awarebayes/RecNN

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TD3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Note on this tutorials:**\n",
    "**They mostly contain low level implementations explaining what is going on inside the library.**\n",
    "\n",
    "**Most of the stuff explained here is already available out of the box for your usage.**\n",
    "\n",
    "If you do not care about the detailed implementation with code, go to the [Library Basics]/algorithms how to/td3, there is a 20 liner version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from tqdm.auto import tqdm\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from torch.utils.tensorboard import SummaryWriter\n",
    "import torch.nn.functional as F\n",
    "import torch_optimizer as optim\n",
    "\n",
    "\n",
    "from IPython.display import clear_output\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# comment out if you are not using themes\n",
    "from jupyterthemes import jtplot\n",
    "jtplot.style(theme='grade3')\n",
    "\n",
    "# == recnn ==\n",
    "import sys\n",
    "sys.path.append(\"../../\")\n",
    "import recnn\n",
    "\n",
    "cuda = torch.device('cuda')\n",
    "\n",
    "# ---\n",
    "frame_size = 10\n",
    "batch_size = 25\n",
    "n_epochs   = 100\n",
    "plot_every = 30\n",
    "step       = 0\n",
    "# --- \n",
    "\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "# embeddgings: https://drive.google.com/open?id=1EQ_zXBR3DKpmJR3jBgLvt-xoOvArGMsL\n",
    "dirs = recnn.data.env.DataPath(\n",
    "    base=\"../../data/\",\n",
    "    embeddings=\"embeddings/ml20_pca128.pkl\",\n",
    "    ratings=\"ml-20m/ratings.csv\",\n",
    "    cache=\"cache/frame_env.pkl\", # cache will generate after you run\n",
    "    use_cache=True\n",
    ")\n",
    "env = recnn.data.env.FrameEnv(dirs, frame_size, batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "def soft_update(net, target_net, soft_tau=1e-2):\n",
    "    for target_param, param in zip(target_net.parameters(), net.parameters()):\n",
    "            target_param.data.copy_(\n",
    "                target_param.data * (1.0 - soft_tau) + param.data * soft_tau\n",
    "            )\n",
    "            \n",
    "def run_tests():\n",
    "    test_batch = next(iter(env.test_dataloader))\n",
    "    losses = td3_update(step, test_batch, params, writer, learn=False)\n",
    "    \n",
    "    gen_actions = debug['gen_action']\n",
    "    true_actions = env.base.embeddings.detach().cpu().numpy()\n",
    "    \n",
    "    f = plotter.kde_reconstruction_error(ad, gen_actions, true_actions, cuda)\n",
    "    writer.add_figure('rec_error',f, losses['step'])\n",
    "    return losses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "def td3_update(step, batch, params, writer, learn=True):\n",
    "    \n",
    "    state, action, reward, next_state, done = recnn.data.get_base_batch(batch)\n",
    "    \n",
    "    # --------------------------------------------------------#\n",
    "    # Value Learning\n",
    "    \n",
    "    reward     = reward.unsqueeze(1)\n",
    "    done       = done.unsqueeze(1)\n",
    "    \n",
    "    next_action = target_policy_net(next_state)\n",
    "    noise = torch.normal(torch.zeros(next_action.size()),\n",
    "                         params['noise_std']).to(cuda)\n",
    "    noise = torch.clamp(noise, -params['noise_clip'], params['noise_clip'])\n",
    "    next_action += noise\n",
    "    \n",
    "    with torch.no_grad():\n",
    "        target_q_value1  = target_value_net1(next_state, next_action)\n",
    "        target_q_value2  = target_value_net2(next_state, next_action)\n",
    "        target_q_value   = torch.min(target_q_value1, target_q_value2)\n",
    "        expected_q_value = reward + (1.0 - done) * params['gamma'] * target_q_value\n",
    "    \n",
    "    q_value1 = value_net1(state, action)\n",
    "    q_value2 = value_net2(state, action)\n",
    "\n",
    "    value_loss1 = value_criterion(q_value1, expected_q_value.detach())\n",
    "    value_loss2 = value_criterion(q_value2, expected_q_value.detach())\n",
    "    \n",
    "    if learn:\n",
    "        value_optimizer1.zero_grad()\n",
    "        value_loss1.backward()\n",
    "        value_optimizer1.step()\n",
    "\n",
    "        value_optimizer2.zero_grad()\n",
    "        value_loss2.backward()\n",
    "        value_optimizer2.step()\n",
    "    else:\n",
    "        debug['next_action'] = next_action\n",
    "        writer.add_figure('next_action',\n",
