4.神经网络.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "eb98d736",
   "metadata": {},
   "source": [
    "## 多层感知机"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cda402a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[ 0.0564,  0.3624, -0.2350, -0.1679, -0.1006,  0.1623,  0.1666, -0.0841,\n",
       "          0.2777, -0.2282],\n",
       "        [ 0.1388,  0.3262, -0.2209, -0.1086,  0.0419,  0.2177,  0.1464,  0.0087,\n",
       "          0.3764, -0.0959]], grad_fn=<AddmmBackward0>)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "from torch import nn\n",
    "from torch.nn import functional as F\n",
    "\n",
    "net = nn.Sequential(nn.Linear(20,256),nn.ReLU(),nn.Linear(256,10))\n",
    "\n",
    "X = torch.rand(2,20)\n",
    "net(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d033a4d4",
   "metadata": {},
   "source": [
    "多层感知机自己实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "68b654ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "class MLP(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.hidden = nn.Linear(20,256)\n",
    "        self.out = nn.Linear(256,10)\n",
    "    \n",
    "    def forward(self,X):\n",
    "        return self.out(F.relu(self.hidden(X)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1870885b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[ 0.0890,  0.0463, -0.1599, -0.0522, -0.0762,  0.2852, -0.2299, -0.2200,\n",
       "         -0.0646, -0.0457],\n",
       "        [ 0.0739, -0.0284, -0.0985, -0.0635, -0.0030,  0.3078, -0.2228, -0.0801,\n",
       "         -0.0412, -0.0737]], grad_fn=<AddmmBackward0>)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net = MLP()\n",
    "net(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6099716a",
   "metadata": {},
   "source": [
    "## Demo-天气预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "16ada3cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import torch\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8eb056c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>week</th>\n",
       "      <th>temp_2</th>\n",
       "      <th>temp_1</th>\n",
       "      <th>average</th>\n",
       "      <th>actual</th>\n",
       "      <th>friend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Fri</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45.6</td>\n",
       "      <td>45</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Sat</td>\n",
       "      <td>44</td>\n",
       "      <td>45</td>\n",
       "      <td>45.7</td>\n",
       "      <td>44</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Sun</td>\n",
       "      <td>45</td>\n",
       "      <td>44</td>\n",
       "      <td>45.8</td>\n",
       "      <td>41</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mon</td>\n",
       "      <td>44</td>\n",
       "      <td>41</td>\n",
       "      <td>45.9</td>\n",
       "      <td>40</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Tues</td>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "      <td>46.0</td>\n",
       "      <td>44</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  month  day  week  temp_2  temp_1  average  actual  friend\n",
       "0  2016      1    1   Fri      45      45     45.6      45      29\n",
       "1  2016      1    2   Sat      44      45     45.7      44      61\n",
       "2  2016      1    3   Sun      45      44     45.8      41      56\n",
       "3  2016      1    4   Mon      44      41     45.9      40      53\n",
       "4  2016      1    5  Tues      41      40     46.0      44      41"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据集\n",
    "features = pd.read_csv(\"./data/weather.csv\")\n",
    "features.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7bbcdee",
   "metadata": {},
   "source": [
    "temp_2：前天的最高温度值<br>\n",
    "temp_1：昨天的最高温度值<br>\n",
    "average：在历史中，每年这一天的平均最高温度值<br>\n",
    "actual：标签值，当天的真实最高温度<br>\n",
    "friend：朋友预测的可能值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "62aa9980",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(348, 9)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e333965c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将时间转换为时间序列\n",
    "import datetime\n",
    "\n",
    "# 分别得到年、月、日\n",
    "years = features['year']\n",
    "months = features['month']\n",
    "days = features['day']\n",
    "\n",
    "# datetime格式\n",
    "dates = [str(int(year))+'-'+str(int(month))+'-'+str(int(day)) for year,month,day in zip(years,months,days)]\n",
    "dates = [datetime.datetime.strptime(date,'%Y-%m-%d') for date in dates]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a6bc5b63",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>temp_2</th>\n",
       "      <th>temp_1</th>\n",
       "      <th>average</th>\n",
       "      <th>actual</th>\n",
       "      <th>friend</th>\n",
       "      <th>week_Fri</th>\n",
       "      <th>week_Mon</th>\n",
       "      <th>week_Sat</th>\n",
       "      <th>week_Sun</th>\n",
       "      <th>week_Thurs</th>\n",
       "      <th>week_Tues</th>\n",
       "      <th>week_Wed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>45.6</td>\n",
       "      <td>45</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>45</td>\n",
       "      <td>45.7</td>\n",
       "      <td>44</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>45</td>\n",
       "      <td>44</td>\n",
       "      <td>45.8</td>\n",
       "      <td>41</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>44</td>\n",
       "      <td>41</td>\n",
