test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/hanliying/opt/anaconda3/envs/pytorch-cpu/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import glob\n",
    "import shutil\n",
    "import random\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from os.path import join\n",
    "from torch.utils.data import Dataset\n",
    "import torch\n",
    "try:\n",
    "    from . import utils2 as U\n",
    "except Exception:\n",
    "    import utils as U\n",
    "from abc import ABC\n",
    "import configparser\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['./IMU/wisdm/raw/watch/accel/data_1600_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1601_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1602_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1603_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1604_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1605_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1606_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1607_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1608_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1609_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1610_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1611_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1612_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1613_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1614_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1615_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1616_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1617_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1618_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1619_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1620_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1621_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1622_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1623_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1624_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1625_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1626_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1627_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1628_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1629_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1630_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1631_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1632_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1633_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1634_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1635_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1636_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1637_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1638_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1639_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1640_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1641_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1642_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1643_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1644_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1645_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1646_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1647_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1648_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1649_accel_watch.txt', './IMU/wisdm/raw/watch/accel/data_1650_accel_watch.txt']\n"
     ]
    }
   ],
   "source": [
    "root = \"./IMU/wisdm\"\n",
    "csv_files = glob.glob(join(root, \"raw/watch/accel/*.txt\"))\n",
    "csv_files.sort()\n",
    "print(csv_files)\n",
    "\n",
    "dfs = []\n",
    "for index, csv_file in enumerate(csv_files):\n",
    "    df = pd.read_csv(csv_file, names=['userID', 'label', 'timestamp', 'x', 'y', 'z'], header=0)\n",
    "    df['z'] = df['z'].str.replace(';','').astype(float)\n",
    "    if index < 1/5 * len(csv_files): df['fold'] = 1\n",
    "    elif index < 2/5 * len(csv_files): df['fold'] = 2\n",
    "    elif index < 3/5 * len(csv_files): df['fold'] = 3\n",
    "    elif index < 4/5 * len(csv_files): df['fold'] = 4\n",
    "    else: df['fold'] = 5\n",
    "    dfs.append(df)\n",
    "\n",
    "df = pd.concat(dfs, axis=0, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1678626, 7)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df.dropna()\n",
    "lis_s = ['A', 'B', 'D', 'E', 'F', 'G', 'J', 'K']\n",
    "# for i in range(len(lis_s)):\n",
    "#     if i == 0:\n",
    "#         tmp = df['label'] == lis_s[i]\n",
    "#     else:\n",
    "#         tmp = tmp | (df['label'] == lis_s[i])\n",
    "# df = df[tmp]\n",
    "# df = df[(df['label'] == 'A') | (df['label'] == 'B') | (df['label'] == 'D') | (df['label'] == 'E') \\\n",
    "#     | (df['label'] == 'F') | (df['label'] == 'G') | (df['label'] == 'J') | (df['label'] == 'K')]\n",
    "# ABDEFGJK\n",
    "# print(tmp)\n",
    "# print(df[tmp])\n",
    "# (3776995, 7)\n",
    "# df = df.sort_values(by = ['userID', 'timestamp'], ignore_index=True)\n",
    "df = df[df.label.isin(lis_s)]\n",
    "df.shape\n",
    "# df1 1678626"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "(3, 100)\n",
      "(3, 100)\n"
     ]
    }
   ],
   "source": [
    "accels = []\n",
    "labels = []\n",
    "folds = []\n",
    "pairs = set(zip(df.userID, df.label))\n",
    "# print(pairs)\n",
    "for pair in pairs:\n",
    "    # print(pair)\n",
    "    # masked1 = df[df['userID'] == pair[0]]\n",
    "    # masked2 = masked1[masked1['label'] == pair[1]]\n",
    "    # df_temp = masked2[0:3600] # each activity is collected for 3 min = 3x60x20 frames\n",
    "    start = 0\n",
    "    end = 3500\n",
    "    df_temp = df[(df['userID'] == pair[0]) & (df['label'] == pair[1])][start:end]\n",
    "    num_sequence = (end - start) // 100\n",
    "    \n",
    "    for i in range(num_sequence):\n",
    "        rows = df_temp.iloc[i * 100 : (i + 1) * 100]\n",
    "        accel = rows[['x','y','z']].values.T\n",
    "        print(accel.shape)\n",
    "        assert len(set(rows['fold'].values)) == 1\n",
    "        fold = set(rows['fold'].values).pop()\n",
    "        # raise len(fold) == 1\n",
    "        # print(df_temp)\n",
    "        # print(accel)              \n",
    "        accels.append(accel)\n",
    "        labels.append(pair[1])\n",
    "        folds.append(fold)\n",
    "    \n",
    "    # print(df_temp)\n",
    "# accels = np.concatenate(accels, axis=0)\n",
    "# accels = accels.transpose((0,2,1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14175"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# print(accels)\n",
    "# print(labels)\n",
    "# torch.tensor(x).dtype\n",
    "# accels = [row.x,row.y,row.z]\n",
    "b = np.array(labels)\n",
    "len(accels)\n",
    "# b.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(0, 'A'), (1, 'B'), (1, 'C')}"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target = [0,1,1]\n",
    "category = ['A','B','C']\n",
    "classes = set(zip(target, category))\n",
    "# classes = sorted(classes, key=lambda x: x[0])\n",
    "# classes = [c[1] for c in classes]\n",
    "# classes = sorted(set(category))\n",
    "classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'walking': 'A',\n",
       " 'jogging': 'B',\n",
       " 'stairs': 'C',\n",
       " 'sitting': 'D',\n",
       " 'standing': 'E',\n",
       " 'typing': 'F',\n",
       " 'teeth': 'G',\n",
       " 'soup': 'H',\n",
       " 'chips': 'I',\n",
       " 'pasta': 'J',\n",
       " 'drinking': 'K',\n",
       " 'sandwich': 'L',\n",
       " 'kicking': 'M',\n",
       " 'catch': 'O',\n",
       " 'dribbling': 'P',\n",
       " 'writing': 'Q',\n",
       " 'clapping': 'R',\n",
       " 'folding': 'S'}"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_key = pd.read_csv(\"./IMU/wisdm/activity_key.txt\", sep=' = ',names=['activity', 'label'], engine='python')\n",
    "dict(df_key.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ESC50 meta/esc50.csv\n",
      "KITCHEN20 kitchen20.csv\n"
     ]
    }
   ],
   "source": [
    "csv_file=['meta/esc50.csv','kitchen20.csv']\n",
    "root=['ESC50','KITCHEN20']\n",
    "for r, f in zip(root, csv_file):\n",
    "    print(r,f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(1, dtype=torch.int32)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.tensor(1).int()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from multimodal import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./Audio/ESC50/meta/esc50.csv\n",
      "./Audio/kitchen20/kitchen20.csv\n",
      "loading  fold1\n",
      "loading  fold2\n",
      "loading  fold3\n",
      "loading  fold4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/hanliying/Documents/UCLA/Research/master-thesis-project/dataset/esc.py:74: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  self.df = self.df[0].append(self.df[1:])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading  fold1\n",
      "loading  fold2\n",
      "loading  fold3\n",
      "loading  fold4\n",
      "Loading...\n",
      "{'brush_teeth': 0, 'click_mouse': 1, 'drink': 2, 'eat': 3, 'flush_toilet': 4, 'sit': 5, 'type': 6, 'walk': 7, 'wash': 8}\n"
     ]
    }
   ],
   "source": [
    "from torch.utils.data import DataLoader\n",
    "from torch import nn\n",
    "from torch import optim\n",
    "\n",
    "time_window = 5\n",
    "audio_rate = 16000\n",
    "audio_input_length = int(audio_rate * time_window)\n",
    "\n",
    "audio_set = ESC70Select(\n",
    "    # root='./Audio/kitchen20/',\n",
    "    root=['./Audio/ESC50', './Audio/kitchen20'],\n",
    "    folds=[1, 2, 3, 4],\n",
    "    transforms=lambda x : nn.functional.pad(x, ((audio_input_length - x.shape[1]) // 2, (audio_input_length - x.shape[1]) // 2)) if (x.shape[1] % 2) == 0 \\\n",
    "        else nn.functional.pad(x, ((audio_input_length - x.shape[1]) // 2, (audio_input_length - x.shape[1]) // 2 + 1)),  \n",
    "    overwrite=False,\n",
    "    use_bc_learning=False,\n",
    "    audio_rate=audio_rate)\n",
    "\n",
    "imu_set = WISDMSelect(\n",
    "    folds=[1, 2, 3, 4],\n",
    "    time_window=time_window,\n",
    "    overwrite=False)\n",
    "\n",
    "multimodal_set = MultimodalDataset(audio_set, imu_set, time_window=time_window)\n",
    "print(multimodal_set.get_label_mapping())\n",
    "data_loader = DataLoader(multimodal_set, batch_size=2, \n",
    "                            shuffle=True, num_workers=4)\n",
    "\n",
    "num_window = 17280 # corresponding to 6 hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "class AudioAE(nn.Module):\n",
    "    \"\"\"Autoencoder for Audio embeddings\"\"\"\n",
    "\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.encoder = nn.Sequential(\n",
    "            nn.Conv1d(1, 16, 9, stride=2, padding=2), nn.ReLU(), nn.BatchNorm1d(16),\n",
    "            nn.Conv1d(16, 32, 9, stride=2, padding=2), nn.ReLU(), nn.BatchNorm1d(32),\n",
    "            nn.Conv1d(32, 64, 9), nn.ReLU(), nn.BatchNorm1d(64)\n",
    "            )\n",
    "        self.decoder = nn.Sequential(\n",
    "            nn.ConvTranspose1d(64, 32, 9), nn.ReLU(), nn.BatchNorm1d(32),\n",
    "            nn.ConvTranspose1d(32, 16, 9, stride=2, padding=2, output_padding=1), nn.ReLU(), nn.BatchNorm1d(16),\n",
    "            nn.ConvTranspose1d(16, 1, 9, stride=2, padding=2, output_padding=1), nn.ReLU(), nn.BatchNorm1d(1),\n",
    "            nn.Tanh()\n",
    "            )\n",
    " \n",
    "    def forward(self, x):\n",
    "        x = self.encoder(x)\n",
    "        x = self.decoder(x)\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:1, Loss:0.0176\n",
      "Epoch:2, Loss:0.0044\n",
      "Epoch:3, Loss:0.0024\n",
      "Epoch:4, Loss:0.0026\n",
      "Epoch:5, Loss:0.0029\n",
      "Epoch:6, Loss:0.0043\n",
      "Epoch:7, Loss:0.0038\n",
      "Epoch:8, Loss:0.0049\n",
      "Epoch:9, Loss:0.0041\n",
      "Epoch:10, Loss:0.0019\n",
      "Epoch:11, Loss:0.0015\n",
      "Epoch:12, Loss:0.0018\n",
      "Epoch:13, Loss:0.0016\n",
      "Epoch:14, Loss:0.0012\n",
      "Epoch:15, Loss:0.0024\n",
      "Epoch:16, Loss:0.0023\n",
      "Epoch:17, Loss:0.0014\n",
      "Epoch:18, Loss:0.0009\n",
      "Epoch:19, Loss:0.0040\n",
      "Epoch:20, Loss:0.0025\n",
      "Epoch:21, Loss:0.0010\n",
      "Epoch:22, Loss:0.0026\n",
      "Epoch:23, Loss:0.0038\n",
      "Epoch:24, Loss:0.0013\n",
      "Epoch:25, Loss:0.0012\n",
      "Epoch:26, Loss:0.0008\n",
      "Epoch:27, Loss:0.0018\n",
      "Epoch:28, Loss:0.0017\n",
      "Epoch:29, Loss:0.0022\n",
      "Epoch:30, Loss:0.0007\n",
      "Epoch:31, Loss:0.0023\n",
      "Epoch:32, Loss:0.0008\n",
      "Epoch:33, Loss:0.0007\n",
      "Epoch:34, Loss:0.0014\n",
      "Epoch:35, Loss:0.0013\n",
      "Epoch:36, Loss:0.0008\n",
      "Epoch:37, Loss:0.0012\n",
      "Epoch:38, Loss:0.0010\n",
      "Epoch:39, Loss:0.0007\n",
      "Epoch:40, Loss:0.0013\n",
      "Epoch:41, Loss:0.0016\n",
      "Epoch:42, Loss:0.0010\n",
      "Epoch:43, Loss:0.0006\n",
      "Epoch:44, Loss:0.0004\n",
      "Epoch:45, Loss:0.0003\n",
      "Epoch:46, Loss:0.0014\n",
      "Epoch:47, Loss:0.0005\n",
      "Epoch:48, Loss:0.0006\n",
      "Epoch:49, Loss:0.0008\n",
      "Epoch:50, Loss:0.0003\n",
      "Epoch:51, Loss:0.0005\n",
      "Epoch:52, Loss:0.0007\n",
      "Epoch:53, Loss:0.0004\n",
      "Epoch:54, Loss:0.0007\n",
      "Epoch:55, Loss:0.0006\n",
      "Epoch:56, Loss:0.0004\n",
      "Epoch:57, Loss:0.0006\n",
      "Epoch:58, Loss:0.0005\n",
      "Epoch:59, Loss:0.0005\n",
      "Epoch:60, Loss:0.0003\n",
      "Epoch:61, Loss:0.0004\n",
      "Epoch:62, Loss:0.0006\n",
      "Epoch:63, Loss:0.0002\n",
      "Epoch:64, Loss:0.0003\n",
      "Epoch:65, Loss:0.0003\n",
      "Epoch:66, Loss:0.0006\n",
      "Epoch:67, Loss:0.0002\n",
      "Epoch:68, Loss:0.0005\n",
      "Epoch:69, Loss:0.0003\n",
      "Epoch:70, Loss:0.0004\n",
      "Epoch:71, Loss:0.0004\n",
      "Epoch:72, Loss:0.0006\n",
      "Epoch:73, Loss:0.0004\n",
      "Epoch:74, Loss:0.0006\n",
      "Epoch:75, Loss:0.0003\n",
      "Epoch:76, Loss:0.0002\n",
      "Epoch:77, Loss:0.0005\n",
      "Epoch:78, Loss:0.0003\n",
      "Epoch:79, Loss:0.0004\n",
      "Epoch:80, Loss:0.0005\n",
      "Epoch:81, Loss:0.0005\n",
      "Epoch:82, Loss:0.0003\n",
      "Epoch:83, Loss:0.0003\n",
      "Epoch:84, Loss:0.0004\n",
      "Epoch:85, Loss:0.0003\n",
      "Epoch:86, Loss:0.0002\n",
      "Epoch:87, Loss:0.0002\n",
      "Epoch:88, Loss:0.0002\n",
      "Epoch:89, Loss:0.0004\n",
      "Epoch:90, Loss:0.0003\n",
      "Epoch:91, Loss:0.0005\n",
      "Epoch:92, Loss:0.0002\n",
      "Epoch:93, Loss:0.0002\n",
      "Epoch:94, Loss:0.0003\n",
      "Epoch:95, Loss:0.0002\n",
      "Epoch:96, Loss:0.0003\n",
      "Epoch:97, Loss:0.0006\n",
      "Epoch:98, Loss:0.0004\n",
      "Epoch:99, Loss:0.0002\n",
      "Epoch:100, Loss:0.0007\n"
     ]
    },
    {
     "data": {
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       "  \n",
       "          [[-0.0031, -0.0030, -0.0029,  ..., -0.0376, -0.0042, -0.0017]]]),\n",
       "  tensor([[[ 0.0184, -0.0119,  0.0101,  ...,  0.0228,  0.0229,  0.0162]],\n",
       "  \n",
       "          [[ 0.0199, -0.0115,  0.0100,  ...,  0.0221,  0.0228,  0.0157]],\n",
       "  \n",
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       "         grad_fn=<TanhBackward0>)),\n",
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       "         grad_fn=<TanhBackward0>)),\n",
       " (7,\n",
       "  tensor([[[-1.3428e-03,  1.7090e-03,  2.4719e-03,  ...,  8.5449e-04,\n",
       "            -1.8921e-03, -1.6174e-03]],\n",
       "  \n",
       "          [[-6.1035e-05, -3.0518e-05, -1.5259e-04,  ...,  3.8147e-03,\n",
       "             2.8687e-03,  2.0447e-03]],\n",
       "  \n",
       "          [[-4.4556e-03, -2.8076e-03,  9.7351e-03,  ...,  0.0000e+00,\n",
       "             3.0518e-05,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.8311e-04,  1.5259e-04,  1.5259e-04,  ..., -5.7678e-03,\n",
       "            -3.8147e-03, -2.5940e-03]],\n",
       "  \n",
       "          [[ 3.1433e-03,  3.1128e-03,  3.2654e-03,  ...,  9.7656e-04,\n",
       "             9.4604e-04,  1.1597e-03]],\n",
       "  \n",
       "          [[-9.1553e-05, -6.4087e-04, -4.2725e-04,  ...,  1.5259e-03,\n",
       "             2.6855e-03,  3.9673e-04]]]),\n",
       "  tensor([[[ 0.0192, -0.0201,  0.0087,  ...,  0.0196,  0.0246,  0.0065]],\n",
       "  \n",
       "          [[ 0.0191, -0.0203,  0.0086,  ...,  0.0199,  0.0246,  0.0065]],\n",
       "  \n",
       "          [[ 0.0195, -0.0197,  0.0084,  ...,  0.0194,  0.0245,  0.0065]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0191, -0.0203,  0.0085,  ...,  0.0194,  0.0247,  0.0066]],\n",
       "  \n",
       "          [[ 0.0197, -0.0200,  0.0075,  ...,  0.0196,  0.0245,  0.0064]],\n",
       "  \n",
       "          [[ 0.0190, -0.0201,  0.0086,  ...,  0.0176,  0.0246,  0.0069]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (8,\n",
       "  tensor([[[ 0.0078,  0.0053,  0.0017,  ..., -0.0060,  0.0057,  0.0273]],\n",
       "  \n",
       "          [[ 0.0059, -0.0081, -0.0034,  ...,  0.0047, -0.0123,  0.0095]],\n",
       "  \n",
       "          [[ 0.0125,  0.0093,  0.0071,  ...,  0.0034,  0.0430,  0.0922]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0126,  0.0116,  0.0077,  ..., -0.0053, -0.0070, -0.0055]],\n",
       "  \n",
       "          [[ 0.0011, -0.0004, -0.0016,  ...,  0.0009,  0.0022,  0.0044]],\n",
       "  \n",
       "          [[-0.0101, -0.0029, -0.0045,  ..., -0.0086,  0.0011,  0.0012]]]),\n",
       "  tensor([[[ 0.0169, -0.0211,  0.0070,  ...,  0.0297,  0.0162,  0.0077]],\n",
       "  \n",
       "          [[ 0.0171, -0.0198,  0.0041,  ...,  0.0268,  0.0199,  0.0095]],\n",
       "  \n",
       "          [[ 0.0169, -0.0201,  0.0033,  ...,  0.0277,  0.0177,  0.0103]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0166, -0.0207,  0.0036,  ...,  0.0260,  0.0203,  0.0097]],\n",
       "  \n",
       "          [[ 0.0164, -0.0205,  0.0042,  ...,  0.0252,  0.0196,  0.0102]],\n",
       "  \n",
       "          [[ 0.0166, -0.0204,  0.0036,  ...,  0.0260,  0.0201,  0.0096]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (9,\n",
       "  tensor([[[-3.9673e-03, -2.1729e-02, -9.2163e-03,  ...,  1.0742e-02,\n",
       "             1.1139e-02,  5.2490e-03]],\n",
       "  \n",
       "          [[-7.7728e-02, -3.1677e-02, -3.3417e-02,  ..., -9.6741e-03,\n",
       "             2.2858e-02, -7.6294e-03]],\n",
       "  \n",
       "          [[ 6.4087e-04, -4.7913e-03,  9.4604e-04,  ...,  3.6316e-03,\n",
       "             9.8267e-03, -1.2817e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000e+00,  6.1035e-05,  1.2207e-04,  ..., -2.9907e-03,\n",
       "             0.0000e+00,  3.0518e-04]],\n",
       "  \n",
       "          [[-8.0872e-03, -7.9956e-03, -7.8125e-03,  ..., -5.1880e-04,\n",
       "            -5.4932e-04, -6.1035e-04]],\n",
       "  \n",
       "          [[ 0.0000e+00, -9.1553e-05, -1.2207e-04,  ...,  0.0000e+00,\n",
       "            -3.0518e-05,  0.0000e+00]]]),\n",
       "  tensor([[[ 0.0146, -0.0194,  0.0042,  ...,  0.0278,  0.0184,  0.0127]],\n",
       "  \n",
       "          [[ 0.0202, -0.0147,  0.0028,  ...,  0.0347,  0.0195,  0.0132]],\n",
       "  \n",
       "          [[ 0.0137, -0.0204,  0.0009,  ...,  0.0278,  0.0197,  0.0132]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0145, -0.0190,  0.0016,  ...,  0.0275,  0.0186,  0.0143]],\n",
       "  \n",
       "          [[ 0.0141, -0.0196,  0.0032,  ...,  0.0285,  0.0204,  0.0131]],\n",
       "  \n",
       "          [[ 0.0144, -0.0192,  0.0018,  ...,  0.0285,  0.0204,  0.0131]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (10,\n",
