attentionWithdataLoader.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hereagain-Y/TCR_VAE/blob/main/attentionWithdataLoader.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "DY1TEH_7O5bI"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "import torch.nn.functional as F\n",
        "import torch.nn as nn\n",
        "import random\n",
        "import itertools\n",
        "import numpy as np\n",
        "import itertools\n",
        "import pandas as pd \n",
        "import random\n",
        "import time\n",
        "from datetime import datetime\n",
        "from pkgutil import extend_path\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "from six.moves import xrange\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torchvision.transforms as transforms\n",
        "import numpy as np\n",
        "\n",
        "from tqdm import tqdm\n",
        "from torchvision.utils import save_image, make_grid\n",
        "from torch.utils.data import DataLoader, Subset\n",
        "from sklearn.model_selection import train_test_split\n",
        "#\n",
        "from scipy.spatial import distance\n",
        "import random \n",
        "from scipy import spatial\n",
        "from scipy import stats\n",
        "from torch.utils.data import TensorDataset, DataLoader\n",
        "import os\n",
        "import glob"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "3UXMyOTwPKrU"
      },
      "outputs": [],
      "source": [
        "cuda = True\n",
        "device = torch.device(\"cuda\" if cuda else \"cpu\")\n",
        "n_feature = 16   "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hDZAXVLPPPl4",
        "outputId": "3aeefb4a-02a8-419a-b38d-dd77bbafb333"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "dyczPe8tPZ4u"
      },
      "outputs": [],
      "source": [
        "\n",
        "def load_data(path,balance_sample_num):\n",
        "    dat = pd.read_csv(path+\"/latentdata.csv\",sep=',')\n",
        "    index, cnt =np.unique(dat['bags'],return_counts=True)\n",
        "    data_list=[]\n",
        "    for i in index:\n",
        "        data_list.append(dat.loc[dat['bags']==i,'1':].to_numpy().tolist())\n",
        "    max_length=np.max(cnt)\n",
        "    data_list_max_length = []\n",
        "    for i in range(2*balance_sample_num): # zero paddings\n",
        "          #temp_pad = np.zeros((max_length - len(data_list[i]), 32)).tolist()\n",
        "          temp_pad = np.zeros((max_length - len(data_list[i]), 32))\n",
        "          temp_ins = data_list[i]\n",
        "          temp_array = np.concatenate((temp_ins,temp_pad),axis=0)\n",
        "          data_list_max_length.append(temp_array)\n",
        "    seq_array = np.array(data_list_max_length)\n",
        "    label=[0,1]\n",
        "    labels=list(itertools.chain.from_iterable(itertools.repeat(x, balance_sample_num) for x in label))\n",
        "    label_array=np.array(labels)\n",
        "\n",
        "    data = torch.tensor(seq_array, dtype=torch.float32)\n",
        "    target = torch.tensor(label_array,dtype=torch.float32)\n",
        "    dataset_all = TensorDataset(data,target)\n",
        "\n",
        "    return data_list,dataset_all"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "zssAFe1gQsMm"
      },
      "outputs": [],
      "source": [
        "dat = pd.read_csv(\"/content/drive/My Drive/DL/latentdata.csv\",sep=',')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_list,dataset_all =load_data(r'/content/drive/My Drive/DL',9)"
      ],
      "metadata": {
        "id": "J2hi-mjrJDs3"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "XAlwyC1bQE-q"
      },
      "outputs": [],
      "source": [
        "train_loader = DataLoader(dataset_all, batch_size= 10,shuffle=True)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class Attention(nn.Module):\n",
        "    def __init__(self):\n",
        "        super(Attention, self).__init__()\n",
        "        self.L =32\n",
        "        self.K = 1\n",
        "        self.fclayers=nn.Sequential(\n",
        "            nn.Linear(self.L, self.L),\n",
        "            nn.Dropout(0.5),\n",
        "            nn.ReLU(), # nn,SELU()\n",
        "            nn.Linear(self.L, self.L),\n",
        "            nn.Dropout(0.5),\n",
        "            nn.ReLU(),\n",
        "            nn.Linear(self.L, self.L),\n",
        "            nn.Dropout(0.5),\n",
        "            nn.ReLU()\n",
        "            \n",
        "        )\n",
        "        self.attention = nn.Linear(self.L,self.K)\n",
        "   \n",
        "\n",
        "        self.out = nn.Sequential(\n",
        "            nn.Linear(self.L*self.K,self.L) ,\n",
        "            nn.BatchNorm1d(self.L),\n",
        "            nn.ReLU())\n",
        "        \n",
        "        self.classifier = nn.Sequential(\n",
        "            nn.Linear(self.L * self.K, 1), \n",
        "            nn.Sigmoid()\n",
        "        )\n",
        "    \n",
        "    def forward(self,x):\n",
        "        out = self.fclayers(x) #32\n",
        "\n",
        "        attention = torch.squeeze(self.attention(out)) # 1 \n",
        "        attention = torch.transpose(attention,0,1)\n",
        "\n",
        "     # attention =self.sparseatt(attention)\n",
        "        attention =torch.softmax(attention,dim=1)\n",
        "      #attention_bag= torch.softmax(attention,dim=1) \n",
        "      \n",
        "        out = torch.transpose(out,0,1)\n",
        "        new_features = torch.bmm(torch.unsqueeze(attention, 1), out)\n",
        "        new_features = torch.squeeze(new_features)\n",
        "      \n",
        "        sample_feature =self.out(new_features)\n",
        "        predictions = self.classifier(sample_feature) \n",
        "        Y_hat = torch.ge(predictions, 0.5).float() \n",
        "        return predictions, attention,Y_hat\n",
        "\n",
        "\n",
        "     # attention = torch.transpose(attention,0,1)\n",
        "\n",
        "\n",
        "      # * original to get new futures \n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "    "
      ],
      "metadata": {
        "id": "d-DSxIHzJp0Q"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model = Attention().to(device)"
      ],
      "metadata": {
        "id": "nNU7TZ5QJtKG"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def loss_function( label, prediction ):\n",
        "    reproduction_loss = nn.functional.binary_cross_entropy(label, prediction, reduction='sum')\n",
        "    return reproduction_loss\n",
        "       \n",
        "def calculate_classification_error(Y_hat,Y):\n",
        "    Y = Y.float()\n",
        "    error = 1. - Y_hat.eq(Y).cpu().float().mean().data\n",
        "\n",
        "    return error, Y_hat  "
      ],
      "metadata": {
        "id": "2ygEkKgPJyNP"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "from torch.optim import Adam\n",
        "optimizer = Adam(model.parameters(), lr=1e-3)  \n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import roc_auc_score\n",
        "epochs=1000"
      ],
      "metadata": {
        "id": "skguGgtRJ0eR"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_loss= []\n",
        "for epoch in range(epochs):\n",
        "    overall_loss =0\n",
        "    train_error = 0 \n",
        "    for batch_idx, (data, target) in enumerate(train_loader):\n",
        "      data,target = torch.transpose(data,1,0).to(device),target.to(device) #[5]\n",
        "      optimizer.zero_grad()\n",
        "\n",
        "      predicitons, attention,Y_hat = model(data)\n",
        "      print(attention)\n",
        "      predicitons =torch.squeeze(predicitons)#[5]\n",
        "      loss =loss_function(predicitons,target)\n",
        "      auc = roc_auc_score(target.cpu().detach().numpy(),predicitons.cpu().detach().numpy())\n",
        "      label =target.cpu().detach().numpy()\n",
        "      y = Y_hat.cpu().detach().numpy()\n",
        "      overall_loss += loss.item()\n",
        "      #print(overall_loss)\n",
        "      loss.backward()\n",
        "      optimizer.step()\n",
        "    train_loss.append(overall_loss/len(dataset_all))\n",
        "\n",
        "    if (epoch % 100 == 0):\n",
        "      print(\"\\tEpoch\", epoch , \"complete!\", \"\\tAverage Loss: \", train_loss[epoch],accuracy_score(label, y)*100,'auc:',auc)\n",
        "    \n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "yPuzAl9mKV_1",
        "outputId": "994c4bd9-2b1f-42f8-e5db-6c4d75dad871"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n",
            "        [1.1396e-04, 4.1221e-04, 7.0775e-04,  ..., 1.2553e-04, 6.2074e-05,\n",
            "         6.4524e-05],\n",
            "        [4.0747e-04, 1.0891e-03, 8.1945e-04,  ..., 6.0075e-05, 5.9635e-05,\n",
            "         1.0421e-04],\n",
            "        [1.2449e-04, 2.9477e-04, 2.4801e-04,  ..., 3.7986e-05, 4.4152e-05,\n",
            "         4.6484e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.0131e-04, 3.5415e-04, 3.6732e-04,  ..., 3.4697e-05, 1.7873e-05,\n",
            "         2.0143e-05],\n",
            "        [8.6438e-04, 1.1448e-04, 1.1390e-04,  ..., 5.5977e-05, 4.8042e-05,\n",
            "         7.7320e-05],\n",
            "        [3.3776e-04, 9.8715e-05, 2.7644e-04,  ..., 4.8654e-05, 3.8017e-05,\n",
            "         4.4425e-05],\n",
            "        ...,\n",
            "        [5.3538e-05, 4.3893e-05, 7.3099e-04,  ..., 4.8866e-05, 3.9814e-05,\n",
            "         4.2762e-05],\n",
            "        [1.9570e-04, 1.8529e-03, 3.7145e-04,  ..., 9.8423e-05, 8.0315e-05,\n",
            "         5.4677e-05],\n",
            "        [6.6555e-04, 1.9844e-04, 1.5425e-04,  ..., 8.9803e-05, 9.0231e-05,\n",
            "         1.0042e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[7.5702e-04, 2.2577e-04, 1.2120e-04,  ..., 6.1052e-05, 7.5535e-05,\n",
            "         1.0271e-04],\n",
            "        [8.4675e-04, 1.5129e-04, 1.9106e-04,  ..., 5.4481e-05, 4.7666e-05,\n",
            "         6.6506e-05],\n",
            "        [1.0259e-04, 4.2157e-04, 1.5213e-04,  ..., 1.7004e-05, 2.0443e-05,\n",
            "         1.2802e-05],\n",
            "        ...,\n",
            "        [8.1946e-05, 1.3070e-04, 8.9821e-05,  ..., 2.0651e-05, 1.5548e-05,\n",
            "         2.8793e-05],\n",
            "        [2.7396e-04, 1.9347e-04, 1.9588e-04,  ..., 8.4642e-05, 8.6206e-05,\n",
            "         5.3130e-05],\n",
            "        [2.1857e-04, 1.4523e-03, 2.3609e-04,  ..., 7.2000e-05, 2.7157e-05,\n",
            "         4.9516e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.1413e-04, 1.7712e-03, 2.0120e-04,  ..., 6.9200e-05, 4.5217e-05,\n",
            "         4.5703e-05],\n",
            "        [1.4752e-04, 8.7200e-05, 3.8423e-04,  ..., 1.9907e-05, 2.7478e-05,\n",
            "         3.5128e-05],\n",
            "        [5.1007e-04, 1.2283e-03, 3.0214e-04,  ..., 6.0520e-05, 7.0320e-05,\n",
            "         1.2782e-04],\n",
            "        ...,\n",
            "        [2.4088e-04, 2.5702e-04, 3.1166e-05,  ..., 1.2927e-04, 4.4908e-05,\n",
            "         5.2430e-05],\n",
            "        [2.6135e-04, 1.0886e-04, 4.5611e-04,  ..., 5.1709e-05, 2.9744e-05,\n",
            "         3.9478e-05],\n",
            "        [9.1806e-05, 1.5790e-04, 2.0551e-04,  ..., 1.8595e-05, 2.5014e-05,\n",
            "         1.8839e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[9.6130e-05, 2.0356e-03, 1.4231e-04,  ..., 5.8381e-05, 5.8278e-05,\n",
            "         5.4630e-05],\n",
            "        [4.2589e-05, 1.2219e-04, 1.1141e-04,  ..., 1.6731e-05, 1.7941e-05,\n",
            "         1.4043e-05],\n",
            "        [3.1055e-04, 1.3051e-04, 2.1355e-04,  ..., 7.3227e-05, 7.6267e-05,\n",
            "         4.8244e-05],\n",
            "        ...,\n",
            "        [5.9695e-04, 4.7005e-04, 1.5137e-03,  ..., 7.7481e-05, 1.1559e-04,\n",
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            "        [7.8833e-05, 5.7722e-05, 8.5952e-04,  ..., 4.9274e-05, 4.9526e-05,\n",
            "         3.4396e-05],\n",
            "        [3.9280e-04, 7.2646e-04, 3.3141e-04,  ..., 6.9003e-05, 7.2760e-05,\n",
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            "tensor([[9.3750e-05, 3.7197e-05, 7.0217e-05,  ..., 1.7561e-05, 1.3326e-05,\n",
            "         2.2853e-05],\n",
            "        [3.6090e-05, 3.8730e-05, 1.2280e-04,  ..., 4.1519e-05, 5.0039e-05,\n",
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            "        [2.8191e-04, 1.2767e-04, 1.4646e-04,  ..., 4.2261e-05, 5.1624e-05,\n",
            "         5.2984e-05],\n",
            "        ...,\n",
            "        [1.2571e-04, 2.2412e-04, 1.0860e-04,  ..., 6.1475e-05, 8.1474e-05,\n",
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            "        [5.5341e-04, 2.4430e-04, 1.8131e-04,  ..., 5.8298e-05, 6.5631e-05,\n",
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            "        [2.7889e-05, 7.1504e-05, 3.8148e-05,  ..., 2.3253e-05, 1.7967e-05,\n",
            "         1.4753e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.3615e-03, 2.2237e-04, 2.5298e-04,  ..., 7.4026e-05, 5.3817e-05,\n",
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            "        [2.0626e-04, 1.8176e-03, 3.1071e-04,  ..., 5.8504e-05, 7.2140e-05,\n",
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            "        ...,\n",
            "        [5.4451e-04, 1.9595e-04, 2.0700e-04,  ..., 7.4038e-05, 6.1063e-05,\n",
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            "        [6.8349e-05, 2.6793e-05, 8.2439e-05,  ..., 1.7486e-05, 1.3324e-05,\n",
            "         1.3233e-05],\n",
