py3.8.egg\\gentrl\\lp.py\u001b[0m in \u001b[0;36mlog_prob\u001b[1;34m(self, x, marg)\u001b[0m\n\u001b[0;32m    184\u001b[0m             \u001b[0mnorm_core\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcore\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msum\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdim\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    185\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 186\u001b[1;33m             \u001b[0mpref\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbmm\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpref\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcond_core\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    187\u001b[0m             \u001b[0mnorm_pref\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnorm_pref\u001b[0m \u001b[1;33m@\u001b[0m \u001b[0mnorm_core\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    188\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "model.train_as_rl(penalized_logP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.84;valid_perc: 0.9141;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.99;valid_perc: 0.9206;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.92;valid_perc: 0.9179;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.8;valid_perc: 0.9135;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.91;valid_perc: 0.917;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.81;valid_perc: 0.9128;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.65;valid_perc: 0.9067;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.77;valid_perc: 0.9108;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.69;valid_perc: 0.9087;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.87;valid_perc: 0.9155;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.79;valid_perc: 0.912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 17.07;valid_perc: 0.9232;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 17.14;valid_perc: 0.9259;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 17.09;valid_perc: 0.9243;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 17.0;valid_perc: 0.9212;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 17.01;valid_perc: 0.9209;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.92;valid_perc: 0.9168;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 17.09;valid_perc: 0.924;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.97;valid_perc: 0.9194;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.9;valid_perc: 0.9164;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.81;valid_perc: 0.9117;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.62;valid_perc: 0.9044;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.79;valid_perc: 0.9113;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.75;valid_perc: 0.9096;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.69;valid_perc: 0.9069;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.91;valid_perc: 0.9157;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.65;valid_perc: 0.9056;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.71;valid_perc: 0.9073;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.51;valid_perc: 0.8995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.64;valid_perc: 0.9043;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.77;valid_perc: 0.91;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.64;valid_perc: 0.9044;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.41;valid_perc: 0.8949;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.24;valid_perc: 0.888;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.14;valid_perc: 0.8836;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.34;valid_perc: 0.8912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.21;valid_perc: 0.8862;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.12;valid_perc: 0.8828;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.05;valid_perc: 0.8792;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.97;valid_perc: 0.8762;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 16.01;valid_perc: 0.8771;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.93;valid_perc: 0.8737;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.55;valid_perc: 0.8586;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.41;valid_perc: 0.8527;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.55;valid_perc: 0.8585;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.31;valid_perc: 0.8483;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.0;valid_perc: 0.8349;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.19;valid_perc: 0.8426;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.08;valid_perc: 0.8383;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.09;valid_perc: 0.8387;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 15.0;valid_perc: 0.8347;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.81;valid_perc: 0.8271;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.68;valid_perc: 0.8212;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.77;valid_perc: 0.8251;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.6;valid_perc: 0.8177;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.65;valid_perc: 0.8193;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.43;valid_perc: 0.8102;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.18;valid_perc:  0.8;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.42;valid_perc: 0.8102;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.59;valid_perc: 0.817;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.4;valid_perc: 0.809;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.23;valid_perc: 0.8018;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.44;valid_perc: 0.8109;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.45;valid_perc: 0.8106;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.14;valid_perc: 0.7975;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.39;valid_perc: 0.8081;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.25;valid_perc: 0.8021;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.31;valid_perc: 0.8045;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.19;valid_perc: 0.7998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.44;valid_perc: 0.8099;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.33;valid_perc: 0.8054;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.33;valid_perc: 0.8051;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.18;valid_perc: 0.7996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.41;valid_perc: 0.8085;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.19;valid_perc: 0.7998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.07;valid_perc: 0.7945;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.27;valid_perc: 0.8023;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.05;valid_perc: 0.7935;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.83;valid_perc: 0.7842;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.81;valid_perc: 0.7832;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.85;valid_perc: 0.7851;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 14.16;valid_perc: 0.7978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.99;valid_perc: 0.7906;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.78;valid_perc: 0.7817;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.41;valid_perc: 0.7669;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.55;valid_perc: 0.772;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.72;valid_perc: 0.7793;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.81;valid_perc: 0.7834;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.8;valid_perc: 0.7822;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.75;valid_perc: 0.78;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.41;valid_perc: 0.766;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.66;valid_perc: 0.7763;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.81;valid_perc: 0.7828;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.51;valid_perc: 0.7706;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.58;valid_perc: 0.7725;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.48;valid_perc: 0.7687;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.39;valid_perc: 0.765;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.3;valid_perc: 0.7616;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.14;valid_perc: 0.7545;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.0;valid_perc: 0.7489;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.36;valid_perc: 0.7633;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.92;valid_perc: 0.7449;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.14;valid_perc: 0.7543;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.8;valid_perc: 0.7401;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.74;valid_perc: 0.7377;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.93;valid_perc: 0.7459;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.84;valid_perc: 0.7417;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.63;valid_perc: 0.7328;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.59;valid_perc: 0.7315;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 13.02;valid_perc: 0.749;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.47;valid_perc: 0.7264;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 11.66;valid_perc: 0.6925;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.16;valid_perc: 0.7131;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.02;valid_perc: 0.7074;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 12.06;valid_perc: 0.7093;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 11.19;valid_perc: 0.6731;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 11.77;valid_perc: 0.6972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 11.1;valid_perc: 0.6692;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 11.35;valid_perc: 0.6792;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 10.83;valid_perc: 0.6579;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 11.27;valid_perc: 0.6759;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 10.91;valid_perc: 0.6607;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 10.67;valid_perc: 0.6513;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 10.2;valid_perc: 0.6316;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 10.14;valid_perc: 0.629;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 10.03;valid_perc: 0.6241;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 9.947;valid_perc: 0.6209;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 9.708;valid_perc: 0.6109;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 9.409;valid_perc: 0.5985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 9.788;valid_perc: 0.6141;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 8.604;valid_perc: 0.5651;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 8.73;valid_perc: 0.5704;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 8.662;valid_perc: 0.5673;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 8.444;valid_perc: 0.5585;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 8.236;valid_perc: 0.5497;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.658;valid_perc: 0.5256;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.369;valid_perc: 0.5136;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  6.8;valid_perc: 0.4899;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.932;valid_perc: 0.4956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.121;valid_perc: 0.5032;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 7.107;valid_perc: 0.5027;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.297;valid_perc: 0.469;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.789;valid_perc: 0.4893;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.466;valid_perc: 0.476;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.056;valid_perc: 0.4588;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.408;valid_perc: 0.432;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.25;valid_perc: 0.4256;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.394;valid_perc: 0.4316;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.889;valid_perc: 0.4106;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.852;valid_perc: 0.4091;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.707;valid_perc: 0.403;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.436;valid_perc: 0.3918;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.97;valid_perc: 0.3723;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.568;valid_perc: 0.3971;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.273;valid_perc: 0.385;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.816;valid_perc: 0.4074;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.114;valid_perc: 0.3787;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.241;valid_perc: 0.3423;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.025;valid_perc: 0.3335;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.159;valid_perc: 0.339;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.22;valid_perc: 0.3416;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.139;valid_perc: 0.3381;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.294;valid_perc: 0.3032;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.767;valid_perc: 0.2813;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.6833;valid_perc: 0.2366;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.002296;valid_perc: 0.2082;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.183;valid_perc: 0.159;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.104;valid_perc: 0.1208;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.498;valid_perc: 0.1044;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.763;valid_perc: 0.0933;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.995;valid_perc: 0.0837;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.984;valid_perc: 0.0841;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.884;valid_perc: 0.0883;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.84;valid_perc: 0.0901;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.258;valid_perc: 0.0726;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.215;valid_perc: 0.0745;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.258;valid_perc: 0.0727;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.229;valid_perc: 0.0739;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.051;valid_perc: 0.0814;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.182;valid_perc: 0.0759;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.398;valid_perc: 0.0669;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.34;valid_perc: 0.0693;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.304;valid_perc: 0.0707;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.224;valid_perc: 0.0741;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.296;valid_perc: 