       "      <td>45.9</td>\n",
       "      <td>40</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "      <td>46.0</td>\n",
       "      <td>44</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  month  day  temp_2  temp_1  average  actual  friend  week_Fri  \\\n",
       "0  2016      1    1      45      45     45.6      45      29         1   \n",
       "1  2016      1    2      44      45     45.7      44      61         0   \n",
       "2  2016      1    3      45      44     45.8      41      56         0   \n",
       "3  2016      1    4      44      41     45.9      40      53         0   \n",
       "4  2016      1    5      41      40     46.0      44      41         0   \n",
       "\n",
       "   week_Mon  week_Sat  week_Sun  week_Thurs  week_Tues  week_Wed  \n",
       "0         0         0         0           0          0         0  \n",
       "1         0         1         0           0          0         0  \n",
       "2         0         0         1           0          0         0  \n",
       "3         1         0         0           0          0         0  \n",
       "4         0         0         0           0          1         0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 将week转为独热编码\n",
    "features = pd.get_dummies(features)\n",
    "features.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "688c6c2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 分离y_train\n",
    "labels = np.array(features['actual'])\n",
    "\n",
    "# 在特征中去掉y_train\n",
    "features = features.drop('actual',axis = 1)\n",
    "\n",
    "# 名字单独保存一下，以备后患\n",
    "feature_list = list(features.columns)\n",
    "\n",
    "# 转换成合适的格式\n",
    "features = np.array(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ebf08ab4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(348, 14)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8a43eda7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#有些数值大有些数值小，做标准化\n",
    "from sklearn import preprocessing\n",
    "input_features = preprocessing.StandardScaler().fit_transform(features)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e1e764b",
   "metadata": {},
   "source": [
    "StandardScaler<br>\n",
    "z = (x - u) / s<br>\n",
    "每个属性/每列来说所有数据都聚集在0附近，标准差为1，使得新的X数据集方差为1，均值为0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8bbb731",
   "metadata": {},
   "source": [
    "### 搭建网络模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "841af6a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将array转为张量\n",
    "x = torch.tensor(input_features,dtype = float)\n",
    "y = torch.tensor(labels,dtype = float)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d2dff5d",
   "metadata": {},
   "source": [
    "我们打算搭建具有一个隐藏层的多层感知机，为此，我们设定两个线性模型及参数，并且随机初始化它们。<br>\n",
    "观察训练集的特征为14，所以输入层的w必须是(14,m)，其中m我随意指定为128，意为将14个输入特征转化为隐藏层的128个隐藏特征。由矩阵相乘知识可以得出的是348×128的矩阵，所以我们的biases指定为(128×1)。隐藏层同理。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "de266c13",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 权重参数初始化\n",
    "weights = torch.randn((14,128),dtype = float,requires_grad = True)\n",
    "biases = torch.randn(128,dtype = float,requires_grad = True)\n",
    "weights2 = torch.randn((128,1),dtype = float,requires_grad = True)\n",
    "biases2 = torch.randn(1,dtype = float,requires_grad = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0e64a989",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 学习率\n",
    "learning_rate = 0.01\n",
    "losses = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "114bed51",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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     "output_type": "stream",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        ...,\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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    {
     "name": "stdout",
     "output_type": "stream",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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    {
     "name": "stdout",
     "output_type": "stream",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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    {
     "name": "stdout",
     "output_type": "stream",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        ...,\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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     "output_type": "stream",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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     "output_type": "stream",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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    {
     "name": "stdout",
     "output_type": "stream",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "loss--- tensor(nan, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        ...,\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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    {
     "name": "stdout",
     "output_type": "stream",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
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      "        ...,\n",
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      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n",
      "tensor([[nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        ...,\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan],\n",
      "        [nan, nan, nan,  ..., nan, nan, nan]], dtype=torch.float64)\n"
     ]
    }
   ],
   "source": [