    "                    recnn.utils.pairwise_distances_fig(next_action[:50]), step)\n",
    "        writer.add_histogram('value1', q_value1, step)\n",
    "        writer.add_histogram('value2', q_value2, step)\n",
    "        writer.add_histogram('target_value', target_q_value, step)\n",
    "        writer.add_histogram('expected_value', expected_q_value, step)\n",
    "\n",
    "    # --------------------------------------------------------#\n",
    "    # Policy learning\n",
    "\n",
    "    gen_action = policy_net(state)\n",
    "    policy_loss = value_net1(state, gen_action)\n",
    "    policy_loss = -policy_loss\n",
    "    \n",
    "        \n",
    "    if not learn: \n",
    "        debug['gen_action'] = gen_action\n",
    "        writer.add_figure('gen_action',\n",
    "                    recnn.utils.pairwise_distances_fig(gen_action[:50]), step)\n",
    "        writer.add_histogram('policy_loss', policy_loss, step)\n",
    "        \n",
    "    policy_loss = policy_loss.mean()\n",
    "    \n",
    "    # delayed policy update\n",
    "    if step % params['policy_update'] == 0 and learn:\n",
    "        policy_optimizer.zero_grad()\n",
    "        policy_loss.backward()\n",
    "        torch.nn.utils.clip_grad_norm_(policy_net.parameters(), -1, 1)\n",
    "        policy_optimizer.step()\n",
    "\n",
    "        soft_update(value_net1, target_value_net1, soft_tau=params['soft_tau'])\n",
    "        soft_update(value_net2, target_value_net2, soft_tau=params['soft_tau'])\n",
    "    \n",
    "    losses = {'value1': value_loss1.item(),\n",
    "              'value2': value_loss2.item(),\n",
    "              'policy': policy_loss.item(),\n",
    "              'step'  : step}\n",
    "    recnn.utils.write_losses(writer, losses, kind='train' if learn else 'test')\n",
    "    return losses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "# === TD3 settings ===\n",
    "params = {\n",
    "    'gamma': 0.99,\n",
    "    'noise_std': 0.5,\n",
    "    'noise_clip': 3,\n",
    "    'soft_tau': 0.001,\n",
    "    'policy_update': 10,\n",
    "    \n",
    "    'policy_lr': 1e-5,\n",
    "    'value_lr': 1e-5,\n",
    "    \n",
    "    'actor_weight_init': 25e-2,\n",
    "    'critic_weight_init': 6e-1,\n",
    "}\n",
    "# === end ==="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "value_net1  = recnn.nn.models.Critic(1290, 128, 256, params['critic_weight_init']).to(cuda)\n",
    "value_net2 = recnn.nn.models.Critic(1290, 128, 256, params['critic_weight_init']).to(cuda)\n",
    "policy_net = recnn.nn.models.Actor(1290, 128, 256, params['actor_weight_init']).to(cuda)\n",
    "\n",
    "target_value_net1 = recnn.nn.models.Critic(1290, 128, 256).to(cuda)\n",
    "target_value_net2 = recnn.nn.models.Critic(1290, 128, 256).to(cuda)\n",
    "target_policy_net = recnn.nn.models.Actor(1290, 128, 256).to(cuda)\n",
    "\n",
    "soft_update(value_net1, target_value_net1, soft_tau=1.0)\n",
    "soft_update(value_net2, target_value_net2, soft_tau=1.0)\n",
    "soft_update(policy_net, target_policy_net, soft_tau=1.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "value_criterion = nn.MSELoss()\n",
    "\n",
    "value_optimizer1 = optim.Ranger(value_net1.parameters(), lr=params['value_lr'],  weight_decay=1e-2)\n",
    "value_optimizer2 = optim.Ranger(value_net2.parameters(), lr=params['value_lr'],  weight_decay=1e-2)\n",
    "policy_optimizer = optim.Ranger(policy_net.parameters(), lr=params['policy_lr'], weight_decay=1e-5)\n",
    "\n",
    "ad = recnn.nn.models.AnomalyDetector().to(cuda)\n",
    "ad.load_state_dict(torch.load('../../models/anomaly.pt'))\n",
    "ad.eval()\n",
    "\n",
    "\n",
    "loss = {\n",
    "    'train': {'value1': [], 'value2': [], 'policy': [], 'step': []},\n",
    "    'test': {'value1': [], 'value2': [], 'policy': [], 'step': []}\n",
    "    }\n",
    "debug = {}\n",
    "\n",
    "writer = SummaryWriter(log_dir='../../runs')\n",
    "plotter = recnn.utils.Plotter(loss, [['value1', 'policy']],)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "pycharm": {
     "is_executing": true
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    "tags": []
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   "outputs": [
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     "text": "step 5130\n"
    },