            "        [1.2636e-04, 9.0355e-05, 3.4868e-04,  ..., 4.2755e-05, 4.8616e-05,\n",
            "         3.9406e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.5587e-04, 4.2514e-04, 6.5717e-03,  ..., 5.2722e-05, 1.0811e-04,\n",
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            "        [3.1880e-05, 2.2518e-04, 9.3255e-05,  ..., 1.2323e-05, 1.2684e-05,\n",
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            "        [5.8704e-04, 2.0984e-04, 1.0925e-04,  ..., 3.2804e-05, 4.5367e-05,\n",
            "         6.3931e-05],\n",
            "        ...,\n",
            "        [1.2776e-04, 3.3604e-04, 1.2593e-04,  ..., 5.5003e-05, 4.4871e-05,\n",
            "         3.7455e-05],\n",
            "        [4.3366e-05, 5.3112e-05, 4.3533e-05,  ..., 3.4351e-05, 6.5423e-05,\n",
            "         3.2103e-04],\n",
            "        [1.9879e-04, 3.3258e-04, 4.2642e-04,  ..., 4.3420e-05, 4.9957e-05,\n",
            "         4.2237e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.8032e-04, 4.9723e-04, 3.5526e-04,  ..., 7.3966e-05, 6.1378e-05,\n",
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            "        [8.0106e-05, 3.3544e-05, 6.1818e-05,  ..., 2.2795e-05, 1.6972e-05,\n",
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            "        [4.3348e-04, 2.0563e-03, 3.4902e-04,  ..., 5.0815e-05, 6.9054e-05,\n",
            "         7.1855e-05],\n",
            "        ...,\n",
            "        [3.8446e-04, 4.7500e-04, 1.7635e-04,  ..., 5.8360e-05, 5.2713e-05,\n",
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            "        [1.9691e-04, 2.1062e-04, 7.6216e-04,  ..., 3.6549e-05, 4.0758e-05,\n",
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            "tensor([[4.0863e-03, 8.2534e-04, 1.6002e-04,  ..., 3.3385e-05, 5.3464e-05,\n",
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            "        [2.5424e-04, 6.9818e-05, 5.6742e-05,  ..., 2.3872e-05, 2.7233e-05,\n",
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            "        [1.2471e-04, 7.0222e-05, 3.5954e-05,  ..., 4.1546e-05, 7.9754e-05,\n",
            "         1.4897e-04],\n",
            "        ...,\n",
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            "         3.4832e-05],\n",
            "        [4.6209e-04, 1.9437e-04, 2.7497e-04,  ..., 7.3505e-05, 1.0423e-04,\n",
            "         8.4103e-05],\n",
            "        [1.0169e-04, 7.7920e-05, 1.6074e-04,  ..., 2.4237e-05, 2.6115e-05,\n",
            "         2.6968e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.3115e-04, 1.9724e-04, 6.3252e-04,  ..., 6.8493e-05, 7.2748e-05,\n",
            "         5.3494e-05],\n",
            "        [5.3871e-05, 9.4113e-05, 1.9031e-05,  ..., 5.4852e-05, 3.0944e-05,\n",
            "         4.8574e-05],\n",
            "        [1.1301e-04, 5.6213e-04, 4.3423e-04,  ..., 3.8700e-05, 6.3787e-05,\n",
            "         5.5674e-05],\n",
            "        ...,\n",
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            "         5.6697e-05],\n",
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            "         2.5004e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.6436e-05, 7.5174e-05, 1.2230e-04,  ..., 2.6520e-05, 1.6423e-05,\n",
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            "         1.0295e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.3364e-05],\n",
            "        ...,\n",
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            "         8.1539e-05],\n",
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            "         3.0761e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.3926e-05],\n",
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            "         2.1931e-05],\n",
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            "         1.1005e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.8745e-05],\n",
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            "         3.3407e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.1404e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.3326e-05],\n",
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            "         6.5220e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.3661e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.9165e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.9186e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.6542e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0288e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0042e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.2239e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.7055e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0220e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0614e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.1534e-05],\n",
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            "         1.2571e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.2360e-04],\n",
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            "         5.5125e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.0338e-05],\n",
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            "         5.2052e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.9738e-04, 6.7275e-05, 7.9196e-05,  ..., 2.3122e-05, 1.6334e-05,\n",
            "         3.0766e-05],\n",
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            "         5.2662e-05],\n",
            "        ...,\n",
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            "         3.9766e-05],\n",
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            "         2.4918e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.3616e-05],\n",
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            "         9.7637e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.0465e-05],\n",
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            "         7.6048e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.2632e-05],\n",
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            "         7.7434e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.6562e-04, 3.0524e-04, 2.4212e-04,  ..., 4.6546e-05, 7.4814e-05,\n",
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            "         2.5606e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0707e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.9309e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.1718e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.3369e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.6614e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.6551e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.2600e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.1223e-04],\n",
            "        ...,\n",
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            "         3.5225e-05],\n",
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            "         1.8533e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.5466e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.9240e-05],\n",
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            "         5.4011e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.8616e-05],\n",
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            "         3.2853e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.8730e-05],\n",
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            "         4.8048e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.3569e-05],\n",
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            "         7.4014e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.0794e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.0181e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.4534e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.8429e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.4496e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.2584e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.8267e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.4503e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.4131e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.3771e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.9798e-05],\n",
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            "        [5.1569e-05, 5.9795e-05, 9.0266e-05,  ..., 1.1045e-04, 7.4658e-05,\n",
            "         5.5084e-05],\n",
            "        [3.0673e-04, 1.1088e-04, 1.8427e-04,  ..., 6.5035e-05, 1.0997e-04,\n",
            "         9.4234e-05],\n",
            "        [3.4326e-04, 2.6008e-04, 5.2420e-04,  ..., 9.5340e-05, 1.2917e-04,\n",
            "         8.6156e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.8504e-04, 2.5580e-04, 1.2975e-04,  ..., 8.6902e-05, 5.1960e-05,\n",
            "         6.7401e-05],\n",
            "        [7.8608e-05, 1.1333e-04, 2.2689e-04,  ..., 8.5118e-05, 7.5927e-05,\n",
            "         8.2759e-05],\n",
            "        [9.2064e-04, 3.7998e-04, 5.4038e-04,  ..., 5.7340e-05, 4.4387e-05,\n",
            "         5.2947e-05],\n",
            "        ...,\n",
            "        [7.9120e-05, 2.6584e-04, 3.5475e-04,  ..., 4.1483e-05, 3.7891e-05,\n",
            "         3.0685e-05],\n",
            "        [2.3664e-04, 1.1590e-04, 6.6466e-05,  ..., 3.8984e-05, 4.1265e-05,\n",
            "         2.0998e-05],\n",
            "        [6.7550e-05, 1.3492e-04, 1.4117e-04,  ..., 4.8597e-05, 3.7550e-05,\n",
            "         2.8628e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.1507e-04, 2.9369e-04, 1.6820e-04,  ..., 5.5707e-05, 9.8722e-05,\n",
            "         1.0227e-04],\n",
            "        [1.2001e-03, 2.4931e-04, 4.1898e-04,  ..., 1.4587e-04, 9.9988e-05,\n",
            "         1.0150e-04],\n",
            "        [2.3444e-04, 1.2199e-04, 5.0586e-05,  ..., 2.6847e-05, 3.2875e-05,\n",
            "         3.2376e-05],\n",
            "        ...,\n",
            "        [4.2936e-04, 2.4442e-04, 3.1832e-04,  ..., 1.2825e-04, 7.5907e-05,\n",
            "         9.8837e-05],\n",
            "        [1.1463e-04, 1.5912e-04, 3.3209e-04,  ..., 5.6742e-05, 9.1603e-05,\n",
            "         6.1894e-05],\n",
            "        [9.1109e-05, 7.3662e-05, 1.3864e-04,  ..., 3.3611e-05, 3.1793e-05,\n",
            "         3.2308e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.4058e-04, 3.2652e-04, 6.9361e-04,  ..., 6.8660e-05, 5.4380e-05,\n",
            "         6.6693e-05],\n",
            "        [3.9620e-04, 5.4972e-04, 1.1218e-04,  ..., 5.7685e-05, 5.6225e-05,\n",
            "         4.6811e-05],\n",
            "        [4.3789e-05, 9.6905e-05, 1.0580e-04,  ..., 3.7418e-05, 3.3339e-05,\n",
            "         2.6863e-05],\n",
            "        ...,\n",
            "        [5.0457e-04, 2.0899e-04, 3.6886e-04,  ..., 5.8892e-05, 8.4320e-05,\n",
            "         7.1286e-05],\n",
            "        [7.7198e-04, 3.3358e-04, 7.8864e-04,  ..., 4.9070e-05, 7.3944e-05,\n",
            "         5.2196e-05],\n",
            "        [1.9707e-04, 5.0573e-05, 1.0511e-04,  ..., 3.4579e-05, 2.7261e-05,\n",
            "         2.9315e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.5450e-04, 2.8258e-04, 1.3233e-04,  ..., 5.8720e-05, 1.0728e-04,\n",
            "         7.1568e-05],\n",
            "        [2.5672e-04, 1.8292e-04, 1.5555e-04,  ..., 4.7516e-05, 1.1437e-04,\n",
            "         1.2095e-04],\n",
            "        [1.2772e-04, 1.0461e-04, 1.8370e-04,  ..., 2.8641e-05, 2.6601e-05,\n",
            "         3.0837e-05],\n",
            "        ...,\n",
            "        [1.3443e-04, 1.6479e-04, 1.5820e-04,  ..., 5.0574e-05, 3.7741e-05,\n",
            "         5.7115e-05],\n",
            "        [2.6025e-04, 5.2088e-04, 3.7694e-04,  ..., 8.1072e-05, 8.1696e-05,\n",
            "         7.3678e-05],\n",
            "        [1.8248e-04, 1.9006e-04, 2.0998e-04,  ..., 3.8230e-05, 5.0798e-05,\n",
            "         5.0680e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.6839e-04, 4.2722e-04, 4.5941e-04,  ..., 5.7485e-05, 1.0782e-04,\n",
            "         1.0655e-04],\n",
            "        [1.2173e-04, 1.2942e-04, 3.7364e-04,  ..., 2.8659e-05, 2.6113e-05,\n",
            "         2.5024e-05],\n",
            "        [1.1344e-04, 2.5268e-04, 1.2371e-04,  ..., 4.2121e-05, 3.4973e-05,\n",
            "         2.3890e-05],\n",
            "        ...,\n",
            "        [1.4630e-04, 4.3273e-04, 1.7234e-04,  ..., 3.7145e-05, 3.9371e-05,\n",
            "         1.8272e-05],\n",
            "        [1.0711e-04, 1.2273e-04, 2.5362e-04,  ..., 3.1615e-05, 2.8880e-05,\n",
            "         4.7125e-05],\n",
            "        [9.9006e-05, 2.6916e-04, 1.5823e-04,  ..., 7.8611e-05, 7.8254e-05,\n",
            "         3.5584e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.0592e-05, 4.6267e-05, 1.2861e-04,  ..., 2.6409e-05, 2.3759e-05,\n",
            "         2.5392e-05],\n",
            "        [1.5739e-04, 3.2227e-04, 6.7475e-05,  ..., 2.2063e-05, 2.4585e-05,\n",
            "         2.9970e-05],\n",
            "        [2.0938e-04, 9.1469e-04, 4.5722e-04,  ..., 5.7155e-05, 5.3857e-05,\n",
            "         4.9432e-05],\n",
            "        ...,\n",
            "        [3.0584e-04, 8.3225e-04, 1.0964e-03,  ..., 1.3576e-04, 9.8396e-05,\n",
            "         1.2394e-04],\n",
            "        [2.1643e-04, 1.8759e-04, 2.8579e-04,  ..., 8.9396e-05, 9.3200e-05,\n",
            "         7.0332e-05],\n",
            "        [3.2975e-04, 1.1423e-04, 5.9815e-05,  ..., 3.3313e-05, 3.0287e-05,\n",