0.0713;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.398;valid_perc: 0.0667;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.294;valid_perc: 0.0711;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.399;valid_perc: 0.0667;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.319;valid_perc: 0.0701;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.481;valid_perc: 0.0634;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.558;valid_perc: 0.0602;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.261;valid_perc: 0.0726;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.396;valid_perc: 0.0669;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.354;valid_perc: 0.0686;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.521;valid_perc: 0.0617;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.409;valid_perc: 0.0663;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.547;valid_perc: 0.0606;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.595;valid_perc: 0.0586;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.573;valid_perc: 0.0595;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.589;valid_perc: 0.0588;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.562;valid_perc: 0.0599;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.554;valid_perc: 0.0603;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.611;valid_perc: 0.0579;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.72;valid_perc: 0.0534;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.677;valid_perc: 0.0551;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.751;valid_perc: 0.0521;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.717;valid_perc: 0.0535;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.667;valid_perc: 0.0556;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.715;valid_perc: 0.0536;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.612;valid_perc: 0.0579;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.691;valid_perc: 0.0546;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.695;valid_perc: 0.0545;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.941;valid_perc: 0.0442;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.891;valid_perc: 0.0463;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.879;valid_perc: 0.0468;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.941;valid_perc: 0.0442;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.038;valid_perc: 0.0402;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.977;valid_perc: 0.0428;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.019;valid_perc: 0.0411;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.107;valid_perc: 0.0374;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.161;valid_perc: 0.0352;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.133;valid_perc: 0.0363;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.099;valid_perc: 0.0378;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.132;valid_perc: 0.0364;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.982;valid_perc: 0.0427;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.037;valid_perc: 0.0404;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.042;valid_perc: 0.0402;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.056;valid_perc: 0.0397;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.162;valid_perc: 0.0352;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.114;valid_perc: 0.0373;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.096;valid_perc: 0.038;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.066;valid_perc: 0.0393;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.039;valid_perc: 0.0404;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.878;valid_perc: 0.0472;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.984;valid_perc: 0.0428;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.012;valid_perc: 0.0416;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.882;valid_perc: 0.0471;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.922;valid_perc: 0.0454;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.891;valid_perc: 0.0468;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.882;valid_perc: 0.0472;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.815;valid_perc: 0.0499;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.816;valid_perc: 0.05;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.882;valid_perc: 0.0471;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.747;valid_perc: 0.053;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.714;valid_perc: 0.0542;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.675;valid_perc: 0.0559;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.671;valid_perc: 0.0561;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.645;valid_perc: 0.0571;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.734;valid_perc: 0.0535;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.572;valid_perc: 0.0604;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.696;valid_perc: 0.0551;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.54;valid_perc: 0.0617;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.624;valid_perc: 0.0582;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.607;valid_perc: 0.059;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.532;valid_perc: 0.062;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.466;valid_perc: 0.0649;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.497;valid_perc: 0.0637;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.516;valid_perc: 0.0628;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.519;valid_perc: 0.0627;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.621;valid_perc: 0.0584;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.502;valid_perc: 0.0635;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.482;valid_perc: 0.0644;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.521;valid_perc: 0.0628;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.532;valid_perc: 0.0623;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.596;valid_perc: 0.0596;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.488;valid_perc: 0.0644;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.49;valid_perc: 0.0643;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.368;valid_perc: 0.0694;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.413;valid_perc: 0.0675;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.555;valid_perc: 0.0614;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.424;valid_perc: 0.0672;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.558;valid_perc: 0.0614;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.492;valid_perc: 0.0643;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.398;valid_perc: 0.0683;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.451;valid_perc: 0.0662;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.461;valid_perc: 0.0657;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.301;valid_perc: 0.0727;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.348;valid_perc: 0.0706;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.28;valid_perc: 0.0735;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.519;valid_perc: 0.0633;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.619;valid_perc: 0.0591;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.556;valid_perc: 0.0618;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.275;valid_perc: 0.074;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.35;valid_perc: 0.0709;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.419;valid_perc: 0.0676;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.354;valid_perc: 0.0707;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.415;valid_perc: 0.068;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.403;valid_perc: 0.0684;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-52-82512d4ed78b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mmodel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtrain_as_rl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpenalized_logP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\gentrl-0.1-py3.8.egg\\gentrl\\gentrl.py\u001b[0m in \u001b[0;36mtrain_as_rl\u001b[1;34m(self, reward_fn, num_iterations, verbose_step, batch_size, cond_lb, cond_rb, lr_lp, lr_dec)\u001b[0m\n\u001b[0;32m    219\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    220\u001b[0m             \u001b[0mz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mexploit_z\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexpl_z\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 221\u001b[1;33m             \u001b[0msmiles\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdec\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m50\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mz\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margmax\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    222\u001b[0m             \u001b[0mzc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdevice\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    223\u001b[0m             \u001b[0mconc_zy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mz\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mzc\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdim\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\gentrl-0.1-py3.8.egg\\gentrl\\decoder.py\u001b[0m in \u001b[0;36msample\u001b[1;34m(self, max_len, latents, argmax)\u001b[0m\n\u001b[0;32m    147\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    148\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmax_len\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 149\u001b[1;33m             \u001b[0mlogits\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_logits\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcur_tokens\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlatents\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msampling\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    150\u001b[0m             \u001b[0mlogits\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlogits\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdetach\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    151\u001b[0m             \u001b[0mlogits\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlog_softmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlogits\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdim\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\gentrl-0.1-py3.8.egg\\gentrl\\decoder.py\u001b[0m in \u001b[0;36mget_logits\u001b[1;34m(self, input_tensor, z, sampling)\u001b[0m\n\u001b[0;32m     70\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     71\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mdil_conv_layer\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdil_conv_layers\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 72\u001b[1;33m             \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdil_conv_layer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msampling\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msampling\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     73\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     74\u001b[0m         \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlogits_1x1_layer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\torch\\nn\\modules\\module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[1;34m(self, *input, **kwargs)\u001b[0m\n\u001b[0;32m    725\u001b[0m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_slow_forward\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    726\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 727\u001b[1;33m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mforward\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    728\u001b[0m         for hook in itertools.chain(\n\u001b[0;32m    729\u001b[0m                 \u001b[0m_global_forward_hooks\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\gentrl-0.1-py3.8.egg\\gentrl\\decoder.py\u001b[0m in \u001b[0;36mforward\u001b[1;34m(self, x_inp, sampling)\u001b[0m\n\u001b[0;32m    230\u001b[0m                               dim=2)\n\u001b[0;32m    231\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 232\u001b[1;33m             \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdilated_conv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdilation\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    233\u001b[0m             \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m:\u001b[0m\u001b[0mx_inp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    234\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\torch\\nn\\modules\\module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[1;34m(self, *input, **kwargs)\u001b[0m\n\u001b[0;32m    725\u001b[0m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_slow_forward\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    726\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 727\u001b[1;33m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mforward\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    728\u001b[0m         for hook in itertools.chain(\n\u001b[0;32m    729\u001b[0m                 \u001b[0m_global_forward_hooks\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\torch\\nn\\modules\\conv.py\u001b[0m in \u001b[0;36mforward\u001b[1;34m(self, input)\u001b[0m\n\u001b[0;32m    256\u001b[0m                             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mweight\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbias\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstride\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    257\u001b[0m                             _single(0), self.dilation, self.groups)\n\u001b[1;32m--> 258\u001b[1;33m         return F.conv1d(input, self.weight, self.bias, self.stride,\n\u001b[0m\u001b[0;32m    259\u001b[0m                         self.padding, self.dilation, self.groups)\n\u001b[0;32m    260\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "model.train_as_rl(penalized_logP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.034;valid_perc: 0.2315;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.013;valid_perc: 0.2274;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.934;valid_perc: 0.2434;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.973;valid_perc: 0.2344;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -4.0;valid_perc: 0.2286;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.959;valid_perc: 0.2376;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.94;valid_perc: 0.2408;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.919;valid_perc: 0.2426;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.95;valid_perc: 0.2364;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.911;valid_perc: 0.2466;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.924;valid_perc: 0.2424;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.881;valid_perc: 