       "  tensor([[[-5.5237e-03, -4.6387e-03, -5.1575e-03,  ..., -1.1292e-03,\n",
       "             3.0518e-05,  1.8311e-04]],\n",
       "  \n",
       "          [[ 0.0000e+00,  6.1035e-05,  1.2207e-04,  ..., -2.9907e-03,\n",
       "             0.0000e+00,  3.0518e-04]],\n",
       "  \n",
       "          [[ 3.0518e-05, -6.1035e-05, -1.8311e-04,  ..., -1.0376e-02,\n",
       "             1.6510e-02, -5.0354e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.0345e-02,  1.0590e-02,  1.1017e-02,  ..., -5.7373e-03,\n",
       "            -1.4587e-02, -1.4313e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00,  4.2725e-04,  2.7466e-04,  ..., -1.9836e-03,\n",
       "            -1.9836e-03, -3.5400e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]]]),\n",
       "  tensor([[[ 0.0196, -0.0119,  0.0061,  ...,  0.0262,  0.0218,  0.0168]],\n",
       "  \n",
       "          [[ 0.0201, -0.0116,  0.0041,  ...,  0.0239,  0.0190,  0.0175]],\n",
       "  \n",
       "          [[ 0.0200, -0.0117,  0.0043,  ...,  0.0251,  0.0185,  0.0159]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0212, -0.0115,  0.0012,  ...,  0.0264,  0.0217,  0.0167]],\n",
       "  \n",
       "          [[ 0.0201, -0.0116,  0.0042,  ...,  0.0263,  0.0218,  0.0169]],\n",
       "  \n",
       "          [[ 0.0200, -0.0117,  0.0043,  ...,  0.0262,  0.0218,  0.0168]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (11,\n",
       "  tensor([[[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 3.8147e-03,  2.9297e-03,  2.3804e-03,  ..., -3.9673e-04,\n",
       "            -3.9673e-04, -3.3569e-04]],\n",
       "  \n",
       "          [[-5.7983e-04,  2.1362e-03,  8.2703e-03,  ..., -6.1035e-05,\n",
       "             6.7139e-04,  1.7090e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-3.0518e-05, -2.1362e-04, -6.1035e-05,  ..., -5.4932e-04,\n",
       "            -7.6294e-04, -6.4087e-04]],\n",
       "  \n",
       "          [[-4.2725e-04, -4.2725e-04, -4.5776e-04,  ...,  3.8055e-02,\n",
       "             2.3163e-02, -1.7578e-02]],\n",
       "  \n",
       "          [[-3.0518e-03, -5.0964e-03, -5.1880e-03,  ..., -9.7168e-02,\n",
       "            -7.5836e-02, -8.1848e-02]]]),\n",
       "  tensor([[[ 0.0168, -0.0172,  0.0004,  ...,  0.0238,  0.0219,  0.0128]],\n",
       "  \n",
       "          [[ 0.0167, -0.0171,  0.0002,  ...,  0.0239,  0.0219,  0.0128]],\n",
       "  \n",
       "          [[ 0.0171, -0.0166,  0.0007,  ...,  0.0239,  0.0221,  0.0128]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0168, -0.0171,  0.0004,  ...,  0.0237,  0.0219,  0.0129]],\n",
       "  \n",
       "          [[ 0.0168, -0.0172,  0.0004,  ...,  0.0272,  0.0109,  0.0105]],\n",
       "  \n",
       "          [[ 0.0165, -0.0177,  0.0009,  ...,  0.0267,  0.0007,  0.0087]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (12,\n",
       "  tensor([[[ 2.5635e-03,  1.6479e-03,  1.1902e-03,  ...,  2.5848e-02,\n",
       "             2.4841e-02,  2.6031e-02]],\n",
       "  \n",
       "          [[-6.1035e-05,  5.4932e-04, -9.1553e-04,  ...,  3.3722e-02,\n",
       "             4.1992e-02,  7.3853e-03]],\n",
       "  \n",
       "          [[ 6.2561e-03,  5.3101e-03,  5.1575e-03,  ..., -6.1035e-05,\n",
       "             6.7139e-04,  2.7466e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.8351e-02, -5.7404e-02,  3.2135e-02,  ..., -6.6132e-02,\n",
       "             5.0354e-02, -3.2959e-02]],\n",
       "  \n",
       "          [[ 1.9226e-03,  8.8501e-04,  1.2512e-03,  ..., -1.4343e-03,\n",
       "            -1.3123e-03, -1.0376e-03]],\n",
       "  \n",
       "          [[-1.4038e-01, -7.0557e-02, -1.2271e-01,  ...,  7.9163e-02,\n",
       "             6.1096e-02,  5.0354e-02]]]),\n",
       "  tensor([[[ 0.0247, -0.0050,  0.0013,  ...,  0.0293,  0.0204,  0.0192]],\n",
       "  \n",
       "          [[ 0.0243, -0.0061,  0.0016,  ...,  0.0326,  0.0089,  0.0165]],\n",
       "  \n",
       "          [[ 0.0236, -0.0063,  0.0021,  ...,  0.0299,  0.0234,  0.0182]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0273,  0.0090,  0.0189,  ...,  0.0261, -0.0010,  0.0169]],\n",
       "  \n",
       "          [[ 0.0243, -0.0055,  0.0013,  ...,  0.0302,  0.0235,  0.0182]],\n",
       "  \n",
       "          [[ 0.0285,  0.0074,  0.0198,  ...,  0.0329,  0.0145,  0.0201]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (13,\n",
       "  tensor([[[ 1.3550e-02,  1.3947e-02,  1.4252e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 2.5635e-03,  1.6479e-03,  1.1902e-03,  ...,  2.5848e-02,\n",
       "             2.4841e-02,  2.6031e-02]],\n",
       "  \n",
       "          [[-4.8828e-04, -2.1362e-04, -3.0518e-04,  ..., -3.0518e-04,\n",
       "             1.8311e-04, -3.0518e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 5.9204e-03,  4.9133e-03,  4.9438e-03,  ..., -6.7749e-03,\n",
       "            -8.0261e-03, -1.1139e-02]],\n",
       "  \n",
       "          [[-1.0101e-02, -2.8687e-03, -4.4861e-03,  ..., -8.5754e-03,\n",
       "             1.0681e-03,  1.2207e-03]],\n",
       "  \n",
       "          [[ 9.1553e-05,  3.3569e-04,  1.5259e-04,  ..., -2.1362e-04,\n",
       "             1.2207e-04, -9.1553e-05]]]),\n",
       "  tensor([[[ 0.0246, -0.0174, -0.0083,  ...,  0.0269,  0.0225,  0.0111]],\n",
       "  \n",
       "          [[ 0.0231, -0.0174, -0.0018,  ...,  0.0246,  0.0186,  0.0122]],\n",
       "  \n",
       "          [[ 0.0232, -0.0179, -0.0018,  ...,  0.0270,  0.0225,  0.0111]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0230, -0.0185, -0.0021,  ...,  0.0258,  0.0216,  0.0113]],\n",
       "  \n",
       "          [[ 0.0230, -0.0183, -0.0044,  ...,  0.0261,  0.0210,  0.0108]],\n",
       "  \n",
       "          [[ 0.0232, -0.0179, -0.0019,  ...,  0.0269,  0.0225,  0.0111]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (14,\n",
       "  tensor([[[ 0.0012, -0.0081,  0.0062,  ..., -0.0291,  0.0258,  0.0145]],\n",
       "  \n",
       "          [[ 0.0011,  0.0014,  0.0005,  ...,  0.0010,  0.0021,  0.0017]],\n",
       "  \n",
       "          [[-0.0009, -0.0008, -0.0007,  ...,  0.0002,  0.0002,  0.0002]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0049, -0.0304, -0.0540,  ..., -0.0164, -0.0128, -0.0141]],\n",
       "  \n",
       "          [[ 0.0556,  0.0281,  0.0207,  ..., -0.0207,  0.0136,  0.0843]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ..., -0.0029,  0.0480,  0.0134]]]),\n",
       "  tensor([[[ 0.0245, -0.0153, -0.0004,  ...,  0.0321,  0.0112,  0.0058]],\n",
       "  \n",
       "          [[ 0.0233, -0.0164, -0.0013,  ...,  0.0260,  0.0217,  0.0076]],\n",
       "  \n",
       "          [[ 0.0231, -0.0169, -0.0014,  ...,  0.0260,  0.0218,  0.0077]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0258, -0.0182, -0.0025,  ...,  0.0259,  0.0212,  0.0076]],\n",
       "  \n",
       "          [[ 0.0237, -0.0168, -0.0042,  ...,  0.0259,  0.0110,  0.0084]],\n",
       "  \n",
       "          [[ 0.0231, -0.0169, -0.0015,  ...,  0.0240, -0.0013,  0.0071]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (15,\n",
       "  tensor([[[-9.1553e-05,  9.1553e-05, -4.5776e-04,  ..., -9.1553e-05,\n",
       "            -2.1362e-04, -5.7983e-04]],\n",
       "  \n",
       "          [[-8.0872e-03, -7.9956e-03, -7.8125e-03,  ..., -5.1880e-04,\n",
       "            -5.4932e-04, -6.1035e-04]],\n",
       "  \n",
       "          [[ 7.6080e-02,  6.5155e-02,  3.8177e-02,  ..., -1.2207e-04,\n",
       "             1.2268e-02,  2.8839e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -2.8992e-03,\n",
       "             4.7974e-02,  1.3428e-02]],\n",
       "  \n",
       "          [[-2.1973e-03, -7.6904e-03, -4.9133e-03,  ..., -7.1411e-03,\n",
       "            -7.1106e-03, -4.2725e-03]],\n",
       "  \n",
       "          [[ 1.0071e-03, -6.4087e-04,  2.1362e-04,  ...,  2.0752e-03,\n",
       "             7.2327e-03,  1.8311e-04]]]),\n",
       "  tensor([[[ 0.0141, -0.0124, -0.0081,  ...,  0.0297,  0.0237,  0.0132]],\n",
       "  \n",
       "          [[ 0.0137, -0.0125, -0.0077,  ...,  0.0298,  0.0237,  0.0132]],\n",
       "  \n",
       "          [[ 0.0180, -0.0008,  0.0041,  ...,  0.0294,  0.0189,  0.0145]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0142, -0.0124, -0.0081,  ...,  0.0274,  0.0023,  0.0124]],\n",
       "  \n",
       "          [[ 0.0142, -0.0127, -0.0077,  ...,  0.0298,  0.0233,  0.0129]],\n",
       "  \n",
       "          [[ 0.0143, -0.0122, -0.0082,  ...,  0.0296,  0.0236,  0.0132]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (16,\n",
       "  tensor([[[-1.7700e-03, -2.3193e-03, -2.5330e-03,  ..., -1.2238e-02,\n",
       "            -1.4343e-02, -1.4191e-02]],\n",
       "  \n",
       "          [[-3.2043e-03, -3.5095e-03, -3.5095e-03,  ..., -2.0111e-02,\n",
       "            -3.5065e-02, -9.7717e-02]],\n",
       "  \n",
       "          [[ 1.0986e-03,  1.2207e-03,  1.8005e-03,  ...,  3.2349e-03,\n",
       "             2.1362e-03,  1.8311e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-3.4180e-03, -1.0651e-02, -1.0193e-02,  ...,  1.4496e-02,\n",
       "             1.1688e-02,  1.3031e-02]],\n",
       "  \n",
       "          [[-9.1553e-05,  9.1553e-05,  3.9673e-04,  ..., -7.6294e-04,\n",
       "            -6.1035e-04, -6.7139e-04]],\n",
       "  \n",
       "          [[ 6.8359e-03, -1.0071e-03, -4.2725e-04,  ..., -4.4861e-03,\n",
       "            -4.9133e-03,  3.3264e-03]]]),\n",
       "  tensor([[[ 0.0162, -0.0137, -0.0037,  ...,  0.0290,  0.0239,  0.0144]],\n",
       "  \n",
       "          [[ 0.0168, -0.0139, -0.0053,  ...,  0.0259, -0.0044,  0.0146]],\n",
       "  \n",
       "          [[ 0.0177, -0.0132, -0.0063,  ...,  0.0295,  0.0251,  0.0153]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0174, -0.0114, -0.0061,  ...,  0.0296,  0.0252,  0.0156]],\n",
       "  \n",
       "          [[ 0.0176, -0.0133, -0.0063,  ...,  0.0295,  0.0251,  0.0150]],\n",
       "  \n",
       "          [[ 0.0189, -0.0133, -0.0068,  ...,  0.0279,  0.0228,  0.0145]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (17,\n",
       "  tensor([[[ 2.1667e-03,  1.2512e-03,  1.1902e-03,  ..., -8.7891e-03,\n",
       "            -7.9956e-03, -9.1248e-03]],\n",
       "  \n",
       "          [[-1.4038e-01, -7.0557e-02, -1.2271e-01,  ...,  7.9163e-02,\n",
       "             6.1096e-02,  5.0354e-02]],\n",
       "  \n",
       "          [[ 4.8828e-04, -4.2725e-04, -2.1362e-03,  ...,  6.4087e-04,\n",
       "            -2.1362e-03, -6.5613e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 2.1362e-04, -4.3335e-03, -5.0659e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  3.0518e-05,  ..., -7.3456e-02,\n",
       "            -7.7423e-02, -7.4677e-02]],\n",
       "  \n",
       "          [[ 1.0345e-02,  1.0590e-02,  1.1017e-02,  ..., -5.7373e-03,\n",
       "            -1.4587e-02, -1.4313e-02]]]),\n",
       "  tensor([[[ 0.0200, -0.0118, -0.0033,  ...,  0.0254,  0.0238,  0.0132]],\n",
       "  \n",
       "          [[ 0.0295, -0.0008,  0.0087,  ...,  0.0238,  0.0152,  0.0169]],\n",
       "  \n",
       "          [[ 0.0193, -0.0116, -0.0025,  ...,  0.0254,  0.0238,  0.0132]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0268, -0.0084, -0.0027,  ...,  0.0247,  0.0245,  0.0138]],\n",
       "  \n",
       "          [[ 0.0199, -0.0118, -0.0033,  ...,  0.0226,  0.0097,  0.0093]],\n",
       "  \n",
       "          [[ 0.0218, -0.0098, -0.0034,  ...,  0.0247,  0.0239,  0.0137]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (18,\n",
       "  tensor([[[-4.5166e-03, -4.2114e-03, -3.7842e-03,  ...,  2.2888e-03,\n",
       "             1.8616e-03,  1.1597e-03]],\n",
       "  \n",
       "          [[ 5.6152e-03,  8.3008e-03,  3.6621e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -1.5869e-03,\n",
       "            -1.0986e-03, -1.0986e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.4719e-03,  1.2207e-03, -3.7842e-03,  ...,  3.9673e-04,\n",
       "            -6.1035e-05, -3.6621e-04]],\n",
       "  \n",
       "          [[-1.4008e-02, -1.4526e-02, -1.6418e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 1.0986e-03,  1.2207e-03,  1.8005e-03,  ...,  3.2349e-03,\n",
       "             2.1362e-03,  1.8311e-04]]]),\n",
       "  tensor([[[ 0.0162, -0.0170, -0.0139,  ...,  0.0270,  0.0281,  0.0004]],\n",
       "  \n",
       "          [[ 0.0161, -0.0173, -0.0139,  ...,  0.0269,  0.0280,  0.0006]],\n",
       "  \n",
       "          [[ 0.0170, -0.0169, -0.0147,  ...,  0.0272,  0.0282,  0.0004]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0179, -0.0145, -0.0145,  ...,  0.0269,  0.0280,  0.0006]],\n",
       "  \n",
       "          [[ 0.0187, -0.0128, -0.0148,  ...,  0.0269,  0.0280,  0.0006]],\n",
       "  \n",
       "          [[ 0.0171, -0.0168, -0.0148,  ...,  0.0275,  0.0279,  0.0010]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (19,\n",
       "  tensor([[[ 0.0022,  0.0013,  0.0012,  ..., -0.0088, -0.0080, -0.0091]],\n",
       "  \n",
       "          [[-0.0075, -0.0080, -0.0076,  ..., -0.0043, -0.0039, -0.0041]],\n",
       "  \n",
       "          [[-0.0118, -0.0242, -0.0086,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.2380, -0.2042, -0.1952,  ..., -0.0217, -0.0185, -0.0160]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0023,  0.0023,  0.0024]],\n",
       "  \n",
       "          [[ 0.0056,  0.0069,  0.0084,  ..., -0.0065, -0.0065, -0.0062]]]),\n",
       "  tensor([[[ 0.0111, -0.0157, -0.0121,  ...,  0.0266,  0.0217,  0.0078]],\n",
       "  \n",
       "          [[ 0.0107, -0.0156, -0.0118,  ...,  0.0266,  0.0218,  0.0078]],\n",
       "  \n",
       "          [[ 0.0103, -0.0147, -0.0111,  ...,  0.0266,  0.0219,  0.0080]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0143, -0.0091, -0.0070,  ...,  0.0283,  0.0185,  0.0050]],\n",
       "  \n",
       "          [[ 0.0109, -0.0156, -0.0121,  ...,  0.0265,  0.0219,  0.0080]],\n",
       "  \n",
       "          [[ 0.0111, -0.0155, -0.0123,  ...,  0.0267,  0.0219,  0.0079]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (20,\n",
       "  tensor([[[-1.5259e-03, -1.7792e-02, -2.2705e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-3.6621e-04, -9.7656e-04, -1.3123e-03,  ...,  2.7466e-04,\n",
       "             9.1553e-05, -1.6174e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-7.0190e-04,  3.3569e-04,  1.6479e-03,  ..., -6.1035e-05,\n",
       "            -9.1553e-05, -1.2207e-04]],\n",
       "  \n",
       "          [[-8.0872e-03, -7.9956e-03, -7.8125e-03,  ..., -5.1880e-04,\n",
       "            -5.4932e-04, -6.1035e-04]],\n",
       "  \n",
       "          [[-5.0049e-03, -5.0964e-03, -4.7607e-03,  ...,  1.4008e-02,\n",
       "             1.4008e-02,  1.4069e-02]]]),\n",
       "  tensor([[[ 0.0172, -0.0117, -0.0063,  ...,  0.0232,  0.0255,  0.0097]],\n",
       "  \n",
       "          [[ 0.0181, -0.0136, -0.0046,  ...,  0.0231,  0.0251,  0.0097]],\n",
       "  \n",
       "          [[ 0.0181, -0.0136, -0.0047,  ...,  0.0232,  0.0255,  0.0097]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0181, -0.0128, -0.0044,  ...,  0.0232,  0.0255,  0.0097]],\n",
       "  \n",
       "          [[ 0.0177, -0.0138, -0.0044,  ...,  0.0232,  0.0256,  0.0097]],\n",
       "  \n",
       "          [[ 0.0179, -0.0138, -0.0046,  ...,  0.0217,  0.0251,  0.0105]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (21,\n",
       "  tensor([[[-5.7983e-03, -6.4392e-03, -7.5378e-03,  ...,  2.2583e-03,\n",
       "             2.1973e-03,  1.8005e-03]],\n",
       "  \n",
       "          [[-3.2043e-03, -4.2114e-03, -4.3335e-03,  ..., -7.2937e-03,\n",
       "            -7.6599e-03, -9.2163e-03]],\n",
       "  \n",
       "          [[ 2.4719e-03,  4.0894e-03,  3.3875e-03,  ..., -4.8828e-04,\n",
       "            -2.9907e-03, -3.7842e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.2573e-02,  1.1597e-02,  7.6599e-03,  ..., -5.3406e-03,\n",
       "            -6.9885e-03, -5.4932e-03]],\n",
       "  \n",
       "          [[ 9.1553e-05,  2.8687e-02,  6.1707e-02,  ...,  6.5002e-03,\n",
       "             9.1553e-03,  8.8806e-03]],\n",
       "  \n",
       "          [[-1.4008e-02, -1.4526e-02, -1.6418e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]]]),\n",
       "  tensor([[[ 0.0217, -0.0188, -0.0087,  ...,  0.0264,  0.0293,  0.0085]],\n",
       "  \n",
       "          [[ 0.0218, -0.0193, -0.0091,  ...,  0.0266,  0.0288,  0.0083]],\n",
       "  \n",
       "          [[ 0.0219, -0.0194, -0.0092,  ...,  0.0265,  0.0292,  0.0084]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0220, -0.0192, -0.0094,  ...,  0.0266,  0.0289,  0.0084]],\n",
       "  \n",
       "          [[ 0.0198, -0.0196, -0.0128,  ...,  0.0262,  0.0280,  0.0081]],\n",
       "  \n",
       "          [[ 0.0217, -0.0190, -0.0088,  ...,  0.0266,  0.0291,  0.0084]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (22,\n",
       "  tensor([[[-3.0518e-05,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  5.7373e-02,\n",
       "             2.8229e-02, -3.3569e-04]],\n",
       "  \n",
       "          [[ 4.7394e-02,  7.2479e-02,  9.4269e-02,  ..., -7.1655e-02,\n",
       "            -1.1169e-02, -2.4536e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.8311e-04,  3.0518e-05, -6.1035e-05,  ...,  4.2725e-04,\n",
       "             4.8828e-04,  3.9673e-04]],\n",
       "  \n",
       "          [[-3.5400e-03, -4.2114e-03, -5.2795e-03,  ...,  9.3872e-02,\n",
       "             1.2210e-01,  1.5958e-01]],\n",
       "  \n",
       "          [[ 5.5237e-02,  7.7484e-02,  4.7333e-02,  ..., -6.1035e-02,\n",
       "            -6.5369e-02, -5.5511e-02]]]),\n",
       "  tensor([[[ 0.0151, -0.0273, -0.0248,  ...,  0.0302,  0.0233,  0.0005]],\n",
       "  \n",
       "          [[ 0.0151, -0.0273, -0.0248,  ...,  0.0285,  0.0190,  0.0018]],\n",
       "  \n",
       "          [[ 0.0194, -0.0237, -0.0244,  ...,  0.0234, -0.0081,  0.0042]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0151, -0.0273, -0.0248,  ...,  0.0302,  0.0234,  0.0005]],\n",
       "  \n",
       "          [[ 0.0151, -0.0273, -0.0248,  ...,  0.0297,  0.0018,  0.0024]],\n",
       "  \n",
       "          [[ 0.0160, -0.0259, -0.0244,  ...,  0.0298,  0.0242,  0.0012]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (23,\n",
       "  tensor([[[ 0.0013,  0.0008,  0.0007,  ...,  0.0095, -0.0106, -0.0263]],\n",
       "  \n",
       "          [[ 0.0237,  0.0209,  0.0204,  ...,  0.0239,  0.0256,  0.0257]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ..., -0.0029, -0.0030, -0.0027]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0011, -0.0027, -0.0018,  ...,  0.0261,  0.0270,  0.0327]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[-0.0002, -0.0002, -0.0003,  ..., -0.0005, -0.0005, -0.0005]]]),\n",
       "  tensor([[[ 0.0152, -0.0166, -0.0086,  ...,  0.0234,  0.0057,  0.0059]],\n",
       "  \n",
       "          [[ 0.0155, -0.0162, -0.0088,  ...,  0.0208,  0.0235,  0.0075]],\n",
       "  \n",
       "          [[ 0.0152, -0.0165, -0.0085,  ...,  0.0225,  0.0238,  0.0067]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0150, -0.0166, -0.0082,  ...,  0.0221,  0.0248,  0.0073]],\n",
       "  \n",
       "          [[ 0.0152, -0.0165, -0.0085,  ...,  0.0227,  0.0238,  0.0068]],\n",
       "  \n",
       "          [[ 0.0152, -0.0165, -0.0085,  ...,  0.0227,  0.0238,  0.0068]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (24,\n",
       "  tensor([[[ 0.0083,  0.0909,  0.1680,  ..., -0.0025,  0.0049,  0.0042]],\n",
       "  \n",
       "          [[-0.0140, -0.0145, -0.0164,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0059,  0.0049,  0.0049,  ..., -0.0068, -0.0080, -0.0111]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ..., -0.0157,  0.0120,  0.0219]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ..., -0.0859,  0.0086,  0.0782]]]),\n",