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252.225273 \nL 208.811332 251.878486 \nL 209.245362 249.257955 \nL 209.3177 249.311743 \nL 209.462377 250.334086 \nL 210.041084 256.451546 \nL 210.185761 255.671085 \nL 210.547452 252.929281 \nL 210.619791 253.144231 \nL 210.981482 256.607403 \nL 211.053821 256.402392 \nL 211.198498 254.004984 \nL 211.632528 244.263849 \nL 211.704866 244.596108 \nL 212.211235 250.771302 \nL 212.355911 249.55594 \nL 212.86228 241.195012 \nL 212.934618 241.519547 \nL 213.151633 246.04035 \nL 213.513325 254.510362 \nL 213.73034 256.108562 \nL 213.875017 256.335926 \nL 214.019693 255.935554 \nL 214.309047 253.37144 \nL 214.526062 252.257309 \nL 214.670739 252.887825 \nL 215.177107 257.009889 \nL 215.321784 256.151173 \nL 216.045167 248.692499 \nL 216.117506 248.813248 \nL 216.262183 249.884654 \nL 216.768551 255.815967 \nL 216.913228 254.717803 \nL 217.27492 251.013419 \nL 217.347258 251.162735 \nL 217.564273 253.344371 \nL 217.925965 256.905727 \nL 218.14298 257.6667 \nL 218.287657 257.64853 \nL 218.432333 256.840676 \nL 218.649348 253.540432 \nL 218.938702 248.852788 \nL 219.01104 248.683553 \nL 219.155717 250.000537 \nL 219.662085 258.614104 \nL 219.734424 258.437858 \nL 219.951439 255.442326 \nL 220.240792 251.670502 \nL 220.313131 251.524004 \nL 220.457807 251.866193 \nL 220.891837 253.041574 \nL 221.036514 253.16188 \nL 221.181191 252.317647 \nL 221.615221 246.601217 \nL 221.687559 246.662279 \nL 222.410943 251.157805 \nL 222.917311 259.903861 \nL 222.98965 259.843557 \nL 223.134326 258.670907 \nL 223.640695 252.902907 \nL 223.713033 253.021116 \nL 223.930048 254.942547 \nL 224.219402 256.992202 \nL 224.29174 256.811565 \nL 224.508755 254.608431 \nL 224.72577 252.291101 \nL 224.798109 252.23909 \nL 224.942785 253.731593 \nL 225.376816 260.634982 \nL 225.449154 260.476081 \nL 225.666169 258.311168 \nL 226.027861 255.250821 \nL 226.100199 255.130894 \nL 226.172537 255.222859 \nL 226.389553 256.575495 \nL 226.534229 257.331296 \nL 226.606568 257.186634 \nL 226.751244 255.395487 \nL 227.112936 248.638703 \nL 227.185274 248.62909 \nL 227.329951 250.386999 \nL 227.83632 258.375604 \nL 228.053335 259.379332 \nL 228.125673 259.431602 \nL 228.27035 259.069554 \nL 228.559703 258.03538 \nL 228.849057 257.875102 \nL 229.066072 256.502999 \nL 229.355425 255.114184 \nL 229.500102 255.567979 \nL 229.934132 258.16505 \nL 230.078809 257.530958 \nL 230.368162 255.866634 \nL 230.512839 257.011999 \nL 230.946869 262.423937 \nL 231.091546 262.585599 \nL 231.308561 262.141956 \nL 231.887268 260.548733 \nL 232.031944 260.494937 \nL 232.176621 260.001152 \nL 232.393636 257.446781 \nL 232.827666 248.015216 \nL 233.11702 241.641272 \nL 233.189358 241.494567 \nL 233.334035 244.586371 \nL 234.057418 271.659873 \nL 234.129757 271.779845 \nL 234.274433 271.060648 \nL 234.563787 267.27054 \nL 234.925479 263.207812 \nL 235.214832 261.230246 \nL 235.721201 255.365112 \nL 235.865877 255.585039 \nL 235.938216 255.702136 \nL 236.010554 255.646855 \nL 236.299907 254.442511 \nL 236.372246 254.657058 \nL 236.516922 256.444374 \nL 236.950953 263.603174 \nL 237.095629 263.992244 \nL 237.240306 263.818219 \nL 237.529659 263.47031 \nL 237.746675 263.563503 \nL 237.891351 263.74641 \nL 238.036028 264.320088 \nL 238.253043 266.557419 \nL 238.542396 269.755861 \nL 238.614735 269.81032 \nL 238.759412 268.669463 \nL 239.26578 262.273973 \nL 239.410457 261.895875 \nL 239.482795 261.93101 \nL 239.627472 262.542655 \nL 239.989164 265.167441 \nL 240.061502 264.968327 \nL 240.278517 262.530322 \nL 240.56787 260.033849 \nL 240.640209 260.088858 \nL 241.001901 261.811557 \nL 241.074239 261.787231 \nL 241.218916 260.94734 \nL 241.797623 254.328542 \nL 241.869961 254.648849 \nL 242.086976 258.504126 \nL 242.448668 265.340385 \nL 242.593344 265.896506 \nL 242.738021 265.747529 \nL 242.955036 265.543737 \nL 243.099713 265.763553 \nL 243.316728 266.842137 \nL 243.750758 270.432825 \nL 243.823096 270.247265 \nL 243.967773 268.578762 \nL 244.763495 254.40919 \nL 244.835833 254.416351 \nL 245.125187 255.194465 \nL 245.197525 254.88761 \nL 245.342202 252.798286 \nL 245.631555 247.209896 \nL 245.703894 247.434302 \nL 245.84857 250.784454 \nL 246.210262 260.581823 \nL 246.282601 260.736126 \nL 246.499616 259.809819 \nL 246.571954 259.918366 \nL 246.716631 261.541608 \nL 247.222999 270.314332 \nL 247.295338 270.344318 \nL 247.440014 269.430155 \nL 248.52509 258.516321 \nL 248.669766 258.512344 \nL 248.742105 258.512031 \nL 248.886781 257.745784 \nL 249.248473 252.750871 \nL 249.320812 252.951439 \nL 249.465488 255.88186 \nL 249.971857 271.347835 \nL 250.116534 272.118211 \nL 250.188872 272.042803 \nL 250.622902 270.949132 \nL 250.767579 270.942832 \nL 250.912255 270.423702 \nL 251.490962 266.693904 \nL 251.924992 266.07605 \nL 252.142008 264.294978 \nL 252.431361 261.660809 \nL 252.503699 261.51182 \nL 252.576038 261.625128 \nL 252.793053 263.141051 \nL 253.082406 265.12748 \nL 253.154745 265.0695 \nL 253.299421 264.097105 \nL 253.588775 261.619561 \nL 253.661113 261.654895 \nL 253.80579 262.808662 \nL 254.23982 270.075352 \nL 254.529173 273.353124 \nL 254.601512 273.30452 \nL 254.746188 272.163308 \nL 255.54191 262.428499 \nL 255.686587 263.239747 \nL 256.337632 269.893992 \nL 256.482309 270.118148 \nL 256.626986 269.343854 \nL 256.988677 266.40833 \nL 257.278031 265.711056 \nL 257.567384 262.724856 \nL 257.784399 261.301936 \nL 257.856738 261.501285 \nL 258.001414 263.161007 \nL 258.580121 272.997506 \nL 259.08649 273.855184 \nL 259.158828 273.704082 \nL 259.303505 272.290368 \nL 259.737535 265.536198 \nL 259.809873 265.934838 \nL 260.026888 270.169573 \nL 260.243904 273.74139 \nL 260.316242 273.843492 \nL 260.460919 272.588936 \nL 260.750272 270.128263 \nL 260.894949 271.341728 \nL 261.401317 278.494578 \nL 261.473656 278.435316 \nL 261.618332 277.426602 \nL 262.341716 270.527236 \nL 262.486393 270.160013 \nL 262.558731 270.291949 \nL 262.703408 271.376212 \nL 263.065099 275.201163 \nL 263.137438 275.047232 \nL 263.282114 273.40252 \nL 263.716145 266.814294 \nL 263.788483 266.811658 \nL 263.93316 267.990733 \nL 264.511867 274.928823 \nL 264.656543 274.175655 \nL 265.090573 269.870441 \nL 265.162912 269.932512 \nL 265.307588 270.990497 \nL 265.741619 277.796178 \nL 266.030972 280.350656 \nL 266.10331 280.406641 \nL 266.247987 280.074957 \nL 266.537341 278.488299 \nL 267.043709 274.665889 \nL 267.116047 274.707333 \nL 267.260724 275.566789 \nL 267.767093 279.870509 \nL 268.201123 281.151516 \nL 268.345799 280.401523 \nL 268.562815 276.837611 \nL 268.924506 270.701993 \nL 268.996845 270.556158 \nL 269.141521 271.223172 \nL 269.430875 272.564789 \nL 269.575552 272.662627 \nL 269.720228 273.412144 \nL 269.937243 276.700157 \nL 270.298935 281.48857 \nL 270.443612 281.679973 \nL 270.588289 281.327425 \nL 270.877642 279.738232 \nL 271.456349 275.967085 \nL 271.528687 275.860896 \nL 271.601026 275.911011 \nL 271.818041 276.82147 \nL 272.107394 277.861108 \nL 272.252071 277.5395 \nL 272.541424 276.502266 \nL 272.613763 276.523551 \nL 272.758439 277.045926 \nL 273.047793 278.387059 \nL 273.120131 278.415074 \nL 273.409484 277.970808 \nL 273.481823 278.065512 \nL 273.698838 279.020225 \nL 273.988191 280.057606 \nL 274.132868 280.045202 \nL 274.711575 279.305305 \nL 275.000928 277.998924 \nL 275.434958 276.172154 \nL 275.579635 277.078621 \nL 275.868989 282.386221 \nL 276.086004 285.231758 \nL 276.158342 285.365208 \nL 276.303019 284.663632 \nL 276.664711 282.429188 \nL 276.881726 281.50493 \nL 277.315756 278.10671 \nL 277.460432 279.56295 \nL 278.039139 288.640126 \nL 278.400831 289.724491 \nL 278.473169 289.777707 \nL 278.545508 289.673787 \nL 278.690184 288.795758 \nL 278.9072 285.374439 \nL 279.34123 276.634871 \nL 279.413568 276.429437 \nL 279.558245 277.387612 \nL 279.847598 279.66313 \nL 279.992275 278.260022 \nL 280.498643 267.118498 \nL 280.570982 267.247488 \nL 280.715658 269.488357 \nL 281.149689 277.562928 \nL 281.222027 277.539378 \nL 281.366704 276.05295 \nL 281.800734 268.255754 \nL 281.873072 268.796703 \nL 282.017749 272.804106 \nL 282.451779 288.254069 \nL 282.524117 288.696156 \nL 282.596456 288.594944 \nL 282.958148 286.834914 \nL 283.102824 287.452566 \nL 283.392178 289.329284 \nL 283.464516 289.245511 \nL 283.609193 287.936068 \nL 284.043223 282.982763 \nL 284.260238 282.955004 \nL 284.404915 282.15287 \nL 285.05596 275.502518 \nL 285.200637 276.370116 \nL 285.779343 283.143702 \nL 285.92402 282.737809 \nL 286.719742 279.053046 \nL 286.864419 279.031979 \nL 287.153772 279.289766 \nL 287.443126 279.140106 \nL 287.587802 279.652302 \nL 288.021833 283.013534 \nL 288.094171 282.964591 \nL 288.528201 281.297845 \nL 288.600539 281.33051 \nL 288.817554 281.900094 \nL 289.106908 282.596632 \nL 289.251585 282.125618 \nL 289.613276 280.57697 \nL 289.757953 281.191425 \nL 290.119645 283.207768 \nL 290.264322 282.437267 \nL 290.481337 278.974892 \nL 290.915367 271.553059 \nL 290.987705 271.680272 \nL 291.132382 273.413546 \nL 292.072781 290.515204 \nL 292.217457 290.918141 \nL 292.289796 290.893071 \nL 292.506811 290.159598 \nL 292.723826 289.437556 \nL 292.868502 289.469327 \nL 293.013179 289.536902 \nL 293.157856 288.825179 \nL 293.374871 285.127533 \nL 293.808901 276.94095 \nL 293.881239 277.306543 \nL 294.098254 281.945565 \nL 294.459946 291.039735 \nL 294.532285 291.474344 \nL 294.604623 291.337159 \nL 295.038653 287.984103 \nL 295.18333 288.830241 \nL 295.979052 