            "         4.9925e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.3200e-04, 4.6200e-04, 1.4503e-04,  ..., 6.6659e-05, 1.0182e-04,\n",
            "         1.1907e-04],\n",
            "        [2.4716e-04, 6.3228e-04, 8.3268e-04,  ..., 7.2507e-05, 1.0202e-04,\n",
            "         5.5416e-05],\n",
            "        [1.8568e-04, 2.5349e-04, 3.0512e-04,  ..., 7.6380e-05, 5.7690e-05,\n",
            "         1.0020e-04],\n",
            "        ...,\n",
            "        [4.4911e-04, 1.6599e-04, 1.4537e-04,  ..., 7.1977e-05, 4.8590e-05,\n",
            "         7.3801e-05],\n",
            "        [9.5202e-05, 5.9861e-05, 2.7490e-04,  ..., 1.3336e-04, 1.0156e-04,\n",
            "         7.4327e-05],\n",
            "        [6.8830e-05, 1.8801e-04, 1.1559e-04,  ..., 2.3209e-05, 2.4352e-05,\n",
            "         4.1991e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.9782e-04, 1.1542e-04, 4.3684e-04,  ..., 7.4223e-05, 6.8401e-05,\n",
            "         5.0422e-05],\n",
            "        [3.4759e-04, 3.2496e-04, 3.6839e-04,  ..., 5.4314e-05, 4.5423e-05,\n",
            "         5.3861e-05],\n",
            "        [1.7301e-04, 3.1321e-04, 1.7507e-04,  ..., 8.9052e-05, 7.6044e-05,\n",
            "         1.1901e-04],\n",
            "        ...,\n",
            "        [5.1906e-04, 2.6096e-04, 6.6505e-04,  ..., 1.0433e-04, 9.0313e-05,\n",
            "         4.4658e-05],\n",
            "        [1.5761e-04, 1.8439e-04, 6.9369e-05,  ..., 3.2784e-05, 3.5333e-05,\n",
            "         4.0473e-05],\n",
            "        [2.2637e-04, 4.1198e-04, 2.2227e-04,  ..., 5.6275e-05, 6.1892e-05,\n",
            "         4.8788e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[9.8469e-05, 4.8080e-05, 1.6661e-04,  ..., 2.7440e-05, 2.9818e-05,\n",
            "         2.6396e-05],\n",
            "        [5.1706e-04, 8.0404e-04, 3.1383e-04,  ..., 8.4119e-05, 8.8771e-05,\n",
            "         1.0370e-04],\n",
            "        [3.8618e-04, 1.5175e-04, 3.0978e-04,  ..., 6.3357e-05, 8.3331e-05,\n",
            "         5.3271e-05],\n",
            "        ...,\n",
            "        [5.1959e-05, 4.1185e-05, 5.5924e-05,  ..., 1.9926e-05, 3.3867e-05,\n",
            "         2.8623e-05],\n",
            "        [4.3198e-05, 8.8284e-05, 5.2513e-04,  ..., 7.4152e-05, 6.5995e-05,\n",
            "         7.0290e-05],\n",
            "        [3.3247e-04, 3.5977e-04, 2.8527e-04,  ..., 1.0871e-04, 1.0367e-04,\n",
            "         1.0633e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.0406e-04, 2.3665e-04, 1.2925e-04,  ..., 3.8395e-05, 6.9163e-05,\n",
            "         4.8220e-05],\n",
            "        [3.7608e-04, 1.4246e-04, 8.3441e-05,  ..., 3.1266e-05, 3.5495e-05,\n",
            "         2.8503e-05],\n",
            "        [2.1223e-04, 1.5133e-04, 3.3579e-04,  ..., 7.4616e-05, 7.4809e-05,\n",
            "         9.6758e-05],\n",
            "        ...,\n",
            "        [5.5916e-04, 1.2627e-04, 3.7622e-04,  ..., 1.0402e-04, 5.0823e-05,\n",
            "         3.7083e-05],\n",
            "        [9.2982e-04, 1.4204e-04, 3.4804e-04,  ..., 5.4735e-05, 8.8966e-05,\n",
            "         5.0553e-05],\n",
            "        [1.8286e-04, 6.9177e-04, 1.2923e-04,  ..., 2.9258e-05, 1.9144e-05,\n",
            "         2.9465e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.0909e-04, 2.5875e-04, 2.2817e-04,  ..., 7.4065e-05, 1.0672e-04,\n",
            "         9.7130e-05],\n",
            "        [1.6132e-04, 1.0871e-04, 1.4744e-04,  ..., 3.8031e-05, 3.0051e-05,\n",
            "         3.2945e-05],\n",
            "        [3.9551e-04, 1.5856e-04, 2.2076e-04,  ..., 1.2694e-04, 1.2379e-04,\n",
            "         1.1726e-04],\n",
            "        ...,\n",
            "        [7.4589e-05, 4.8835e-05, 8.5514e-05,  ..., 2.0224e-05, 3.0426e-05,\n",
            "         2.1367e-05],\n",
            "        [1.4100e-04, 2.6388e-04, 2.3719e-04,  ..., 4.8978e-05, 5.9861e-05,\n",
            "         4.3182e-05],\n",
            "        [2.1466e-04, 5.0083e-04, 5.0952e-04,  ..., 1.2275e-04, 6.2491e-05,\n",
            "         7.3426e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "\tEpoch 100 complete! \tAverage Loss:  0.5135480562845866 100.0 auc: 1.0\n",
            "tensor([[5.6856e-04, 2.7455e-04, 4.6146e-04,  ..., 9.0862e-05, 9.6075e-05,\n",
            "         1.3809e-04],\n",
            "        [4.2048e-04, 5.1556e-04, 1.8613e-04,  ..., 5.7800e-05, 9.1642e-05,\n",
            "         3.5260e-05],\n",
            "        [2.6195e-04, 5.2128e-05, 3.8829e-05,  ..., 6.0517e-05, 5.8215e-05,\n",
            "         1.8753e-04],\n",
            "        ...,\n",
            "        [3.0815e-04, 1.1881e-04, 1.6021e-04,  ..., 5.2893e-05, 4.2488e-05,\n",
            "         1.0787e-04],\n",
            "        [7.5435e-04, 1.4628e-04, 3.3543e-04,  ..., 1.1946e-04, 9.8653e-05,\n",
            "         8.6893e-05],\n",
            "        [1.8751e-04, 1.6003e-04, 1.3399e-04,  ..., 2.4940e-05, 4.0880e-05,\n",
            "         3.5710e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.1157e-04, 4.0409e-05, 1.3980e-04,  ..., 2.8934e-05, 2.1786e-05,\n",
            "         3.2569e-05],\n",
            "        [1.8519e-04, 3.2222e-04, 1.2139e-04,  ..., 3.4129e-05, 3.4853e-05,\n",
            "         3.9460e-05],\n",
            "        [1.2961e-04, 4.7169e-04, 4.0960e-04,  ..., 3.3266e-05, 4.0222e-05,\n",
            "         6.4283e-05],\n",
            "        ...,\n",
            "        [1.7897e-04, 5.2821e-04, 1.2336e-04,  ..., 5.9861e-05, 9.7969e-05,\n",
            "         7.5867e-05],\n",
            "        [1.2560e-04, 4.8612e-04, 6.4810e-04,  ..., 1.1573e-04, 8.7197e-05,\n",
            "         1.0501e-04],\n",
            "        [7.0294e-05, 1.3937e-04, 5.1300e-05,  ..., 3.1427e-05, 3.4128e-05,\n",
            "         2.1028e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.4459e-04, 2.9936e-04, 1.3589e-04,  ..., 1.0907e-04, 6.6137e-05,\n",
            "         7.7487e-05],\n",
            "        [1.8578e-04, 1.9014e-04, 8.4791e-05,  ..., 8.5585e-05, 7.3675e-05,\n",
            "         4.1814e-05],\n",
            "        [1.5643e-04, 3.6981e-04, 2.4456e-04,  ..., 7.5617e-05, 7.1333e-05,\n",
            "         8.1824e-05],\n",
            "        ...,\n",
            "        [4.1776e-04, 3.2913e-04, 3.0275e-04,  ..., 7.8394e-05, 8.3400e-05,\n",
            "         1.0274e-04],\n",
            "        [3.0573e-04, 9.1256e-05, 1.7733e-04,  ..., 4.3849e-05, 4.2828e-05,\n",
            "         4.0604e-05],\n",
            "        [9.6168e-04, 3.1272e-04, 3.1477e-04,  ..., 7.6065e-05, 8.5491e-05,\n",
            "         1.0947e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.0524e-04, 1.9668e-04, 5.4665e-05,  ..., 1.3694e-04, 7.8994e-05,\n",
            "         6.0478e-04],\n",
            "        [4.7481e-04, 2.6516e-04, 2.3785e-04,  ..., 7.8192e-05, 4.6597e-05,\n",
            "         4.8782e-05],\n",
            "        [5.5521e-05, 1.5540e-04, 2.5969e-04,  ..., 3.3149e-05, 3.4851e-05,\n",
            "         3.7002e-05],\n",
            "        ...,\n",
            "        [6.9998e-05, 1.3145e-04, 1.4370e-04,  ..., 3.0416e-05, 3.9967e-05,\n",
            "         3.8643e-05],\n",
            "        [3.3025e-05, 3.5906e-05, 5.4654e-05,  ..., 3.5440e-05, 2.1018e-05,\n",
            "         2.0465e-05],\n",
            "        [1.5329e-04, 2.4090e-04, 2.1663e-04,  ..., 7.1902e-05, 6.7476e-05,\n",
            "         6.0916e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.8305e-04, 4.6144e-04, 4.9638e-04,  ..., 1.0078e-04, 5.3555e-05,\n",
            "         6.7493e-05],\n",
            "        [8.6603e-04, 4.6314e-04, 4.4759e-04,  ..., 7.7239e-05, 9.8599e-05,\n",
            "         1.3856e-04],\n",
            "        [3.8595e-04, 2.8007e-04, 1.7926e-03,  ..., 6.6883e-05, 9.4484e-05,\n",
            "         1.0182e-04],\n",
            "        ...,\n",
            "        [6.5621e-04, 1.7647e-04, 1.9066e-04,  ..., 9.7876e-05, 7.1382e-05,\n",
            "         5.2105e-05],\n",
            "        [4.1153e-05, 7.9234e-05, 2.5380e-04,  ..., 5.1563e-05, 7.0228e-05,\n",
            "         5.6693e-05],\n",
            "        [1.4675e-04, 8.1356e-05, 5.2715e-04,  ..., 1.9462e-05, 2.9948e-05,\n",
            "         2.2223e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.5734e-04, 8.2583e-04, 1.9267e-04,  ..., 5.5865e-05, 8.1554e-05,\n",
            "         7.4815e-05],\n",
            "        [3.4644e-04, 1.5039e-04, 3.0853e-04,  ..., 9.3186e-05, 1.0674e-04,\n",
            "         6.0276e-05],\n",
            "        [1.4119e-04, 1.9670e-04, 1.5941e-04,  ..., 3.4337e-05, 2.8239e-05,\n",
            "         2.6134e-05],\n",
            "        ...,\n",
            "        [2.1617e-04, 5.1618e-04, 3.3386e-04,  ..., 1.6022e-04, 8.4372e-05,\n",
            "         1.1901e-04],\n",
            "        [4.9396e-05, 3.3647e-04, 8.6653e-05,  ..., 2.3006e-05, 3.1670e-05,\n",
            "         2.2507e-05],\n",
            "        [6.9514e-04, 3.9269e-04, 2.2279e-04,  ..., 6.2179e-05, 7.5961e-05,\n",
            "         4.3711e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[8.8255e-05, 1.0639e-04, 5.6511e-05,  ..., 3.6744e-05, 5.2199e-05,\n",
            "         3.9370e-05],\n",
            "        [1.6217e-03, 1.1117e-04, 2.3650e-04,  ..., 6.0114e-05, 6.5503e-05,\n",
            "         1.0083e-04],\n",
            "        [6.5176e-05, 9.8938e-05, 1.3266e-04,  ..., 2.2016e-05, 2.6342e-05,\n",
            "         2.4677e-05],\n",
            "        ...,\n",
            "        [1.8329e-04, 4.1433e-05, 7.9097e-05,  ..., 1.1803e-04, 8.2231e-05,\n",
            "         4.7012e-05],\n",
            "        [1.7638e-04, 1.9875e-04, 2.5302e-04,  ..., 5.5400e-05, 7.6842e-05,\n",
            "         3.9149e-05],\n",
            "        [3.2030e-04, 8.1562e-04, 4.2586e-04,  ..., 9.4964e-05, 1.2564e-04,\n",
            "         7.1661e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.0774e-04, 1.8927e-04, 1.8767e-04,  ..., 1.3419e-04, 6.7301e-05,\n",
            "         7.0495e-05],\n",
            "        [2.6125e-04, 1.8392e-04, 1.6675e-04,  ..., 4.9844e-05, 5.4645e-05,\n",
            "         7.2165e-05],\n",
            "        [1.7717e-03, 3.7198e-04, 2.9877e-04,  ..., 5.3691e-05, 6.7946e-05,\n",
            "         6.8680e-05],\n",
            "        ...,\n",
            "        [2.4100e-04, 9.0116e-04, 2.9607e-04,  ..., 6.5614e-05, 1.1034e-04,\n",
            "         7.9526e-05],\n",
            "        [5.6761e-05, 1.9592e-04, 8.0706e-05,  ..., 3.1854e-05, 3.6417e-05,\n",
            "         2.2321e-05],\n",
            "        [1.8482e-04, 1.5034e-04, 1.3497e-04,  ..., 2.0415e-05, 4.2142e-05,\n",
            "         3.8098e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.8516e-04, 1.4818e-04, 7.2563e-05,  ..., 2.3477e-05, 3.7970e-05,\n",
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            "         3.7244e-05],\n",
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            "         6.4264e-05],\n",
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            "         7.9906e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.9692e-05],\n",
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            "         2.6331e-05],\n",
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            "         2.8127e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.6267e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0610e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.7514e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.8016e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0059e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "        [5.0856e-04, 2.4805e-04, 2.5797e-04,  ..., 1.3370e-04, 9.7219e-05,\n",
            "         9.9256e-05],\n",
            "        ...,\n",
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            "         3.4802e-05],\n",
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            "         9.5242e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.8907e-04, 3.3322e-03, 1.6833e-04,  ..., 9.8577e-05, 7.8361e-05,\n",
            "         1.0199e-04],\n",
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            "         8.5401e-05],\n",
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            "         7.3453e-05],\n",
            "        ...,\n",
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            "         1.6537e-04],\n",
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            "         3.9135e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.2581e-04],\n",
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            "         6.2213e-05],\n",
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            "         8.1146e-05],\n",
            "        ...,\n",
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            "         2.1162e-05],\n",
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            "         5.7814e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.9201e-05],\n",
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            "         7.9402e-05],\n",
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            "         3.2386e-05],\n",
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            "         8.4177e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.5042e-05],\n",
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            "         8.4008e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.6911e-05, 1.4743e-04, 6.0240e-05,  ..., 3.0605e-05, 1.5632e-05,\n",