       "  tensor([[[ 0.0196, -0.0107,  0.0221,  ...,  0.0239,  0.0249,  0.0014]],\n",
       "  \n",
       "          [[ 0.0128, -0.0253, -0.0195,  ...,  0.0240,  0.0250,  0.0013]],\n",
       "  \n",
       "          [[ 0.0131, -0.0254, -0.0201,  ...,  0.0240,  0.0250,  0.0013]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0131, -0.0254, -0.0202,  ...,  0.0237,  0.0250,  0.0014]],\n",
       "  \n",
       "          [[ 0.0131, -0.0254, -0.0201,  ...,  0.0241,  0.0248,  0.0013]],\n",
       "  \n",
       "          [[ 0.0131, -0.0254, -0.0201,  ...,  0.0188, -0.0025,  0.0026]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (25,\n",
       "  tensor([[[-1.1292e-03, -1.3428e-03, -4.5776e-04,  ..., -6.1035e-04,\n",
       "            -2.1362e-04, -5.7983e-04]],\n",
       "  \n",
       "          [[ 3.0518e-05,  0.0000e+00, -3.0518e-05,  ..., -1.0681e-03,\n",
       "            -1.0376e-02, -8.1787e-03]],\n",
       "  \n",
       "          [[ 1.1353e-02,  2.1057e-03, -1.7365e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-6.3965e-02, -6.3324e-02, -6.2347e-02,  ...,  1.0101e-02,\n",
       "             1.1230e-02,  1.2207e-02]],\n",
       "  \n",
       "          [[ 3.5095e-03,  1.4954e-03, -3.0518e-05,  ..., -1.6174e-03,\n",
       "            -3.2959e-03,  1.8341e-02]],\n",
       "  \n",
       "          [[-6.6833e-03, -4.3640e-03,  1.2024e-02,  ..., -8.5144e-03,\n",
       "            -1.6571e-02,  2.8687e-03]]]),\n",
       "  tensor([[[ 0.0170, -0.0183, -0.0102,  ...,  0.0188,  0.0243,  0.0032]],\n",
       "  \n",
       "          [[ 0.0172, -0.0181, -0.0103,  ...,  0.0181,  0.0233,  0.0041]],\n",
       "  \n",
       "          [[ 0.0176, -0.0189, -0.0139,  ...,  0.0187,  0.0242,  0.0032]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0158, -0.0059,  0.0113,  ...,  0.0176,  0.0220,  0.0036]],\n",
       "  \n",
       "          [[ 0.0175, -0.0176, -0.0108,  ...,  0.0175,  0.0228,  0.0040]],\n",
       "  \n",
       "          [[ 0.0168, -0.0178, -0.0103,  ...,  0.0211,  0.0161,  0.0020]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (26,\n",
       "  tensor([[[-6.4697e-03, -8.1787e-03, -1.2970e-02,  ...,  4.5776e-03,\n",
       "             4.7607e-03,  5.0659e-03]],\n",
       "  \n",
       "          [[ 3.0823e-03,  3.5400e-03,  1.2146e-02,  ...,  9.1553e-05,\n",
       "            -2.7466e-03,  4.3030e-03]],\n",
       "  \n",
       "          [[ 5.5847e-03,  6.9275e-03,  8.3923e-03,  ..., -6.4697e-03,\n",
       "            -6.5308e-03, -6.1646e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.3428e-03,  1.5259e-03,  9.1553e-05,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-1.4038e-01, -7.0557e-02, -1.2271e-01,  ...,  7.9163e-02,\n",
       "             6.1096e-02,  5.0354e-02]],\n",
       "  \n",
       "          [[ 2.1362e-04,  1.5259e-04,  0.0000e+00,  ...,  2.9083e-02,\n",
       "            -6.8054e-02, -9.1309e-02]]]),\n",
       "  tensor([[[ 0.0095, -0.0242, -0.0194,  ...,  0.0210,  0.0217, -0.0008]],\n",
       "  \n",
       "          [[ 0.0101, -0.0234, -0.0194,  ...,  0.0208,  0.0213, -0.0010]],\n",
       "  \n",
       "          [[ 0.0098, -0.0242, -0.0194,  ...,  0.0212,  0.0216, -0.0009]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0091, -0.0232, -0.0204,  ...,  0.0211,  0.0218, -0.0008]],\n",
       "  \n",
       "          [[ 0.0087, -0.0205, -0.0189,  ...,  0.0199,  0.0165,  0.0018]],\n",
       "  \n",
       "          [[ 0.0097, -0.0244, -0.0194,  ...,  0.0207, -0.0017, -0.0022]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (27,\n",
       "  tensor([[[-0.0042, -0.0017, -0.0060,  ...,  0.0108,  0.0034, -0.0043]],\n",
       "  \n",
       "          [[ 0.0025,  0.0041,  0.0034,  ..., -0.0005, -0.0030, -0.0038]],\n",
       "  \n",
       "          [[ 0.0742,  0.0255, -0.0783,  ..., -0.0616,  0.0807, -0.0023]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0899,  0.0363,  0.0414,  ...,  0.4873,  0.4260,  0.3207]],\n",
       "  \n",
       "          [[ 0.0120, -0.0006, -0.0053,  ..., -0.0127, -0.0146, -0.0134]]]),\n",
       "  tensor([[[ 6.1576e-03, -2.7081e-02, -2.2210e-02,  ...,  2.2611e-02,\n",
       "             1.9800e-02, -1.6225e-04]],\n",
       "  \n",
       "          [[ 6.0056e-03, -2.7087e-02, -2.1964e-02,  ...,  2.2996e-02,\n",
       "             2.0997e-02,  1.6261e-04]],\n",
       "  \n",
       "          [[ 1.1712e-02, -1.5886e-02, -8.3865e-03,  ...,  2.0650e-02,\n",
       "             2.5675e-03, -7.5216e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 6.0171e-03, -2.6948e-02, -2.1900e-02,  ...,  2.3207e-02,\n",
       "             2.0592e-02,  9.7454e-05]],\n",
       "  \n",
       "          [[ 8.3095e-03, -2.0725e-02, -2.3881e-02,  ..., -6.4203e-02,\n",
       "            -1.0744e-01,  8.4616e-02]],\n",
       "  \n",
       "          [[ 6.2599e-03, -2.7282e-02, -2.2262e-02,  ...,  2.2598e-02,\n",
       "             1.9331e-02, -1.7840e-04]]], grad_fn=<TanhBackward0>)),\n",
       " (28,\n",
       "  tensor([[[-0.0003, -0.0004, -0.0010,  ...,  0.0025,  0.0018,  0.0053]],\n",
       "  \n",
       "          [[-0.0067, -0.0011, -0.0010,  ..., -0.0151,  0.0063,  0.0044]],\n",
       "  \n",
       "          [[-0.0075, -0.0080, -0.0076,  ..., -0.0043, -0.0039, -0.0041]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0174,  0.0172,  0.0161,  ..., -0.0137, -0.0159, -0.0112]],\n",
       "  \n",
       "          [[-0.0036, -0.0044, -0.0054,  ..., -0.0034, -0.0022, -0.0007]],\n",
       "  \n",
       "          [[ 0.0548,  0.0539,  0.0606,  ..., -0.0023, -0.0023, -0.0021]]]),\n",
       "  tensor([[[ 0.0066, -0.0277, -0.0235,  ...,  0.0233,  0.0195, -0.0052]],\n",
       "  \n",
       "          [[ 0.0069, -0.0272, -0.0237,  ...,  0.0229,  0.0198, -0.0050]],\n",
       "  \n",
       "          [[ 0.0065, -0.0277, -0.0232,  ...,  0.0234,  0.0191, -0.0055]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0070, -0.0270, -0.0238,  ...,  0.0234,  0.0188, -0.0056]],\n",
       "  \n",
       "          [[ 0.0066, -0.0278, -0.0233,  ...,  0.0233,  0.0191, -0.0054]],\n",
       "  \n",
       "          [[ 0.0096, -0.0260, -0.0225,  ...,  0.0234,  0.0193, -0.0054]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (29,\n",
       "  tensor([[[ 0.0270,  0.0331,  0.0381,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[-0.0013, -0.0009,  0.0061,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0742,  0.0255, -0.0783,  ..., -0.0616,  0.0807, -0.0023]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ..., -0.0088, -0.0126, -0.0098]],\n",
       "  \n",
       "          [[-0.0031, -0.0051, -0.0052,  ..., -0.0972, -0.0758, -0.0818]],\n",
       "  \n",
       "          [[-0.0050, -0.0051, -0.0048,  ...,  0.0140,  0.0140,  0.0141]]]),\n",
       "  tensor([[[ 0.0074, -0.0255, -0.0207,  ...,  0.0196,  0.0235, -0.0021]],\n",
       "  \n",
       "          [[ 0.0061, -0.0240, -0.0197,  ...,  0.0196,  0.0235, -0.0021]],\n",
       "  \n",
       "          [[ 0.0137, -0.0034, -0.0007,  ...,  0.0128, -0.0031, -0.0052]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0058, -0.0249, -0.0193,  ...,  0.0181,  0.0233, -0.0015]],\n",
       "  \n",
       "          [[ 0.0056, -0.0249, -0.0190,  ...,  0.0164,  0.0090, -0.0057]],\n",
       "  \n",
       "          [[ 0.0056, -0.0250, -0.0191,  ...,  0.0174,  0.0235, -0.0012]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (30,\n",
       "  tensor([[[ 3.2959e-03,  3.5095e-03,  2.5635e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-2.9846e-02, -3.1647e-02, -4.8615e-02,  ..., -8.3313e-03,\n",
       "            -2.8687e-03, -2.0447e-03]],\n",
       "  \n",
       "          [[ 1.7090e-03,  1.4343e-03,  1.4954e-03,  ..., -1.2207e-03,\n",
       "            -3.6621e-04,  1.8005e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-5.3107e-01, -5.0726e-01, -4.8831e-01,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 2.1362e-04,  1.5259e-04,  0.0000e+00,  ...,  2.9083e-02,\n",
       "            -6.8054e-02, -9.1309e-02]],\n",
       "  \n",
       "          [[ 1.8921e-03, -2.1362e-04,  5.1880e-04,  ..., -1.9226e-02,\n",
       "             7.3547e-03,  1.1444e-02]]]),\n",
       "  tensor([[[ 0.0022, -0.0305, -0.0273,  ...,  0.0232,  0.0160, -0.0086]],\n",
       "  \n",
       "          [[ 0.0009, -0.0296, -0.0252,  ...,  0.0229,  0.0155, -0.0089]],\n",
       "  \n",
       "          [[ 0.0023, -0.0304, -0.0274,  ...,  0.0230,  0.0158, -0.0086]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0126,  0.0060,  0.0076,  ...,  0.0232,  0.0160, -0.0086]],\n",
       "  \n",
       "          [[ 0.0022, -0.0304, -0.0273,  ...,  0.0225, -0.0048, -0.0087]],\n",
       "  \n",
       "          [[ 0.0022, -0.0304, -0.0272,  ...,  0.0203,  0.0151, -0.0088]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (31,\n",
       "  tensor([[[-3.0518e-05, -2.1362e-04, -6.1035e-05,  ..., -5.4932e-04,\n",
       "            -7.6294e-04, -6.4087e-04]],\n",
       "  \n",
       "          [[-3.0518e-05,  3.0518e-05, -3.0518e-05,  ..., -9.6771e-02,\n",
       "            -1.2924e-01, -6.9336e-02]],\n",
       "  \n",
       "          [[-8.0566e-03,  3.4119e-02,  3.8086e-02,  ...,  5.3406e-03,\n",
       "             1.2054e-02,  1.6266e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 7.9346e-04,  7.3242e-04,  5.4932e-04,  ..., -2.4414e-04,\n",
       "            -2.4414e-04, -2.1362e-04]],\n",
       "  \n",
       "          [[ 1.3550e-02,  1.3947e-02,  1.4252e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]]]),\n",
       "  tensor([[[ 0.0032, -0.0330, -0.0265,  ...,  0.0180,  0.0216, -0.0065]],\n",
       "  \n",
       "          [[ 0.0032, -0.0331, -0.0265,  ...,  0.0042, -0.0093, -0.0096]],\n",
       "  \n",
       "          [[ 0.0030, -0.0326, -0.0265,  ...,  0.0148, -0.0013, -0.0031]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0032, -0.0330, -0.0265,  ...,  0.0180,  0.0216, -0.0065]],\n",
       "  \n",
       "          [[ 0.0038, -0.0326, -0.0273,  ...,  0.0180,  0.0216, -0.0065]],\n",
       "  \n",
       "          [[ 0.0032, -0.0331, -0.0265,  ...,  0.0180,  0.0216, -0.0065]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (32,\n",
       "  tensor([[[ 3.6621e-04,  3.6621e-04,  3.6621e-04,  ...,  5.4016e-03,\n",
       "             5.4932e-03,  5.5847e-03]],\n",
       "  \n",
       "          [[-5.3107e-01, -5.0726e-01, -4.8831e-01,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-3.0518e-05, -2.7466e-04, -3.9673e-04,  ...,  0.0000e+00,\n",
       "             3.0518e-05, -1.2207e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 4.5776e-04,  3.3569e-04, -3.6621e-04,  ...,  2.2736e-02,\n",
       "            -8.3923e-03, -1.9836e-03]]]),\n",
       "  tensor([[[-0.0018, -0.0336, -0.0273,  ...,  0.0177,  0.0192, -0.0073]],\n",
       "  \n",
       "          [[ 0.0914,  0.1062,  0.0567,  ...,  0.0183,  0.0191, -0.0075]],\n",
       "  \n",
       "          [[-0.0019, -0.0337, -0.0273,  ...,  0.0183,  0.0191, -0.0075]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0018, -0.0336, -0.0273,  ...,  0.0183,  0.0191, -0.0075]],\n",
       "  \n",
       "          [[-0.0018, -0.0336, -0.0273,  ...,  0.0183,  0.0191, -0.0075]],\n",
       "  \n",
       "          [[-0.0019, -0.0336, -0.0273,  ...,  0.0173,  0.0147, -0.0087]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (33,\n",
       "  tensor([[[ 0.0000e+00, -3.0518e-05, -3.0518e-05,  ...,  3.9673e-04,\n",
       "             3.6621e-04,  3.0518e-04]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  3.0841e-01,\n",
       "            -1.9983e-01, -1.7438e-01]],\n",
       "  \n",
       "          [[ 1.9836e-03,  1.9897e-02,  1.1017e-02,  ...,  2.5696e-02,\n",
       "             1.9531e-02,  9.7046e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.3550e-02,  1.3947e-02,  1.4252e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-1.1292e-02, -5.4321e-03,  1.3428e-03,  ..., -9.1553e-04,\n",
       "            -2.4414e-02, -6.2500e-02]],\n",
       "  \n",
       "          [[-6.1035e-05,  5.4932e-04, -9.1553e-04,  ...,  3.3722e-02,\n",
       "             4.1992e-02,  7.3853e-03]]]),\n",
       "  tensor([[[ 0.0005, -0.0312, -0.0225,  ...,  0.0157,  0.0205, -0.0078]],\n",
       "  \n",
       "          [[ 0.0005, -0.0312, -0.0225,  ..., -0.0057, -0.0252, -0.0159]],\n",
       "  \n",
       "          [[ 0.0003, -0.0301, -0.0227,  ...,  0.0148,  0.0198, -0.0081]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0008, -0.0307, -0.0230,  ...,  0.0157,  0.0205, -0.0078]],\n",
       "  \n",
       "          [[ 0.0011, -0.0306, -0.0231,  ...,  0.0148,  0.0045, -0.0122]],\n",
       "  \n",
       "          [[ 0.0005, -0.0312, -0.0225,  ...,  0.0174,  0.0167, -0.0084]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (34,\n",
       "  tensor([[[ 9.7656e-04, -3.3569e-02,  6.2500e-02,  ..., -2.0233e-02,\n",
       "            -1.1536e-02,  7.6294e-04]],\n",
       "  \n",
       "          [[ 1.2817e-03,  6.8359e-03,  9.8572e-03,  ...,  1.0651e-02,\n",
       "             9.3079e-03,  8.3618e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  4.2725e-04,  2.7466e-04,  ..., -1.9836e-03,\n",
       "            -1.9836e-03, -3.5400e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000e+00, -1.2207e-04, -1.8616e-03,  ...,  4.0894e-03,\n",
       "             5.7373e-03,  4.3640e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 3.3569e-04,  3.9673e-04,  3.3569e-04,  ...,  1.1353e-02,\n",
       "             1.2787e-01,  3.6102e-02]]]),\n",
       "  tensor([[[ 0.0023, -0.0310, -0.0288,  ...,  0.0195,  0.0190, -0.0132]],\n",
       "  \n",
       "          [[ 0.0009, -0.0375, -0.0306,  ...,  0.0199,  0.0205, -0.0141]],\n",
       "  \n",
       "          [[ 0.0009, -0.0375, -0.0304,  ...,  0.0202,  0.0205, -0.0141]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0009, -0.0374, -0.0303,  ...,  0.0202,  0.0205, -0.0142]],\n",
       "  \n",
       "          [[ 0.0009, -0.0374, -0.0303,  ...,  0.0203,  0.0205, -0.0142]],\n",
       "  \n",
       "          [[ 0.0009, -0.0374, -0.0304,  ...,  0.0204, -0.0103, -0.0157]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (35,\n",
       "  tensor([[[ 6.4392e-03, -6.5308e-03,  5.0659e-03,  ...,  6.0120e-03,\n",
       "            -4.0283e-03, -2.1973e-03]],\n",
       "  \n",
       "          [[ 3.0212e-03,  2.5940e-03,  2.1362e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -8.7585e-03,\n",
       "            -1.2604e-02, -9.7656e-03]],\n",
       "  \n",
       "          [[ 5.1880e-04,  1.7700e-03, -3.0518e-05,  ..., -2.3499e-03,\n",
       "            -4.5166e-03, -7.8735e-03]],\n",
       "  \n",
       "          [[-1.1902e-03, -7.0190e-04, -1.0071e-03,  ..., -6.1035e-05,\n",
       "             3.0518e-05,  0.0000e+00]]]),\n",
       "  tensor([[[ 3.7327e-05, -3.0377e-02, -2.1391e-02,  ...,  1.3615e-02,\n",
       "             1.9528e-02, -1.3403e-02]],\n",
       "  \n",
       "          [[ 6.8575e-04, -3.2636e-02, -2.4253e-02,  ...,  1.3678e-02,\n",
       "             1.9303e-02, -1.3854e-02]],\n",
       "  \n",
       "          [[ 6.8921e-04, -3.2665e-02, -2.4271e-02,  ...,  1.3678e-02,\n",
       "             1.9303e-02, -1.3854e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 6.9213e-04, -3.2666e-02, -2.4277e-02,  ...,  1.2248e-02,\n",
       "             1.8825e-02, -1.2984e-02]],\n",
       "  \n",
       "          [[ 9.7172e-04, -3.3117e-02, -2.5096e-02,  ...,  1.3538e-02,\n",
       "             1.8917e-02, -1.4082e-02]],\n",
       "  \n",
       "          [[ 6.6842e-04, -3.2715e-02, -2.4328e-02,  ...,  1.3676e-02,\n",
       "             1.9315e-02, -1.3849e-02]]], grad_fn=<TanhBackward0>)),\n",
       " (36,\n",
       "  tensor([[[ 0.0000,  0.0000,  0.0000,  ...,  0.0004,  0.0004,  0.0001]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ..., -0.0029,  0.0480,  0.0134]],\n",
       "  \n",
       "          [[ 0.0120, -0.0048, -0.0025,  ...,  0.0023, -0.0030, -0.0003]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0524,  0.0274,  0.0053,  ...,  0.0262,  0.0224,  0.0006]],\n",
       "  \n",
       "          [[ 0.0474,  0.0725,  0.0943,  ..., -0.0717, -0.0112, -0.0245]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]]]),\n",
       "  tensor([[[-0.0021, -0.0353, -0.0275,  ...,  0.0159,  0.0176, -0.0156]],\n",
       "  \n",
       "          [[-0.0021, -0.0353, -0.0275,  ...,  0.0141, -0.0029, -0.0181]],\n",
       "  \n",
       "          [[-0.0022, -0.0351, -0.0272,  ...,  0.0159,  0.0175, -0.0158]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0013, -0.0352, -0.0288,  ...,  0.0171,  0.0173, -0.0176]],\n",
       "  \n",
       "          [[ 0.0028, -0.0240, -0.0159,  ...,  0.0023, -0.0245, -0.0179]],\n",
       "  \n",
       "          [[-0.0021, -0.0353, -0.0275,  ...,  0.0159,  0.0176, -0.0157]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (37,\n",
       "  tensor([[[-5.8289e-03, -6.8054e-03, -7.4463e-03,  ...,  6.2714e-02,\n",
       "             5.3375e-02,  4.3518e-02]],\n",
       "  \n",
       "          [[ 3.8147e-03,  2.9297e-03,  2.3804e-03,  ..., -3.9673e-04,\n",
       "            -3.9673e-04, -3.3569e-04]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-4.3945e-03, -3.5400e-03, -1.0986e-03,  ...,  7.6294e-04,\n",
       "             4.5776e-04, -6.1035e-05]],\n",
       "  \n",
       "          [[-9.1553e-05,  9.1553e-05,  3.9673e-04,  ..., -7.6294e-04,\n",
       "            -6.1035e-04, -6.7139e-04]],\n",
       "  \n",
       "          [[-2.5330e-02, -2.4445e-02, -2.0721e-02,  ..., -3.1433e-03,\n",
       "            -2.8076e-03,  5.7983e-04]]]),\n",
       "  tensor([[[-0.0050, -0.0341, -0.0270,  ...,  0.0098,  0.0065, -0.0137]],\n",
       "  \n",
       "          [[-0.0049, -0.0342, -0.0274,  ...,  0.0112,  0.0150, -0.0155]],\n",
       "  \n",
       "          [[-0.0050, -0.0342, -0.0272,  ...,  0.0112,  0.0150, -0.0155]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0051, -0.0340, -0.0274,  ...,  0.0113,  0.0149, -0.0155]],\n",
       "  \n",
       "          [[-0.0050, -0.0342, -0.0272,  ...,  0.0113,  0.0150, -0.0155]],\n",
       "  \n",
       "          [[-0.0053, -0.0338, -0.0273,  ...,  0.0109,  0.0148, -0.0155]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (38,\n",
       "  tensor([[[-1.9531e-03,  2.6855e-03, -1.0071e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 3.0823e-03,  3.5400e-03,  1.2146e-02,  ...,  9.1553e-05,\n",
       "            -2.7466e-03,  4.3030e-03]],\n",
       "  \n",
       "          [[ 1.2207e-04, -3.0518e-05, -6.1035e-05,  ..., -2.7466e-04,\n",
       "             6.1035e-04,  4.8828e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 6.2561e-03,  4.4250e-03,  2.7161e-03,  ..., -6.1035e-05,\n",
       "             3.6621e-04,  7.0190e-04]],\n",
       "  \n",
       "          [[-5.7983e-03, -6.4392e-03, -7.5378e-03,  ...,  2.2583e-03,\n",
       "             2.1973e-03,  1.8005e-03]],\n",
       "  \n",
       "          [[ 5.5603e-02,  2.8076e-02,  2.0721e-02,  ..., -2.0660e-02,\n",
       "             1.3580e-02,  8.4290e-02]]]),\n",
       "  tensor([[[ 0.0036, -0.0272, -0.0258,  ...,  0.0128,  0.0134, -0.0241]],\n",
       "  \n",
       "          [[-0.0065, -0.0412, -0.0361,  ...,  0.0124,  0.0129, -0.0242]],\n",
       "  \n",
       "          [[-0.0075, -0.0422, -0.0370,  ...,  0.0128,  0.0134, -0.0240]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0077, -0.0422, -0.0369,  ...,  0.0128,  0.0134, -0.0241]],\n",
       "  \n",
       "          [[-0.0074, -0.0405, -0.0349,  ...,  0.0124,  0.0134, -0.0237]],\n",
       "  \n",
       "          [[-0.0067, -0.0394, -0.0334,  ...,  0.0091, -0.0070, -0.0218]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (39,\n",