295.3835 \nL 296.05139 295.371632 \nL 296.196067 294.648268 \nL 296.413082 291.573086 \nL 296.847112 284.423239 \nL 296.91945 284.204175 \nL 296.991789 284.236904 \nL 297.136465 284.356833 \nL 297.281142 283.1916 \nL 297.570496 275.570739 \nL 297.787511 272.373451 \nL 297.932187 274.565548 \nL 298.510894 289.48263 \nL 298.800248 291.14131 \nL 298.872586 291.321284 \nL 298.944924 291.270995 \nL 299.089601 290.003044 \nL 299.306616 284.562746 \nL 299.59597 278.070886 \nL 299.668308 278.492599 \nL 299.812985 282.330595 \nL 300.247015 296.372723 \nL 300.319353 296.582072 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291.067539 \nL 309.72334 291.748215 \nL 310.302046 297.571737 \nL 310.374385 297.464605 \nL 310.5914 295.712651 \nL 310.880753 293.50175 \nL 310.953092 293.56575 \nL 311.097768 294.465551 \nL 311.45946 297.354194 \nL 311.531798 297.446649 \nL 311.676475 296.973733 \nL 312.182844 294.283513 \nL 312.399859 293.564579 \nL 312.689212 292.339958 \nL 312.761551 292.447215 \nL 312.978566 293.828358 \nL 313.340257 297.738692 \nL 313.774288 303.34971 \nL 313.918964 302.104236 \nL 314.642348 291.490814 \nL 315.00404 289.90116 \nL 315.148716 290.627365 \nL 315.582746 295.309923 \nL 315.655085 295.186175 \nL 315.8721 292.898124 \nL 316.089115 290.81174 \nL 316.161453 290.83766 \nL 316.30613 292.199748 \nL 316.74016 298.390394 \nL 316.812499 298.221996 \nL 316.957175 296.473843 \nL 317.391205 290.395879 \nL 317.463544 290.462073 \nL 317.60822 291.572334 \nL 318.114589 298.648025 \nL 318.186927 298.6301 \nL 318.331604 297.364984 \nL 318.693296 293.885624 \nL 318.837973 293.925639 \nL 319.054988 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207.942977 \nL 592.78333 207.092143 \nL 592.928007 207.160661 \nL 593.579052 208.37147 \nL 593.940744 209.408414 \nL 594.08542 209.379795 \nL 594.881142 208.429626 \nL 595.098157 208.605622 \nL 595.676864 209.502042 \nL 596.110894 212.143075 \nL 596.183233 212.092453 \nL 596.327909 211.366202 \nL 596.906616 207.686424 \nL 597.051293 207.708934 \nL 597.340646 208.270105 \nL 597.412985 208.221588 \nL 597.63 207.416906 \nL 597.847015 206.703002 \nL 597.919353 206.755986 \nL 598.06403 207.403112 \nL 598.49806 209.860715 \nL 598.642737 209.545424 \nL 599.149105 207.7942 \nL 599.583135 207.03806 \nL 599.727812 207.278644 \nL 600.089504 208.167466 \nL 600.234181 207.859584 \nL 600.740549 206.166351 \nL 600.885226 206.476962 \nL 601.246918 207.640038 \nL 601.391594 207.565669 \nL 601.680948 207.259914 \nL 601.897963 207.765881 \nL 602.04264 208.028744 \nL 602.114978 207.961951 \nL 602.331993 207.024829 \nL 602.549008 206.356481 \nL 602.693685 206.519313 \nL 602.983038 206.948664 \nL 603.127715 207.097427 \nL 603.272392 207.606192 \nL 603.706422 209.985449 \nL 603.77876 209.959031 \nL 603.923437 209.441119 \nL 604.357467 207.513522 \nL 604.502144 207.490492 \nL 604.719159 207.958237 \nL 605.008512 208.470795 \nL 605.153189 208.264615 \nL 605.514881 207.537834 \nL 605.659557 207.767693 \nL 606.672294 210.434854 \nL 606.816971 210.273715 \nL 607.32334 209.136144 \nL 607.75737 209.523128 \nL 607.974385 209.093105 \nL 609.421152 205.325866 \nL 609.638167 205.305544 \nL 609.999859 205.500133 \nL 610.144535 205.820864 \nL 610.361551 206.936885 \nL 611.012596 211.030125 \nL 611.229611 211.048096 \nL 611.446626 211.095743 \nL 612.097671 211.799307 \nL 612.314686 211.722424 \nL 612.459363 211.867479 \nL 612.676378 212.508803 \nL 613.182746 214.284805 \nL 613.327423 214.054202 \nL 614.123145 211.633597 \nL 614.412499 211.544252 \nL 614.629514 210.84706 \nL 614.918867 210.061631 \nL 615.063544 210.406388 \nL 615.497574 211.942899 \nL 615.642251 211.73645 \nL 616.148619 210.08936 \nL 616.437973 209.143446 \nL 616.510311 209.175443 \nL 616.654988 209.703206 \nL 617.161356 212.375581 \nL 617.45071 212.573731 \nL 617.740063 212.618954 \nL 618.246431 212.348343 \nL 618.463447 213.255558 \nL 619.042153 216.659746 \nL 619.18683 216.614431 \nL 619.403845 215.767909 \nL 619.693199 214.646548 \nL 619.765537 214.650596 \nL 619.910214 215.104449 \nL 620.344244 217.124168 \nL 620.416582 217.118622 \nL 620.633597 216.569043 \nL 620.922951 215.987907 \nL 621.067627 216.205053 \nL 621.501658 217.312993 \nL 621.791011 217.388901 \nL 622.008026 218.126111 \nL 622.369718 219.561607 \nL 622.586733 219.671162 \nL 622.803748 219.454473 \nL 623.744147 218.071311 \nL 624.105838 218.455201 \nL 624.539868 218.132294 \nL 624.829222 218.710833 \nL 625.118575 219.019678 \nL 625.33559 219.201766 \nL 625.841959 220.054151 \nL 626.203651 219.854165 \nL 626.420666 220.588158 \nL 626.710019 221.590139 \nL 