0.2472;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.881;valid_perc: 0.248;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.88;valid_perc: 0.2492;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.855;valid_perc: 0.2572;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.851;valid_perc: 0.2536;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.86;valid_perc: 0.2524;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.833;valid_perc: 0.2552;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.796;valid_perc: 0.2618;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.787;valid_perc: 0.268;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.765;valid_perc: 0.2674;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.806;valid_perc: 0.2628;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.722;valid_perc: 0.2726;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.69;valid_perc: 0.28;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.704;valid_perc: 0.281;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.736;valid_perc: 0.2704;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.711;valid_perc: 0.277;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.684;valid_perc: 0.2818;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.706;valid_perc: 0.2774;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.657;valid_perc: 0.287;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.661;valid_perc: 0.2876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.651;valid_perc: 0.291;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.58;valid_perc:  0.3;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.61;valid_perc: 0.2924;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.611;valid_perc: 0.293;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.518;valid_perc: 0.308;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.577;valid_perc: 0.3008;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.601;valid_perc: 0.2892;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.532;valid_perc: 0.3058;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.565;valid_perc: 0.298;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.498;valid_perc: 0.31;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.496;valid_perc: 0.3082;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.515;valid_perc: 0.3078;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.494;valid_perc: 0.3088;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.495;valid_perc: 0.3092;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.433;valid_perc: 0.3192;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.431;valid_perc: 0.3158;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.415;valid_perc: 0.3218;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.395;valid_perc: 0.3228;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.426;valid_perc: 0.3156;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.44;valid_perc: 0.3124;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.356;valid_perc: 0.3304;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.328;valid_perc: 0.3352;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.307;valid_perc: 0.334;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.324;valid_perc: 0.3374;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.295;valid_perc: 0.3388;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.233;valid_perc: 0.3474;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.344;valid_perc: 0.3262;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.228;valid_perc: 0.3488;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.283;valid_perc: 0.3384;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.291;valid_perc: 0.3358;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.29;valid_perc: 0.335;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.177;valid_perc: 0.3586;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.16;valid_perc: 0.3598;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.173;valid_perc: 0.354;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.114;valid_perc: 0.3632;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.112;valid_perc: 0.3644;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.14;valid_perc: 0.3602;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.113;valid_perc: 0.3628;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.115;valid_perc: 0.3674;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.069;valid_perc: 0.3706;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.104;valid_perc: 0.3642;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.027;valid_perc: 0.3814;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.982;valid_perc: 0.3848;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.068;valid_perc: 0.3698;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.012;valid_perc: 0.3838;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.969;valid_perc: 0.3876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.933;valid_perc: 0.3956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.961;valid_perc: 0.3876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.028;valid_perc: 0.376;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -3.035;valid_perc: 0.3774;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.986;valid_perc: 0.3786;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.936;valid_perc: 0.3894;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.859;valid_perc: 0.4018;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.838;valid_perc: 0.4056;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.873;valid_perc: 0.4004;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.787;valid_perc: 0.4152;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.868;valid_perc: 0.3986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.878;valid_perc: 0.3984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.738;valid_perc: 0.4216;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.886;valid_perc: 0.3952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.754;valid_perc: 0.417;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.753;valid_perc: 0.4198;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.697;valid_perc: 0.4286;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.745;valid_perc: 0.4214;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.79;valid_perc: 0.4128;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.765;valid_perc: 0.4102;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.697;valid_perc: 0.4254;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.671;valid_perc: 0.425;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.643;valid_perc: 0.438;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.601;valid_perc: 0.4408;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.67;valid_perc: 0.4288;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.717;valid_perc: 0.4224;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.606;valid_perc: 0.4396;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.596;valid_perc: 0.4368;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.637;valid_perc: 0.4314;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.499;valid_perc: 0.4592;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.623;valid_perc: 0.439;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.611;valid_perc: 0.4366;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.617;valid_perc: 0.4344;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.568;valid_perc: 0.4462;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.577;valid_perc: 0.4456;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.575;valid_perc: 0.44;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.482;valid_perc: 0.456;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.502;valid_perc: 0.4526;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.507;valid_perc: 0.4502;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.478;valid_perc: 0.4584;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.502;valid_perc: 0.4528;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.449;valid_perc: 0.463;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.464;valid_perc: 0.4546;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.43;valid_perc: 0.4658;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.399;valid_perc: 0.4726;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.387;valid_perc: 0.4696;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.401;valid_perc: 0.467;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.461;valid_perc: 0.461;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.396;valid_perc: 0.4712;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.346;valid_perc: 0.4722;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.389;valid_perc: 0.4674;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.341;valid_perc: 0.4766;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.393;valid_perc: 0.4682;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.216;valid_perc: 0.4956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.339;valid_perc: 0.4754;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.271;valid_perc: 0.4876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.341;valid_perc: 0.4746;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.248;valid_perc: 0.4938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.241;valid_perc: 0.4894;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.308;valid_perc: 0.4802;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.171;valid_perc:  0.5;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.236;valid_perc: 0.4938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.203;valid_perc: 0.4968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.242;valid_perc: 0.4918;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.237;valid_perc: 0.4892;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.248;valid_perc: 0.4834;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.232;valid_perc: 0.4894;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.216;valid_perc: 0.495;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.157;valid_perc: 0.5008;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.131;valid_perc: 0.5062;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.05;valid_perc: 0.517;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.134;valid_perc: 0.5036;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.179;valid_perc: 0.492;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.042;valid_perc: 0.5176;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.095;valid_perc: 0.5096;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.157;valid_perc: 0.5006;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.054;valid_perc: 0.518;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.101;valid_perc: 0.5096;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.096;valid_perc: 0.509;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.098;valid_perc: 0.5078;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.046;valid_perc: 0.5188;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.109;valid_perc: 0.5078;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.054;valid_perc: 0.5134;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.046;valid_perc: 0.5152;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.956;valid_perc: 0.5312;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.969;valid_perc: 0.5294;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.975;valid_perc: 0.5226;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.992;valid_perc: 0.5242;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.972;valid_perc: 0.528;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.043;valid_perc: 0.5144;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.973;valid_perc: 0.5244;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -2.0;valid_perc: 0.5214;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.923;valid_perc: 0.5344;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.953;valid_perc: 0.5298;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.911;valid_perc: 0.5374;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.894;valid_perc: 0.5394;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.891;valid_perc: 0.5342;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.869;valid_perc: 0.5408;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.874;valid_perc: 0.5394;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.844;valid_perc: 0.5492;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.853;valid_perc: 0.544;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.741;valid_perc: 0.5604;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.843;valid_perc: 0.5448;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.828;valid_perc: 0.547;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.859;valid_perc: 0.5426;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.776;valid_perc: 0.5584;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.78;valid_perc: 0.5574;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.759;valid_perc: 0.5534;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.789;valid_perc: 0.5494;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.724;valid_perc: 0.5616;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.796;valid_perc: 0.5528;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.759;valid_perc: 0.5552;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.742;valid_perc: 0.559;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.739;valid_perc: 0.5578;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.833;valid_perc: 0.5436;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.728;valid_perc: 0.5642;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.698;valid_perc: 0.5646;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.659;valid_perc: 0.5718;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.641;valid_perc: 0.573;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.609;valid_perc: 0.5808;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.555;valid_perc: 0.5842;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.669;valid_perc: 0.5676;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.637;valid_perc: 0.575;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.597;valid_perc: 0.5812;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.626;valid_perc: 0.5714;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.557;valid_perc: 0.5876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.606;valid_perc: 0.576;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.636;valid_perc: 0.5742;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.605;valid_perc: 0.5768;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.57;valid_perc: 0.585;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.544;valid_perc: 0.5876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.586;valid_perc: 0.5782;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.461;valid_perc: 0.5986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.454;valid_perc: 