       "  tensor([[[ 0.0652,  0.0420,  0.0140,  ..., -0.0406, -0.0213, -0.0063]],\n",
       "  \n",
       "          [[-0.0013, -0.0009,  0.0061,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0022,  0.0013,  0.0012,  ..., -0.0088, -0.0080, -0.0091]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0063,  0.0052,  0.0059,  ...,  0.0021,  0.0005, -0.0003]],\n",
       "  \n",
       "          [[-0.0002, -0.0004, -0.0005,  ...,  0.0036,  0.0033,  0.0031]],\n",
       "  \n",
       "          [[ 0.0009,  0.0004,  0.0011,  ...,  0.0039,  0.0032,  0.0053]]]),\n",
       "  tensor([[[-0.0056, -0.0416, -0.0350,  ...,  0.0139,  0.0073, -0.0248]],\n",
       "  \n",
       "          [[-0.0053, -0.0465, -0.0407,  ...,  0.0156,  0.0162, -0.0277]],\n",
       "  \n",
       "          [[-0.0049, -0.0467, -0.0408,  ...,  0.0156,  0.0158, -0.0280]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0051, -0.0465, -0.0406,  ...,  0.0156,  0.0162, -0.0277]],\n",
       "  \n",
       "          [[-0.0050, -0.0465, -0.0405,  ...,  0.0157,  0.0162, -0.0277]],\n",
       "  \n",
       "          [[-0.0052, -0.0465, -0.0407,  ...,  0.0154,  0.0164, -0.0274]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (40,\n",
       "  tensor([[[-0.0640, -0.0633, -0.0623,  ...,  0.0101,  0.0112,  0.0122]],\n",
       "  \n",
       "          [[ 0.0057,  0.0076,  0.0091,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[-0.0592,  0.0718,  0.0534,  ..., -0.1253, -0.1304,  0.0262]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0020,  0.0199,  0.0110,  ...,  0.0257,  0.0195,  0.0097]],\n",
       "  \n",
       "          [[-0.0557, -0.0423, -0.0076,  ..., -0.0009,  0.0359,  0.0185]]]),\n",
       "  tensor([[[-0.0122, -0.0345, -0.0222,  ...,  0.0114,  0.0114, -0.0259]],\n",
       "  \n",
       "          [[-0.0094, -0.0427, -0.0353,  ...,  0.0117,  0.0119, -0.0262]],\n",
       "  \n",
       "          [[-0.0068, -0.0326, -0.0263,  ...,  0.0039, -0.0150, -0.0261]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0093, -0.0447, -0.0388,  ...,  0.0117,  0.0119, -0.0262]],\n",
       "  \n",
       "          [[-0.0087, -0.0440, -0.0384,  ...,  0.0112,  0.0112, -0.0265]],\n",
       "  \n",
       "          [[-0.0090, -0.0435, -0.0368,  ...,  0.0104,  0.0117, -0.0246]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (41,\n",
       "  tensor([[[ 3.9673e-04, -9.1553e-05, -5.1880e-04,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 7.7820e-03,  5.3406e-03,  1.7090e-03,  ..., -6.0425e-03,\n",
       "             5.6763e-03,  2.7283e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-4.5776e-03, -4.2725e-03, -1.5259e-03,  ..., -3.9673e-04,\n",
       "             0.0000e+00,  4.8828e-04]],\n",
       "  \n",
       "          [[ 2.2278e-03,  4.5776e-04, -1.0986e-03,  ..., -1.8311e-04,\n",
       "             4.8828e-04,  7.9346e-04]],\n",
       "  \n",
       "          [[ 1.3550e-02,  1.3947e-02,  1.4252e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]]]),\n",
       "  tensor([[[-0.0129, -0.0535, -0.0471,  ...,  0.0114,  0.0150, -0.0335]],\n",
       "  \n",
       "          [[-0.0138, -0.0487, -0.0415,  ...,  0.0100,  0.0034, -0.0329]],\n",
       "  \n",
       "          [[-0.0130, -0.0536, -0.0473,  ...,  0.0114,  0.0150, -0.0335]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0128, -0.0540, -0.0479,  ...,  0.0114,  0.0150, -0.0335]],\n",
       "  \n",
       "          [[-0.0126, -0.0535, -0.0473,  ...,  0.0112,  0.0151, -0.0335]],\n",
       "  \n",
       "          [[-0.0126, -0.0519, -0.0461,  ...,  0.0114,  0.0150, -0.0335]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (42,\n",
       "  tensor([[[-4.8828e-04, -2.1362e-04, -3.0518e-04,  ..., -3.0518e-04,\n",
       "             1.8311e-04, -3.0518e-04]],\n",
       "  \n",
       "          [[ 4.6082e-02, -2.2888e-03,  1.3428e-03,  ...,  3.8147e-03,\n",
       "             1.5442e-02, -3.6011e-03]],\n",
       "  \n",
       "          [[-1.3031e-02, -2.6215e-02, -3.2715e-02,  ..., -8.1207e-02,\n",
       "            -8.4961e-02, -1.4893e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.1902e-03, -7.0190e-04, -1.0071e-03,  ..., -6.1035e-05,\n",
       "             3.0518e-05,  0.0000e+00]],\n",
       "  \n",
       "          [[-2.1545e-02,  1.3611e-02,  8.0505e-02,  ...,  3.3569e-04,\n",
       "            -9.4604e-04, -1.0376e-03]],\n",
       "  \n",
       "          [[ 5.9204e-03,  4.9133e-03,  4.9438e-03,  ..., -6.7749e-03,\n",
       "            -8.0261e-03, -1.1139e-02]]]),\n",
       "  tensor([[[-0.0161, -0.0482, -0.0376,  ...,  0.0052,  0.0110, -0.0304]],\n",
       "  \n",
       "          [[-0.0146, -0.0477, -0.0381,  ...,  0.0053,  0.0035, -0.0335]],\n",
       "  \n",
       "          [[-0.0149, -0.0473, -0.0354,  ..., -0.0016, -0.0052, -0.0272]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0161, -0.0481, -0.0376,  ...,  0.0053,  0.0110, -0.0303]],\n",
       "  \n",
       "          [[-0.0136, -0.0340, -0.0320,  ...,  0.0053,  0.0110, -0.0303]],\n",
       "  \n",
       "          [[-0.0160, -0.0482, -0.0375,  ...,  0.0048,  0.0109, -0.0304]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (43,\n",
       "  tensor([[[ 3.0518e-05, -6.1035e-05, -1.8311e-04,  ..., -1.0376e-02,\n",
       "             1.6510e-02, -5.0354e-03]],\n",
       "  \n",
       "          [[-2.0142e-03, -1.9836e-03, -2.8076e-03,  ...,  2.2278e-03,\n",
       "             1.8005e-03,  7.0190e-04]],\n",
       "  \n",
       "          [[-3.6438e-02, -9.7351e-03,  5.3406e-03,  ...,  2.3499e-02,\n",
       "             6.4880e-02, -4.7485e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.1545e-02,  1.3611e-02,  8.0505e-02,  ...,  3.3569e-04,\n",
       "            -9.4604e-04, -1.0376e-03]],\n",
       "  \n",
       "          [[ 1.3123e-02,  1.2970e-02,  1.4069e-02,  ..., -4.6997e-03,\n",
       "             1.4404e-02,  1.2756e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00, -3.0518e-05, -3.0518e-05,  ..., -1.3611e-02,\n",
       "            -8.3923e-03, -3.5095e-03]]]),\n",
       "  tensor([[[-0.0228, -0.0519, -0.0397,  ...,  0.0015,  0.0100, -0.0314]],\n",
       "  \n",
       "          [[-0.0228, -0.0519, -0.0395,  ...,  0.0017,  0.0111, -0.0312]],\n",
       "  \n",
       "          [[-0.0206, -0.0396, -0.0308,  ..., -0.0014, -0.0147, -0.0350]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0204, -0.0372, -0.0330,  ...,  0.0016,  0.0112, -0.0311]],\n",
       "  \n",
       "          [[-0.0230, -0.0513, -0.0388,  ...,  0.0018,  0.0100, -0.0312]],\n",
       "  \n",
       "          [[-0.0228, -0.0519, -0.0397,  ...,  0.0015,  0.0109, -0.0311]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (44,\n",
       "  tensor([[[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  4.2725e-04,\n",
       "             3.9673e-04,  1.2207e-04]],\n",
       "  \n",
       "          [[-1.8311e-04, -2.4414e-04, -1.8311e-04,  ..., -3.0518e-05,\n",
       "            -9.1553e-05,  0.0000e+00]],\n",
       "  \n",
       "          [[-5.6458e-03, -5.2185e-03, -7.6599e-03,  ...,  3.5400e-03,\n",
       "             6.1035e-05,  4.6387e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 9.1553e-05,  3.3569e-04,  1.5259e-04,  ..., -2.1362e-04,\n",
       "             1.2207e-04, -9.1553e-05]],\n",
       "  \n",
       "          [[ 1.0349e-01,  8.9935e-02,  2.2247e-02,  ...,  3.6621e-04,\n",
       "             1.5259e-04,  3.0518e-05]],\n",
       "  \n",
       "          [[ 5.5237e-03,  5.7373e-03,  5.4932e-03,  ..., -2.3438e-02,\n",
       "            -5.7129e-02, -5.6458e-02]]]),\n",
       "  tensor([[[-0.0240, -0.0487, -0.0395,  ..., -0.0023,  0.0067, -0.0333]],\n",
       "  \n",
       "          [[-0.0240, -0.0487, -0.0395,  ..., -0.0023,  0.0067, -0.0333]],\n",
       "  \n",
       "          [[-0.0239, -0.0486, -0.0393,  ..., -0.0024,  0.0061, -0.0332]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0240, -0.0487, -0.0395,  ..., -0.0024,  0.0067, -0.0332]],\n",
       "  \n",
       "          [[-0.0202, -0.0326, -0.0304,  ..., -0.0026,  0.0067, -0.0332]],\n",
       "  \n",
       "          [[-0.0243, -0.0483, -0.0392,  ..., -0.0098, -0.0167, -0.0415]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (45,\n",
       "  tensor([[[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 1.2207e-03, -1.2207e-04,  9.4604e-04,  ..., -1.8311e-04,\n",
       "            -3.3569e-04, -3.0518e-04]],\n",
       "  \n",
       "          [[-1.6785e-03, -7.0801e-03, -9.9182e-03,  ..., -8.3923e-03,\n",
       "            -1.0895e-02, -1.3092e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.3798e-01, -2.0419e-01, -1.9516e-01,  ..., -2.1667e-02,\n",
       "            -1.8463e-02, -1.5991e-02]],\n",
       "  \n",
       "          [[ 1.7365e-02,  1.7181e-02,  1.6052e-02,  ..., -1.3702e-02,\n",
       "            -1.5930e-02, -1.1200e-02]],\n",
       "  \n",
       "          [[ 1.0349e-01,  8.9935e-02,  2.2247e-02,  ...,  3.6621e-04,\n",
       "             1.5259e-04,  3.0518e-05]]]),\n",
       "  tensor([[[-0.0322, -0.0698, -0.0594,  ...,  0.0111,  0.0051, -0.0431]],\n",
       "  \n",
       "          [[-0.0322, -0.0697, -0.0593,  ...,  0.0110,  0.0051, -0.0431]],\n",
       "  \n",
       "          [[-0.0317, -0.0696, -0.0596,  ...,  0.0111,  0.0050, -0.0432]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0306, -0.0683, -0.0573,  ...,  0.0093,  0.0038, -0.0439]],\n",
       "  \n",
       "          [[-0.0322, -0.0698, -0.0597,  ...,  0.0109,  0.0047, -0.0434]],\n",
       "  \n",
       "          [[-0.0296, -0.0675, -0.0586,  ...,  0.0110,  0.0051, -0.0431]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (46,\n",
       "  tensor([[[ 6.4087e-04, -4.7913e-03,  9.4604e-04,  ...,  3.6316e-03,\n",
       "             9.8267e-03, -1.2817e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-3.0518e-05, -4.0588e-03, -1.4038e-03,  ...,  1.5564e-03,\n",
       "             1.3428e-03,  3.0518e-05]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.5137e-02, -1.4069e-02, -1.2909e-02,  ...,  7.9346e-04,\n",
       "             7.3242e-04,  3.9673e-04]],\n",
       "  \n",
       "          [[-4.4556e-03, -2.4414e-04, -4.8828e-04,  ..., -4.2725e-04,\n",
       "             2.7466e-04, -9.1553e-05]],\n",
       "  \n",
       "          [[ 1.3123e-03, -1.0986e-03,  1.4343e-03,  ...,  1.8311e-04,\n",
       "             1.6479e-03,  3.6011e-03]]]),\n",
       "  tensor([[[-0.0293, -0.0576, -0.0472,  ..., -0.0046,  0.0061, -0.0411]],\n",
       "  \n",
       "          [[-0.0297, -0.0571, -0.0465,  ..., -0.0045,  0.0065, -0.0410]],\n",
       "  \n",
       "          [[-0.0295, -0.0571, -0.0465,  ..., -0.0047,  0.0062, -0.0412]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0283, -0.0548, -0.0418,  ..., -0.0045,  0.0066, -0.0410]],\n",
       "  \n",
       "          [[-0.0297, -0.0571, -0.0464,  ..., -0.0045,  0.0065, -0.0410]],\n",
       "  \n",
       "          [[-0.0296, -0.0572, -0.0466,  ..., -0.0045,  0.0065, -0.0411]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (47,\n",
       "  tensor([[[ 1.1963e-02, -6.1035e-04, -5.2795e-03,  ..., -1.2726e-02,\n",
       "            -1.4587e-02, -1.3397e-02]],\n",
       "  \n",
       "          [[ 3.0518e-04, -4.5776e-04,  2.4414e-04,  ...,  4.5776e-04,\n",
       "            -2.7466e-04, -3.0518e-04]],\n",
       "  \n",
       "          [[ 3.0518e-05,  3.0518e-05,  0.0000e+00,  ...,  3.3569e-04,\n",
       "             3.3569e-04,  3.0518e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 3.0518e-05,  6.1035e-05,  0.0000e+00,  ..., -2.8992e-03,\n",
       "             4.9133e-03,  2.6245e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -2.4414e-04,\n",
       "             2.1362e-04,  0.0000e+00]],\n",
       "  \n",
       "          [[-8.0566e-03,  3.4119e-02,  3.8086e-02,  ...,  5.3406e-03,\n",
       "             1.2054e-02,  1.6266e-02]]]),\n",
       "  tensor([[[-0.0246, -0.0627, -0.0551,  ...,  0.0009,  0.0031, -0.0487]],\n",
       "  \n",
       "          [[-0.0241, -0.0623, -0.0551,  ...,  0.0017,  0.0062, -0.0477]],\n",
       "  \n",
       "          [[-0.0242, -0.0623, -0.0550,  ...,  0.0016,  0.0062, -0.0476]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0242, -0.0623, -0.0550,  ...,  0.0017,  0.0060, -0.0478]],\n",
       "  \n",
       "          [[-0.0242, -0.0623, -0.0550,  ...,  0.0015,  0.0062, -0.0476]],\n",
       "  \n",
       "          [[-0.0251, -0.0592, -0.0483,  ..., -0.0062, -0.0249, -0.0470]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (48,\n",
       "  tensor([[[ 1.2207e-03, -8.1177e-03,  6.1646e-03,  ..., -2.9114e-02,\n",
       "             2.5848e-02,  1.4496e-02]],\n",
       "  \n",
       "          [[-3.6621e-04, -9.7656e-04, -1.3123e-03,  ...,  2.7466e-04,\n",
       "             9.1553e-05, -1.6174e-03]],\n",
       "  \n",
       "          [[ 1.9226e-03,  8.8501e-04,  1.2512e-03,  ..., -1.4343e-03,\n",
       "            -1.3123e-03, -1.0376e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.0284e-02,  3.9673e-04, -1.6785e-03,  ...,  2.7161e-03,\n",
       "             3.2043e-03,  2.6245e-03]],\n",
       "  \n",
       "          [[-3.6926e-03, -4.0283e-03, -5.0964e-03,  ..., -6.7139e-04,\n",
       "            -1.4648e-03, -5.4932e-04]],\n",
       "  \n",
       "          [[ 5.5603e-02,  2.8076e-02,  2.0721e-02,  ..., -2.0660e-02,\n",
       "             1.3580e-02,  8.4290e-02]]]),\n",
       "  tensor([[[-0.0223, -0.0520, -0.0400,  ..., -0.0074, -0.0126, -0.0493]],\n",
       "  \n",
       "          [[-0.0220, -0.0571, -0.0493,  ..., -0.0019,  0.0042, -0.0515]],\n",
       "  \n",
       "          [[-0.0221, -0.0571, -0.0493,  ..., -0.0017,  0.0042, -0.0515]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0218, -0.0568, -0.0492,  ..., -0.0018,  0.0044, -0.0514]],\n",
       "  \n",
       "          [[-0.0221, -0.0569, -0.0491,  ..., -0.0017,  0.0041, -0.0514]],\n",
       "  \n",
       "          [[-0.0216, -0.0526, -0.0428,  ..., -0.0106, -0.0204, -0.0469]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (49,\n",
       "  tensor([[[-1.8860e-02, -1.4954e-02, -1.5167e-02,  ..., -2.0905e-02,\n",
       "            -2.0325e-02, -1.9867e-02]],\n",
       "  \n",
       "          [[ 1.1993e-02, -4.7607e-03, -2.5024e-03,  ...,  2.2888e-03,\n",
       "            -2.9907e-03, -2.7466e-04]],\n",
       "  \n",
       "          [[ 5.8899e-03, -8.0872e-03, -3.3569e-03,  ...,  4.7302e-03,\n",
       "            -1.2299e-02,  9.4910e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.2329e-02,  5.4321e-03, -4.2725e-03,  ...,  5.0659e-03,\n",
       "            -5.6763e-03,  1.7700e-03]],\n",
       "  \n",
       "          [[ 8.8501e-04, -1.8311e-04, -3.3569e-04,  ...,  3.0823e-03,\n",
       "             5.1575e-03,  1.5259e-04]],\n",
       "  \n",
       "          [[-5.4932e-04,  4.5776e-04,  9.1553e-05,  ...,  2.1362e-04,\n",
       "             8.1482e-03,  1.5930e-02]]]),\n",
       "  tensor([[[-0.0334, -0.0544, -0.0431,  ..., -0.0114, -0.0007, -0.0546]],\n",
       "  \n",
       "          [[-0.0335, -0.0569, -0.0465,  ..., -0.0134,  0.0039, -0.0495]],\n",
       "  \n",
       "          [[-0.0333, -0.0571, -0.0472,  ..., -0.0143,  0.0037, -0.0493]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0248, -0.0333, -0.0212,  ..., -0.0136,  0.0011, -0.0488]],\n",
       "  \n",
       "          [[-0.0339, -0.0585, -0.0475,  ..., -0.0140,  0.0037, -0.0495]],\n",
       "  \n",
       "          [[-0.0339, -0.0585, -0.0474,  ..., -0.0151, -0.0016, -0.0502]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (50,\n",
       "  tensor([[[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  4.8828e-04,\n",
       "             3.9673e-04,  3.3569e-04]],\n",
       "  \n",
       "          [[ 3.2959e-02,  3.9612e-02,  4.2725e-02,  ...,  3.1036e-02,\n",
       "             3.0884e-02,  3.2227e-02]],\n",
       "  \n",
       "          [[-2.5330e-02, -2.4445e-02, -2.0721e-02,  ..., -3.1433e-03,\n",
       "            -2.8076e-03,  5.7983e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.1993e-02, -4.7607e-03, -2.5024e-03,  ...,  2.2888e-03,\n",
       "            -2.9907e-03, -2.7466e-04]],\n",
       "  \n",
       "          [[-1.5137e-02, -1.4069e-02, -1.2909e-02,  ...,  7.9346e-04,\n",
       "             7.3242e-04,  3.9673e-04]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -9.1553e-05,\n",
       "             6.1035e-05, -6.1035e-05]]]),\n",
       "  tensor([[[-0.0311, -0.0572, -0.0490,  ..., -0.0129,  0.0056, -0.0515]],\n",
       "  \n",
       "          [[-0.0300, -0.0460, -0.0387,  ..., -0.0148, -0.0229, -0.0514]],\n",
       "  \n",
       "          [[-0.0310, -0.0551, -0.0471,  ..., -0.0125,  0.0044, -0.0534]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0307, -0.0540, -0.0458,  ..., -0.0123,  0.0053, -0.0517]],\n",
       "  \n",
       "          [[-0.0263, -0.0400, -0.0317,  ..., -0.0127,  0.0058, -0.0515]],\n",
       "  \n",
       "          [[-0.0311, -0.0572, -0.0490,  ..., -0.0129,  0.0056, -0.0515]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (51,\n",
       "  tensor([[[ 6.2561e-03,  4.4250e-03,  2.7161e-03,  ..., -6.1035e-05,\n",
       "             3.6621e-04,  7.0190e-04]],\n",
       "  \n",
       "          [[-1.9531e-03,  2.6855e-03, -1.0071e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-1.2726e-02, -8.8501e-03, -5.9204e-03,  ..., -1.3458e-02,\n",
       "            -7.9651e-03,  2.8076e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 9.7656e-04, -3.3569e-02,  6.2500e-02,  ..., -2.0233e-02,\n",
       "            -1.1536e-02,  7.6294e-04]],\n",
       "  \n",
       "          [[ 6.4087e-04, -4.7913e-03,  9.4604e-04,  ...,  3.6316e-03,\n",
       "             9.8267e-03, -1.2817e-03]],\n",
       "  \n",
       "          [[ 2.5635e-03,  1.6479e-03,  1.1902e-03,  ...,  2.5848e-02,\n",
       "             2.4841e-02,  2.6031e-02]]]),\n",
       "  tensor([[[-0.0307, -0.0651, -0.0565,  ..., -0.0026,  0.0009, -0.0594]],\n",
       "  \n",
       "          [[-0.0248, -0.0496, -0.0450,  ..., -0.0025,  0.0008, -0.0594]],\n",
       "  \n",
       "          [[-0.0306, -0.0650, -0.0565,  ..., -0.0025,  0.0008, -0.0591]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0313, -0.0556, -0.0463,  ..., -0.0042, -0.0015, -0.0581]],\n",
       "  \n",
       "          [[-0.0301, -0.0660, -0.0580,  ..., -0.0028,  0.0004, -0.0595]],\n",
       "  \n",
       "          [[-0.0308, -0.0650, -0.0563,  ..., -0.0049,  0.0002, -0.0578]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (52,\n",
       "  tensor([[[-3.5400e-03, -4.2114e-03, -5.2795e-03,  ...,  9.3872e-02,\n",
       "             1.2210e-01,  1.5958e-01]],\n",
       "  \n",
       "          [[ 2.8076e-03,  7.4463e-03,  5.9814e-03,  ...,  1.3489e-02,\n",
       "             1.3824e-02,  1.0773e-02]],\n",
       "  \n",
       "          [[-1.5259e-04, -2.4414e-04, -3.3569e-04,  ...,  2.4414e-04,\n",
       "            -1.5259e-04,  2.1362e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 4.6082e-02, -2.2888e-03,  1.3428e-03,  ...,  3.8147e-03,\n",
       "             1.5442e-02, -3.6011e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-2.9846e-02, -3.1647e-02, -4.8615e-02,  ..., -8.3313e-03,\n",
       "            -2.8687e-03, -2.0447e-03]]]),\n",
       "  tensor([[[-0.0450, -0.0684, -0.0541,  ..., -0.0330, -0.0612, -0.0696]],\n",
       "  \n",
       "          [[-0.0438, -0.0667, -0.0524,  ..., -0.0181,  0.0008, -0.0594]],\n",
       "  \n",
       "          [[-0.0445, -0.0684, -0.0540,  ..., -0.0183,  0.0015, -0.0587]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0429, -0.0652, -0.0503,  ..., -0.0185, -0.0149, -0.0648]],\n",
       "  \n",