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            "         3.3665e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.6911e-04, 2.3808e-04, 1.6317e-04,  ..., 1.0066e-04, 1.0756e-04,\n",
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            "         3.1152e-05],\n",
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            "         2.8284e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.9264e-05],\n",
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            "         3.0027e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.8857e-05],\n",
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            "         9.2724e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.4428e-05],\n",
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            "         4.6754e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.9322e-05],\n",
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            "         3.5101e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.6965e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.9402e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.9790e-05],\n",
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            "         2.4998e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.8207e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.8522e-04],\n",
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            "         7.3934e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.5392e-05],\n",
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            "         6.0134e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.3291e-05],\n",
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            "         9.5260e-05],\n",
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            "         3.4940e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.9994e-05],\n",
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            "         4.6514e-05],\n",
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            "         3.1019e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.5556e-05, 2.8114e-05, 4.6495e-05,  ..., 1.1722e-04, 5.4546e-04,\n",
            "         6.8054e-05],\n",
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            "         6.1588e-05],\n",
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            "         2.0453e-05],\n",
            "        ...,\n",
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            "         4.5943e-05],\n",
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            "         1.7932e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.2608e-04, 1.8911e-04, 2.3841e-04,  ..., 4.4450e-05, 5.9733e-05,\n",
            "         3.8823e-05],\n",
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            "         1.6959e-05],\n",
            "        ...,\n",
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            "         6.7439e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.2196e-05],\n",
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            "         1.7736e-05],\n",
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            "         8.9361e-05],\n",
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            "         2.3595e-05],\n",
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            "         2.2414e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.4674e-05],\n",
            "        ...,\n",
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            "         2.1867e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.3185e-03, 1.7283e-04, 3.5701e-04,  ..., 7.6469e-05, 6.0728e-05,\n",
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            "         1.1759e-05],\n",
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            "         3.3008e-05],\n",
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            "         6.4018e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.0578e-04, 5.8548e-05, 2.0968e-04,  ..., 4.0733e-05, 3.2708e-05,\n",
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            "         4.9680e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.9304e-05],\n",
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            "         1.8466e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.7107e-05],\n",
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            "         6.2141e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.6689e-05],\n",
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            "         3.7015e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.8820e-05],\n",
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            "         2.4646e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.5848e-05],\n",
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            "         1.4544e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.8056e-06],\n",
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            "         3.1091e-05],\n",
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            "         3.3476e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.7974e-05],\n",
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            "         6.4438e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.7755e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.8019e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.3791e-04],\n",
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            "         1.5614e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.3666e-05],\n",
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            "         7.2891e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[7.3002e-05, 6.5585e-05, 8.1880e-05,  ..., 1.0499e-04, 7.5166e-05,\n",
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            "         7.5026e-05],\n",
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            "         4.9244e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[5.2058e-04, 1.3689e-04, 3.1556e-04,  ..., 4.0366e-05, 3.9183e-05,\n",
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            "         1.9640e-05],\n",
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            "         4.4423e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.8824e-04, 7.4464e-05, 2.3401e-04,  ..., 2.2640e-05, 1.9395e-05,\n",
            "         2.7376e-05],\n",
            "        [2.5049e-04, 2.3078e-04, 3.1438e-04,  ..., 4.4162e-05, 8.2146e-05,\n",
            "         4.3409e-05],\n",
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            "         1.1964e-04],\n",
            "        ...,\n",
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            "         2.0596e-05],\n",
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            "         1.7644e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[9.4419e-05, 2.3126e-04, 2.6161e-04,  ..., 3.2246e-05, 4.9635e-05,\n",
            "         5.7301e-05],\n",
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            "         8.8295e-05],\n",
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            "         4.3609e-05],\n",
            "        ...,\n",
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            "         4.6561e-05],\n",
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            "         1.6264e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.4414e-05],\n",
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            "         8.3442e-05],\n",
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            "         1.3891e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.6515e-05],\n",
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            "         2.3830e-05],\n",
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            "         4.0140e-05],\n",
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            "         5.4767e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.6836e-05],\n",
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            "         6.7050e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0401e-04],\n",
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            "         1.1967e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.3054e-05],\n",
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            "         4.3615e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.9977e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.6632e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.1027e-05],\n",
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            "         1.1625e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.4891e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.7698e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.4597e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.0675e-06]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.4755e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.6193e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.4315e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.6439e-05],\n",
            "        ...,\n",
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            "         3.6064e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.6292e-04, 1.3865e-04, 1.0920e-03,  ..., 3.0751e-05, 2.8264e-05,\n",
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            "         1.6083e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.6229e-05],\n",
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            "         1.2002e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.1896e-05],\n",
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            "         1.0610e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.4041e-05],\n",
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            "         2.0246e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.7554e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.2474e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.6439e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.1436e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.1398e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0061e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.4269e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.9239e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.9680e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.3276e-05],\n",
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            "        [1.2119e-04, 1.6469e-04, 7.8872e-05,  ..., 1.7072e-05, 1.4311e-05,\n",
            "         2.1797e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.8144e-05, 1.7400e-04, 1.0510e-04,  ..., 3.0388e-05, 2.4574e-05,\n",
            "         2.9115e-05],\n",
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            "         5.4165e-05],\n",
            "        ...,\n",
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            "         5.9339e-05],\n",
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            "         2.5541e-05],\n",
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            "         6.1860e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.0634e-04, 1.3508e-04, 1.7854e-04,  ..., 2.9542e-05, 2.8199e-05,\n",
            "         4.2971e-05],\n",
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            "         1.0302e-04],\n",
            "        ...,\n",
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            "         2.9939e-05],\n",
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            "         8.2322e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[7.6999e-05, 5.6556e-04, 5.9823e-05,  ..., 1.5930e-05, 3.1073e-05,\n",
            "         2.1649e-05],\n",
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            "         8.3874e-05],\n",
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            "         5.7967e-05],\n",
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            "         3.5077e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.2779e-04],\n",
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            "         6.7195e-05],\n",
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            "         1.7225e-05],\n",
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            "         3.3058e-05],\n",
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            "         3.4914e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.8721e-04, 1.6255e-04, 4.4695e-04,  ..., 9.7760e-05, 1.0208e-04,\n",
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            "         2.6353e-05],\n",
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            "         1.0579e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.4314e-05],\n",
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            "         2.4384e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.6558e-05],\n",
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            "         3.7374e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.5082e-05],\n",
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            "         1.1279e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.6784e-05],\n",
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            "         1.4481e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.7554e-05],\n",
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            "         8.5680e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.0258e-05],\n",