0.5996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.474;valid_perc: 0.5966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.53;valid_perc: 0.5874;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.456;valid_perc: 0.5994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.517;valid_perc: 0.5876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.405;valid_perc: 0.6062;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.438;valid_perc: 0.6032;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.378;valid_perc: 0.6114;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.436;valid_perc: 0.6046;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.403;valid_perc: 0.6088;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.348;valid_perc: 0.6134;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.374;valid_perc: 0.6112;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.417;valid_perc: 0.602;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.334;valid_perc: 0.612;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.259;valid_perc: 0.625;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.279;valid_perc: 0.6244;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.301;valid_perc: 0.6206;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.296;valid_perc: 0.6238;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.336;valid_perc: 0.6176;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.269;valid_perc: 0.6222;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.305;valid_perc: 0.621;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.182;valid_perc: 0.6384;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.277;valid_perc: 0.625;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.218;valid_perc: 0.6338;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.24;valid_perc: 0.6268;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.237;valid_perc: 0.632;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.13;valid_perc: 0.6432;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.226;valid_perc: 0.6308;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.182;valid_perc: 0.6386;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.131;valid_perc: 0.6442;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.192;valid_perc: 0.633;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.093;valid_perc: 0.6462;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.182;valid_perc: 0.6372;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.046;valid_perc: 0.6582;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.052;valid_perc: 0.6566;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.075;valid_perc: 0.649;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.145;valid_perc: 0.6406;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.072;valid_perc: 0.6504;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9906;valid_perc: 0.6654;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9903;valid_perc: 0.6648;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.988;valid_perc: 0.6658;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -1.02;valid_perc: 0.662;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9669;valid_perc: 0.6682;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9233;valid_perc: 0.6758;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9686;valid_perc: 0.6646;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.97;valid_perc: 0.6654;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.8763;valid_perc: 0.6794;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9434;valid_perc: 0.6656;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.87;valid_perc: 0.6792;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.8858;valid_perc: 0.6748;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.8824;valid_perc: 0.676;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.8872;valid_perc: 0.6772;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.9339;valid_perc: 0.6692;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.782;valid_perc: 0.6912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.883;valid_perc: 0.678;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7787;valid_perc: 0.6894;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7289;valid_perc:  0.7;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7781;valid_perc: 0.693;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7472;valid_perc: 0.6964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7564;valid_perc: 0.6972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7;valid_perc: 0.7024;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7552;valid_perc: 0.6936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.678;valid_perc: 0.7042;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.735;valid_perc: 0.6962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.7614;valid_perc: 0.6922;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.6002;valid_perc: 0.7206;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.6295;valid_perc: 0.7142;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.563;valid_perc: 0.7194;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.6755;valid_perc: 0.7034;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.6694;valid_perc: 0.705;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.625;valid_perc: 0.7098;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.5379;valid_perc: 0.7276;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.5466;valid_perc: 0.7234;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.5047;valid_perc: 0.725;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.5399;valid_perc: 0.7212;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.4995;valid_perc: 0.7258;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.4832;valid_perc: 0.7288;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.5272;valid_perc: 0.7228;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.4224;valid_perc: 0.7392;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.4427;valid_perc: 0.735;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.4453;valid_perc: 0.732;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.4724;valid_perc: 0.73;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.4324;valid_perc: 0.7338;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.2669;valid_perc: 0.7622;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.3543;valid_perc: 0.7452;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.2961;valid_perc: 0.7522;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.3254;valid_perc: 0.7506;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.3936;valid_perc: 0.738;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.3138;valid_perc: 0.7536;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.3288;valid_perc: 0.7446;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.2581;valid_perc: 0.7554;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.3642;valid_perc: 0.7408;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.2931;valid_perc: 0.7544;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.1679;valid_perc: 0.7702;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.2566;valid_perc: 0.7576;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.1713;valid_perc: 0.7714;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.1732;valid_perc: 0.7632;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.2051;valid_perc: 0.7636;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.2103;valid_perc: 0.7636;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.1781;valid_perc: 0.7686;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.05994;valid_perc: 0.7822;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.08168;valid_perc: 0.7758;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.1462;valid_perc: 0.7716;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.1313;valid_perc: 0.77;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.1143;valid_perc: 0.7714;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: -0.02771;valid_perc: 0.7836;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.002632;valid_perc: 0.7866;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.02235;valid_perc: 0.7928;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.0323;valid_perc: 0.7914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.02882;valid_perc: 0.7906;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.05317;valid_perc: 0.7914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.004297;valid_perc: 0.7838;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.07415;valid_perc: 0.7936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.04627;valid_perc: 0.7912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.1099;valid_perc: 0.7972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.1204;valid_perc:  0.8;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.07854;valid_perc: 0.792;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.08781;valid_perc: 0.7912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.1312;valid_perc: 0.7996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.1281;valid_perc: 0.7988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.1648;valid_perc: 0.8006;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.1365;valid_perc: 0.7986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.2433;valid_perc: 0.8134;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.2281;valid_perc: 0.8074;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.2021;valid_perc: 0.8054;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.2464;valid_perc: 0.8112;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.2478;valid_perc: 0.8114;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.2493;valid_perc: 0.8102;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.2515;valid_perc: 0.8092;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3488;valid_perc: 0.8266;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3108;valid_perc: 0.8176;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3695;valid_perc: 0.8212;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3122;valid_perc: 0.8162;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4016;valid_perc: 0.827;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.41;valid_perc: 0.8264;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4044;valid_perc: 0.8276;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4192;valid_perc: 0.826;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3669;valid_perc: 0.8204;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.3697;valid_perc: 0.8222;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4464;valid_perc: 0.8274;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4533;valid_perc: 0.8276;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4722;valid_perc: 0.8308;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5952;valid_perc: 0.8498;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.4289;valid_perc: 0.8212;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5076;valid_perc: 0.8356;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5897;valid_perc: 0.8466;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5935;valid_perc: 0.846;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5414;valid_perc: 0.8356;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5706;valid_perc: 0.8412;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5674;valid_perc: 0.8414;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.6496;valid_perc: 0.8498;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.5669;valid_perc: 0.8356;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.6346;valid_perc: 0.846;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.7316;valid_perc: 0.8596;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.7113;valid_perc: 0.8518;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.6384;valid_perc: 0.8462;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.6974;valid_perc: 0.848;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.6529;valid_perc: 0.8422;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.6845;valid_perc: 0.848;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.7382;valid_perc: 0.8548;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.7287;valid_perc: 0.851;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.7539;valid_perc: 0.8564;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.789;valid_perc: 0.8572;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.8286;valid_perc: 0.8654;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.7971;valid_perc: 0.8568;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.7929;valid_perc: 0.8534;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.8509;valid_perc: 0.8654;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.8212;valid_perc: 0.8602;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.9042;valid_perc: 0.8704;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.898;valid_perc: 0.8658;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.8617;valid_perc: 0.864;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.9138;valid_perc: 0.871;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.9094;valid_perc: 0.8706;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.9211;valid_perc: 0.8682;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.038;valid_perc: 0.883;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.9683;valid_perc: 0.8738;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.006;valid_perc: 0.8788;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.001;valid_perc: 0.8738;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.045;valid_perc: 0.8828;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 0.9939;valid_perc: 0.875;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.105;valid_perc: 0.8874;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.025;valid_perc: 0.8782;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.115;valid_perc: 0.8834;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.065;valid_perc: 0.8784;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.119;valid_perc: 0.8868;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.129;valid_perc: 0.8824;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.109;valid_perc: 0.8814;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.189;valid_perc: 0.8902;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.167;valid_perc: 0.8894;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.16;valid_perc: 0.8872;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.149;valid_perc: 0.8832;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.233;valid_perc: 0.8948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.213;valid_perc: 0.8898;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.247;valid_perc: 0.894;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.274;valid_perc: 0.8968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.259;valid_perc: 0.8952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.237;valid_perc: 0.892;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.301;valid_perc: 