       "          [[-0.0445, -0.0684, -0.0540,  ..., -0.0184,  0.0017, -0.0587]],\n",
       "  \n",
       "          [[-0.0444, -0.0643, -0.0492,  ..., -0.0183,  0.0004, -0.0592]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (53,\n",
       "  tensor([[[-0.0042, -0.0017, -0.0060,  ...,  0.0108,  0.0034, -0.0043]],\n",
       "  \n",
       "          [[ 0.0002,  0.0002,  0.0002,  ..., -0.0058, -0.0038, -0.0026]],\n",
       "  \n",
       "          [[-0.0092, -0.0167, -0.0199,  ..., -0.0038, -0.0045, -0.0012]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0029,  0.0016,  0.0041,  ...,  0.0004,  0.0008,  0.0008]],\n",
       "  \n",
       "          [[-0.0253, -0.0244, -0.0207,  ..., -0.0031, -0.0028,  0.0006]],\n",
       "  \n",
       "          [[ 0.0002, -0.0043, -0.0051,  ...,  0.0000,  0.0000,  0.0000]]]),\n",
       "  tensor([[[-0.0379, -0.0748, -0.0620,  ..., -0.0105, -0.0014, -0.0654]],\n",
       "  \n",
       "          [[-0.0380, -0.0744, -0.0615,  ..., -0.0101, -0.0009, -0.0651]],\n",
       "  \n",
       "          [[-0.0380, -0.0740, -0.0611,  ..., -0.0100, -0.0017, -0.0654]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0380, -0.0743, -0.0614,  ..., -0.0102, -0.0007, -0.0650]],\n",
       "  \n",
       "          [[-0.0384, -0.0737, -0.0605,  ..., -0.0102, -0.0007, -0.0650]],\n",
       "  \n",
       "          [[-0.0356, -0.0691, -0.0553,  ..., -0.0102, -0.0007, -0.0650]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (54,\n",
       "  tensor([[[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-1.5259e-04, -8.5449e-04, -4.3030e-03,  ..., -7.7820e-03,\n",
       "            -5.7983e-03, -3.5400e-03]],\n",
       "  \n",
       "          [[ 3.0518e-05,  0.0000e+00, -3.0518e-05,  ..., -1.0681e-03,\n",
       "            -1.0376e-02, -8.1787e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-9.1858e-03, -1.6663e-02, -1.9928e-02,  ..., -3.8452e-03,\n",
       "            -4.4556e-03, -1.1597e-03]],\n",
       "  \n",
       "          [[-5.8289e-03, -6.8054e-03, -7.4463e-03,  ...,  6.2714e-02,\n",
       "             5.3375e-02,  4.3518e-02]],\n",
       "  \n",
       "          [[-6.6833e-03, -4.3640e-03,  1.2024e-02,  ..., -8.5144e-03,\n",
       "            -1.6571e-02,  2.8687e-03]]]),\n",
       "  tensor([[[-0.0386, -0.0731, -0.0614,  ..., -0.0107, -0.0034, -0.0661]],\n",
       "  \n",
       "          [[-0.0386, -0.0731, -0.0615,  ..., -0.0108, -0.0030, -0.0660]],\n",
       "  \n",
       "          [[-0.0386, -0.0731, -0.0614,  ..., -0.0114, -0.0042, -0.0656]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0386, -0.0726, -0.0609,  ..., -0.0106, -0.0048, -0.0666]],\n",
       "  \n",
       "          [[-0.0386, -0.0725, -0.0603,  ..., -0.0130, -0.0120, -0.0621]],\n",
       "  \n",
       "          [[-0.0386, -0.0727, -0.0608,  ..., -0.0112, -0.0051, -0.0667]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (55,\n",
       "  tensor([[[-2.7466e-04, -5.4932e-04, -6.7139e-04,  ...,  4.8828e-04,\n",
       "             5.4932e-04,  5.1880e-04]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  3.0518e-05,  ..., -3.2196e-02,\n",
       "             3.0212e-03,  7.1655e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.1973e-03, -1.6479e-03, -1.8311e-03,  ..., -2.5635e-03,\n",
       "            -2.6245e-03, -2.6245e-03]],\n",
       "  \n",
       "          [[-4.0344e-02, -3.7537e-03,  4.5349e-02,  ..., -1.3123e-02,\n",
       "            -7.8156e-02, -2.3102e-02]],\n",
       "  \n",
       "          [[ 8.8501e-04, -1.8311e-04, -3.3569e-04,  ...,  3.0823e-03,\n",
       "             5.1575e-03,  1.5259e-04]]]),\n",
       "  tensor([[[-0.0475, -0.0745, -0.0641,  ..., -0.0191, -0.0021, -0.0690]],\n",
       "  \n",
       "          [[-0.0476, -0.0744, -0.0640,  ..., -0.0190, -0.0021, -0.0690]],\n",
       "  \n",
       "          [[-0.0476, -0.0745, -0.0641,  ..., -0.0386, -0.0715, -0.0828]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0475, -0.0745, -0.0640,  ..., -0.0190, -0.0022, -0.0691]],\n",
       "  \n",
       "          [[-0.0443, -0.0589, -0.0531,  ..., -0.0287, -0.0348, -0.0772]],\n",
       "  \n",
       "          [[-0.0475, -0.0744, -0.0641,  ..., -0.0194, -0.0024, -0.0692]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (56,\n",
       "  tensor([[[-0.0403, -0.0038,  0.0453,  ..., -0.0131, -0.0782, -0.0231]],\n",
       "  \n",
       "          [[ 0.0044,  0.0036,  0.0036,  ...,  0.0085,  0.0031,  0.0172]],\n",
       "  \n",
       "          [[-0.0123,  0.0054, -0.0043,  ...,  0.0051, -0.0057,  0.0018]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[-0.1568, -0.2625, -0.2172,  ..., -0.0053, -0.0303,  0.0664]],\n",
       "  \n",
       "          [[ 0.0524,  0.0274,  0.0053,  ...,  0.0262,  0.0224,  0.0006]]]),\n",
       "  tensor([[[-0.0501, -0.0742, -0.0571,  ..., -0.0187, -0.0303, -0.0728]],\n",
       "  \n",
       "          [[-0.0489, -0.0793, -0.0665,  ..., -0.0149, -0.0084, -0.0715]],\n",
       "  \n",
       "          [[-0.0481, -0.0745, -0.0596,  ..., -0.0145, -0.0062, -0.0706]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0488, -0.0792, -0.0664,  ..., -0.0143, -0.0058, -0.0702]],\n",
       "  \n",
       "          [[-0.0399, -0.0451, -0.0579,  ..., -0.0177, -0.0103, -0.0698]],\n",
       "  \n",
       "          [[-0.0480, -0.0782, -0.0658,  ..., -0.0145, -0.0058, -0.0718]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (57,\n",
       "  tensor([[[ 7.9346e-04,  7.3242e-04,  5.4932e-04,  ..., -2.4414e-04,\n",
       "            -2.4414e-04, -2.1362e-04]],\n",
       "  \n",
       "          [[-2.7466e-04,  1.5259e-04,  3.9673e-04,  ..., -1.8311e-03,\n",
       "            -1.8616e-03, -1.4648e-03]],\n",
       "  \n",
       "          [[-6.1035e-05, -3.0518e-05, -6.1035e-05,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.5259e-04, -8.5449e-04, -4.3030e-03,  ..., -7.7820e-03,\n",
       "            -5.7983e-03, -3.5400e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  3.0518e-05,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 5.2429e-02,  2.7374e-02,  5.2795e-03,  ...,  2.6215e-02,\n",
       "             2.2400e-02,  6.1035e-04]]]),\n",
       "  tensor([[[-0.0503, -0.0737, -0.0625,  ..., -0.0235, -0.0092, -0.0735]],\n",
       "  \n",
       "          [[-0.0503, -0.0737, -0.0625,  ..., -0.0236, -0.0091, -0.0735]],\n",
       "  \n",
       "          [[-0.0503, -0.0737, -0.0625,  ..., -0.0235, -0.0092, -0.0735]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0503, -0.0736, -0.0625,  ..., -0.0237, -0.0087, -0.0734]],\n",
       "  \n",
       "          [[-0.0503, -0.0737, -0.0625,  ..., -0.0235, -0.0092, -0.0735]],\n",
       "  \n",
       "          [[-0.0499, -0.0716, -0.0606,  ..., -0.0227, -0.0109, -0.0785]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (58,\n",
       "  tensor([[[-1.8860e-02, -1.4954e-02, -1.5167e-02,  ..., -2.0905e-02,\n",
       "            -2.0325e-02, -1.9867e-02]],\n",
       "  \n",
       "          [[ 2.0142e-03,  1.4954e-03,  1.2207e-03,  ..., -2.5330e-03,\n",
       "            -2.9602e-03, -2.0752e-03]],\n",
       "  \n",
       "          [[-1.1383e-02, -1.3153e-02, -4.8523e-03,  ...,  9.8267e-03,\n",
       "             9.4604e-04, -2.5330e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-7.7728e-02, -3.1677e-02, -3.3417e-02,  ..., -9.6741e-03,\n",
       "             2.2858e-02, -7.6294e-03]],\n",
       "  \n",
       "          [[ 9.1553e-05,  2.8687e-02,  6.1707e-02,  ...,  6.5002e-03,\n",
       "             9.1553e-03,  8.8806e-03]],\n",
       "  \n",
       "          [[ 8.8806e-03,  8.8806e-03,  7.9346e-03,  ..., -6.1035e-02,\n",
       "            -6.6315e-02, -5.5756e-02]]]),\n",
       "  tensor([[[-0.0565, -0.0854, -0.0710,  ..., -0.0186, -0.0137, -0.0791]],\n",
       "  \n",
       "          [[-0.0571, -0.0861, -0.0716,  ..., -0.0185, -0.0127, -0.0784]],\n",
       "  \n",
       "          [[-0.0568, -0.0853, -0.0710,  ..., -0.0189, -0.0126, -0.0782]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0561, -0.0828, -0.0677,  ..., -0.0201, -0.0160, -0.0765]],\n",
       "  \n",
       "          [[-0.0558, -0.0791, -0.0624,  ..., -0.0192, -0.0135, -0.0788]],\n",
       "  \n",
       "          [[-0.0573, -0.0864, -0.0719,  ..., -0.0238, -0.0173, -0.0761]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (59,\n",
       "  tensor([[[ 5.6152e-03,  8.3008e-03,  3.6621e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-5.5237e-03, -4.6387e-03, -5.1575e-03,  ..., -1.1292e-03,\n",
       "             3.0518e-05,  1.8311e-04]],\n",
       "  \n",
       "          [[ 1.2573e-02,  1.1597e-02,  7.6599e-03,  ..., -5.3406e-03,\n",
       "            -6.9885e-03, -5.4932e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.1362e-04, -3.6621e-04, -5.1880e-04,  ...,  3.5706e-03,\n",
       "             3.2654e-03,  3.0518e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -1.5869e-03,\n",
       "            -1.0986e-03, -1.0986e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  4.2725e-04,\n",
       "             3.9673e-04,  1.2207e-04]]]),\n",
       "  tensor([[[-0.0531, -0.0747, -0.0623,  ..., -0.0245, -0.0082, -0.0733]],\n",
       "  \n",
       "          [[-0.0532, -0.0739, -0.0615,  ..., -0.0245, -0.0083, -0.0733]],\n",
       "  \n",
       "          [[-0.0530, -0.0744, -0.0620,  ..., -0.0245, -0.0082, -0.0733]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0535, -0.0749, -0.0626,  ..., -0.0246, -0.0086, -0.0732]],\n",
       "  \n",
       "          [[-0.0535, -0.0749, -0.0626,  ..., -0.0244, -0.0084, -0.0733]],\n",
       "  \n",
       "          [[-0.0535, -0.0749, -0.0626,  ..., -0.0245, -0.0083, -0.0733]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (60,\n",
       "  tensor([[[ 0.0000,  0.0000,  0.0000,  ..., -0.0029,  0.0480,  0.0134]],\n",
       "  \n",
       "          [[-0.0253, -0.0244, -0.0207,  ..., -0.0031, -0.0028,  0.0006]],\n",
       "  \n",
       "          [[ 0.0524,  0.0274,  0.0053,  ...,  0.0262,  0.0224,  0.0006]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0010, -0.0006,  0.0002,  ...,  0.0021,  0.0072,  0.0002]],\n",
       "  \n",
       "          [[ 0.0032,  0.0057,  0.0041,  ...,  0.0314,  0.0291,  0.0257]],\n",
       "  \n",
       "          [[-0.0123, -0.0014, -0.0053,  ...,  0.0028, -0.0079, -0.0070]]]),\n",
       "  tensor([[[-0.0557, -0.0813, -0.0706,  ..., -0.0247, -0.0381, -0.0853]],\n",
       "  \n",
       "          [[-0.0559, -0.0803, -0.0689,  ..., -0.0269, -0.0118, -0.0796]],\n",
       "  \n",
       "          [[-0.0561, -0.0787, -0.0662,  ..., -0.0262, -0.0136, -0.0844]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0558, -0.0811, -0.0703,  ..., -0.0269, -0.0109, -0.0792]],\n",
       "  \n",
       "          [[-0.0562, -0.0811, -0.0699,  ..., -0.0296, -0.0233, -0.0766]],\n",
       "  \n",
       "          [[-0.0558, -0.0816, -0.0707,  ..., -0.0269, -0.0117, -0.0795]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (61,\n",
       "  tensor([[[-5.4932e-04,  4.5776e-04,  9.1553e-05,  ...,  2.1362e-04,\n",
       "             8.1482e-03,  1.5930e-02]],\n",
       "  \n",
       "          [[ 8.8806e-03,  8.8806e-03,  7.9346e-03,  ..., -6.1035e-02,\n",
       "            -6.6315e-02, -5.5756e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.4343e-03,  1.3733e-03,  1.8311e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-5.5817e-02, -3.5248e-02,  2.2156e-02,  ...,  8.7280e-03,\n",
       "             1.4160e-02,  1.3062e-02]],\n",
       "  \n",
       "          [[-9.1553e-05,  9.1553e-05,  3.9673e-04,  ..., -7.6294e-04,\n",
       "            -6.1035e-04, -6.7139e-04]]]),\n",
       "  tensor([[[-0.0562, -0.0883, -0.0758,  ..., -0.0246, -0.0150, -0.0877]],\n",
       "  \n",
       "          [[-0.0562, -0.0883, -0.0761,  ..., -0.0303, -0.0212, -0.0845]],\n",
       "  \n",
       "          [[-0.0562, -0.0882, -0.0758,  ..., -0.0235, -0.0146, -0.0876]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0562, -0.0883, -0.0759,  ..., -0.0235, -0.0146, -0.0876]],\n",
       "  \n",
       "          [[-0.0552, -0.0835, -0.0717,  ..., -0.0240, -0.0145, -0.0875]],\n",
       "  \n",
       "          [[-0.0562, -0.0882, -0.0757,  ..., -0.0235, -0.0146, -0.0877]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (62,\n",
       "  tensor([[[ 9.7656e-04, -3.3569e-02,  6.2500e-02,  ..., -2.0233e-02,\n",
       "            -1.1536e-02,  7.6294e-04]],\n",
       "  \n",
       "          [[-3.9673e-04, -4.2725e-04, -3.3569e-04,  ...,  6.1035e-05,\n",
       "             0.0000e+00,  1.8311e-04]],\n",
       "  \n",
       "          [[-2.5940e-03, -2.8076e-03, -2.8076e-03,  ..., -1.9226e-03,\n",
       "            -1.8311e-03, -2.4109e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  3.0518e-05,  ..., -7.3456e-02,\n",
       "            -7.7423e-02, -7.4677e-02]],\n",
       "  \n",
       "          [[-1.6785e-03, -7.0801e-03, -9.9182e-03,  ..., -8.3923e-03,\n",
       "            -1.0895e-02, -1.3092e-02]],\n",
       "  \n",
       "          [[-4.2114e-03, -1.6785e-03, -6.0425e-03,  ...,  1.0834e-02,\n",
       "             3.4485e-03, -4.3030e-03]]]),\n",
       "  tensor([[[-0.0604, -0.0627, -0.0595,  ..., -0.0364, -0.0237, -0.0781]],\n",
       "  \n",
       "          [[-0.0674, -0.0799, -0.0675,  ..., -0.0349, -0.0175, -0.0786]],\n",
       "  \n",
       "          [[-0.0671, -0.0803, -0.0678,  ..., -0.0347, -0.0178, -0.0786]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0674, -0.0799, -0.0675,  ..., -0.0341, -0.0267, -0.0862]],\n",
       "  \n",
       "          [[-0.0671, -0.0790, -0.0666,  ..., -0.0346, -0.0177, -0.0786]],\n",
       "  \n",
       "          [[-0.0672, -0.0805, -0.0682,  ..., -0.0351, -0.0202, -0.0791]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (63,\n",
       "  tensor([[[-1.2512e-03, -9.4604e-04,  6.0730e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 2.7008e-02,  3.3051e-02,  3.8086e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-4.5166e-03, -4.2114e-03, -3.7842e-03,  ...,  2.2888e-03,\n",
       "             1.8616e-03,  1.1597e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.4719e-03,  1.2207e-03, -3.7842e-03,  ...,  3.9673e-04,\n",
       "            -6.1035e-05, -3.6621e-04]],\n",
       "  \n",
       "          [[ 1.8707e-02,  1.3367e-02,  1.5564e-03,  ...,  9.1553e-05,\n",
       "             1.8311e-04,  2.1362e-04]],\n",
       "  \n",
       "          [[-5.1270e-03, -5.2795e-03, -5.4321e-03,  ...,  6.3171e-03,\n",
       "             1.0864e-02,  1.2268e-02]]]),\n",
       "  tensor([[[-0.0690, -0.0849, -0.0714,  ..., -0.0402, -0.0204, -0.0905]],\n",
       "  \n",
       "          [[-0.0658, -0.0666, -0.0586,  ..., -0.0402, -0.0204, -0.0905]],\n",
       "  \n",
       "          [[-0.0688, -0.0857, -0.0717,  ..., -0.0402, -0.0205, -0.0905]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0689, -0.0849, -0.0711,  ..., -0.0402, -0.0204, -0.0905]],\n",
       "  \n",
       "          [[-0.0679, -0.0814, -0.0666,  ..., -0.0402, -0.0204, -0.0905]],\n",
       "  \n",
       "          [[-0.0687, -0.0857, -0.0716,  ..., -0.0402, -0.0207, -0.0906]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (64,\n",
       "  tensor([[[ 1.6479e-02, -1.7792e-02, -3.8788e-02,  ...,  2.8687e-03,\n",
       "            -6.8359e-03, -4.1443e-02]],\n",
       "  \n",
       "          [[-3.9673e-04, -4.2725e-04, -3.3569e-04,  ...,  6.1035e-05,\n",
       "             0.0000e+00,  1.8311e-04]],\n",
       "  \n",
       "          [[ 0.0000e+00,  3.0518e-05,  3.0518e-05,  ...,  2.7649e-02,\n",
       "             2.5360e-02,  2.0142e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.1261e-02, -1.1108e-02, -1.1047e-02,  ...,  1.2848e-02,\n",
       "             1.0010e-02,  1.1719e-02]],\n",
       "  \n",
       "          [[ 3.2471e-02,  2.2400e-02,  2.3712e-02,  ...,  6.5002e-03,\n",
       "             6.3477e-03,  6.9885e-03]],\n",
       "  \n",
       "          [[ 1.2573e-02,  1.1597e-02,  7.6599e-03,  ..., -5.3406e-03,\n",
       "            -6.9885e-03, -5.4932e-03]]]),\n",
       "  tensor([[[-0.0624, -0.0787, -0.0671,  ..., -0.0682, -0.0990, -0.1040]],\n",
       "  \n",
       "          [[-0.0601, -0.0811, -0.0696,  ..., -0.0310, -0.0121, -0.0828]],\n",
       "  \n",
       "          [[-0.0602, -0.0810, -0.0695,  ..., -0.0319, -0.0127, -0.0832]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0601, -0.0812, -0.0695,  ..., -0.0317, -0.0133, -0.0827]],\n",
       "  \n",
       "          [[-0.0586, -0.0789, -0.0672,  ..., -0.0310, -0.0124, -0.0829]],\n",
       "  \n",
       "          [[-0.0600, -0.0815, -0.0698,  ..., -0.0309, -0.0121, -0.0829]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (65,\n",
       "  tensor([[[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -1.5259e-04,\n",
       "            -9.1553e-05, -3.0518e-04]],\n",
       "  \n",
       "          [[-1.1383e-02, -1.3153e-02, -4.8523e-03,  ...,  9.8267e-03,\n",
       "             9.4604e-04, -2.5330e-03]],\n",
       "  \n",
       "          [[ 3.3569e-04,  2.7466e-04,  1.5259e-04,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.4343e-03,  2.1362e-03, -2.6550e-03,  ...,  6.3477e-03,\n",
       "             7.1716e-03,  7.2937e-03]],\n",
       "  \n",
       "          [[-1.2299e-02, -1.4343e-03, -5.2795e-03,  ...,  2.7771e-03,\n",
       "            -7.9041e-03, -7.0496e-03]],\n",
       "  \n",
       "          [[ 5.5847e-03,  6.9275e-03,  8.3923e-03,  ..., -6.4697e-03,\n",
       "            -6.5308e-03, -6.1646e-03]]]),\n",
       "  tensor([[[-0.0687, -0.0895, -0.0781,  ..., -0.0366, -0.0138, -0.0921]],\n",
       "  \n",
       "          [[-0.0682, -0.0808, -0.0668,  ..., -0.0374, -0.0167, -0.0914]],\n",
       "  \n",
       "          [[-0.0687, -0.0895, -0.0781,  ..., -0.0367, -0.0137, -0.0921]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0687, -0.0892, -0.0782,  ..., -0.0368, -0.0137, -0.0921]],\n",
       "  \n",
       "          [[-0.0690, -0.0896, -0.0786,  ..., -0.0363, -0.0159, -0.0942]],\n",
       "  \n",
       "          [[-0.0687, -0.0896, -0.0783,  ..., -0.0365, -0.0136, -0.0922]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (66,\n",
       "  tensor([[[ 3.0518e-05,  6.1035e-05,  0.0000e+00,  ..., -2.8992e-03,\n",
       "             4.9133e-03,  2.6245e-03]],\n",
       "  \n",
       "          [[ 1.0376e-03,  7.0190e-04,  7.0190e-04,  ...,  2.1973e-03,\n",
       "             9.7656e-04, -3.2654e-03]],\n",
       "  \n",
       "          [[ 8.5449e-04,  7.6294e-04,  6.7139e-04,  ..., -7.0190e-03,\n",
       "            -6.6528e-03, -6.5308e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.4343e-03,  2.1362e-03, -2.6550e-03,  ...,  6.3477e-03,\n",
       "             7.1716e-03,  7.2937e-03]],\n",
       "  \n",
       "          [[ 3.5095e-03,  1.4954e-03, -3.0518e-05,  ..., -1.6174e-03,\n",
       "            -3.2959e-03,  1.8341e-02]],\n",
       "  \n",
       "          [[-1.8921e-03, -1.9226e-03, -9.1553e-05,  ..., -4.3030e-03,\n",
       "             8.2397e-04, -1.4954e-03]]]),\n",
       "  tensor([[[-0.0788, -0.0935, -0.0777,  ..., -0.0418, -0.0249, -0.0974]],\n",
       "  \n",
       "          [[-0.0789, -0.0934, -0.0776,  ..., -0.0415, -0.0254, -0.0974]],\n",
       "  \n",
       "          [[-0.0789, -0.0934, -0.0776,  ..., -0.0418, -0.0248, -0.0973]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0789, -0.0934, -0.0775,  ..., -0.0419, -0.0249, -0.0974]],\n",
       "  \n",
       "          [[-0.0786, -0.0934, -0.0778,  ..., -0.0419, -0.0272, -0.0968]],\n",
       "  \n",
       "          [[-0.0788, -0.0935, -0.0776,  ..., -0.0427, -0.0256, -0.0967]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (67,\n",
       "  tensor([[[ 1.9226e-03,  6.9580e-03,  9.3994e-03,  ...,  1.8311e-04,\n",