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            "         1.3906e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.8759e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.5255e-05],\n",
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            "         2.6266e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.9026e-05],\n",
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            "         7.1976e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.7650e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.5463e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.7358e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.0410e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.6093e-04, 2.7199e-04, 2.0397e-04,  ..., 4.3650e-05, 5.9259e-05,\n",
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            "         3.7865e-05],\n",
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            "         7.0623e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.0065e-05, 1.8281e-04, 6.5570e-05,  ..., 3.8129e-05, 6.9978e-05,\n",
            "         3.0747e-05],\n",
            "        [1.5475e-04, 1.7850e-04, 1.6975e-04,  ..., 8.1343e-05, 6.4503e-05,\n",
            "         4.9637e-05],\n",
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            "         3.7706e-05],\n",
            "        ...,\n",
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            "         7.2153e-05],\n",
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            "         2.9415e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.9266e-04, 2.0948e-04, 6.0422e-04,  ..., 6.3796e-05, 7.1731e-05,\n",
            "         7.7867e-05],\n",
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            "         4.0643e-05],\n",
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            "         1.0624e-04],\n",
            "        ...,\n",
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            "         1.3002e-05],\n",
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            "         8.0041e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.1896e-05],\n",
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            "         3.4485e-05],\n",
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            "         7.4086e-05],\n",
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            "         6.8227e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.2963e-05],\n",
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            "         1.2482e-05],\n",
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            "         7.9080e-05],\n",
            "        ...,\n",
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            "         9.0385e-05],\n",
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            "         3.3966e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[5.7697e-05, 6.0498e-05, 8.6457e-05,  ..., 1.6742e-05, 2.3355e-05,\n",
            "         1.5891e-05],\n",
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            "         3.0677e-05],\n",
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            "         4.4467e-05],\n",
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            "         7.9128e-05],\n",
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            "         4.7511e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[9.2566e-05, 8.3386e-05, 1.3433e-04,  ..., 2.3320e-05, 2.4206e-05,\n",
            "         1.2887e-05],\n",
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            "         2.9338e-05],\n",
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            "         5.6432e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.6554e-05],\n",
            "        ...,\n",
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            "         2.2010e-05],\n",
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            "         5.5826e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.2747e-05],\n",
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            "         3.8493e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.2079e-05],\n",
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            "         7.6676e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.7074e-05],\n",
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            "         6.1749e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[7.5552e-05, 9.7769e-05, 5.4998e-05,  ..., 2.9779e-05, 3.0835e-05,\n",
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            "         7.0392e-05],\n",
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            "         4.2602e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.2498e-05],\n",
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            "         2.2398e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.6660e-05],\n",
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            "         1.0982e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.7668e-05],\n",
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            "         5.0009e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.8368e-05],\n",
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            "         5.7555e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.9297e-05],\n",
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            "         2.0017e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.3206e-04, 9.1146e-04, 2.7576e-04,  ..., 1.3247e-04, 6.6981e-05,\n",
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            "         2.3936e-05],\n",
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            "         2.5381e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.2770e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.4505e-05],\n",
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            "         1.9857e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "        [2.9156e-04, 3.2864e-04, 6.3325e-04,  ..., 7.5840e-05, 1.1505e-04,\n",
            "         1.4608e-04],\n",
            "        ...,\n",
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            "         7.1601e-05],\n",
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            "         9.3793e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.3202e-04, 2.4411e-04, 7.7607e-04,  ..., 2.3158e-05, 2.5264e-05,\n",
            "         2.6384e-05],\n",
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            "         1.0077e-04],\n",
            "        ...,\n",
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            "         5.9637e-05],\n",
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            "         9.0574e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.3175e-05],\n",
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            "         9.2214e-05],\n",
            "        ...,\n",
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            "         1.4851e-04],\n",
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            "         8.0770e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.1690e-05],\n",
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            "         2.3457e-05],\n",
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            "         2.2831e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.0971e-04, 1.9664e-04, 3.0585e-03,  ..., 5.2027e-05, 9.3357e-05,\n",
            "         5.2595e-05],\n",
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            "         9.5094e-05],\n",
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            "         6.3368e-05],\n",
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            "         5.7910e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.8280e-04, 5.2788e-04, 4.0213e-04,  ..., 1.3170e-04, 6.3537e-05,\n",
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            "         2.1199e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.5098e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.1411e-05],\n",
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            "         2.8582e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.9047e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.5264e-05],\n",
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            "         7.6120e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.3438e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.6470e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.7252e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.3918e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.6442e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.3504e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.9011e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.0209e-05],\n",
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            "         2.2173e-05],\n",
            "        [1.6394e-04, 3.8962e-04, 2.0431e-04,  ..., 9.7128e-05, 7.5000e-05,\n",
            "         1.0684e-04],\n",
            "        [3.5413e-05, 5.2206e-05, 2.5725e-04,  ..., 2.7704e-05, 3.8981e-05,\n",
            "         2.1544e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.0837e-04, 1.6875e-04, 2.9357e-04,  ..., 6.0537e-05, 5.1719e-05,\n",
            "         9.3457e-05],\n",
            "        [9.3679e-05, 1.5393e-04, 1.0880e-04,  ..., 8.3594e-05, 8.6927e-05,\n",
            "         5.2136e-05],\n",
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            "         7.9440e-05],\n",
            "        ...,\n",
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            "         8.1084e-05],\n",
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            "         1.2070e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[7.2453e-05, 1.2091e-04, 2.5788e-04,  ..., 2.1906e-05, 4.6011e-05,\n",
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            "         5.8285e-05],\n",
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            "         1.6310e-05],\n",
            "        ...,\n",
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            "         9.6416e-05],\n",
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            "         9.5316e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.2806e-04, 2.1360e-04, 2.1764e-04,  ..., 9.7293e-05, 1.0570e-04,\n",
            "         5.7422e-05],\n",
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            "         3.8092e-05],\n",
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            "         1.1040e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.3014e-05],\n",
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            "         5.8973e-05],\n",
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            "         5.5747e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.9232e-04, 1.3452e-04, 2.6130e-04,  ..., 8.4314e-05, 1.1447e-04,\n",
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            "         2.8434e-05],\n",
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            "         8.7533e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.4465e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.0909e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.2591e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0861e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.2528e-05],\n",
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            "         7.2273e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.9750e-05],\n",
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            "         1.3673e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.2800e-05],\n",
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            "         4.5709e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.1800e-05],\n",
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            "         6.5894e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.4823e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.1786e-05],\n",
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            "         2.7497e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.5714e-05],\n",
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            "         2.6840e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.3782e-04, 5.5379e-04, 2.3878e-04,  ..., 2.4047e-05, 2.6220e-05,\n",
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            "         4.7079e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.1817e-05],\n",
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            "         2.7251e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.4304e-05],\n",
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            "        [2.9857e-04, 3.6802e-04, 1.9579e-04,  ..., 5.0926e-05, 9.0644e-05,\n",
            "         8.9126e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.9517e-04, 5.1428e-04, 4.1663e-04,  ..., 8.5839e-05, 3.8218e-05,\n",
            "         4.6728e-05],\n",
            "        [5.4333e-04, 3.0651e-04, 2.4536e-04,  ..., 1.2763e-04, 1.2752e-04,\n",
            "         1.1765e-04],\n",
            "        [4.5745e-05, 4.8775e-05, 8.0211e-05,  ..., 2.7706e-05, 2.0782e-05,\n",
            "         2.8417e-05],\n",
            "        ...,\n",
            "        [4.2794e-05, 2.9324e-04, 1.9163e-04,  ..., 1.8724e-05, 2.2439e-05,\n",
            "         2.4706e-05],\n",
            "        [6.2908e-04, 2.4556e-04, 1.1245e-04,  ..., 6.1034e-05, 8.6359e-05,\n",
            "         8.9648e-05],\n",
            "        [2.4468e-04, 1.2878e-04, 3.9077e-04,  ..., 1.0615e-04, 7.3437e-05,\n",