0.8966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.319;valid_perc: 0.9012;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.328;valid_perc: 0.9004;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.342;valid_perc: 0.9002;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.326;valid_perc: 0.8988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.325;valid_perc: 0.8978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.398;valid_perc: 0.9074;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.405;valid_perc: 0.9068;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.365;valid_perc: 0.8984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.416;valid_perc: 0.9076;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.394;valid_perc: 0.9034;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.414;valid_perc: 0.9038;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.424;valid_perc: 0.9064;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.412;valid_perc: 0.9044;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.386;valid_perc: 0.9022;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.445;valid_perc: 0.9048;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.485;valid_perc: 0.9122;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.446;valid_perc: 0.9022;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.503;valid_perc: 0.9098;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.502;valid_perc: 0.9112;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.556;valid_perc: 0.9146;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.475;valid_perc: 0.9048;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  1.5;valid_perc: 0.9058;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.561;valid_perc: 0.9138;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.575;valid_perc: 0.914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.617;valid_perc: 0.922;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.594;valid_perc: 0.9158;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.538;valid_perc: 0.9076;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.614;valid_perc: 0.919;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.558;valid_perc: 0.911;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.623;valid_perc: 0.9152;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.609;valid_perc: 0.9154;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.652;valid_perc: 0.9202;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.66;valid_perc: 0.9174;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.68;valid_perc: 0.9204;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.679;valid_perc: 0.919;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.698;valid_perc: 0.9198;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.701;valid_perc: 0.922;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.758;valid_perc: 0.9262;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.711;valid_perc: 0.9194;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.768;valid_perc: 0.9292;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.709;valid_perc: 0.9186;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.767;valid_perc: 0.927;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.762;valid_perc: 0.9272;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.792;valid_perc: 0.9286;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.783;valid_perc: 0.9274;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.823;valid_perc: 0.932;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.864;valid_perc: 0.9358;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.846;valid_perc: 0.9312;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.829;valid_perc: 0.9282;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.834;valid_perc: 0.9296;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.841;valid_perc: 0.929;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.85;valid_perc: 0.9292;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.892;valid_perc: 0.9338;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.884;valid_perc: 0.9324;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.893;valid_perc: 0.9334;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.89;valid_perc: 0.9326;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.946;valid_perc: 0.9396;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.95;valid_perc: 0.9366;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.934;valid_perc: 0.9374;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.896;valid_perc: 0.931;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.927;valid_perc: 0.933;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.967;valid_perc: 0.9394;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.959;valid_perc: 0.9362;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.97;valid_perc: 0.9384;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.966;valid_perc: 0.9372;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.003;valid_perc: 0.9382;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.046;valid_perc: 0.9462;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.991;valid_perc: 0.937;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 1.983;valid_perc: 0.936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.008;valid_perc: 0.9386;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.054;valid_perc: 0.9448;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.019;valid_perc: 0.9378;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.061;valid_perc: 0.943;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.068;valid_perc: 0.945;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.121;valid_perc: 0.9486;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.051;valid_perc: 0.9416;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.058;valid_perc: 0.9408;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.053;valid_perc: 0.9394;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  2.1;valid_perc: 0.946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.069;valid_perc: 0.9402;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.076;valid_perc: 0.9428;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.131;valid_perc: 0.9472;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.124;valid_perc: 0.9468;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.144;valid_perc: 0.9476;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.154;valid_perc: 0.9482;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.118;valid_perc: 0.944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.115;valid_perc: 0.9414;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.137;valid_perc: 0.9448;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.155;valid_perc: 0.9466;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.122;valid_perc: 0.9416;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.161;valid_perc: 0.946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.18;valid_perc: 0.948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.145;valid_perc: 0.9458;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.207;valid_perc: 0.9492;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.229;valid_perc: 0.9532;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.179;valid_perc: 0.946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.235;valid_perc: 0.9534;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.241;valid_perc: 0.9508;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.185;valid_perc: 0.9464;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.231;valid_perc: 0.9516;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.285;valid_perc: 0.9548;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.243;valid_perc: 0.9514;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.262;valid_perc: 0.9532;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.26;valid_perc: 0.9528;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.252;valid_perc: 0.9524;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.286;valid_perc: 0.956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.289;valid_perc: 0.9538;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.274;valid_perc: 0.9532;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.276;valid_perc: 0.9528;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.266;valid_perc: 0.9494;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.295;valid_perc: 0.955;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.295;valid_perc: 0.9556;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.347;valid_perc: 0.96;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.284;valid_perc: 0.9508;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.295;valid_perc: 0.952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.315;valid_perc: 0.9536;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.323;valid_perc: 0.9538;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.324;valid_perc: 0.954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.331;valid_perc: 0.956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.36;valid_perc: 0.959;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.375;valid_perc: 0.9598;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.342;valid_perc: 0.9536;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.36;valid_perc: 0.9574;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.327;valid_perc: 0.9524;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.385;valid_perc: 0.9596;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.326;valid_perc: 0.9538;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.393;valid_perc: 0.958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.399;valid_perc: 0.9568;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.427;valid_perc: 0.9626;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.411;valid_perc: 0.9604;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.389;valid_perc: 0.9584;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.408;valid_perc: 0.9598;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.375;valid_perc: 0.954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.442;valid_perc: 0.9628;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.447;valid_perc: 0.9614;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.433;valid_perc: 0.9582;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.419;valid_perc: 0.9574;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.424;valid_perc: 0.957;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.441;valid_perc: 0.9592;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.456;valid_perc: 0.9592;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.495;valid_perc: 0.9648;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.487;valid_perc: 0.9638;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.492;valid_perc: 0.9638;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.477;valid_perc: 0.9626;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.513;valid_perc: 0.967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.517;valid_perc: 0.9656;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.484;valid_perc: 0.962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.54;valid_perc: 0.9672;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.487;valid_perc: 0.9594;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.479;valid_perc: 0.9598;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.515;valid_perc: 0.9646;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.561;valid_perc: 0.9674;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.527;valid_perc: 0.964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.513;valid_perc: 0.9624;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.537;valid_perc: 0.9646;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.572;valid_perc: 0.9666;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.557;valid_perc: 0.9662;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.567;valid_perc: 0.9648;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.608;valid_perc: 0.9716;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.569;valid_perc: 0.9646;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.564;valid_perc: 0.9656;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.573;valid_perc: 0.9656;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.57;valid_perc: 0.965;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.582;valid_perc: 0.965;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.566;valid_perc: 0.965;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.565;valid_perc: 0.9632;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.563;valid_perc: 0.962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.634;valid_perc: 0.9704;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.584;valid_perc: 0.9636;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.64;valid_perc: 0.9712;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.602;valid_perc: 0.9642;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.596;valid_perc: 0.9636;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.63;valid_perc: 0.967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.666;valid_perc: 0.971;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.665;valid_perc: 0.9712;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.632;valid_perc: 0.9686;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.627;valid_perc: 0.9676;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.609;valid_perc: 0.9644;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.624;valid_perc: 0.9666;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.696;valid_perc: 0.9722;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.657;valid_perc: 0.9672;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.669;valid_perc: 0.9682;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.653;valid_perc: 0.9682;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.664;valid_perc: 0.967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.663;valid_perc: 0.9656;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.72;valid_perc: 0.973;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.664;valid_perc: 0.966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.72;valid_perc: 0.9696;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.72;valid_perc: 0.971;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.712;valid_perc: 0.9684;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.722;valid_perc: 0.968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.726;valid_perc: 0.97;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.729;valid_perc: 0.9678;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.715;valid_perc: 0.9654;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.758;valid_perc: 0.9706;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.782;valid_perc: 0.973;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.75;valid_perc: 0.9688;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.798;valid_perc: 