626.782358 221.591473 \nL 626.927034 221.285308 \nL 627.288726 220.42749 \nL 627.433403 220.675963 \nL 627.795095 221.510095 \nL 628.373801 221.472456 \nL 628.590816 220.591639 \nL 628.88017 219.285813 \nL 628.952508 219.289275 \nL 629.097185 219.816727 \nL 629.74823 223.320595 \nL 629.892907 223.193243 \nL 630.109922 222.222533 \nL 630.471614 220.323226 \nL 630.543952 220.310903 \nL 630.688629 220.743995 \nL 631.194997 222.971989 \nL 631.412012 223.236695 \nL 631.556689 223.181758 \nL 631.773704 222.561368 \nL 632.063058 221.897922 \nL 632.352411 222.054166 \nL 632.569426 221.544059 \nL 632.714103 221.277836 \nL 632.85878 221.460254 \nL 633.220471 222.302631 \nL 633.365148 221.841708 \nL 634.088532 218.140196 \nL 634.233208 218.289286 \nL 634.739577 219.367143 \nL 634.956592 219.1426 \nL 635.173607 218.890961 \nL 635.318284 218.955449 \nL 635.607637 219.197528 \nL 635.969329 218.994565 \nL 636.186344 219.486796 \nL 636.692712 220.887848 \nL 637.126743 221.616914 \nL 637.271419 221.61389 \nL 637.488434 221.213617 \nL 637.777788 220.76857 \nL 638.067141 220.640741 \nL 638.57351 219.883672 \nL 638.935202 220.159676 \nL 639.152217 220.534922 \nL 639.513908 221.941225 \nL 639.8756 223.152325 \nL 640.092615 223.253364 \nL 640.237292 223.298 \nL 640.454307 223.734422 \nL 640.74366 224.278666 \nL 641.105352 224.214782 \nL 641.322367 224.831499 \nL 641.901074 226.788181 \nL 642.045751 226.848035 \nL 642.262766 226.345784 \nL 642.479781 225.975068 \nL 642.624458 226.078005 \nL 643.42018 227.138733 \nL 643.709533 227.259106 \nL 643.926548 227.728587 \nL 644.215902 228.401111 \nL 644.360578 228.38684 \nL 644.577593 227.937752 \nL 644.939285 226.546209 \nL 645.300977 225.009562 \nL 645.445654 224.965148 \nL 645.662669 225.574763 \nL 646.02436 226.526601 \nL 646.241376 226.438639 \nL 646.458391 226.388997 \nL 646.964759 226.686928 \nL 647.615804 226.13543 \nL 647.977496 225.12108 \nL 648.773218 222.592564 \nL 648.990233 222.158535 \nL 649.062571 222.209087 \nL 649.207248 222.752462 \nL 649.713617 225.421953 \nL 649.858293 224.918373 \nL 650.437 221.797365 \nL 650.798692 221.231944 \nL 651.088045 219.967198 \nL 651.377399 218.757117 \nL 651.449737 218.739105 \nL 651.594414 219.222003 \nL 651.883767 221.711572 \nL 652.245459 224.359162 \nL 652.390136 224.609266 \nL 652.534813 224.346468 \nL 653.113519 222.261344 \nL 653.330535 222.677742 \nL 653.54755 222.887919 \nL 653.764565 222.418534 \nL 653.98158 222.030719 \nL 654.126256 222.281541 \nL 654.704963 224.262918 \nL 655.138993 224.845392 \nL 655.428347 225.188909 \nL 655.7177 225.153105 \nL 655.934715 225.267859 \nL 656.368746 226.105525 \nL 656.585761 226.93184 \nL 657.019791 228.854145 \nL 657.164467 228.790011 \nL 657.381482 228.138131 \nL 657.815513 226.029925 \nL 658.249543 223.917737 \nL 658.321881 223.929091 \nL 658.466558 224.409204 \nL 659.045265 227.247864 \nL 659.189941 227.190739 \nL 659.768648 226.245056 \nL 659.913325 226.394298 \nL 660.13034 227.162488 \nL 660.709047 229.824427 \nL 660.926062 229.813937 \nL 661.070739 229.588731 \nL 661.287754 228.692934 \nL 661.794122 226.230946 \nL 662.372829 225.350027 \nL 662.517506 225.778381 \nL 663.096213 228.575152 \nL 663.240889 228.248276 \nL 663.747258 226.32172 \nL 663.891935 226.671837 \nL 664.10895 228.363748 \nL 664.759995 234.308143 \nL 664.832333 234.285741 \nL 665.266363 233.37012 \nL 665.338702 233.453572 \nL 665.772732 234.280007 \nL 666.2791 234.042674 \nL 666.713131 235.063561 \nL 666.785469 235.000648 \nL 667.002484 234.183785 \nL 667.436514 232.177343 \nL 667.581191 232.152614 \nL 667.870544 232.797662 \nL 668.304574 233.547665 \nL 668.521589 233.576813 \nL 668.738605 233.515905 \nL 668.883281 233.723488 \nL 669.534326 235.440512 \nL 670.040695 235.642338 \nL 670.25771 235.126127 \nL 670.619402 234.393518 \nL 670.908755 234.116899 \nL 671.198109 233.195978 \nL 671.415124 232.590503 \nL 671.487462 232.576908 \nL 671.632139 232.924837 \nL 671.993831 235.179443 \nL 672.283184 236.258055 \nL 672.427861 236.051581 \nL 672.934229 234.779204 \nL 673.223583 234.298563 \nL 673.585274 233.759435 \nL 674.091643 233.619289 \nL 674.23632 233.885344 \nL 674.598011 235.575812 \nL 674.887365 236.375003 \nL 675.249057 236.673499 \nL 675.900102 238.076776 \nL 676.768162 237.759839 \nL 677.202192 238.088134 \nL 677.636222 237.497845 \nL 677.780899 237.962734 \nL 678.431944 241.090616 \nL 678.576621 240.937845 \nL 679.08299 239.334418 \nL 679.155328 239.407676 \nL 679.372343 240.156883 \nL 679.661696 241.172086 \nL 679.734035 241.205209 \nL 679.878711 240.911135 \nL 680.602095 238.144257 \nL 680.746772 238.167653 \nL 680.963787 238.70787 \nL 681.25314 239.502519 \nL 681.397817 239.485043 \nL 681.759509 238.926505 \nL 681.831847 238.977602 \nL 682.048862 239.562437 \nL 682.555231 241.055726 \nL 683.061599 242.004627 \nL 683.350953 242.451681 \nL 683.640306 242.980936 \nL 684.146675 243.270349 \nL 684.291351 243.432326 \nL 684.436028 243.211771 \nL 684.653043 241.918595 \nL 685.014735 239.865634 \nL 685.087073 239.863809 \nL 685.23175 240.243868 \nL 685.593442 241.286389 \nL 685.738118 241.101908 \nL 686.606179 239.062065 \nL 686.895532 238.954663 \nL 687.112547 239.078419 \nL 687.401901 239.775921 \nL 687.618916 240.082319 \nL 687.763592 239.839511 \nL 688.052946 238.336303 \nL 688.342299 237.037157 \nL 688.486976 236.937069 \nL 688.848668 237.043486 \nL 689.065683 236.998701 \nL 689.21036 237.335876 \nL 689.789066 240.045179 \nL 689.861405 239.972593 \nL 690.07842 239.194941 \nL 690.367773 238.176305 \nL 690.51245 238.228144 \nL 691.018818 239.595441 \nL 691.091157 239.535303 \nL 691.597525 238.782677 \nL 691.886879 238.939661 \nL 692.320909 239.448896 \nL 692.682601 239.774378 \nL 693.044292 239.845581 \nL 693.188969 239.682557 \nL 693.767676 238.432961 \nL 693.840014 238.487702 \nL 694.129368 239.075623 \nL 694.852751 240.663479 \nL 695.142105 241.355042 \nL 695.79315 243.342736 \nL 696.154842 243.218791 \nL 696.299518 243.559818 \nL 696.878225 245.528461 \nL 697.167579 245.471518 \nL 697.384594 245.223014 \nL 697.673947 244.182026 \nL 697.890962 243.510351 \nL 698.035639 243.575355 \nL 699.265391 246.505274 \nL 699.410068 246.421366 \nL 699.699421 245.68844 \nL 700.061113 244.73577 \nL 700.20579 244.758972 \nL 700.784497 245.517213 \nL 702.014249 244.940927 \nL 702.303602 245.072911 \nL 702.448279 244.81355 \nL 703.244001 242.586805 \nL 703.388677 243.015708 \nL 703.967384 245.647389 \nL 704.473753 245.738782 \nL 704.61843 245.270482 \nL 705.197136 242.258806 \nL 705.341813 242.665176 \nL 705.703505 245.530046 \nL 705.92052 246.48216 \nL 705.992858 246.418137 \nL 706.209873 245.375113 \nL 706.426888 244.593994 \nL 706.499227 244.69452 \nL 706.716242 246.02434 \nL 707.077934 248.330575 \nL 707.367287 248.781921 \nL 707.584302 249.136984 \nL 708.163009 250.780255 \nL 708.307686 250.443041 \nL 708.886393 248.505671 \nL 709.031069 248.574642 \nL 709.248084 249.1358 \nL 709.682114 250.32342 \nL 709.89913 250.384791 \nL 710.188483 250.007854 \nL 710.694851 249.259668 \nL 710.911867 249.325037 \nL 711.273558 249.445862 \nL 711.490573 249.334596 \nL 711.779927 248.793848 \nL 712.141619 248.154289 \nL 712.358634 247.869203 \nL 712.575649 247.1765 \nL 712.937341 245.860681 \nL 713.082017 245.824786 \nL 713.299032 246.288081 \nL 713.588386 246.822334 \nL 713.733062 246.699074 \nL 713.950078 245.897934 \nL 714.456446 243.529947 \nL 714.601123 243.818691 \nL 715.107491 245.505311 \nL 715.252168 245.464651 \nL 715.541521 245.321699 \nL 715.686198 245.551373 \nL 716.554258 247.682455 \nL 716.698935 247.720482 \nL 716.843612 247.548877 \nL 717.132965 246.747252 \nL 717.78401 244.601019 \nL 717.928687 244.713459 \nL 718.145702 245.451751 \nL 718.579732 246.967311 \nL 718.941424 248.0467 \nL 719.230778 248.766926 \nL 719.375454 248.526984 \nL 720.0265 246.237311 \nL 720.171176 246.396102 \nL 721.039237 248.152388 \nL 721.617943 248.680895 \nL 721.834958 248.361235 \nL 722.124312 247.926531 \nL 722.268989 248.023183 \nL 722.486004 248.605622 \nL 722.992372 250.190875 \nL 723.137049 250.205358 \nL 723.354064 249.844627 \nL 723.715756 249.20535 \nL 724.149786 249.051136 \nL 724.800831 248.179646 \nL 725.017846 248.383365 \nL 725.162523 248.500331 \nL 725.3072 248.307186 \nL 725.813568 246.765225 \nL 726.319937 247.133202 \nL 726.536952 246.940263 \nL 726.681628 247.083101 \nL 726.970982 248.096254 \nL 727.260335 248.71276 \nL 727.405012 248.582875 \nL 727.766704 248.000975 \nL 727.91138 248.15567 \nL 728.634764 249.723339 \nL 728.851779 250.054316 \nL 729.213471 250.639624 \nL 729.358148 250.467887 \nL 729.647501 250.067052 \nL 729.792178 250.256336 \nL 730.515561 251.786091 \nL 731.02193 252.218268 \nL 731.45596 252.672447 \nL 731.672975 252.846568 \nL 731.817652 252.752676 \nL 732.107005 252.486234 \nL 732.251682 252.684624 \nL 732.613374 253.357432 \nL 732.75805 253.27788 \nL 733.481434 252.164425 \nL 733.987802 250.895746 \nL 734.132479 250.903116 \nL 734.421833 251.272766 \nL 735.000539 252.704117 \nL 735.289893 253.681371 \nL 735.651585 255.010093 \nL 735.796261 255.069849 \nL 736.230291 254.834371 \nL 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\n"
     },
     "metadata": {}
    },
    {
     "output_type": "stream",