            "         1.0526e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.7864e-05, 5.4925e-05, 3.1008e-05,  ..., 3.3999e-05, 3.5853e-05,\n",
            "         2.0019e-04],\n",
            "        [1.3260e-04, 1.8551e-04, 9.9646e-05,  ..., 1.9150e-05, 2.7690e-05,\n",
            "         3.1042e-05],\n",
            "        [3.4551e-05, 4.0536e-05, 3.8853e-05,  ..., 1.7932e-05, 1.7525e-05,\n",
            "         2.6544e-05],\n",
            "        ...,\n",
            "        [1.6193e-04, 4.4700e-05, 1.1046e-04,  ..., 1.4128e-05, 3.1238e-05,\n",
            "         1.6870e-05],\n",
            "        [9.3966e-04, 6.4482e-04, 1.7224e-03,  ..., 1.1182e-04, 7.8712e-05,\n",
            "         6.8917e-05],\n",
            "        [6.4765e-04, 2.8145e-04, 1.8553e-04,  ..., 4.5829e-05, 3.7406e-05,\n",
            "         4.1818e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.4302e-03, 4.1406e-04, 3.1404e-04,  ..., 7.7753e-05, 9.1318e-05,\n",
            "         6.3646e-05],\n",
            "        [1.7721e-04, 5.8359e-04, 6.6409e-04,  ..., 5.0038e-05, 3.3235e-05,\n",
            "         3.8786e-05],\n",
            "        [2.2911e-04, 6.3712e-04, 4.0192e-04,  ..., 2.5085e-05, 1.8896e-05,\n",
            "         2.6398e-05],\n",
            "        ...,\n",
            "        [1.0131e-04, 2.8603e-04, 9.3308e-05,  ..., 6.0868e-05, 2.5008e-05,\n",
            "         5.5509e-05],\n",
            "        [6.4434e-05, 4.8190e-05, 5.9916e-05,  ..., 1.6690e-05, 2.6926e-05,\n",
            "         2.9953e-05],\n",
            "        [1.1870e-04, 2.1306e-04, 5.7191e-04,  ..., 5.8102e-05, 2.9011e-05,\n",
            "         4.4697e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.4613e-05, 4.5247e-05, 1.1490e-04,  ..., 2.2759e-05, 2.2554e-05,\n",
            "         1.0343e-05],\n",
            "        [1.3742e-03, 1.0909e-03, 3.3543e-04,  ..., 3.0699e-05, 6.2088e-05,\n",
            "         6.0849e-05],\n",
            "        [7.7874e-04, 2.1408e-04, 8.7650e-04,  ..., 8.8116e-05, 2.8165e-05,\n",
            "         4.1636e-05],\n",
            "        ...,\n",
            "        [4.4352e-05, 1.1405e-04, 3.3321e-05,  ..., 3.4378e-05, 1.9329e-05,\n",
            "         1.9610e-05],\n",
            "        [5.7210e-04, 6.4604e-04, 6.0171e-04,  ..., 6.1953e-05, 7.5098e-05,\n",
            "         6.5557e-05],\n",
            "        [1.1173e-04, 6.1976e-05, 2.3230e-05,  ..., 4.5281e-05, 6.1272e-05,\n",
            "         7.7139e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[5.7711e-04, 8.5255e-04, 3.0217e-04,  ..., 7.1328e-05, 6.9349e-05,\n",
            "         4.9391e-05],\n",
            "        [3.6318e-05, 2.9816e-05, 3.1283e-04,  ..., 2.4156e-05, 7.7256e-06,\n",
            "         1.6068e-05],\n",
            "        [4.7209e-04, 5.5562e-04, 9.7878e-04,  ..., 6.4062e-05, 7.5348e-05,\n",
            "         4.1107e-05],\n",
            "        ...,\n",
            "        [3.7028e-04, 6.1346e-04, 3.1185e-04,  ..., 1.1225e-04, 7.6582e-05,\n",
            "         1.2595e-04],\n",
            "        [1.1071e-03, 6.9170e-04, 1.0374e-04,  ..., 5.0795e-05, 7.9986e-05,\n",
            "         6.3845e-05],\n",
            "        [2.5497e-04, 3.9424e-04, 4.9317e-04,  ..., 7.1800e-05, 1.1009e-04,\n",
            "         7.4244e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.4790e-04, 1.1072e-04, 1.7151e-04,  ..., 6.4987e-05, 5.9745e-05,\n",
            "         4.3100e-05],\n",
            "        [8.7662e-05, 1.0892e-04, 1.3640e-04,  ..., 2.0938e-05, 2.3461e-05,\n",
            "         1.2255e-05],\n",
            "        [3.3041e-05, 3.4164e-05, 1.5692e-04,  ..., 8.8434e-05, 2.6347e-05,\n",
            "         3.0497e-05],\n",
            "        ...,\n",
            "        [1.8991e-04, 4.4521e-04, 2.4665e-04,  ..., 1.0281e-04, 8.3582e-05,\n",
            "         6.3491e-05],\n",
            "        [1.9494e-04, 1.4986e-04, 4.3732e-04,  ..., 8.9251e-05, 3.9691e-05,\n",
            "         7.0076e-05],\n",
            "        [1.2428e-03, 2.9271e-04, 1.5587e-04,  ..., 4.6617e-05, 5.1130e-05,\n",
            "         2.0913e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.7406e-05, 3.6805e-05, 1.8088e-04,  ..., 1.4849e-05, 9.7394e-06,\n",
            "         1.0767e-05],\n",
            "        [2.0718e-04, 6.2381e-04, 1.9264e-04,  ..., 2.5363e-05, 4.8480e-05,\n",
            "         5.2103e-05],\n",
            "        [4.3213e-04, 3.5850e-04, 3.3614e-04,  ..., 9.5636e-05, 9.4233e-05,\n",
            "         7.0909e-05],\n",
            "        ...,\n",
            "        [1.0210e-04, 1.2668e-04, 3.4651e-04,  ..., 1.3072e-05, 1.2891e-05,\n",
            "         1.6399e-05],\n",
            "        [3.3389e-03, 2.3967e-04, 2.3918e-04,  ..., 9.1416e-05, 4.3189e-05,\n",
            "         1.1529e-04],\n",
            "        [2.6110e-04, 5.6141e-04, 5.5310e-04,  ..., 7.0390e-05, 2.8420e-05,\n",
            "         8.8118e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.8331e-05, 1.1049e-04, 1.5062e-04,  ..., 2.2723e-05, 2.1164e-05,\n",
            "         1.2357e-05],\n",
            "        [2.6199e-04, 1.7181e-04, 3.0418e-04,  ..., 4.3089e-05, 5.3329e-05,\n",
            "         3.3070e-05],\n",
            "        [1.3305e-04, 1.9519e-04, 6.5341e-05,  ..., 1.1794e-05, 1.1531e-05,\n",
            "         2.2123e-05],\n",
            "        ...,\n",
            "        [9.5276e-05, 1.2550e-04, 7.0318e-04,  ..., 4.8737e-05, 7.4660e-05,\n",
            "         7.4244e-05],\n",
            "        [3.9375e-04, 1.9159e-04, 4.2384e-04,  ..., 3.7588e-05, 9.1517e-05,\n",
            "         5.4540e-05],\n",
            "        [1.6185e-04, 2.7444e-04, 3.3755e-04,  ..., 6.1725e-05, 3.8215e-05,\n",
            "         3.1156e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.4012e-04, 6.0038e-05, 4.5072e-05,  ..., 6.7996e-06, 1.5363e-05,\n",
            "         7.5455e-06],\n",
            "        [1.2355e-04, 1.1189e-04, 2.2994e-05,  ..., 8.3997e-05, 5.2795e-05,\n",
            "         1.7496e-05],\n",
            "        [2.8154e-04, 2.5959e-04, 7.9417e-04,  ..., 1.0284e-04, 1.0200e-04,\n",
            "         5.9662e-05],\n",
            "        ...,\n",
            "        [1.2443e-04, 1.1596e-03, 1.1251e-04,  ..., 3.0783e-05, 4.1509e-05,\n",
            "         5.2808e-05],\n",
            "        [4.4558e-04, 8.0507e-04, 7.5479e-04,  ..., 5.0903e-05, 6.7862e-05,\n",
            "         6.6311e-05],\n",
            "        [7.7446e-05, 5.2000e-05, 1.0080e-04,  ..., 2.1937e-05, 2.8969e-05,\n",
            "         1.1760e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.5402e-04, 2.2387e-04, 2.4697e-04,  ..., 5.8617e-05, 1.1107e-04,\n",
            "         5.5813e-05],\n",
            "        [1.2630e-04, 2.5839e-04, 1.1571e-04,  ..., 3.7308e-05, 3.1833e-05,\n",
            "         4.1300e-05],\n",
            "        [3.8250e-04, 9.8578e-04, 2.2699e-04,  ..., 8.4012e-05, 9.0816e-05,\n",
            "         5.4629e-05],\n",
            "        ...,\n",
            "        [3.4943e-04, 2.4462e-04, 1.0634e-03,  ..., 7.5066e-05, 2.9221e-05,\n",
            "         4.2838e-05],\n",
            "        [9.9202e-05, 8.0569e-05, 6.5490e-05,  ..., 2.6810e-05, 1.0827e-05,\n",
            "         1.1980e-05],\n",
            "        [1.5558e-04, 4.3980e-05, 8.9664e-05,  ..., 1.7372e-05, 1.6805e-05,\n",
            "         9.5497e-06]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.8061e-04, 5.2094e-04, 3.6450e-04,  ..., 1.1430e-04, 7.3351e-05,\n",
            "         5.4871e-05],\n",
            "        [8.7761e-05, 4.7805e-05, 5.6144e-05,  ..., 2.0817e-05, 2.3826e-05,\n",
            "         2.2067e-05],\n",
            "        [1.4930e-04, 9.4439e-04, 1.7111e-04,  ..., 7.5792e-05, 5.0393e-05,\n",
            "         4.9686e-05],\n",
            "        ...,\n",
            "        [1.6968e-04, 1.6911e-04, 4.7002e-04,  ..., 8.9883e-05, 1.1408e-04,\n",
            "         6.1979e-05],\n",
            "        [3.4298e-04, 1.3587e-04, 4.0510e-04,  ..., 6.1517e-05, 5.9206e-05,\n",
            "         5.6918e-05],\n",
            "        [7.0216e-05, 2.0339e-05, 9.1832e-05,  ..., 2.4574e-04, 9.5992e-05,\n",
            "         2.9224e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.3164e-04, 1.9366e-04, 8.6914e-05,  ..., 4.3891e-05, 3.3551e-05,\n",
            "         3.9180e-05],\n",
            "        [1.9381e-04, 8.6363e-05, 1.5264e-04,  ..., 7.7473e-05, 3.3922e-05,\n",
            "         2.1765e-05],\n",
            "        [1.4974e-04, 3.0455e-04, 5.4859e-04,  ..., 9.6602e-05, 9.1672e-05,\n",
            "         6.7101e-05],\n",
            "        ...,\n",
            "        [1.3926e-04, 1.1777e-04, 2.1313e-04,  ..., 1.6781e-05, 3.8465e-05,\n",
            "         5.9158e-05],\n",
            "        [4.6809e-05, 2.9518e-04, 3.7916e-04,  ..., 3.7639e-05, 4.4035e-05,\n",
            "         7.4886e-05],\n",
            "        [2.1091e-04, 5.5469e-04, 2.5758e-04,  ..., 6.7485e-05, 4.5064e-05,\n",
            "         4.3151e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.8829e-04, 1.6930e-04, 2.5681e-04,  ..., 4.7599e-05, 5.9077e-05,\n",
            "         2.9438e-05],\n",
            "        [6.7118e-05, 9.8601e-05, 1.6762e-05,  ..., 2.5547e-05, 2.6225e-05,\n",
            "         4.1018e-05],\n",
            "        [7.2913e-05, 3.7540e-05, 5.5994e-05,  ..., 1.9588e-05, 1.3761e-05,\n",
            "         1.6260e-05],\n",
            "        ...,\n",
            "        [9.6380e-04, 1.7445e-03, 5.4617e-04,  ..., 5.6886e-05, 2.4763e-05,\n",
            "         8.3679e-05],\n",
            "        [5.1639e-04, 1.7956e-04, 3.8762e-04,  ..., 1.1894e-04, 8.6440e-05,\n",
            "         7.9500e-05],\n",
            "        [4.4045e-05, 6.6192e-05, 1.2082e-04,  ..., 1.3295e-05, 2.0165e-05,\n",
            "         1.4101e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.8768e-05, 5.6605e-04, 8.7828e-05,  ..., 6.6770e-06, 2.1459e-05,\n",
            "         1.8246e-05],\n",
            "        [6.6990e-04, 4.6246e-04, 1.4841e-03,  ..., 6.7227e-05, 1.0683e-04,\n",
            "         8.1125e-05],\n",
            "        [5.9456e-04, 1.1490e-03, 1.0669e-04,  ..., 8.8556e-05, 6.8490e-05,\n",
            "         8.3635e-05],\n",
            "        ...,\n",
            "        [2.7164e-04, 2.9370e-04, 1.5754e-04,  ..., 5.4772e-05, 4.7646e-05,\n",
            "         7.6161e-05],\n",
            "        [6.9765e-05, 8.4971e-05, 6.9557e-05,  ..., 3.1522e-05, 2.8178e-05,\n",
            "         2.6070e-05],\n",
            "        [1.3293e-04, 6.7151e-05, 6.4945e-05,  ..., 3.1349e-05, 1.1816e-05,\n",
            "         2.4021e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.0805e-04, 1.2162e-04, 1.5167e-04,  ..., 3.7529e-05, 3.0301e-05,\n",
            "         5.1395e-05],\n",
            "        [2.5104e-04, 2.5290e-04, 1.8932e-04,  ..., 5.7911e-05, 4.9291e-05,\n",
            "         6.2007e-05],\n",
            "        [2.4337e-03, 2.1599e-04, 1.7761e-04,  ..., 3.7019e-05, 7.4603e-05,\n",
            "         8.9691e-05],\n",
            "        ...,\n",
            "        [1.0511e-04, 1.9594e-04, 1.1606e-04,  ..., 3.3812e-05, 2.2885e-05,\n",
            "         2.6631e-05],\n",
            "        [3.5164e-05, 1.9109e-04, 9.9405e-05,  ..., 1.3638e-05, 2.7418e-05,\n",
            "         1.0571e-05],\n",
            "        [9.4225e-05, 3.8290e-05, 6.4784e-05,  ..., 1.1892e-05, 1.6897e-05,\n",
            "         1.7440e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.2307e-03, 3.1316e-04, 1.0802e-04,  ..., 4.6478e-05, 5.3719e-05,\n",
            "         6.5106e-05],\n",
            "        [6.2031e-05, 4.3787e-05, 6.5287e-05,  ..., 1.0670e-04, 2.7108e-05,\n",
            "         1.0453e-04],\n",
            "        [1.2887e-04, 2.5148e-03, 1.2509e-03,  ..., 4.9613e-05, 5.1255e-05,\n",
            "         6.3530e-05],\n",
            "        ...,\n",
            "        [4.7294e-05, 8.3738e-05, 9.0134e-05,  ..., 1.6330e-05, 2.3030e-05,\n",
            "         1.5439e-05],\n",
            "        [2.4739e-04, 1.9189e-04, 9.2714e-05,  ..., 9.1093e-05, 6.4490e-05,\n",
            "         5.1048e-05],\n",
            "        [4.4021e-04, 2.2526e-04, 5.2041e-04,  ..., 6.8473e-05, 6.6299e-05,\n",
            "         7.1603e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[8.7390e-05, 3.5831e-04, 7.8337e-05,  ..., 5.4274e-05, 1.9041e-05,\n",
            "         4.2540e-05],\n",
            "        [2.2531e-05, 5.7045e-05, 5.5869e-05,  ..., 1.5146e-05, 1.6623e-05,\n",
            "         1.5606e-05],\n",
            "        [4.4006e-05, 3.1788e-05, 7.7177e-05,  ..., 3.2535e-05, 2.0388e-05,\n",
            "         3.5256e-05],\n",
            "        ...,\n",
            "        [4.7487e-04, 3.4795e-04, 1.2517e-03,  ..., 7.9514e-05, 6.8188e-05,\n",
            "         9.9677e-05],\n",
            "        [7.1560e-04, 4.7989e-04, 2.4250e-04,  ..., 1.1307e-04, 6.9544e-05,\n",
            "         8.9772e-05],\n",
            "        [2.7558e-04, 1.9034e-04, 5.1955e-04,  ..., 5.8057e-05, 4.5336e-05,\n",
            "         6.9476e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.2431e-04, 1.0750e-04, 7.0676e-04,  ..., 7.6715e-05, 5.4680e-05,\n",
            "         1.5671e-04],\n",
            "        [2.1653e-04, 3.5499e-04, 4.4360e-04,  ..., 4.2794e-05, 5.6629e-05,\n",
            "         4.3946e-05],\n",
            "        [9.6288e-04, 4.1416e-04, 2.7108e-04,  ..., 4.1743e-05, 1.8683e-05,\n",
            "         6.0892e-05],\n",
            "        ...,\n",