    "# 梯度下降\n",
    "for i in range(1000):\n",
    "    # 计算隐藏层-线性模型\n",
    "    hidden = x.mm(weights) + biases\n",
    "    # 加入激活函数-加入激活函数\n",
    "    hidden = torch.relu(hidden)\n",
    "    # 预测结果计算\n",
    "    predictions = hidden.mm(weights2) + biases2    \n",
    "    # 计算损失\n",
    "    loss = torch.mean((predictions - y) ** 2)\n",
    "    # 记录损失\n",
    "    losses.append(loss.data.numpy())\n",
    "    \n",
    "    if i%100 == 0:\n",
    "        print('loss---',loss)\n",
    "\n",
    "    # 反向传播\n",
    "    loss.backward()\n",
    "\n",
    "\n",
    "    print(weights.grad.data)\n",
    "    # 更新参数\n",
    "    weights.data.add_(-learning_rate * weights.grad.data)\n",
    "    biases.data.add_(-learning_rate * biases.grad.data)\n",
    "    weights2.data.add_(-learning_rate * weights2.grad.data)\n",
    "    biases2.data.add_(-learning_rate * biases2.grad.data)\n",
    "    \n",
    "    # 每次迭代前清空梯度\n",
    "    weights.grad.data.zero_()\n",
    "    biases.grad.data.zero_()\n",
    "    weights2.grad.data.zero_()\n",
    "    biases2.grad.data.zero_()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7657e83e",
   "metadata": {},
   "source": [
    "## 使用API实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "a6cdaf7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 指定规模\n",
    "input_size = input_features.shape[1]\n",
    "hidden_size = 128\n",
    "output_size = 1\n",
    "batch_size = 16\n",
    "\n",
    "# 搭建网络\n",
    "my_nn = torch.nn.Sequential(\n",
    "    torch.nn.Linear(input_size,hidden_size),\n",
    "    torch.nn.Sigmoid(),\n",
    "    torch.nn.Linear(hidden_size,output_size),\n",
    ")\n",
    "\n",
    "# 定义损失函数\n",
    "cost = torch.nn.MSELoss(reduction = 'mean')\n",
    "optimizer = torch.optim.Adam(my_nn.parameters(),lr = 0.001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "de35ec55",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Users\\QianWu\\anaconda3\\lib\\site-packages\\torch\\nn\\modules\\loss.py:530: UserWarning: Using a target size (torch.Size([16])) that is different to the input size (torch.Size([16, 1])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.\n",
      "  return F.mse_loss(input, target, reduction=self.reduction)\n",
      "D:\\Users\\QianWu\\anaconda3\\lib\\site-packages\\torch\\nn\\modules\\loss.py:530: UserWarning: Using a target size (torch.Size([12])) that is different to the input size (torch.Size([12, 1])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.\n",
      "  return F.mse_loss(input, target, reduction=self.reduction)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 3930.1135\n",
      "100 37.743317\n",
      "200 35.646347\n",
      "300 35.30317\n",
      "400 35.13176\n",
      "500 34.995995\n",
      "600 34.874374\n",
      "700 34.755116\n",
      "800 34.635433\n",
      "900 34.514103\n"
     ]
    }
   ],
   "source": [
    "# 训练网络\n",
    "losses = []\n",
    "for i in range(1000):\n",
    "    batch_loss = []\n",
    "    # 小批量随机梯度下降进行训练\n",
    "    for start in range(0,len(input_features),batch_size):\n",
    "        end = start+batch_size if start + batch_size < len(input_features) else len(input_features)\n",
    "        xx = torch.tensor(input_features[start:end],dtype = torch.float,requires_grad = True)\n",
    "        yy = torch.tensor(labels[start:end],dtype = torch.float,requires_grad = True)\n",
    "        prediction = my_nn(xx)\n",
    "        loss = cost(prediction,yy)\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward(retain_graph=True)\n",
    "        optimizer.step()\n",
    "        batch_loss.append(loss.data.numpy())\n",
    "        \n",
    "    # 打印损失\n",
    "    # 打印损失值\n",
    "    if i % 100 == 0:\n",
    "        losses.append(np.mean(batch_loss))\n",
    "        print(i,np.mean(batch_loss))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91dbddb8",
   "metadata": {},
   "source": [
    "### 评估模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "bfd56baf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = torch.tensor(input_features,dtype = torch.float)\n",
    "predict = my_nn(x).data.numpy()\n",
    "\n",
    "# 转换日期格式\n",
    "dates = [str(int(year))+'-'+str(int(month))+'-'+str(int(day)) for year,month,day in zip(years,months,days)]\n",
    "dates = [datetime.datetime.strptime(date,'%Y-%m-%d') for date in dates]\n",
    "\n",
    "# 创建一个表格来存日期和其对应的标签数值\n",
    "true_data = pd.DataFrame(data = {'date':dates,'actual':labels})\n",
    "\n",
    "# 同理，在创建一个来存日期和其对应的模型预测值\n",
    "mouths = features[:,feature_list.index('month')]\n",
    "days = features[:,feature_list.index('day')]\n",
    "years = features[:,feature_list.index('year')]\n",
    "\n",
    "test_dates = [str(int(year))+'-'+str(int(month))+'-'+str(int(day)) for year,month,day in zip(years,months,days)]\n",
    "test_dates = [datetime.datetime.strptime(date,'%Y-%m-%d') for date in test_dates]\n",
    "\n",
    "predictions_data = pd.DataFrame(data = {'date':test_dates,'prediction':predict.reshape(-1)})\n",
    "\n",
    "# 真实值\n",
    "plt.plot(true_data['date'],true_data['actual'],'b-',label = 'actual')\n",
    "\n",
    "# 预测值\n",
    "plt.plot(predictions_data['date'],predictions_data['prediction'],'ro',label = 'prediction')\n",
    "plt.xticks(rotation = '60')\n",
    "plt.legend()\n",
    "\n",
    "# 图名\n",
    "plt.xlabel('Date');plt.ylabel('Maximum Temperature (F)');plt.title('Actual and Predicted Values')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe017797",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}