       "             2.1362e-04,  2.4414e-04]],\n",
       "  \n",
       "          [[-4.4556e-03, -2.8076e-03,  9.7351e-03,  ...,  0.0000e+00,\n",
       "             3.0518e-05,  0.0000e+00]],\n",
       "  \n",
       "          [[-6.9885e-03, -6.7749e-03, -6.8970e-03,  ...,  5.5542e-03,\n",
       "            -1.2878e-02, -1.2756e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.7466e-04,  1.5259e-04,  3.9673e-04,  ..., -1.8311e-03,\n",
       "            -1.8616e-03, -1.4648e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -1.5869e-03,\n",
       "            -1.0986e-03, -1.0986e-03]],\n",
       "  \n",
       "          [[-3.0518e-05, -6.1035e-05,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00, -6.1035e-05]]]),\n",
       "  tensor([[[-0.0587, -0.0843, -0.0720,  ..., -0.0321, -0.0160, -0.0928]],\n",
       "  \n",
       "          [[-0.0576, -0.0768, -0.0629,  ..., -0.0320, -0.0159, -0.0928]],\n",
       "  \n",
       "          [[-0.0586, -0.0843, -0.0717,  ..., -0.0321, -0.0196, -0.0943]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0587, -0.0844, -0.0720,  ..., -0.0321, -0.0159, -0.0928]],\n",
       "  \n",
       "          [[-0.0587, -0.0843, -0.0720,  ..., -0.0322, -0.0160, -0.0928]],\n",
       "  \n",
       "          [[-0.0587, -0.0843, -0.0720,  ..., -0.0321, -0.0159, -0.0928]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (68,\n",
       "  tensor([[[-1.9531e-03,  2.6855e-03, -1.0071e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00, -3.0518e-05,  ...,  7.4707e-02,\n",
       "             5.7190e-02,  6.2500e-02]],\n",
       "  \n",
       "          [[-5.9235e-02,  7.1838e-02,  5.3406e-02,  ..., -1.2531e-01,\n",
       "            -1.3040e-01,  2.6245e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.8860e-02, -1.4954e-02, -1.5167e-02,  ..., -2.0905e-02,\n",
       "            -2.0325e-02, -1.9867e-02]],\n",
       "  \n",
       "          [[-3.0518e-05, -6.1035e-05,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00, -6.1035e-05]],\n",
       "  \n",
       "          [[ 3.0518e-05,  0.0000e+00, -3.0518e-05,  ..., -1.0681e-03,\n",
       "            -1.0376e-02, -8.1787e-03]]]),\n",
       "  tensor([[[-0.0551, -0.0563, -0.0575,  ..., -0.0372, -0.0187, -0.0866]],\n",
       "  \n",
       "          [[-0.0672, -0.0814, -0.0722,  ..., -0.0396, -0.0248, -0.0854]],\n",
       "  \n",
       "          [[-0.0603, -0.0680, -0.0686,  ..., -0.0442, -0.0508, -0.0897]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0667, -0.0800, -0.0704,  ..., -0.0368, -0.0212, -0.0888]],\n",
       "  \n",
       "          [[-0.0672, -0.0814, -0.0722,  ..., -0.0372, -0.0187, -0.0866]],\n",
       "  \n",
       "          [[-0.0672, -0.0813, -0.0722,  ..., -0.0377, -0.0202, -0.0862]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (69,\n",
       "  tensor([[[-3.9673e-04, -4.2725e-04, -3.3569e-04,  ...,  6.1035e-05,\n",
       "             0.0000e+00,  1.8311e-04]],\n",
       "  \n",
       "          [[ 3.0518e-04, -4.5776e-04,  2.4414e-04,  ...,  4.5776e-04,\n",
       "            -2.7466e-04, -3.0518e-04]],\n",
       "  \n",
       "          [[-3.6316e-03, -4.3030e-03, -4.5471e-03,  ...,  4.3335e-03,\n",
       "             4.1809e-03,  3.5400e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 9.7778e-02, -1.8738e-02, -9.3597e-02,  ...,  2.9236e-02,\n",
       "             2.9877e-02,  4.4586e-02]],\n",
       "  \n",
       "          [[-2.1362e-04, -3.6621e-04, -5.1880e-04,  ...,  3.5706e-03,\n",
       "             3.2654e-03,  3.0518e-03]],\n",
       "  \n",
       "          [[ 3.0518e-05,  3.0518e-05,  0.0000e+00,  ...,  3.3569e-04,\n",
       "             3.3569e-04,  3.0518e-04]]]),\n",
       "  tensor([[[-0.0764, -0.0992, -0.0852,  ..., -0.0379, -0.0235, -0.0983]],\n",
       "  \n",
       "          [[-0.0764, -0.0993, -0.0853,  ..., -0.0379, -0.0236, -0.0983]],\n",
       "  \n",
       "          [[-0.0763, -0.0993, -0.0851,  ..., -0.0384, -0.0237, -0.0981]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0710, -0.0741, -0.0668,  ..., -0.0396, -0.0333, -0.0980]],\n",
       "  \n",
       "          [[-0.0764, -0.0992, -0.0853,  ..., -0.0380, -0.0236, -0.0983]],\n",
       "  \n",
       "          [[-0.0764, -0.0992, -0.0852,  ..., -0.0380, -0.0235, -0.0983]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (70,\n",
       "  tensor([[[-3.9673e-03, -2.1729e-02, -9.2163e-03,  ...,  1.0742e-02,\n",
       "             1.1139e-02,  5.2490e-03]],\n",
       "  \n",
       "          [[-1.1292e-03, -1.3428e-03, -4.5776e-04,  ..., -6.1035e-04,\n",
       "            -2.1362e-04, -5.7983e-04]],\n",
       "  \n",
       "          [[-2.8900e-02,  1.8097e-02,  3.4180e-03,  ...,  5.9326e-02,\n",
       "             2.2247e-02, -9.5184e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 5.7983e-04,  5.7983e-04,  4.8828e-04,  ..., -6.1035e-05,\n",
       "             3.9978e-03,  2.7466e-03]],\n",
       "  \n",
       "          [[-1.6418e-02, -1.0620e-02, -1.6388e-02,  ..., -9.8877e-03,\n",
       "            -5.2490e-03, -1.1658e-02]],\n",
       "  \n",
       "          [[ 1.4648e-03,  7.0190e-04, -4.8828e-04,  ...,  1.0132e-02,\n",
       "             9.4910e-03,  9.8267e-03]]]),\n",
       "  tensor([[[-0.0699, -0.0904, -0.0748,  ..., -0.0378, -0.0218, -0.0976]],\n",
       "  \n",
       "          [[-0.0697, -0.0905, -0.0757,  ..., -0.0373, -0.0219, -0.0976]],\n",
       "  \n",
       "          [[-0.0691, -0.0843, -0.0680,  ..., -0.0390, -0.0510, -0.0975]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0697, -0.0907, -0.0758,  ..., -0.0373, -0.0220, -0.0976]],\n",
       "  \n",
       "          [[-0.0693, -0.0897, -0.0743,  ..., -0.0374, -0.0224, -0.0977]],\n",
       "  \n",
       "          [[-0.0696, -0.0908, -0.0760,  ..., -0.0377, -0.0221, -0.0973]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (71,\n",
       "  tensor([[[ 2.8381e-03, -2.2583e-03,  2.2278e-03,  ...,  1.2207e-03,\n",
       "             1.4343e-03,  1.1292e-03]],\n",
       "  \n",
       "          [[-9.1919e-02, -3.4119e-02,  3.3783e-02,  ...,  1.8005e-03,\n",
       "             7.9346e-04,  2.1362e-03]],\n",
       "  \n",
       "          [[-1.2726e-02, -8.8501e-03, -5.9204e-03,  ..., -1.3458e-02,\n",
       "            -7.9651e-03,  2.8076e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-2.9846e-02, -3.1647e-02, -4.8615e-02,  ..., -8.3313e-03,\n",
       "            -2.8687e-03, -2.0447e-03]],\n",
       "  \n",
       "          [[-5.4932e-04,  4.5776e-04,  9.1553e-05,  ...,  2.1362e-04,\n",
       "             8.1482e-03,  1.5930e-02]],\n",
       "  \n",
       "          [[ 7.4219e-02,  2.5452e-02, -7.8339e-02,  ..., -6.1554e-02,\n",
       "             8.0658e-02, -2.3193e-03]]]),\n",
       "  tensor([[[-0.0746, -0.0944, -0.0796,  ..., -0.0393, -0.0231, -0.0993]],\n",
       "  \n",
       "          [[-0.0743, -0.0801, -0.0640,  ..., -0.0395, -0.0231, -0.0993]],\n",
       "  \n",
       "          [[-0.0745, -0.0944, -0.0805,  ..., -0.0393, -0.0231, -0.0991]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0739, -0.0930, -0.0777,  ..., -0.0399, -0.0240, -0.0998]],\n",
       "  \n",
       "          [[-0.0747, -0.0945, -0.0804,  ..., -0.0396, -0.0236, -0.0991]],\n",
       "  \n",
       "          [[-0.0681, -0.0728, -0.0613,  ..., -0.0436, -0.0498, -0.1070]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (72,\n",
       "  tensor([[[-2.1362e-04,  1.5259e-04,  3.6621e-04,  ..., -1.7975e-02,\n",
       "            -1.8036e-02, -1.2756e-02]],\n",
       "  \n",
       "          [[-6.6833e-03, -4.3640e-03,  1.2024e-02,  ..., -8.5144e-03,\n",
       "            -1.6571e-02,  2.8687e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00, -3.0518e-05, -3.0518e-05,  ...,  3.9673e-04,\n",
       "             3.6621e-04,  3.0518e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.2512e-03,  8.2397e-04,  6.7139e-04,  ...,  9.4910e-03,\n",
       "            -1.0559e-02, -2.6276e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  5.7373e-02,\n",
       "             2.8229e-02, -3.3569e-04]],\n",
       "  \n",
       "          [[ 2.5635e-03,  1.6479e-03,  1.1902e-03,  ...,  2.5848e-02,\n",
       "             2.4841e-02,  2.6031e-02]]]),\n",
       "  tensor([[[-0.0814, -0.0988, -0.0888,  ..., -0.0433, -0.0270, -0.0996]],\n",
       "  \n",
       "          [[-0.0816, -0.0984, -0.0881,  ..., -0.0401, -0.0268, -0.1006]],\n",
       "  \n",
       "          [[-0.0813, -0.0989, -0.0890,  ..., -0.0402, -0.0253, -0.1004]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0813, -0.0988, -0.0890,  ..., -0.0460, -0.0410, -0.1013]],\n",
       "  \n",
       "          [[-0.0813, -0.0989, -0.0890,  ..., -0.0441, -0.0463, -0.0991]],\n",
       "  \n",
       "          [[-0.0813, -0.0988, -0.0890,  ..., -0.0413, -0.0267, -0.1000]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (73,\n",
       "  tensor([[[ 0.0057,  0.0076,  0.0091,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[-0.0067, -0.0011, -0.0010,  ..., -0.0151,  0.0063,  0.0044]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0034, -0.0028, -0.0029,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[-0.0424, -0.0432, -0.0434,  ..., -0.0052,  0.0166,  0.0402]],\n",
       "  \n",
       "          [[ 0.0038,  0.0029,  0.0024,  ..., -0.0004, -0.0004, -0.0003]]]),\n",
       "  tensor([[[-0.0831, -0.1010, -0.0817,  ..., -0.0421, -0.0274, -0.1092]],\n",
       "  \n",
       "          [[-0.0827, -0.1045, -0.0856,  ..., -0.0421, -0.0274, -0.1092]],\n",
       "  \n",
       "          [[-0.0828, -0.1045, -0.0855,  ..., -0.0428, -0.0276, -0.1090]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0827, -0.1044, -0.0852,  ..., -0.0421, -0.0274, -0.1092]],\n",
       "  \n",
       "          [[-0.0823, -0.1041, -0.0850,  ..., -0.0480, -0.0315, -0.1070]],\n",
       "  \n",
       "          [[-0.0827, -0.1046, -0.0856,  ..., -0.0421, -0.0274, -0.1092]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (74,\n",
       "  tensor([[[-3.0518e-05, -4.0588e-03, -1.4038e-03,  ...,  1.5564e-03,\n",
       "             1.3428e-03,  3.0518e-05]],\n",
       "  \n",
       "          [[ 3.5400e-02, -1.9531e-02,  2.5391e-02,  ...,  4.0039e-02,\n",
       "             5.1483e-02,  3.4729e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  5.7373e-02,\n",
       "             2.8229e-02, -3.3569e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.2695e-02,  8.1787e-03,  9.0942e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-3.0518e-05, -2.1362e-04, -6.1035e-05,  ..., -5.4932e-04,\n",
       "            -7.6294e-04, -6.4087e-04]],\n",
       "  \n",
       "          [[-6.9885e-03, -6.7749e-03, -6.8970e-03,  ...,  5.5542e-03,\n",
       "            -1.2878e-02, -1.2756e-02]]]),\n",
       "  tensor([[[-0.0760, -0.0852, -0.0748,  ..., -0.0482, -0.0258, -0.0962]],\n",
       "  \n",
       "          [[-0.0745, -0.0711, -0.0627,  ..., -0.0476, -0.0343, -0.0960]],\n",
       "  \n",
       "          [[-0.0761, -0.0852, -0.0748,  ..., -0.0487, -0.0512, -0.0970]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0762, -0.0845, -0.0741,  ..., -0.0467, -0.0252, -0.0958]],\n",
       "  \n",
       "          [[-0.0762, -0.0852, -0.0748,  ..., -0.0467, -0.0250, -0.0958]],\n",
       "  \n",
       "          [[-0.0759, -0.0855, -0.0749,  ..., -0.0464, -0.0351, -0.0990]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (75,\n",
       "  tensor([[[ 0.0127,  0.0082,  0.0091,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0023,  0.0023,  0.0024]],\n",
       "  \n",
       "          [[ 0.0003,  0.0004,  0.0009,  ...,  0.0008,  0.0011,  0.0008]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0298, -0.0316, -0.0486,  ..., -0.0083, -0.0029, -0.0020]],\n",
       "  \n",
       "          [[-0.0163, -0.0385, -0.0508,  ..., -0.0816, -0.0351, -0.0565]],\n",
       "  \n",
       "          [[ 0.0237,  0.0209,  0.0204,  ...,  0.0239,  0.0256,  0.0257]]]),\n",
       "  tensor([[[-0.0908, -0.0963, -0.0853,  ..., -0.0584, -0.0371, -0.1121]],\n",
       "  \n",
       "          [[-0.0908, -0.0970, -0.0853,  ..., -0.0585, -0.0370, -0.1121]],\n",
       "  \n",
       "          [[-0.0908, -0.0968, -0.0853,  ..., -0.0585, -0.0371, -0.1121]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0891, -0.0900, -0.0791,  ..., -0.0588, -0.0376, -0.1123]],\n",
       "  \n",
       "          [[-0.0833, -0.0639, -0.0649,  ..., -0.0591, -0.0627, -0.1217]],\n",
       "  \n",
       "          [[-0.0906, -0.0971, -0.0855,  ..., -0.0603, -0.0407, -0.1102]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (76,\n",
       "  tensor([[[ 0.0015,  0.0007, -0.0005,  ...,  0.0101,  0.0095,  0.0098]],\n",
       "  \n",
       "          [[ 0.0006,  0.0018,  0.0033,  ..., -0.0003, -0.0013, -0.0016]],\n",
       "  \n",
       "          [[ 0.0010, -0.0336,  0.0625,  ..., -0.0202, -0.0115,  0.0008]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0253, -0.0244, -0.0207,  ..., -0.0031, -0.0028,  0.0006]],\n",
       "  \n",
       "          [[ 0.0003,  0.0005,  0.0008,  ...,  0.0000, -0.0009, -0.0014]],\n",
       "  \n",
       "          [[-0.0057, -0.0049, -0.0041,  ..., -0.0014, -0.0014, -0.0015]]]),\n",
       "  tensor([[[-0.0808, -0.1044, -0.0882,  ..., -0.0429, -0.0292, -0.1080]],\n",
       "  \n",
       "          [[-0.0808, -0.1044, -0.0883,  ..., -0.0428, -0.0293, -0.1081]],\n",
       "  \n",
       "          [[-0.0790, -0.0917, -0.0811,  ..., -0.0444, -0.0297, -0.1069]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0810, -0.1040, -0.0875,  ..., -0.0430, -0.0294, -0.1082]],\n",
       "  \n",
       "          [[-0.0808, -0.1044, -0.0882,  ..., -0.0428, -0.0293, -0.1081]],\n",
       "  \n",
       "          [[-0.0808, -0.1043, -0.0880,  ..., -0.0428, -0.0292, -0.1081]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (77,\n",
       "  tensor([[[ 9.1553e-05, -3.3569e-04, -9.7656e-04,  ...,  1.4038e-03,\n",
       "             1.1292e-03, -1.5259e-03]],\n",
       "  \n",
       "          [[-1.0284e-02,  3.9673e-04, -1.6785e-03,  ...,  2.7161e-03,\n",
       "             3.2043e-03,  2.6245e-03]],\n",
       "  \n",
       "          [[-3.2043e-03, -3.5095e-03, -3.5095e-03,  ..., -2.0111e-02,\n",
       "            -3.5065e-02, -9.7717e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-8.9417e-03,  4.5776e-04, -2.7466e-04,  ...,  1.3824e-02,\n",
       "            -1.2024e-02, -2.0142e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -8.5938e-02,\n",
       "             8.5754e-03,  7.8156e-02]],\n",
       "  \n",
       "          [[-5.7983e-04,  2.1362e-03,  8.2703e-03,  ..., -6.1035e-05,\n",
       "             6.7139e-04,  1.7090e-03]]]),\n",
       "  tensor([[[-0.0958, -0.1060, -0.0922,  ..., -0.0536, -0.0383, -0.1136]],\n",
       "  \n",
       "          [[-0.0955, -0.1055, -0.0920,  ..., -0.0536, -0.0379, -0.1136]],\n",
       "  \n",
       "          [[-0.0956, -0.1059, -0.0922,  ..., -0.0585, -0.0754, -0.1172]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0948, -0.1021, -0.0881,  ..., -0.0539, -0.0390, -0.1138]],\n",
       "  \n",
       "          [[-0.0959, -0.1059, -0.0922,  ..., -0.0556, -0.0713, -0.1198]],\n",
       "  \n",
       "          [[-0.0956, -0.1060, -0.0923,  ..., -0.0534, -0.0379, -0.1137]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (78,\n",
       "  tensor([[[ 0.0000e+00,  0.0000e+00, -3.0518e-05,  ...,  7.4707e-02,\n",
       "             5.7190e-02,  6.2500e-02]],\n",
       "  \n",
       "          [[-1.6296e-02, -3.8513e-02, -5.0781e-02,  ..., -8.1573e-02,\n",
       "            -3.5095e-02, -5.6458e-02]],\n",
       "  \n",
       "          [[ 5.9204e-03,  4.9133e-03,  4.9438e-03,  ..., -6.7749e-03,\n",
       "            -8.0261e-03, -1.1139e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.8311e-04, -2.4414e-04, -1.8311e-04,  ..., -3.0518e-05,\n",
       "            -9.1553e-05,  0.0000e+00]],\n",
       "  \n",
       "          [[-1.5259e-04, -5.1880e-04,  2.7466e-04,  ...,  2.6031e-02,\n",
       "            -6.2256e-03,  7.9041e-03]],\n",
       "  \n",
       "          [[-5.5725e-02, -4.2328e-02, -7.5684e-03,  ..., -9.1553e-04,\n",
       "             3.5919e-02,  1.8524e-02]]]),\n",
       "  tensor([[[-0.0931, -0.0940, -0.0878,  ..., -0.0555, -0.0465, -0.1014]],\n",
       "  \n",
       "          [[-0.0909, -0.0737, -0.0702,  ..., -0.0577, -0.0601, -0.1132]],\n",
       "  \n",
       "          [[-0.0930, -0.0945, -0.0879,  ..., -0.0525, -0.0358, -0.1029]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0931, -0.0941, -0.0877,  ..., -0.0527, -0.0355, -0.1027]],\n",
       "  \n",
       "          [[-0.0930, -0.0943, -0.0877,  ..., -0.0524, -0.0437, -0.1032]],\n",
       "  \n",
       "          [[-0.0895, -0.0874, -0.0808,  ..., -0.0544, -0.0518, -0.1022]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (79,\n",
       "  tensor([[[ 5.7068e-03,  7.5684e-03,  9.1248e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 6.8665e-03,  6.6223e-03,  5.2795e-03,  ..., -1.5564e-03,\n",
       "            -1.0071e-03, -4.5776e-04]],\n",
       "  \n",
       "          [[ 8.8806e-03,  8.8806e-03,  7.9346e-03,  ..., -6.1035e-02,\n",
       "            -6.6315e-02, -5.5756e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 2.4414e-04,  3.0518e-04,  3.9673e-04,  ..., -1.2970e-01,\n",
       "            -1.1404e-01, -1.9745e-02]],\n",
       "  \n",
       "          [[ 7.6080e-02,  6.5155e-02,  3.8177e-02,  ..., -1.2207e-04,\n",
       "             1.2268e-02,  2.8839e-02]],\n",
       "  \n",
       "          [[ 1.4343e-03,  1.3733e-03,  1.8311e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]]]),\n",
       "  tensor([[[-0.0882, -0.0996, -0.0850,  ..., -0.0500, -0.0342, -0.1107]],\n",
       "  \n",
       "          [[-0.0881, -0.1021, -0.0877,  ..., -0.0500, -0.0343, -0.1107]],\n",
       "  \n",
       "          [[-0.0880, -0.1021, -0.0878,  ..., -0.0540, -0.0408, -0.1082]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0880, -0.1022, -0.0878,  ..., -0.0540, -0.0611, -0.1099]],\n",
       "  \n",
       "          [[-0.0864, -0.0828, -0.0702,  ..., -0.0519, -0.0378, -0.1092]],\n",
       "  \n",
       "          [[-0.0880, -0.1022, -0.0878,  ..., -0.0500, -0.0342, -0.1107]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (80,\n",
       "  tensor([[[-7.2937e-03, -8.5449e-04,  2.7466e-04,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-1.7825e-01, -1.7194e-01,  1.0406e-02,  ...,  4.6204e-02,\n",
       "            -9.8877e-03, -1.2408e-01]],\n",
       "  \n",
       "          [[-1.6785e-03, -7.0801e-03, -9.9182e-03,  ..., -8.3923e-03,\n",
       "            -1.0895e-02, -1.3092e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.3733e-03,  5.9814e-03,  2.1362e-04,  ..., -6.5918e-03,\n",
       "            -1.4496e-02, -1.7242e-02]],\n",
       "  \n",
       "          [[-5.9256e-01, -5.7764e-01, -2.1219e-01,  ..., -1.5259e-04,\n",
       "            -4.2725e-04,  5.7983e-04]],\n",
       "  \n",
       "          [[ 1.8311e-03, -3.0823e-03, -1.8616e-03,  ..., -3.0975e-02,\n",
       "             6.4392e-03,  4.9744e-03]]]),\n",
       "  tensor([[[-0.0832, -0.0984, -0.0834,  ..., -0.0483, -0.0323, -0.1084]],\n",
       "  \n",
       "          [[-0.0782, -0.0826, -0.0622,  ..., -0.0458, -0.0513, -0.1125]],\n",
       "  \n",
       "          [[-0.0838, -0.0984, -0.0835,  ..., -0.0483, -0.0323, -0.1084]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0819, -0.0923, -0.0811,  ..., -0.0485, -0.0332, -0.1084]],\n",
       "  \n",
       "          [[-0.0742, -0.0321, -0.1578,  ..., -0.0485, -0.0327, -0.1086]],\n",
       "  \n",
       "          [[-0.0838, -0.0993, -0.0850,  ..., -0.0547, -0.0348, -0.1042]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (81,\n",