            "        [3.3256e-05, 6.7554e-05, 4.9866e-05,  ..., 1.0485e-05, 1.5170e-05,\n",
            "         2.6275e-05],\n",
            "        [2.8589e-05, 5.1678e-05, 6.7732e-05,  ..., 9.8385e-05, 1.2838e-04,\n",
            "         1.8198e-04],\n",
            "        [1.1500e-04, 1.7689e-04, 3.3880e-05,  ..., 1.2028e-05, 1.4306e-05,\n",
            "         1.6021e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "\tEpoch 200 complete! \tAverage Loss:  0.46792297893100315 50.0 auc: 0.6875\n",
            "tensor([[1.7201e-04, 3.1836e-04, 6.7773e-04,  ..., 6.8101e-05, 4.1785e-05,\n",
            "         7.5540e-05],\n",
            "        [4.7654e-05, 2.4237e-04, 1.6129e-04,  ..., 3.1188e-05, 9.3395e-06,\n",
            "         1.3115e-05],\n",
            "        [4.3230e-04, 5.2854e-03, 2.0870e-04,  ..., 5.9601e-05, 4.1699e-05,\n",
            "         9.1720e-05],\n",
            "        ...,\n",
            "        [4.2489e-04, 1.8621e-04, 2.9486e-04,  ..., 3.3272e-05, 6.8137e-05,\n",
            "         1.1345e-04],\n",
            "        [2.8322e-04, 3.2418e-04, 2.3549e-04,  ..., 4.1156e-05, 2.1429e-05,\n",
            "         5.2213e-05],\n",
            "        [9.2110e-05, 5.7423e-05, 2.4239e-04,  ..., 2.2369e-05, 3.2907e-05,\n",
            "         3.2359e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.7426e-04, 7.1783e-04, 2.8690e-04,  ..., 6.9261e-05, 7.7872e-05,\n",
            "         5.0033e-05],\n",
            "        [1.6885e-04, 1.9487e-04, 1.8367e-04,  ..., 4.6534e-05, 3.0740e-05,\n",
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            "         2.6636e-05],\n",
            "        ...,\n",
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            "         2.7901e-05],\n",
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            "         3.0299e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.2811e-05, 4.6788e-05, 3.8756e-05,  ..., 6.6853e-05, 7.0286e-05,\n",
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            "         3.7285e-05],\n",
            "        ...,\n",
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            "         7.2631e-05],\n",
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            "         1.2212e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.4287e-04, 1.8894e-04, 1.0831e-04,  ..., 5.0570e-05, 5.8954e-05,\n",
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            "         3.2834e-05],\n",
            "        ...,\n",
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            "         1.6886e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.2852e-04, 2.0990e-04, 7.5245e-04,  ..., 3.6402e-05, 1.6760e-05,\n",
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            "         7.0668e-05],\n",
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            "         1.0269e-04],\n",
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            "         3.5063e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.3165e-05],\n",
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            "         3.1040e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.1106e-05, 1.4327e-04, 1.8916e-04,  ..., 2.9092e-05, 1.9485e-05,\n",
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            "         2.0206e-05],\n",
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            "         2.4998e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.4838e-05],\n",
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            "         8.0380e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.2368e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.6640e-05],\n",
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            "         1.1770e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.2875e-05],\n",
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            "         1.4356e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0799e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.9204e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.1719e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.1437e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.3653e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.1324e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.1257e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.2811e-05],\n",
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            "         7.4713e-05],\n",
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            "        [2.2979e-04, 4.3455e-04, 1.7260e-04,  ..., 4.7109e-05, 6.0334e-05,\n",
            "         6.1572e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.6254e-04, 1.6876e-04, 4.3085e-04,  ..., 1.0023e-04, 1.0378e-04,\n",
            "         4.9550e-05],\n",
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            "         7.7089e-05],\n",
            "        ...,\n",
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            "         3.2581e-05],\n",
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            "         2.3700e-05],\n",
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            "         4.5130e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.6320e-04, 2.3852e-04, 6.5826e-04,  ..., 4.9338e-05, 8.5851e-05,\n",
            "         5.4806e-05],\n",
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            "         2.4524e-05],\n",
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            "         9.4017e-05],\n",
            "        ...,\n",
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            "         6.5086e-05],\n",
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            "         7.1811e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.0097e-04, 1.9861e-04, 3.4057e-04,  ..., 1.0241e-04, 7.9445e-05,\n",
            "         1.8205e-04],\n",
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            "         6.2074e-05],\n",
            "        ...,\n",
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            "         9.2688e-05],\n",
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            "         3.2227e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.5281e-05],\n",
            "        ...,\n",
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            "         8.2804e-05],\n",
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            "         7.6434e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.0604e-04, 1.5480e-04, 1.3004e-04,  ..., 5.5549e-05, 7.6317e-05,\n",
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            "         5.6180e-05],\n",
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            "         5.7068e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.9516e-04, 4.0639e-04, 7.3727e-05,  ..., 8.0030e-05, 5.2763e-05,\n",
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            "         1.0889e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.2679e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.0110e-05],\n",
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            "         5.8298e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.4140e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.2671e-05],\n",
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            "         3.1900e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.1016e-05],\n",
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            "         1.2970e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         8.6679e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.6779e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.9528e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.3867e-04]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.1661e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[9.1139e-04, 1.9324e-04, 1.9318e-04,  ..., 1.0816e-04, 7.9526e-05,\n",
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            "         3.4636e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.2297e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.1936e-05],\n",
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            "         4.5016e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[9.7116e-05, 7.8867e-05, 5.6991e-04,  ..., 2.6791e-05, 2.7545e-05,\n",
            "         2.7734e-05],\n",
            "        [1.2695e-04, 3.0083e-04, 1.3937e-04,  ..., 1.2914e-04, 9.3505e-05,\n",
            "         7.0258e-05],\n",
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            "         1.7598e-05],\n",
            "        ...,\n",
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            "         3.2039e-05],\n",
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            "         7.8500e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.1389e-04, 5.7451e-04, 1.8291e-04,  ..., 8.8787e-05, 3.3577e-05,\n",
            "         9.0518e-05],\n",
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            "         8.6671e-05],\n",
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            "         1.0475e-04],\n",
            "        ...,\n",
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            "         4.2767e-05],\n",
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            "         2.3311e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.5668e-05],\n",
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            "         7.4716e-05],\n",
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            "         5.7177e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.5570e-05],\n",
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            "         2.3527e-05],\n",
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            "         3.6732e-05],\n",
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            "         1.6673e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[5.7958e-05, 2.6493e-04, 6.1664e-04,  ..., 2.7895e-05, 4.7187e-05,\n",
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            "         6.2847e-05],\n",
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            "         1.4906e-04],\n",
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            "         4.8885e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.0605e-05],\n",
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            "         2.5423e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.2527e-05],\n",
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            "         8.1022e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.5031e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.1679e-04],\n",
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            "         7.9403e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.4630e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.2856e-05],\n",
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            "         2.7796e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         9.5628e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.7984e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.3557e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.1823e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.1703e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.5444e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.5623e-05],\n",
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            "         3.6994e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.1737e-05],\n",
            "        ...,\n",
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            "         5.2935e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.3070e-05],\n",
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            "         5.9348e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.9293e-05],\n",
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            "         7.4174e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.7336e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.0666e-04],\n",
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            "         3.0799e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.9697e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.3170e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         1.3773e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         6.9630e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.1010e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         7.5146e-06]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         3.8963e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.1723e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.7633e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.8891e-05],\n",
            "        [1.2208e-04, 1.1751e-03, 3.9612e-04,  ..., 5.8687e-05, 4.3526e-05,\n",
            "         2.8286e-05],\n",
            "        [4.0137e-05, 5.2359e-05, 4.5953e-05,  ..., 6.0596e-05, 2.6120e-05,\n",
            "         6.9910e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.8819e-04, 8.5869e-05, 1.2272e-04,  ..., 1.7744e-05, 2.5697e-05,\n",
            "         1.8748e-05],\n",
            "        [1.2703e-04, 3.2765e-04, 1.4012e-04,  ..., 2.9433e-05, 4.6874e-05,\n",
            "         4.6848e-05],\n",
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            "         6.8618e-05],\n",
            "        ...,\n",
            "        [6.7584e-05, 4.5832e-05, 1.0941e-04,  ..., 2.3627e-05, 1.0123e-05,\n",
            "         2.4687e-05],\n",
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            "         8.0074e-06],\n",