0.9718;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.793;valid_perc: 0.9716;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.784;valid_perc: 0.97;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.766;valid_perc: 0.966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.815;valid_perc: 0.9706;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.814;valid_perc: 0.9696;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.81;valid_perc: 0.9676;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.859;valid_perc: 0.9738;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.834;valid_perc: 0.9692;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.873;valid_perc: 0.9714;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.925;valid_perc: 0.9752;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.915;valid_perc: 0.9734;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.941;valid_perc: 0.9744;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.931;valid_perc: 0.9718;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.947;valid_perc: 0.9716;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.949;valid_perc: 0.9708;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 2.956;valid_perc: 0.9678;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.017;valid_perc: 0.9726;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.014;valid_perc: 0.969;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.002;valid_perc: 0.9674;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.059;valid_perc: 0.9724;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.083;valid_perc: 0.9722;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.079;valid_perc: 0.9714;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.105;valid_perc: 0.9702;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.118;valid_perc: 0.9696;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.182;valid_perc: 0.9748;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.201;valid_perc: 0.972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.165;valid_perc: 0.967;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.218;valid_perc: 0.9716;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.248;valid_perc: 0.973;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.264;valid_perc: 0.9708;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.304;valid_perc: 0.971;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.329;valid_perc: 0.9734;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.327;valid_perc: 0.9718;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.336;valid_perc: 0.969;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.391;valid_perc: 0.9734;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.435;valid_perc: 0.975;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.451;valid_perc: 0.975;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.462;valid_perc: 0.9758;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.432;valid_perc: 0.972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.497;valid_perc: 0.9736;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.547;valid_perc: 0.9768;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.509;valid_perc: 0.9724;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.56;valid_perc: 0.9754;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.575;valid_perc: 0.9776;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.569;valid_perc: 0.9748;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.584;valid_perc: 0.975;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.661;valid_perc: 0.9814;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.597;valid_perc: 0.974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.629;valid_perc: 0.976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.627;valid_perc: 0.9748;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.616;valid_perc: 0.9736;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.641;valid_perc: 0.9746;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.695;valid_perc: 0.9778;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.655;valid_perc: 0.974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.693;valid_perc: 0.977;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.664;valid_perc: 0.9734;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.683;valid_perc: 0.977;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.706;valid_perc: 0.9754;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.719;valid_perc: 0.9764;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.743;valid_perc: 0.9778;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.757;valid_perc: 0.9784;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  3.8;valid_perc: 0.982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.786;valid_perc: 0.9786;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.765;valid_perc: 0.9778;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.806;valid_perc: 0.9808;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.804;valid_perc: 0.9792;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  3.8;valid_perc: 0.9784;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.846;valid_perc: 0.9824;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.853;valid_perc: 0.9824;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.835;valid_perc: 0.9794;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.857;valid_perc: 0.9814;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.867;valid_perc: 0.9828;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.83;valid_perc: 0.977;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.881;valid_perc: 0.9798;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.857;valid_perc: 0.979;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.902;valid_perc: 0.983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.904;valid_perc: 0.983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.913;valid_perc: 0.9822;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.909;valid_perc: 0.9832;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.904;valid_perc: 0.9814;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.941;valid_perc: 0.9828;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.928;valid_perc: 0.9826;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.964;valid_perc: 0.9844;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.924;valid_perc: 0.982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.962;valid_perc: 0.9838;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.943;valid_perc: 0.9804;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.977;valid_perc: 0.9846;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.968;valid_perc: 0.983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.985;valid_perc: 0.983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.961;valid_perc: 0.9808;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.969;valid_perc: 0.9808;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.957;valid_perc: 0.979;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.021;valid_perc: 0.9846;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 3.988;valid_perc: 0.9812;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.031;valid_perc: 0.9856;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.022;valid_perc: 0.9832;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.003;valid_perc: 0.9816;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.065;valid_perc: 0.9866;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.085;valid_perc: 0.9868;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.056;valid_perc: 0.9828;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.081;valid_perc: 0.9858;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.068;valid_perc: 0.983;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.08;valid_perc: 0.9842;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.099;valid_perc: 0.9858;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.103;valid_perc: 0.9856;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.09;valid_perc: 0.984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.126;valid_perc: 0.985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.122;valid_perc: 0.985;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.101;valid_perc: 0.9826;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.152;valid_perc: 0.9846;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.111;valid_perc: 0.9822;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.175;valid_perc: 0.9882;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.185;valid_perc: 0.9868;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.171;valid_perc: 0.9868;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.202;valid_perc: 0.987;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.194;valid_perc: 0.9862;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.177;valid_perc: 0.9846;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.241;valid_perc: 0.9878;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.237;valid_perc: 0.9886;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.248;valid_perc: 0.9876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.231;valid_perc: 0.9872;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.243;valid_perc: 0.9858;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.293;valid_perc: 0.9902;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.232;valid_perc: 0.9832;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.284;valid_perc: 0.9884;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.269;valid_perc: 0.9872;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.291;valid_perc: 0.988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.307;valid_perc: 0.9878;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.316;valid_perc: 0.9896;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.324;valid_perc: 0.989;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.31;valid_perc: 0.9874;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.323;valid_perc: 0.988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.336;valid_perc: 0.988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.339;valid_perc: 0.9888;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.35;valid_perc: 0.9888;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.355;valid_perc: 0.9892;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.374;valid_perc: 0.99;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.384;valid_perc: 0.991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.393;valid_perc: 0.9912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.364;valid_perc: 0.9886;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.373;valid_perc: 0.988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.389;valid_perc: 0.9886;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.411;valid_perc: 0.9904;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.399;valid_perc: 0.9902;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.42;valid_perc: 0.9914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.416;valid_perc: 0.9896;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.44;valid_perc: 0.9924;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.428;valid_perc: 0.9904;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.421;valid_perc: 0.9888;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.426;valid_perc: 0.9894;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.419;valid_perc: 0.989;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.452;valid_perc: 0.9914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.451;valid_perc: 0.9914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.424;valid_perc: 0.9874;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.424;valid_perc: 0.9876;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.458;valid_perc: 0.9914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.449;valid_perc: 0.9906;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.479;valid_perc: 0.9924;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.478;valid_perc: 0.992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.474;valid_perc: 0.991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.453;valid_perc: 0.9888;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.481;valid_perc: 0.9916;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.463;valid_perc: 0.9904;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.472;valid_perc: 0.99;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.488;valid_perc: 0.9916;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.484;valid_perc: 0.9916;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.482;valid_perc: 0.991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.484;valid_perc: 0.9914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.48;valid_perc: 0.9912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.495;valid_perc: 0.9916;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.496;valid_perc: 0.9912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.494;valid_perc: 0.9908;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.497;valid_perc: 0.991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.523;valid_perc: 0.9938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.506;valid_perc: 0.9912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.533;valid_perc: 0.9936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  4.5;valid_perc: 0.9906;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.522;valid_perc: 0.9926;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.527;valid_perc: 0.9924;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.531;valid_perc: 0.9928;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.516;valid_perc: 0.9914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.506;valid_perc: 0.991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.549;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.509;valid_perc: 0.9904;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.523;valid_perc: 0.991;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.519;valid_perc: 0.9916;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.553;valid_perc: 0.9938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.534;valid_perc: 0.992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.522;valid_perc: 0.9908;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.54;valid_perc: 0.992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.54;valid_perc: 0.992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.55;valid_perc: 0.9924;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.546;valid_perc: 0.9928;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.557;valid_perc: 0.9944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.533;valid_perc: 0.9912;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.565;valid_perc: 0.9942;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.581;valid_perc: 0.995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.568;valid_perc: 0.9942;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.573;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.569;valid_perc: 