       "  tensor([[[ 3.0518e-05,  0.0000e+00, -3.0518e-05,  ..., -1.0681e-03,\n",
       "            -1.0376e-02, -8.1787e-03]],\n",
       "  \n",
       "          [[-4.5776e-03, -4.2725e-03, -1.5259e-03,  ..., -3.9673e-04,\n",
       "             0.0000e+00,  4.8828e-04]],\n",
       "  \n",
       "          [[ 1.2207e-04,  3.0518e-05, -2.7466e-04,  ..., -5.4932e-04,\n",
       "            -4.5776e-04,  4.2725e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.6296e-02, -3.8513e-02, -5.0781e-02,  ..., -8.1573e-02,\n",
       "            -3.5095e-02, -5.6458e-02]],\n",
       "  \n",
       "          [[-3.0518e-04, -3.6621e-04, -9.7656e-04,  ...,  2.4719e-03,\n",
       "             1.8005e-03,  5.3101e-03]],\n",
       "  \n",
       "          [[ 2.4719e-03,  4.0894e-03,  3.3875e-03,  ..., -4.8828e-04,\n",
       "            -2.9907e-03, -3.7842e-03]]]),\n",
       "  tensor([[[-0.1043, -0.1074, -0.0941,  ..., -0.0639, -0.0464, -0.1222]],\n",
       "  \n",
       "          [[-0.1044, -0.1076, -0.0940,  ..., -0.0633, -0.0457, -0.1225]],\n",
       "  \n",
       "          [[-0.1043, -0.1076, -0.0942,  ..., -0.0633, -0.0457, -0.1226]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0981, -0.0768, -0.0764,  ..., -0.0649, -0.0634, -0.1319]],\n",
       "  \n",
       "          [[-0.1044, -0.1076, -0.0942,  ..., -0.0633, -0.0456, -0.1226]],\n",
       "  \n",
       "          [[-0.1044, -0.1074, -0.0938,  ..., -0.0634, -0.0459, -0.1226]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (82,\n",
       "  tensor([[[-0.0275, -0.0247, -0.0227,  ..., -0.0333, -0.0420, -0.0464]],\n",
       "  \n",
       "          [[ 0.0120, -0.0006, -0.0053,  ..., -0.0127, -0.0146, -0.0134]],\n",
       "  \n",
       "          [[-0.0065, -0.0082, -0.0130,  ...,  0.0046,  0.0048,  0.0051]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.5311, -0.5073, -0.4883,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ..., -0.0029, -0.0047, -0.0048]],\n",
       "  \n",
       "          [[ 0.2228,  0.2220,  0.1673,  ..., -0.0589, -0.0562, -0.0577]]]),\n",
       "  tensor([[[-0.1104, -0.1137, -0.0965,  ..., -0.0637, -0.0493, -0.1267]],\n",
       "  \n",
       "          [[-0.1104, -0.1139, -0.0968,  ..., -0.0635, -0.0495, -0.1255]],\n",
       "  \n",
       "          [[-0.1101, -0.1135, -0.0965,  ..., -0.0629, -0.0487, -0.1254]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0593,  0.1052, -0.1625,  ..., -0.0629, -0.0486, -0.1254]],\n",
       "  \n",
       "          [[-0.1104, -0.1139, -0.0968,  ..., -0.0629, -0.0486, -0.1255]],\n",
       "  \n",
       "          [[-0.1075, -0.0972, -0.0804,  ..., -0.0626, -0.0498, -0.1294]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (83,\n",
       "  tensor([[[ 0.0000e+00,  3.0518e-05,  3.0518e-05,  ..., -3.6621e-04,\n",
       "            -7.3242e-04,  3.0518e-05]],\n",
       "  \n",
       "          [[-4.8828e-04, -2.1362e-04, -3.0518e-04,  ..., -3.0518e-04,\n",
       "             1.8311e-04, -3.0518e-04]],\n",
       "  \n",
       "          [[-2.1362e-04, -2.4414e-04, -3.0518e-04,  ..., -4.8828e-04,\n",
       "            -5.1880e-04, -5.1880e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 3.2043e-03, -3.2013e-02, -4.4983e-02,  ..., -1.8616e-02,\n",
       "            -1.8005e-02, -4.3945e-03]],\n",
       "  \n",
       "          [[-3.2043e-03, -3.5095e-03, -3.5095e-03,  ..., -2.0111e-02,\n",
       "            -3.5065e-02, -9.7717e-02]],\n",
       "  \n",
       "          [[ 9.1553e-05,  3.3569e-04,  1.5259e-04,  ..., -2.1362e-04,\n",
       "             1.2207e-04, -9.1553e-05]]]),\n",
       "  tensor([[[-0.0974, -0.1066, -0.0940,  ..., -0.0569, -0.0386, -0.1178]],\n",
       "  \n",
       "          [[-0.0974, -0.1066, -0.0940,  ..., -0.0568, -0.0386, -0.1178]],\n",
       "  \n",
       "          [[-0.0974, -0.1066, -0.0940,  ..., -0.0567, -0.0387, -0.1179]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0949, -0.0892, -0.0783,  ..., -0.0572, -0.0379, -0.1180]],\n",
       "  \n",
       "          [[-0.0970, -0.1064, -0.0934,  ..., -0.0648, -0.0816, -0.1228]],\n",
       "  \n",
       "          [[-0.0974, -0.1066, -0.0940,  ..., -0.0567, -0.0387, -0.1178]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (84,\n",
       "  tensor([[[ 1.4343e-03,  2.1362e-03, -2.6550e-03,  ...,  6.3477e-03,\n",
       "             7.1716e-03,  7.2937e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -8.5938e-02,\n",
       "             8.5754e-03,  7.8156e-02]],\n",
       "  \n",
       "          [[ 1.8707e-02,  1.3367e-02,  1.5564e-03,  ...,  9.1553e-05,\n",
       "             1.8311e-04,  2.1362e-04]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-5.7983e-04,  2.1362e-03,  8.2703e-03,  ..., -6.1035e-05,\n",
       "             6.7139e-04,  1.7090e-03]],\n",
       "  \n",
       "          [[-6.4819e-02,  2.9022e-02,  2.7954e-02,  ...,  3.5898e-01,\n",
       "             7.4463e-02,  1.7163e-01]],\n",
       "  \n",
       "          [[-1.2207e-04, -3.0518e-05,  0.0000e+00,  ..., -1.2897e-01,\n",
       "            -3.0548e-02, -7.2601e-02]]]),\n",
       "  tensor([[[-0.0951, -0.1081, -0.0941,  ..., -0.0533, -0.0414, -0.1208]],\n",
       "  \n",
       "          [[-0.0950, -0.1083, -0.0944,  ..., -0.0552, -0.0752, -0.1257]],\n",
       "  \n",
       "          [[-0.0939, -0.1065, -0.0918,  ..., -0.0532, -0.0414, -0.1208]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0950, -0.1085, -0.0945,  ..., -0.0532, -0.0413, -0.1208]],\n",
       "  \n",
       "          [[-0.0920, -0.0836, -0.0797,  ..., -0.0824, -0.1208, -0.0975]],\n",
       "  \n",
       "          [[-0.0950, -0.1083, -0.0944,  ..., -0.0585, -0.0610, -0.1304]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (85,\n",
       "  tensor([[[ 1.0986e-03,  1.2207e-03,  1.8005e-03,  ...,  3.2349e-03,\n",
       "             2.1362e-03,  1.8311e-04]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -1.8311e-04,\n",
       "            -3.9673e-04, -4.8828e-04]],\n",
       "  \n",
       "          [[ 1.8311e-03, -3.0823e-03, -1.8616e-03,  ..., -3.0975e-02,\n",
       "             6.4392e-03,  4.9744e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 2.8076e-03,  7.4463e-03,  5.9814e-03,  ...,  1.3489e-02,\n",
       "             1.3824e-02,  1.0773e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00, -3.0518e-05, -3.0518e-05,  ..., -6.4087e-03,\n",
       "            -5.6152e-03, -6.8665e-03]],\n",
       "  \n",
       "          [[ 5.1880e-04,  1.7700e-03, -3.0518e-05,  ..., -2.3499e-03,\n",
       "            -4.5166e-03, -7.8735e-03]]]),\n",
       "  tensor([[[-0.1177, -0.1160, -0.1002,  ..., -0.0706, -0.0526, -0.1333]],\n",
       "  \n",
       "          [[-0.1178, -0.1161, -0.1002,  ..., -0.0703, -0.0528, -0.1333]],\n",
       "  \n",
       "          [[-0.1178, -0.1163, -0.1004,  ..., -0.0759, -0.0561, -0.1301]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1177, -0.1158, -0.0994,  ..., -0.0703, -0.0527, -0.1337]],\n",
       "  \n",
       "          [[-0.1178, -0.1161, -0.1001,  ..., -0.0707, -0.0528, -0.1334]],\n",
       "  \n",
       "          [[-0.1178, -0.1161, -0.1001,  ..., -0.0702, -0.0527, -0.1333]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (86,\n",
       "  tensor([[[ 3.9673e-04, -9.1553e-05, -5.1880e-04,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-4.0344e-02, -3.7537e-03,  4.5349e-02,  ..., -1.3123e-02,\n",
       "            -7.8156e-02, -2.3102e-02]],\n",
       "  \n",
       "          [[ 1.0349e-01,  8.9935e-02,  2.2247e-02,  ...,  3.6621e-04,\n",
       "             1.5259e-04,  3.0518e-05]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 5.1147e-02,  3.7720e-02,  2.2095e-02,  ..., -6.2866e-03,\n",
       "            -1.3306e-02,  5.4932e-04]],\n",
       "  \n",
       "          [[-3.6926e-03, -4.0283e-03, -5.0964e-03,  ..., -6.7139e-04,\n",
       "            -1.4648e-03, -5.4932e-04]],\n",
       "  \n",
       "          [[ 4.5471e-03,  2.8992e-03, -2.5635e-03,  ...,  2.6245e-03,\n",
       "             1.3092e-02, -8.8501e-04]]]),\n",
       "  tensor([[[-0.1141, -0.1075, -0.0980,  ..., -0.0728, -0.0519, -0.1300]],\n",
       "  \n",
       "          [[-0.1097, -0.0919, -0.0914,  ..., -0.0766, -0.0817, -0.1343]],\n",
       "  \n",
       "          [[-0.1099, -0.0945, -0.0922,  ..., -0.0729, -0.0519, -0.1299]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1109, -0.0950, -0.0905,  ..., -0.0751, -0.0626, -0.1279]],\n",
       "  \n",
       "          [[-0.1141, -0.1072, -0.0979,  ..., -0.0728, -0.0519, -0.1299]],\n",
       "  \n",
       "          [[-0.1140, -0.1072, -0.0976,  ..., -0.0739, -0.0517, -0.1298]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (87,\n",
       "  tensor([[[ 0.0036,  0.0032,  0.0035,  ..., -0.0080, -0.0055,  0.0013]],\n",
       "  \n",
       "          [[ 0.0045,  0.0029, -0.0026,  ...,  0.0026,  0.0131, -0.0009]],\n",
       "  \n",
       "          [[ 0.0056,  0.0083,  0.0037,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0330,  0.0396,  0.0427,  ...,  0.0310,  0.0309,  0.0322]],\n",
       "  \n",
       "          [[-0.0298, -0.0316, -0.0486,  ..., -0.0083, -0.0029, -0.0020]],\n",
       "  \n",
       "          [[-0.0003, -0.0051, -0.0006,  ...,  0.0003, -0.0002, -0.0005]]]),\n",
       "  tensor([[[-0.1166, -0.1052, -0.0977,  ..., -0.0752, -0.0522, -0.1290]],\n",
       "  \n",
       "          [[-0.1164, -0.1051, -0.0977,  ..., -0.0777, -0.0525, -0.1276]],\n",
       "  \n",
       "          [[-0.1164, -0.1061, -0.0979,  ..., -0.0752, -0.0522, -0.1287]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1136, -0.0952, -0.0940,  ..., -0.0715, -0.0807, -0.1297]],\n",
       "  \n",
       "          [[-0.1151, -0.0899, -0.0875,  ..., -0.0756, -0.0533, -0.1300]],\n",
       "  \n",
       "          [[-0.1164, -0.1053, -0.0979,  ..., -0.0754, -0.0524, -0.1288]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (88,\n",
       "  tensor([[[-3.0518e-05, -2.7466e-04, -3.9673e-04,  ...,  0.0000e+00,\n",
       "             3.0518e-05, -1.2207e-04]],\n",
       "  \n",
       "          [[-4.4556e-03, -2.8076e-03,  9.7351e-03,  ...,  0.0000e+00,\n",
       "             3.0518e-05,  0.0000e+00]],\n",
       "  \n",
       "          [[ 2.1362e-04, -9.1553e-05,  3.9673e-04,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 7.6080e-02,  6.5155e-02,  3.8177e-02,  ..., -1.2207e-04,\n",
       "             1.2268e-02,  2.8839e-02]],\n",
       "  \n",
       "          [[-1.0101e-02, -2.8687e-03, -4.4861e-03,  ..., -8.5754e-03,\n",
       "             1.0681e-03,  1.2207e-03]],\n",
       "  \n",
       "          [[ 2.6367e-02,  2.4597e-02,  2.3132e-02,  ..., -1.3580e-02,\n",
       "            -3.3112e-02, -3.3173e-02]]]),\n",
       "  tensor([[[-0.1053, -0.1069, -0.0942,  ..., -0.0655, -0.0425, -0.1244]],\n",
       "  \n",
       "          [[-0.1011, -0.0924, -0.0881,  ..., -0.0655, -0.0425, -0.1244]],\n",
       "  \n",
       "          [[-0.1054, -0.1069, -0.0942,  ..., -0.0655, -0.0425, -0.1244]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1045, -0.0853, -0.0781,  ..., -0.0694, -0.0611, -0.1232]],\n",
       "  \n",
       "          [[-0.1056, -0.1064, -0.0943,  ..., -0.0667, -0.0432, -0.1246]],\n",
       "  \n",
       "          [[-0.1044, -0.1055, -0.0941,  ..., -0.0680, -0.0508, -0.1319]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (89,\n",
       "  tensor([[[-0.0035, -0.0042, -0.0053,  ...,  0.0939,  0.1221,  0.1596]],\n",
       "  \n",
       "          [[-0.0043, -0.0046, -0.0035,  ..., -0.0052, -0.0046, -0.0042]],\n",
       "  \n",
       "          [[-0.0103, -0.0097, -0.0065,  ...,  0.0005,  0.0027,  0.0021]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0174,  0.0172,  0.0161,  ..., -0.0137, -0.0159, -0.0112]],\n",
       "  \n",
       "          [[ 0.0014,  0.0014,  0.0018,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[-0.0215,  0.0136,  0.0805,  ...,  0.0003, -0.0009, -0.0010]]]),\n",
       "  tensor([[[-0.1007, -0.1086, -0.0920,  ..., -0.0643, -0.0777, -0.1314]],\n",
       "  \n",
       "          [[-0.1003, -0.1086, -0.0918,  ..., -0.0646, -0.0408, -0.1259]],\n",
       "  \n",
       "          [[-0.1003, -0.1088, -0.0925,  ..., -0.0649, -0.0404, -0.1259]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0999, -0.1079, -0.0912,  ..., -0.0649, -0.0412, -0.1273]],\n",
       "  \n",
       "          [[-0.1005, -0.1088, -0.0923,  ..., -0.0643, -0.0405, -0.1258]],\n",
       "  \n",
       "          [[-0.0990, -0.0958, -0.0863,  ..., -0.0643, -0.0405, -0.1258]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (90,\n",
       "  tensor([[[ 0.0064, -0.0065,  0.0051,  ...,  0.0060, -0.0040, -0.0022]],\n",
       "  \n",
       "          [[-0.0013,  0.0017,  0.0025,  ...,  0.0009, -0.0019, -0.0016]],\n",
       "  \n",
       "          [[ 0.0131,  0.0130,  0.0141,  ..., -0.0047,  0.0144,  0.0128]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ..., -0.0094,  0.0007,  0.0054]],\n",
       "  \n",
       "          [[ 0.0022,  0.0013,  0.0012,  ..., -0.0088, -0.0080, -0.0091]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0205,  0.0128,  0.0050]]]),\n",
       "  tensor([[[-0.1182, -0.1162, -0.0984,  ..., -0.0745, -0.0537, -0.1374]],\n",
       "  \n",
       "          [[-0.1184, -0.1179, -0.1012,  ..., -0.0742, -0.0540, -0.1374]],\n",
       "  \n",
       "          [[-0.1180, -0.1173, -0.1007,  ..., -0.0744, -0.0546, -0.1376]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1183, -0.1179, -0.1013,  ..., -0.0798, -0.0643, -0.1444]],\n",
       "  \n",
       "          [[-0.1182, -0.1179, -0.1013,  ..., -0.0741, -0.0542, -0.1375]],\n",
       "  \n",
       "          [[-0.1183, -0.1179, -0.1013,  ..., -0.0742, -0.0544, -0.1373]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (91,\n",
       "  tensor([[[ 3.8147e-03,  2.1973e-03,  1.3428e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-2.9846e-02, -3.1647e-02, -4.8615e-02,  ..., -8.3313e-03,\n",
       "            -2.8687e-03, -2.0447e-03]],\n",
       "  \n",
       "          [[ 2.4414e-04, -1.4038e-03, -1.8921e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 1.5442e-02,  1.1322e-02,  1.0223e-02,  ..., -5.4016e-03,\n",
       "            -1.0986e-03,  1.3733e-03]],\n",
       "  \n",
       "          [[ 2.7771e-03,  2.5024e-03,  2.5024e-03,  ..., -1.2207e-04,\n",
       "            -1.2207e-04, -9.1553e-05]]]),\n",
       "  tensor([[[-0.1028, -0.1007, -0.0883,  ..., -0.0679, -0.0448, -0.1211]],\n",
       "  \n",
       "          [[-0.1015, -0.0879, -0.0792,  ..., -0.0683, -0.0454, -0.1214]],\n",
       "  \n",
       "          [[-0.1029, -0.1005, -0.0883,  ..., -0.0679, -0.0448, -0.1211]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1028, -0.1007, -0.0883,  ..., -0.0679, -0.0448, -0.1211]],\n",
       "  \n",
       "          [[-0.1030, -0.1007, -0.0874,  ..., -0.0683, -0.0444, -0.1210]],\n",
       "  \n",
       "          [[-0.1028, -0.1008, -0.0884,  ..., -0.0679, -0.0448, -0.1211]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (92,\n",
       "  tensor([[[-3.0518e-05,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 1.9196e-02,  2.1912e-02,  3.2440e-02,  ...,  6.5308e-03,\n",
       "             1.6479e-03,  1.0071e-03]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-4.4861e-03,  1.4038e-02, -3.0518e-03,  ...,  4.3640e-03,\n",
       "             2.7802e-02,  1.3824e-02]],\n",
       "  \n",
       "          [[-3.4485e-03, -2.8381e-03, -2.8992e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 6.2561e-03,  4.4250e-03,  2.7161e-03,  ..., -6.1035e-05,\n",
       "             3.6621e-04,  7.0190e-04]]]),\n",
       "  tensor([[[-0.1161, -0.1108, -0.0980,  ..., -0.0777, -0.0562, -0.1364]],\n",
       "  \n",
       "          [[-0.1141, -0.1060, -0.0959,  ..., -0.0784, -0.0564, -0.1363]],\n",
       "  \n",
       "          [[-0.1161, -0.1108, -0.0980,  ..., -0.0777, -0.0562, -0.1364]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1130, -0.1020, -0.0936,  ..., -0.0781, -0.0582, -0.1361]],\n",
       "  \n",
       "          [[-0.1158, -0.1104, -0.0970,  ..., -0.0777, -0.0562, -0.1364]],\n",
       "  \n",
       "          [[-0.1161, -0.1106, -0.0980,  ..., -0.0777, -0.0563, -0.1364]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (93,\n",
       "  tensor([[[ 3.1738e-03,  5.7373e-03,  4.0588e-03,  ...,  3.1433e-02,\n",
       "             2.9114e-02,  2.5696e-02]],\n",
       "  \n",
       "          [[-5.6763e-03,  9.0027e-03,  1.7914e-02,  ..., -4.2175e-02,\n",
       "             6.1066e-02,  1.4395e-01]],\n",
       "  \n",
       "          [[-1.4038e-03, -3.3569e-04, -2.0142e-03,  ...,  9.1553e-05,\n",
       "             0.0000e+00, -9.1553e-05]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.6785e-03, -7.0801e-03, -9.9182e-03,  ..., -8.3923e-03,\n",
       "            -1.0895e-02, -1.3092e-02]],\n",
       "  \n",
       "          [[ 1.1292e-03,  1.0071e-03,  9.1553e-04,  ..., -1.2451e-02,\n",
       "            -1.2604e-02, -1.2848e-02]],\n",
       "  \n",
       "          [[ 8.8806e-03,  8.8806e-03,  7.9346e-03,  ..., -6.1035e-02,\n",
       "            -6.6315e-02, -5.5756e-02]]]),\n",
       "  tensor([[[-0.1150, -0.1132, -0.1008,  ..., -0.0778, -0.0631, -0.1340]],\n",
       "  \n",
       "          [[-0.1107, -0.0922, -0.0884,  ..., -0.0732, -0.0774, -0.1383]],\n",
       "  \n",
       "          [[-0.1151, -0.1134, -0.1012,  ..., -0.0734, -0.0535, -0.1359]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1150, -0.1129, -0.1003,  ..., -0.0734, -0.0536, -0.1360]],\n",
       "  \n",
       "          [[-0.1147, -0.1133, -0.1012,  ..., -0.0735, -0.0536, -0.1360]],\n",
       "  \n",
       "          [[-0.1146, -0.1129, -0.1012,  ..., -0.0772, -0.0716, -0.1339]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (94,\n",
       "  tensor([[[ 1.2207e-04,  3.0518e-05, -2.7466e-04,  ..., -5.4932e-04,\n",
       "            -4.5776e-04,  4.2725e-04]],\n",
       "  \n",
       "          [[ 3.0823e-03,  3.5400e-03,  1.2146e-02,  ...,  9.1553e-05,\n",
       "            -2.7466e-03,  4.3030e-03]],\n",
       "  \n",
       "          [[ 1.3428e-03,  1.5259e-03,  9.1553e-05,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-4.0344e-02, -3.7537e-03,  4.5349e-02,  ..., -1.3123e-02,\n",
       "            -7.8156e-02, -2.3102e-02]],\n",
       "  \n",
       "          [[ 2.1362e-04, -4.3335e-03, -5.0659e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 1.0345e-02,  1.0590e-02,  1.1017e-02,  ..., -5.7373e-03,\n",
       "            -1.4587e-02, -1.4313e-02]]]),\n",
       "  tensor([[[-0.1228, -0.1144, -0.0983,  ..., -0.0820, -0.0600, -0.1409]],\n",
       "  \n",
       "          [[-0.1206, -0.1102, -0.0967,  ..., -0.0832, -0.0608, -0.1409]],\n",
       "  \n",
       "          [[-0.1203, -0.1015, -0.0887,  ..., -0.0821, -0.0600, -0.1408]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1172, -0.0982, -0.0907,  ..., -0.0864, -0.0869, -0.1454]],\n",
       "  \n",
       "          [[-0.1151, -0.0988, -0.0886,  ..., -0.0821, -0.0600, -0.1408]],\n",
       "  \n",
       "          [[-0.1227, -0.1137, -0.0986,  ..., -0.0821, -0.0603, -0.1411]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (95,\n",
       "  tensor([[[ 1.0986e-03,  1.2207e-03,  1.8005e-03,  ...,  3.2349e-03,\n",
       "             2.1362e-03,  1.8311e-04]],\n",
       "  \n",
       "          [[ 4.2725e-04,  5.4932e-04,  9.4604e-04,  ..., -2.2583e-03,\n",
       "            -2.2888e-03, -1.6479e-03]],\n",
       "  \n",
       "          [[-1.3428e-03, -1.3428e-03, -1.3733e-03,  ...,  1.0864e-02,\n",
       "             1.2238e-02, -1.8921e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 2.7008e-02,  3.3051e-02,  3.8086e-02,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  3.0518e-05,  ..., -3.2196e-02,\n",