            "        [1.4901e-04, 1.0623e-04, 5.2760e-04,  ..., 2.6690e-05, 3.0754e-05,\n",
            "         2.8815e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.2501e-03, 1.6578e-04, 5.3507e-04,  ..., 1.8248e-05, 9.2710e-06,\n",
            "         1.3004e-05],\n",
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            "         9.7373e-05],\n",
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            "         3.2809e-05],\n",
            "        ...,\n",
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            "         5.9070e-05],\n",
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            "         3.0110e-05],\n",
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            "         5.1768e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.6240e-04, 4.2057e-04, 1.0245e-04,  ..., 2.9022e-05, 7.9814e-05,\n",
            "         5.2142e-05],\n",
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            "         6.3846e-05],\n",
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            "         1.9037e-05],\n",
            "        ...,\n",
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            "         3.5921e-05],\n",
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            "         4.8577e-06]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.9950e-04, 1.5407e-05, 6.2585e-05,  ..., 1.9093e-05, 9.7496e-06,\n",
            "         9.5747e-06],\n",
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            "         5.7341e-05],\n",
            "        ...,\n",
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            "         8.4674e-05],\n",
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            "         2.1552e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[7.1413e-05, 1.1741e-04, 5.8820e-05,  ..., 1.7093e-05, 9.0968e-06,\n",
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            "         1.1443e-04],\n",
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            "         6.6712e-06],\n",
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            "         2.0470e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[5.9385e-04, 6.6970e-04, 2.7710e-04,  ..., 4.8888e-05, 6.7051e-05,\n",
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            "         5.6035e-05],\n",
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            "         4.9171e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.2307e-05, 1.7762e-04, 2.1598e-04,  ..., 2.6372e-05, 1.5374e-05,\n",
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            "         4.9945e-05],\n",
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            "         2.8059e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.5595e-04, 2.4069e-04, 5.0871e-04,  ..., 8.4842e-05, 4.6640e-05,\n",
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            "         8.5070e-05],\n",
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            "         7.9986e-06]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.9552e-04, 4.0009e-04, 4.1064e-04,  ..., 1.0764e-04, 8.0561e-05,\n",
            "         1.0279e-04],\n",
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            "         1.8462e-04],\n",
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            "         3.0226e-05],\n",
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            "         5.9305e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         2.1139e-05],\n",
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            "         1.5370e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         4.6178e-05],\n",
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            "         4.3669e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.4069e-04, 3.8294e-04, 1.0544e-04,  ..., 1.1294e-05, 9.8402e-06,\n",
            "         7.2275e-06],\n",
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            "         3.4847e-05],\n",
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            "         5.9819e-05],\n",
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            "         6.6197e-06]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[8.6433e-04, 1.0140e-04, 6.1266e-04,  ..., 5.9077e-05, 1.0527e-04,\n",
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            "         1.2172e-05],\n",
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            "         1.5839e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.2085e-04, 3.3632e-04, 3.0053e-04,  ..., 6.7935e-05, 2.9861e-05,\n",
            "         6.9900e-05],\n",
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            "         8.6453e-05],\n",
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            "         1.7103e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
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            "         5.4421e-05],\n",
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            "         5.3909e-05],\n",
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            "         2.7847e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.0224e-04, 1.2804e-03, 2.2472e-04,  ..., 9.4183e-05, 5.8129e-05,\n",
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            "         2.7651e-05],\n",
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            "         5.4405e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.5856e-04, 5.4620e-04, 2.1053e-04,  ..., 3.1358e-05, 1.8045e-05,\n",
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            "         1.9982e-05],\n",
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            "         5.4074e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[5.2164e-05, 6.8932e-05, 4.6747e-05,  ..., 1.0621e-05, 2.2091e-05,\n",
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            "         5.7057e-05],\n",
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            "         9.4751e-06]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[4.0711e-04, 6.8375e-05, 4.2247e-05,  ..., 2.2996e-05, 1.3129e-05,\n",
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            "         5.2826e-05],\n",
            "        ...,\n",
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            "         2.1338e-05],\n",
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            "        [5.6881e-04, 2.8126e-04, 5.7298e-04,  ..., 4.6492e-05, 7.8632e-05,\n",
            "         4.1668e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.9892e-04, 1.9125e-04, 1.8311e-03,  ..., 6.9545e-05, 3.9618e-05,\n",
            "         2.5824e-05],\n",
            "        [9.5592e-05, 7.0954e-04, 4.2900e-05,  ..., 1.4119e-05, 2.5836e-05,\n",
            "         1.4260e-05],\n",
            "        [2.9830e-04, 1.1428e-04, 1.3688e-04,  ..., 9.2830e-05, 2.2242e-05,\n",
            "         3.0721e-05],\n",
            "        ...,\n",
            "        [4.5663e-04, 1.3929e-03, 1.5726e-04,  ..., 3.5314e-05, 7.3072e-05,\n",
            "         2.6443e-05],\n",
            "        [4.0446e-04, 1.0643e-03, 2.8523e-04,  ..., 5.8891e-05, 1.0647e-04,\n",
            "         7.9955e-05],\n",
            "        [2.0772e-04, 9.9988e-04, 6.3680e-04,  ..., 7.4885e-05, 8.5227e-05,\n",
            "         4.3927e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.8780e-03, 3.2994e-04, 2.5141e-04,  ..., 5.4086e-05, 1.4170e-04,\n",
            "         8.6168e-05],\n",
            "        [6.5639e-05, 7.9882e-05, 3.4818e-05,  ..., 7.1686e-05, 1.0807e-04,\n",
            "         1.4656e-04],\n",
            "        [1.0798e-04, 2.0557e-04, 1.1101e-04,  ..., 6.7856e-05, 2.3305e-05,\n",
            "         3.7246e-05],\n",
            "        ...,\n",
            "        [9.1462e-05, 2.4766e-04, 2.5544e-04,  ..., 3.7781e-05, 5.0942e-05,\n",
            "         2.7130e-05],\n",
            "        [9.4648e-05, 1.1931e-04, 8.3564e-05,  ..., 5.2273e-06, 1.3087e-05,\n",
            "         1.5668e-05],\n",
            "        [3.4556e-05, 1.8408e-04, 1.1843e-04,  ..., 2.5734e-05, 1.3040e-05,\n",
            "         2.7843e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[2.3207e-04, 1.2128e-04, 4.0769e-04,  ..., 1.1174e-04, 4.7512e-05,\n",
            "         4.1873e-05],\n",
            "        [4.1475e-04, 3.0397e-04, 2.2479e-04,  ..., 9.4409e-05, 4.9872e-05,\n",
            "         6.5966e-05],\n",
            "        [1.6414e-05, 5.9815e-05, 5.8227e-05,  ..., 7.7432e-05, 5.6244e-05,\n",
            "         6.5261e-05],\n",
            "        ...,\n",
            "        [1.4317e-04, 3.3953e-04, 6.4196e-05,  ..., 1.8601e-05, 1.2454e-05,\n",
            "         3.1829e-05],\n",
            "        [8.4914e-04, 1.5115e-04, 1.7002e-04,  ..., 4.5873e-05, 3.3227e-05,\n",
            "         3.2837e-05],\n",
            "        [5.8085e-04, 4.3117e-04, 1.6285e-04,  ..., 8.1036e-05, 3.1450e-05,\n",
            "         2.7816e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[6.2279e-05, 9.3603e-05, 1.5124e-03,  ..., 2.0902e-05, 3.2455e-05,\n",
            "         2.7656e-05],\n",
            "        [2.7640e-04, 5.0343e-04, 4.2514e-04,  ..., 8.5226e-05, 9.1227e-05,\n",
            "         8.6861e-05],\n",
            "        [1.0141e-04, 6.0375e-04, 3.7011e-04,  ..., 2.7165e-05, 4.5897e-05,\n",
            "         2.3084e-05],\n",
            "        ...,\n",
            "        [6.8640e-04, 4.1399e-04, 8.9256e-04,  ..., 4.0272e-05, 6.8650e-05,\n",
            "         5.3536e-05],\n",
            "        [3.7286e-04, 1.6453e-04, 2.1123e-04,  ..., 5.6825e-05, 3.9848e-05,\n",
            "         4.8794e-05],\n",
            "        [2.1319e-04, 4.9488e-05, 9.3723e-05,  ..., 1.4783e-05, 2.5448e-05,\n",
            "         2.8115e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.0965e-04, 9.6757e-05, 1.1498e-04,  ..., 2.0621e-05, 3.7955e-05,\n",
            "         2.6022e-05],\n",
            "        [7.8551e-05, 1.7068e-04, 4.6076e-04,  ..., 6.3350e-05, 4.0586e-05,\n",
            "         1.6884e-05],\n",
            "        [1.2512e-04, 5.8384e-05, 7.3973e-05,  ..., 1.2325e-05, 2.7308e-05,\n",
            "         9.6686e-06],\n",
            "        ...,\n",
            "        [1.5430e-04, 2.3165e-04, 1.7333e-03,  ..., 7.6283e-05, 4.5614e-05,\n",
            "         4.6660e-05],\n",
            "        [2.7253e-04, 1.4938e-04, 3.0722e-04,  ..., 5.8151e-05, 4.2657e-05,\n",
            "         5.1773e-05],\n",
            "        [5.3258e-04, 1.6698e-04, 4.1834e-04,  ..., 8.2757e-05, 1.1822e-04,\n",
            "         9.0947e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[3.8808e-05, 4.0711e-05, 7.1346e-05,  ..., 1.6340e-05, 2.3671e-05,\n",
            "         1.3566e-05],\n",
            "        [1.2638e-04, 2.8080e-04, 2.0664e-04,  ..., 2.2561e-05, 4.6302e-05,\n",
            "         4.0086e-05],\n",
            "        [4.5306e-05, 6.2269e-05, 7.2179e-05,  ..., 6.0188e-05, 1.2812e-04,\n",
            "         6.1688e-05],\n",
            "        ...,\n",
            "        [3.0162e-04, 5.3234e-05, 1.0264e-04,  ..., 2.5789e-05, 1.3475e-05,\n",
            "         8.9767e-06],\n",
            "        [7.1821e-05, 2.5636e-04, 8.5708e-05,  ..., 1.0740e-05, 6.6433e-06,\n",
            "         2.5140e-05],\n",
            "        [1.3217e-04, 1.9803e-04, 3.1527e-04,  ..., 9.6706e-05, 6.8379e-05,\n",
            "         7.6633e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n",
            "tensor([[1.3679e-04, 1.6655e-04, 3.5475e-04,  ..., 7.6075e-06, 1.1172e-05,\n",
            "         1.8241e-05],\n",
            "        [7.7088e-05, 2.6982e-05, 4.5046e-05,  ..., 1.6991e-05, 6.6404e-06,\n",
            "         2.4895e-05],\n",
            "        [5.1182e-05, 3.9075e-04, 2.0479e-04,  ..., 4.5521e-05, 1.9769e-05,\n",
            "         5.0762e-05],\n",
            "        ...,\n",
            "        [2.2815e-04, 2.3392e-05, 2.3320e-05,  ..., 2.7874e-05, 6.1618e-05,\n",
            "         4.3247e-05],\n",
            "        [3.0085e-04, 8.5732e-05, 1.2407e-04,  ..., 1.9351e-05, 3.5686e-05,\n",
            "         3.0165e-05],\n",
            "        [1.8608e-04, 4.8912e-04, 2.4707e-04,  ..., 8.1703e-05, 4.6535e-05,\n",
            "         3.5739e-05]], device='cuda:0', grad_fn=<SoftmaxBackward0>)\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-32-11b224459967>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     12\u001b[0m       \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0mloss_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpredicitons\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m       \u001b[0mauc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mroc_auc_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcpu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdetach\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mpredicitons\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcpu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdetach\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m       \u001b[0mlabel\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcpu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdetach\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m       \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mY_hat\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcpu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdetach\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m       \u001b[0moverall_loss\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyO/jr4KfxxJosGZDm1kE4T+",
      "include_colab_link": true
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}