0.9944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.582;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.592;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.571;valid_perc: 0.9932;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.577;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.582;valid_perc: 0.995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.573;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.581;valid_perc: 0.9944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.595;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.588;valid_perc: 0.9948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.591;valid_perc: 0.995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.588;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.588;valid_perc: 0.9944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.593;valid_perc: 0.994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.595;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.605;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.583;valid_perc: 0.9928;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.599;valid_perc: 0.9948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.57;valid_perc: 0.992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.608;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.594;valid_perc: 0.9936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.621;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.608;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.607;valid_perc: 0.995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.598;valid_perc: 0.9948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.596;valid_perc: 0.994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.615;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.609;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.626;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.629;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.599;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.62;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.623;valid_perc: 0.9956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.612;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.626;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.61;valid_perc: 0.9944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.631;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.635;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.641;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.619;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.641;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.616;valid_perc: 0.9944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.634;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.626;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.637;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.643;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.63;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.632;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.637;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.619;valid_perc: 0.9938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.628;valid_perc: 0.995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.631;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.635;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.637;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.653;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.64;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.642;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.644;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.653;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.648;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.642;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.639;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.647;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.655;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.657;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.66;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.67;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.642;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.647;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.644;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.652;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.663;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.657;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.655;valid_perc: 0.9956;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.658;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.664;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.67;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.654;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.677;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.66;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.669;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.657;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.665;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.676;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.67;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.663;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.672;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.677;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.65;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.667;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.676;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.675;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.66;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.674;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.667;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.678;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.683;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.684;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.69;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.678;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.69;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.687;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.681;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.682;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.681;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.689;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.695;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.681;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.67;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.666;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.692;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.687;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.703;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.69;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.688;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.681;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.699;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.69;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.695;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.686;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.696;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.686;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.689;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.689;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.684;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.693;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.702;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.692;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.697;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.689;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.706;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.692;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.697;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.706;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.696;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.699;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.699;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.702;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.712;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.696;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.685;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.708;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.712;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.717;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.701;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.714;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  4.7;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.701;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.702;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.711;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.708;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.711;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.704;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.711;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.712;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.711;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.707;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.728;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.722;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.717;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.714;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.71;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.724;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.715;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.72;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.731;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.723;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.729;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.741;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.723;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.739;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.74;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.755;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.76;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.752;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.759;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.775;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.791;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.811;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.809;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.817;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.832;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.844;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.855;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.868;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.856;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.874;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.902;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.884;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.893;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.907;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.908;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.916;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.924;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.922;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.945;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.923;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.941;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.937;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.952;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.938;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.951;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.944;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.972;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.963;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.966;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.986;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.967;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.966;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.972;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.976;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.984;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.98;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.98;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.971;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.974;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.986;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.986;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.986;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.985;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.986;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.982;valid_perc: 0.9972;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.993;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.994;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.984;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.996;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.998;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.996;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  5.0;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.994;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.015;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.014;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 4.995;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.01;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.006;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.009;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.013;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.013;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.015;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.016;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.017;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.008;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.021;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.009;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.026;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.013;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.006;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.022;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.017;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.024;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.026;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.018;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.027;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.025;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.029;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.032;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.016;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.021;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.032;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.037;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.023;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.031;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.024;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.039;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.027;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.036;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.038;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.032;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.025;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.032;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.04;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.023;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.043;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.036;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.03;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.056;valid_perc:  