     "name": "stderr",
     "text": "97%|█████████▋| 5110/5263 [09:25<00:16,  9.03it/s]\n"
    },
    {
     "output_type": "error",
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-19-094c77eae7d1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mepoch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_epochs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mbatch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0menv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain_dataloader\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m         \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtd3_update\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwriter\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m         \u001b[0mplotter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog_losses\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloss\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m         \u001b[0mstep\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-15-f7c7456eb575>\u001b[0m in \u001b[0;36mtd3_update\u001b[0;34m(step, batch, params, writer, learn)\u001b[0m\n\u001b[1;32m     64\u001b[0m         \u001b[0mpolicy_optimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzero_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     65\u001b[0m         \u001b[0mpolicy_loss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 66\u001b[0;31m         \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclip_grad_norm_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpolicy_net\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     67\u001b[0m         \u001b[0mpolicy_optimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     68\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/recnn/lib/python3.8/site-packages/torch/nn/utils/clip_grad.py\u001b[0m in \u001b[0;36mclip_grad_norm_\u001b[0;34m(parameters, max_norm, norm_type)\u001b[0m\n\u001b[1;32m     33\u001b[0m         \u001b[0mtotal_norm\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrad\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdetach\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnorm_type\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnorm_type\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     34\u001b[0m     \u001b[0mclip_coef\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax_norm\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mtotal_norm\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1e-6\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 35\u001b[0;31m     \u001b[0;32mif\u001b[0m \u001b[0mclip_coef\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     36\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     37\u001b[0m             \u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrad\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdetach\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmul_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mclip_coef\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrad\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "for epoch in range(n_epochs):\n",
    "    for batch in tqdm(env.train_dataloader):\n",
    "        loss = td3_update(step, batch, params, writer)\n",
    "        plotter.log_losses(loss)\n",
    "        step += 1\n",
    "        if step % plot_every == 0:\n",
    "            clear_output(True)\n",
    "            print('step', step)\n",
    "            test_loss = run_tests()\n",
    "            plotter.log_losses(test_loss, test=True)\n",
    "            plotter.plot_loss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "torch.save(value_net1.state_dict(), \"../../models/td3_value.pt\")\n",
    "torch.save(policy_net.state_dict(), \"../../models/td3_policy.pt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "gen_actions = debug['gen_action']\n",
    "true_actions = env.base.embeddings.numpy()\n",
    "\n",
    "ad = recnn.nn.AnomalyDetector().to(cuda)\n",
    "ad.load_state_dict(torch.load('../../models/anomaly.pt'))\n",
    "ad.eval()\n",
    "\n",
    "plotter.plot_kde_reconstruction_error(ad, gen_actions, true_actions, cuda)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.5 64-bit",
   "language": "python",
   "name": "python38564bitfba12b29602d49fd94d253df959599f4"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5-final"
  },
  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
    "metadata": {
     "collapsed": false
    },
    "source": []
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}