       "             3.0212e-03,  7.1655e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -1.5747e-02,\n",
       "             1.1993e-02,  2.1912e-02]]]),\n",
       "  tensor([[[-0.1003, -0.1108, -0.0972,  ..., -0.0572, -0.0456, -0.1251]],\n",
       "  \n",
       "          [[-0.1003, -0.1108, -0.0972,  ..., -0.0571, -0.0456, -0.1251]],\n",
       "  \n",
       "          [[-0.1004, -0.1109, -0.0973,  ..., -0.0575, -0.0460, -0.1248]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0979, -0.0940, -0.0836,  ..., -0.0570, -0.0455, -0.1251]],\n",
       "  \n",
       "          [[-0.1004, -0.1109, -0.0973,  ..., -0.0571, -0.0902, -0.1301]],\n",
       "  \n",
       "          [[-0.1004, -0.1109, -0.0973,  ..., -0.0574, -0.0449, -0.1250]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (96,\n",
       "  tensor([[[-3.0518e-05, -3.0518e-05,  0.0000e+00,  ..., -1.8005e-02,\n",
       "             6.7444e-02,  1.6479e-02]],\n",
       "  \n",
       "          [[ 1.0345e-02,  1.0590e-02,  1.1017e-02,  ..., -5.7373e-03,\n",
       "            -1.4587e-02, -1.4313e-02]],\n",
       "  \n",
       "          [[-1.9836e-03, -9.4604e-04,  1.1597e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 4.8828e-04, -4.2725e-04, -2.1362e-03,  ...,  6.4087e-04,\n",
       "            -2.1362e-03, -6.5613e-03]],\n",
       "  \n",
       "          [[ 3.0518e-05, -3.0518e-05,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-7.5073e-03, -8.0261e-03, -7.5684e-03,  ..., -4.3335e-03,\n",
       "            -3.8757e-03, -4.0894e-03]]]),\n",
       "  tensor([[[-0.1035, -0.1096, -0.0968,  ..., -0.0598, -0.0614, -0.1254]],\n",
       "  \n",
       "          [[-0.1034, -0.1094, -0.0968,  ..., -0.0593, -0.0508, -0.1240]],\n",
       "  \n",
       "          [[-0.1038, -0.1098, -0.0971,  ..., -0.0596, -0.0508, -0.1238]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1037, -0.1096, -0.0966,  ..., -0.0596, -0.0511, -0.1240]],\n",
       "  \n",
       "          [[-0.1035, -0.1096, -0.0968,  ..., -0.0596, -0.0508, -0.1238]],\n",
       "  \n",
       "          [[-0.1035, -0.1095, -0.0966,  ..., -0.0597, -0.0510, -0.1239]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (97,\n",
       "  tensor([[[ 0.0028,  0.0074,  0.0060,  ...,  0.0135,  0.0138,  0.0108]],\n",
       "  \n",
       "          [[ 0.0364,  0.0436,  0.0496,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[ 0.0033,  0.0035,  0.0026,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.0002,  0.0002,  0.0004,  ..., -0.0180, -0.0180, -0.0128]],\n",
       "  \n",
       "          [[ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]],\n",
       "  \n",
       "          [[-0.0123, -0.0014, -0.0053,  ...,  0.0028, -0.0079, -0.0070]]]),\n",
       "  tensor([[[-0.1087, -0.1096, -0.0943,  ..., -0.0660, -0.0496, -0.1307]],\n",
       "  \n",
       "          [[-0.1038, -0.1001, -0.0903,  ..., -0.0657, -0.0487, -0.1300]],\n",
       "  \n",
       "          [[-0.1107, -0.1144, -0.0996,  ..., -0.0657, -0.0487, -0.1300]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1110, -0.1137, -0.0990,  ..., -0.0757, -0.0613, -0.1278]],\n",
       "  \n",
       "          [[-0.1108, -0.1139, -0.0992,  ..., -0.0657, -0.0487, -0.1300]],\n",
       "  \n",
       "          [[-0.1106, -0.1135, -0.0983,  ..., -0.0662, -0.0498, -0.1318]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (98,\n",
       "  tensor([[[-5.5817e-02, -3.5248e-02,  2.2156e-02,  ...,  8.7280e-03,\n",
       "             1.4160e-02,  1.3062e-02]],\n",
       "  \n",
       "          [[ 1.0345e-02,  1.0590e-02,  1.1017e-02,  ..., -5.7373e-03,\n",
       "            -1.4587e-02, -1.4313e-02]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ..., -2.9297e-03,\n",
       "            -2.9602e-03, -2.7161e-03]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-1.5259e-04, -5.1880e-04,  2.7466e-04,  ...,  2.6031e-02,\n",
       "            -6.2256e-03,  7.9041e-03]],\n",
       "  \n",
       "          [[-1.9104e-02,  2.8259e-02,  6.6895e-02,  ...,  1.7206e-01,\n",
       "             7.5989e-03, -1.6049e-01]],\n",
       "  \n",
       "          [[ 2.7771e-03,  2.5024e-03,  2.5024e-03,  ..., -1.2207e-04,\n",
       "            -1.2207e-04, -9.1553e-05]]]),\n",
       "  tensor([[[-0.1019, -0.0927, -0.0899,  ..., -0.0636, -0.0481, -0.1304]],\n",
       "  \n",
       "          [[-0.1063, -0.1108, -0.0986,  ..., -0.0628, -0.0476, -0.1309]],\n",
       "  \n",
       "          [[-0.1067, -0.1119, -0.0992,  ..., -0.0629, -0.0477, -0.1309]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1065, -0.1115, -0.0986,  ..., -0.0649, -0.0566, -0.1313]],\n",
       "  \n",
       "          [[-0.0950, -0.0961, -0.0844,  ..., -0.0701, -0.0984, -0.1374]],\n",
       "  \n",
       "          [[-0.1067, -0.1119, -0.0992,  ..., -0.0629, -0.0476, -0.1308]]],\n",
       "         grad_fn=<TanhBackward0>)),\n",
       " (99,\n",
       "  tensor([[[ 1.9226e-03,  8.8501e-04,  1.2512e-03,  ..., -1.4343e-03,\n",
       "            -1.3123e-03, -1.0376e-03]],\n",
       "  \n",
       "          [[-1.6785e-03, -7.0801e-03, -9.9182e-03,  ..., -8.3923e-03,\n",
       "            -1.0895e-02, -1.3092e-02]],\n",
       "  \n",
       "          [[-2.1362e-04,  1.5259e-04,  3.6621e-04,  ..., -1.7975e-02,\n",
       "            -1.8036e-02, -1.2756e-02]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[ 1.2695e-02,  8.1787e-03,  9.0942e-03,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[ 0.0000e+00,  0.0000e+00,  0.0000e+00,  ...,  0.0000e+00,\n",
       "             0.0000e+00,  0.0000e+00]],\n",
       "  \n",
       "          [[-4.4556e-03, -2.8076e-03,  9.7351e-03,  ...,  0.0000e+00,\n",
       "             3.0518e-05,  0.0000e+00]]]),\n",
       "  tensor([[[-0.1111, -0.1147, -0.1008,  ..., -0.0662, -0.0519, -0.1325]],\n",
       "  \n",
       "          [[-0.1113, -0.1146, -0.1005,  ..., -0.0662, -0.0519, -0.1325]],\n",
       "  \n",
       "          [[-0.1111, -0.1147, -0.1007,  ..., -0.0700, -0.0523, -0.1306]],\n",
       "  \n",
       "          ...,\n",
       "  \n",
       "          [[-0.1111, -0.1145, -0.1009,  ..., -0.0662, -0.0519, -0.1325]],\n",
       "  \n",
       "          [[-0.1111, -0.1147, -0.1008,  ..., -0.0662, -0.0519, -0.1325]],\n",
       "  \n",
       "          [[-0.1098, -0.1126, -0.1003,  ..., -0.0662, -0.0519, -0.1325]]],\n",
       "         grad_fn=<TanhBackward0>))]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "audio_AE = AudioAE()\n",
    "\n",
    "criterion = nn.MSELoss() # mean square error loss\n",
    "optimizer = torch.optim.Adam(audio_AE.parameters(),\n",
    "                                lr=1e-3, \n",
    "                                weight_decay=1e-5) # <--\n",
    "train_loader = torch.utils.data.DataLoader(audio_set, \n",
    "                                            batch_size=32, \n",
    "                                            shuffle=True)\n",
    "outputs = []\n",
    "for epoch in range(100):\n",
    "    for data in train_loader:\n",
    "        sound, _ = data\n",
    "        recon = audio_AE(sound)\n",
    "        loss = criterion(recon, sound)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        optimizer.zero_grad()\n",
    "\n",
    "    print('Epoch:{}, Loss:{:.4f}'.format(epoch+1, float(loss)))\n",
    "    outputs.append((epoch, sound, recon),)\n",
    "outputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/hanliying/Documents/UCLA/Research/master-thesis-project/dataset/esc.py:74: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  self.df = self.df[0].append(self.df[1:])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading  fold5\n",
      "loss:  0.00032404850571765564\n"
     ]
    }
   ],
   "source": [
    "audio_set_test = ESC70Select(\n",
    "    # root='./Audio/kitchen20/',\n",
    "    root=['./Audio/ESC50', './Audio/kitchen20'],\n",
    "    folds=[5],\n",
    "    transforms=lambda x : nn.functional.pad(x, ((audio_input_length - x.shape[1]) // 2, (audio_input_length - x.shape[1]) // 2)) if (x.shape[1] % 2) == 0 \\\n",
    "        else nn.functional.pad(x, ((audio_input_length - x.shape[1]) // 2, (audio_input_length - x.shape[1]) // 2 + 1)),  \n",
    "    overwrite=False,\n",
    "    use_bc_learning=False,\n",
    "    audio_rate=audio_rate)\n",
    "\n",
    "test_loader = torch.utils.data.DataLoader(audio_set_test,\n",
    "                                          batch_size=32, \n",
    "                                          shuffle=True)\n",
    "\n",
    "loss = []\n",
    "y_sound = 0\n",
    "true_sound = 0\n",
    "for data in test_loader:\n",
    "    sound, _ = data\n",
    "    recon = audio_AE(sound)\n",
    "    loss.append(criterion(recon, sound).item())\n",
    "    y_sound = recon\n",
    "    true_sound = sound\n",
    "print(\"loss: \", np.mean(loss))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(80000,) (80000,)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fcd93802400>"
      ]
     },
     "execution_count": 358,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "id = -1\n",
    "a = true_sound.detach().numpy()\n",
    "b = y_sound.detach().numpy()\n",
    "# a = outputs[-1][1].detach().numpy()\n",
    "a = a[-1].reshape(-1)\n",
    "# b = outputs[-1][2].detach().numpy()\n",
    "b = b[-1].reshape(-1)\n",
    "print(a.shape,b.shape)\n",
    "\n",
    "# true_sound = true_sound[0].item()\n",
    "plt.subplot(2,1,1)\n",
    "plt.plot(range(a.shape[-1]), a)\n",
    "plt.subplot(2,1,2)\n",
    "plt.plot(range(b.shape[-1]), b)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(448, 1, 80000)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sounds = np.concatenate([s.unsqueeze(0) for s in audio_set.sounds])\n",
    "print(sounds.shape)\n",
    "np.max(sounds)\n",
    "max(np.max(sounds), -np.min(sounds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([100, 32, 50])\n",
      "torch.Size([100, 32, 25])\n",
      "torch.Size([100, 64, 13])\n",
      "torch.Size([100, 64, 6])\n",
      "torch.Size([100, 128, 3])\n",
      "torch.Size([100, 128, 1])\n",
      "torch.Size([100, 128, 3])\n",
      "torch.Size([100, 64, 6])\n",
      "torch.Size([100, 64, 13])\n",
      "torch.Size([100, 32, 25])\n",
      "torch.Size([100, 32, 50])\n",
      "torch.Size([100, 3, 100])\n",
      "torch.Size([100, 128, 1])\n",
      "torch.Size([100, 5])\n"
     ]
    }
   ],
   "source": [
    "input1 = torch.randn(100,1,80000)\n",
    "input2 = torch.randn(100,3,100)\n",
    "\n",
    "e1 = nn.Sequential(\n",
    "            nn.Conv1d(1, 16, 9, stride=2, padding=2), nn.ReLU(), nn.BatchNorm1d(16),\n",
    "            nn.Conv1d(16, 32, 9, stride=2, padding=2), nn.ReLU(), nn.BatchNorm1d(32),\n",
    "            nn.Conv1d(32, 64, 9), nn.ReLU(), nn.BatchNorm1d(64)\n",
    "            )\n",
    "d1 = nn.Sequential(\n",
    "            nn.ConvTranspose1d(64, 32, 9), nn.ReLU(), nn.BatchNorm1d(32),\n",
    "            nn.ConvTranspose1d(32, 16, 9, stride=2, padding=2, output_padding=1), nn.ReLU(), nn.BatchNorm1d(16),\n",
    "            nn.ConvTranspose1d(16, 1, 9, stride=2, padding=2, output_padding=1), nn.ReLU(), nn.BatchNorm1d(1),\n",
    "            nn.Tanh()\n",
    "            )\n",
    "embed1 = e1(input1)\n",
    "output1 = d1(embed1)\n",
    "\n",
    "e2 = nn.Sequential(\n",
    "            nn.Conv1d(3, 32, 3, stride=2, padding=1), nn.ReLU(), nn.BatchNorm1d(32), #-> [n_batch, 32, 50]\n",
    "            nn.Conv1d(32, 64, 3, stride=2, padding=1), nn.ReLU(), nn.BatchNorm1d(64), #-> [n_batch, 64, 25]\n",
    "            nn.Conv1d(64, 128, 3, stride=2, padding=1), nn.ReLU(), nn.BatchNorm1d(128), #-> [n_batch, 128, 13]\n",
    "            )\n",
    "d2 = nn.Sequential(\n",
    "            nn.ConvTranspose1d(128, 64, 3, stride=2, padding=1), nn.ReLU(), nn.BatchNorm1d(64), #-> [n_batch, 64, 25]\n",
    "            nn.ConvTranspose1d(64, 32, 3, stride=2, padding=1, output_padding=1), nn.ReLU(), nn.BatchNorm1d(32), #-> [n_batch, 32, 50]\n",
    "            nn.ConvTranspose1d(32, 3, 3, stride=2, padding=1, output_padding=1), nn.ReLU(), nn.BatchNorm1d(3), #-> [n_batch, 3, 100]\n",
    "            nn.Tanh() #-> give outputs in [-1,1]\n",
    "        )\n",
    "\n",
    "embed2 = e2(input2)\n",
    "output2 = d2(embed2)\n",
    "\n",
    "# print(embed1.shape, embed2.shape)\n",
    "# print(output1.shape, output2.shape)\n",
    "\n",
    "conv1 = nn.Sequential(nn.Conv1d(3, 32, 3, stride=2, padding=1), nn.ReLU(), nn.BatchNorm1d(32))\n",
    "conv2 = nn.Sequential(nn.Conv1d(32, 64, 3, stride=2, padding=1), nn.ReLU(), nn.BatchNorm1d(64))\n",
    "conv3 = nn.Sequential(nn.Conv1d(64, 128, 3, stride=2, padding=1), nn.ReLU(), nn.BatchNorm1d(128))\n",
    "\n",
    "pool = nn.MaxPool1d(2, stride=2, return_indices=True)\n",
    "unpool = nn.MaxUnpool1d(2, stride=2)\n",
    "\n",
    "inv_conv3 = nn.Sequential(nn.ConvTranspose1d(128, 64, 3, stride=2, padding=1, output_padding=1), nn.ReLU(), nn.BatchNorm1d(64))\n",
    "inv_conv2 = nn.Sequential(nn.ConvTranspose1d(64, 32, 3, stride=2, padding=1), nn.ReLU(), nn.BatchNorm1d(32))\n",
    "inv_conv1 = nn.Sequential(nn.ConvTranspose1d(32, 3, 3, stride=2, padding=1, output_padding=1), nn.ReLU(), nn.BatchNorm1d(3))\n",
    "\n",
    "conv1_output = conv1(input2)\n",
    "pool1_output, indices1 = pool(conv1_output)\n",
    "\n",
    "conv2_output = conv2(pool1_output)\n",
    "pool2_output, indices2 = pool(conv2_output)\n",
    "\n",
    "conv3_output = conv3(pool2_output)\n",
    "pool3_output, indices3 = pool(conv3_output)\n",
    "\n",
    "unpool3_output = unpool(pool3_output, indices3, output_size=conv3_output.size())\n",
    "inv_conv3_output = inv_conv3(unpool3_output)\n",
    "\n",
    "unpool2_output = unpool(inv_conv3_output, indices2, output_size=conv2_output.size())\n",
    "inv_conv2_output = inv_conv2(unpool2_output)\n",
    "\n",
    "unpool1_output = unpool(inv_conv2_output, indices1, output_size=conv1_output.size())\n",
    "inv_conv1_output = inv_conv1(unpool1_output)\n",
    "\n",
    "print(conv1_output.shape)\n",
    "print(pool1_output.shape)\n",
    "print(conv2_output.shape)\n",
    "print(pool2_output.shape)\n",
    "print(conv3_output.shape)\n",
    "print(pool3_output.shape)\n",
    "print(unpool3_output.shape)\n",
    "print(inv_conv3_output.shape)\n",
    "print(unpool2_output.shape)\n",
    "print(inv_conv2_output.shape)\n",
    "print(unpool1_output.shape)\n",
    "print(inv_conv1_output.shape)\n",
    "\n",
    "print(pool3_output.squeeze(0).shape)\n",
    "pred = nn.Linear(128, 5)(pool3_output.squeeze(-1))\n",
    "print(pred.shape)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save(audio_AE.state_dict(), './saved_model/audio_AE_parameter.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0739513550858083"
      ]
     },
     "execution_count": 440,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "action_probs = {}\n",
    "action_probs['sit'] = 0.32\n",
    "action_probs['type'] = 0.32\n",
    "action_probs['click_mouse'] = 0.32\n",
    "action_probs['drink'] = 0.04\n",
    "assert sum(action_probs.values()) == 1\n",
    "\n",
    "np.random.rand()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "04:15:00\n",
      "15300\n",
      "15300\n",
      "./saved_model/multimodal_embed_model_3-3.pt\n"
     ]
    }
   ],
   "source": [
    "import datetime\n",
    "t = datetime.time(4, 15, 0)\n",
    "print(t)\n",
    "seconds = (t.hour * 60 + t.minute) * 60 + t.second\n",
    "print(seconds)\n",
    "t = datetime.datetime.strptime(\"04:15\", \"%H:%M\").time()\n",
    "seconds = (t.hour * 60 + t.minute) * 60 + t.second\n",
    "print(seconds)\n",
    "\n",
    "print('./saved_model/multimodal_embed_model_{}-{}.pt'.format(datetime.datetime.now().date().month, datetime.datetime.now().date().day))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum([1,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_1 = pd.DataFrame({\"category\": [\"no_sound\" for _ in range(40)],\n",
    "                     \"fold\": [1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5],\n",
    "                    \"path\": [\"audio/1-1-A.wav\", \"audio/1-1-B.wav\", \"audio/1-1-C.wav\", \"audio/1-1-D.wav\", \"audio/1-1-E.wav\", \"audio/1-1-F.wav\", \"audio/1-1-G.wav\", \"audio/1-1-H.wav\",\n",
    "                             \"audio/2-2-A.wav\", \"audio/2-2-B.wav\", \"audio/2-2-C.wav\", \"audio/2-2-D.wav\", \"audio/2-2-E.wav\", \"audio/2-2-F.wav\", \"audio/2-2-G.wav\", \"audio/2-2-H.wav\",\n",
    "                             \"audio/3-3-A.wav\", \"audio/3-3-B.wav\", \"audio/3-3-C.wav\", \"audio/3-3-D.wav\", \"audio/3-3-E.wav\", \"audio/3-3-F.wav\", \"audio/3-3-G.wav\", \"audio/3-3-H.wav\",\n",
    "                             \"audio/4-4-A.wav\", \"audio/4-4-B.wav\", \"audio/4-4-C.wav\", \"audio/4-4-D.wav\", \"audio/4-4-E.wav\", \"audio/4-4-F.wav\", \"audio/4-4-G.wav\", \"audio/4-4-H.wav\",\n",
    "                             \"audio/5-5-A.wav\", \"audio/5-5-B.wav\", \"audio/5-5-C.wav\", \"audio/5-5-D.wav\", \"audio/5-5-E.wav\", \"audio/5-5-F.wav\", \"audio/5-5-G.wav\", \"audio/5-5-H.wav\"],\n",
    "                    \"target\": [0 for _ in range(40)]})\n",
    "df_1.to_csv(\"silent_sound.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "criterion = nn.MSELoss() # mean square error loss\n",
    "optimizer = torch.optim.Adam(imu_AE.parameters(),\n",
    "                                lr=1e-3, \n",
    "                                weight_decay=1e-5) # <--\n",
    "imu_train_loader = torch.utils.data.DataLoader(imu_set, \n",
    "                                            batch_size=32, \n",
    "                                            shuffle=True)\n",
    "outputs = []\n",
    "for epoch in range(100):\n",
    "    for data in imu_train_loader:\n",
    "        accel, _ = data\n",
    "        recon = imu_AE(accel)\n",
    "        loss = criterion(recon, accel)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        optimizer.zero_grad()\n",
    "\n",
    "    print('Epoch:{}, Loss:{:.4f}'.format(epoch+1, float(loss)))\n",
    "    outputs.append((epoch, accel, recon),)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plot training data\n",
    "id = 11\n",
    "acc = outputs[-1][1].detach().numpy()\n",
    "true_x, true_y, true_z = acc[id][0], acc[id][1], acc[id][2]\n",
    "recon_acc = outputs[-1][2].detach().numpy()\n",
    "x, y, z = recon_acc[id][0], recon_acc[id][1], recon_acc[id][2]\n",
    "print(x.shape,y.shape)\n",
    "\n",
    "# Plot test data\n",
    "# id = 6\n",
    "# acc = true_acc_list[-1].detach().numpy()\n",
    "# recon_acc = recon_acc_list[-1].detach().numpy()\n",
    "# true_x, true_y, true_z = acc[id][0], acc[id][1], acc[id][2]\n",
    "# x, y, z = recon_acc[id][0], recon_acc[id][1], recon_acc[id][2]\n",
    "\n",
    "\n",
    "# true_sound = true_sound[0].item()\n",
    "# plt.plot(range(a.shape[-1]), a)\n",
    "# plt.plot(range(b.shape[-1]), b)\n",
    "plt.subplot(3,1,1)\n",
    "plt.plot(range(x.shape[-1]), true_x)\n",
    "plt.plot(range(x.shape[-1]), x)\n",
    "plt.title(\"x\")\n",
    "plt.legend([\"ground truth\", \"recon\"])\n",
    "\n",
    "plt.subplot(3,1,2)\n",
    "plt.plot(range(x.shape[-1]), true_y)\n",
    "plt.plot(range(x.shape[-1]), y)\n",
    "plt.title(\"y\")\n",
    "plt.legend([\"ground truth\", \"recon\"])\n",
    "\n",
    "plt.subplot(3,1,3)\n",
    "plt.plot(range(x.shape[-1]), true_z)\n",
    "plt.plot(range(x.shape[-1]), z)\n",
    "plt.title(\"z\")\n",
    "plt.legend([\"ground truth\", \"recon\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 256, 1])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input3 = torch.randn(1,256,11)\n",
    "aa = nn.AdaptiveAvgPool1d(1)(input3)\n",
    "aa.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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