1.0;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.025;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.036;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.04;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.038;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.044;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.039;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.043;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.051;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.052;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.038;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.05;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.05;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.045;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.057;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.044;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.053;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.046;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.044;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.043;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.056;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.056;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.053;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.053;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.052;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.048;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.054;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.054;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.056;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.064;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.059;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.052;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.04;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.052;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.06;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.062;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.055;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.057;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.062;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.051;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.051;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.067;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.06;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.063;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.064;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.067;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.057;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.067;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.064;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.072;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.061;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.072;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.071;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.068;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.067;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.063;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.066;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.071;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.075;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.064;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.068;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.073;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.054;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.067;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.072;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.077;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.069;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.065;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.071;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.076;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.077;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.075;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.073;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.075;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.082;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.072;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.077;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.08;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.085;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.071;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.08;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.083;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.081;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.083;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.079;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.075;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.083;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.089;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.078;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.084;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.082;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.079;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.087;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.088;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.089;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.097;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.093;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.088;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.104;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.099;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  5.1;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.103;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.111;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.102;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.111;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.124;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.109;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.126;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.13;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.133;valid_perc: 0.9988;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.145;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.136;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.16;valid_perc: 0.9994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.148;valid_perc: 0.9976;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.182;valid_perc: 0.9996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.165;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.179;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.193;valid_perc: 0.9992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward:  5.2;valid_perc: 0.9986;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.21;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.229;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.237;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.249;valid_perc: 0.999;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.253;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.277;valid_perc: 0.9978;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.302;valid_perc: 0.9982;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.301;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.332;valid_perc: 0.9984;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.341;valid_perc: 0.9974;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.349;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.354;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.374;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.387;valid_perc: 0.9966;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.38;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.405;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.423;valid_perc: 0.997;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.402;valid_perc: 0.9938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.425;valid_perc: 0.9968;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.429;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.439;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.452;valid_perc: 0.996;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.458;valid_perc: 0.995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.468;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.503;valid_perc: 0.998;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.493;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.518;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.517;valid_perc: 0.9942;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.536;valid_perc: 0.9942;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.55;valid_perc: 0.9944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.572;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.576;valid_perc: 0.9938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.601;valid_perc: 0.9952;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.619;valid_perc: 0.994;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.624;valid_perc: 0.9948;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.644;valid_perc: 0.9958;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.663;valid_perc: 0.9964;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.655;valid_perc: 0.9938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.65;valid_perc: 0.9914;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.673;valid_perc: 0.9934;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.723;valid_perc: 0.9954;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.722;valid_perc: 0.9946;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.749;valid_perc: 0.9962;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.737;valid_perc: 0.9928;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.77;valid_perc: 0.995;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.757;valid_perc: 0.9922;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.802;valid_perc: 0.9944;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.811;valid_perc: 0.9936;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.843;valid_perc: 0.9934;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.842;valid_perc: 0.9906;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.873;valid_perc: 0.9916;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.898;valid_perc: 0.992;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.924;valid_perc: 0.9934;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.924;valid_perc: 0.9916;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.932;valid_perc: 0.989;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.994;valid_perc: 0.9938;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 5.989;valid_perc: 0.9916;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.009;valid_perc: 0.9906;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.024;valid_perc: 0.9902;\n",
      "!!!!!!!!!!!!!!!!!!!!!!!!!mean_reward: 6.088;valid_perc: 0.9926;\n",
      "!!!!!!!!!!"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-21-75f0e68b2b29>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mmodel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtrain_as_rl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpenalized_logP\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mverbose_step\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m25\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\gentrl-0.1-py3.8.egg\\gentrl\\gentrl.py\u001b[0m in \u001b[0;36mtrain_as_rl\u001b[1;34m(self, reward_fn, num_iterations, verbose_step, batch_size, cond_lb, cond_rb, lr_lp, lr_dec)\u001b[0m\n\u001b[0;32m    236\u001b[0m             \u001b[0moptimizer_lp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    237\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 238\u001b[1;33m             \u001b[0mvalid_sm\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0ms\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0msmiles\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mget_mol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    239\u001b[0m             cur_stats = {'mean_reward': sum(r_list) / len(smiles),\n\u001b[0;32m    240\u001b[0m                          'valid_perc': len(valid_sm) / len(smiles)}\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\gentrl-0.1-py3.8.egg\\gentrl\\gentrl.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m    236\u001b[0m             \u001b[0moptimizer_lp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    237\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 238\u001b[1;33m             \u001b[0mvalid_sm\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0ms\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0msmiles\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mget_mol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    239\u001b[0m             cur_stats = {'mean_reward': sum(r_list) / len(smiles),\n\u001b[0;32m    240\u001b[0m                          'valid_perc': len(valid_sm) / len(smiles)}\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\molsets-0.1.3-py3.8.egg\\moses\\utils.py\u001b[0m in \u001b[0;36mget_mol\u001b[1;34m(smiles_or_mol)\u001b[0m\n\u001b[0;32m    224\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    225\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 226\u001b[1;33m             \u001b[0mChem\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSanitizeMol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmol\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    227\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    228\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "model.train_as_rl(penalized_logP,verbose_step=25)"
   ]
  }
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