NSMC_Classification_bidirection.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"NSMC_Classification_bidirection.ipynb","provenance":[],"authorship_tag":"ABX9TyOWSjuU91kuga9RBVVTqChB"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","metadata":{"id":"SwtYdmywj8ya"},"source":["이번 장에서는 Bi-LSTM과 lr schduler를 사용해서 NSMC 감성 분석 성능을 끌어 올려보겠습니다."]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"m8X6TCb-6h8v","executionInfo":{"status":"ok","timestamp":1620280277615,"user_tz":-540,"elapsed":17285,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"79edeb7f-29b7-46ea-a5ca-872933885b37"},"source":["from google.colab import drive\n","drive.mount('/content/drive')"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Mounted at /content/drive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"shyy79L76Tlt","executionInfo":{"status":"ok","timestamp":1620280289317,"user_tz":-540,"elapsed":5451,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["import torch\n","import torch.nn as nn\n","import torch.optim as optim\n","import pandas as pd\n","from sklearn.model_selection import train_test_split"],"execution_count":2,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"n3cnoF4_zk6r","executionInfo":{"status":"ok","timestamp":1620280289318,"user_tz":-540,"elapsed":5219,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"8af29fc4-1eb4-462b-b091-f3f92d67c262"},"source":["device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n","print(device)"],"execution_count":3,"outputs":[{"output_type":"stream","text":["cuda\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7cJn0lKa6ePc","executionInfo":{"status":"ok","timestamp":1620280605815,"user_tz":-540,"elapsed":321384,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"c6b7542b-33a9-4264-c94a-af163efe9cda"},"source":["!git clone https://github.com/SOMJANG/Mecab-ko-for-Google-Colab.git\n","%cd Mecab-ko-for-Google-Colab\n","!bash install_mecab-ko_on_colab190912.sh"],"execution_count":4,"outputs":[{"output_type":"stream","text":["Cloning into 'Mecab-ko-for-Google-Colab'...\n","remote: Enumerating objects: 91, done.\u001b[K\n","remote: Counting objects: 100% (91/91), done.\u001b[K\n","remote: Compressing objects: 100% (85/85), done.\u001b[K\n","remote: Total 91 (delta 43), reused 22 (delta 6), pack-reused 0\u001b[K\n","Unpacking objects: 100% (91/91), done.\n","/content/Mecab-ko-for-Google-Colab\n","Installing konlpy.....\n","Collecting konlpy\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/85/0e/f385566fec837c0b83f216b2da65db9997b35dd675e107752005b7d392b1/konlpy-0.5.2-py2.py3-none-any.whl (19.4MB)\n","\u001b[K     |████████████████████████████████| 19.4MB 28.0MB/s \n","\u001b[?25hRequirement already satisfied: numpy>=1.6 in /usr/local/lib/python3.7/dist-packages (from konlpy) (1.19.5)\n","Requirement already satisfied: lxml>=4.1.0 in /usr/local/lib/python3.7/dist-packages (from konlpy) (4.2.6)\n","Collecting JPype1>=0.7.0\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/cd/a5/9781e2ef4ca92d09912c4794642c1653aea7607f473e156cf4d423a881a1/JPype1-1.2.1-cp37-cp37m-manylinux2010_x86_64.whl (457kB)\n","\u001b[K     |████████████████████████████████| 460kB 41.5MB/s \n","\u001b[?25hRequirement already satisfied: tweepy>=3.7.0 in /usr/local/lib/python3.7/dist-packages (from konlpy) 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import Mecab\n","mecab = Mecab()\n","사용자 사전 추가 방법 : https://bit.ly/3k0ZH53\n","NameError: name 'Tagger' is not defined 오류 발생 시 런타임을 재실행 해주세요\n","블로그에 해결 방법을 남겨주신 tana님 감사합니다.\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"I64YvthHBI_0","executionInfo":{"status":"ok","timestamp":1620280606249,"user_tz":-540,"elapsed":320815,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["from torchtext.legacy import data\n","from konlpy.tag import Mecab"],"execution_count":5,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"PYCwdiGnA03M","executionInfo":{"status":"ok","timestamp":1620280606250,"user_tz":-540,"elapsed":320113,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"2e848386-1ce2-422e-d32d-0128eb97c1b6"},"source":["cd /content/drive/MyDrive/torch_example/"],"execution_count":6,"outputs":[{"output_type":"stream","text":["/content/drive/MyDrive/torch_example\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"ONSGndtPBMyr","executionInfo":{"status":"ok","timestamp":1620280606536,"user_tz":-540,"elapsed":319938,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["tokenizer = Mecab()"],"execution_count":7,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"dQg-1dMbLVsU","executionInfo":{"status":"ok","timestamp":1620280609383,"user_tz":-540,"elapsed":322476,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"bf61697a-3c95-46c8-de8f-f73b0478f492"},"source":["train = pd.read_csv(\"./data/nsmc/ratings_train.txt\", sep='\\t')\n","test = pd.read_csv(\"./data/nsmc/ratings_test.txt\", sep='\\t')\n","\n","train = train.drop(columns=['id'])\n","test = test.drop(columns=['id'])\n","\n","print(train.shape)\n","print(test.shape)"],"execution_count":8,"outputs":[{"output_type":"stream","text":["(150000, 2)\n","(50000, 2)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_EL3Fhl5bDdU","executionInfo":{"status":"ok","timestamp":1620280609384,"user_tz":-540,"elapsed":321938,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"e63c5e97-3059-4463-c7e0-9c0f1bec0e6a"},"source":["train_data = train.dropna() #말뭉치에서 nan 값을 제거함\n","test_data = test.dropna()\n","\n","print(train_data.shape)\n","print(test_data.shape)"],"execution_count":9,"outputs":[{"output_type":"stream","text":["(149995, 2)\n","(49997, 2)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"f7ATQyWmMMCF","executionInfo":{"status":"ok","timestamp":1620280609384,"user_tz":-540,"elapsed":321303,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["train_data, valid_data = train_test_split(train_data, test_size=0.3, random_state=32)"],"execution_count":10,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"CWEE8eTSMhqh","executionInfo":{"status":"ok","timestamp":1620280609385,"user_tz":-540,"elapsed":320749,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"f33dc3a8-af0d-4b31-ebd5-3ac7d7e3f004"},"source":["print(len(train_data))\n","print(len(valid_data))"],"execution_count":11,"outputs":[{"output_type":"stream","text":["104996\n","44999\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"NU4u-h4ZBO-6","executionInfo":{"status":"ok","timestamp":1620280609385,"user_tz":-540,"elapsed":320166,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["TEXT = data.Field(sequential=True, use_vocab=True, tokenize=tokenizer.morphs, lower=False, batch_first=True, fix_length=20)\n","LABEL = data.LabelField(dtype = torch.float) "],"execution_count":12,"outputs":[]},{"cell_type":"code","metadata":{"id":"8b4ymeVtNPl_","executionInfo":{"status":"ok","timestamp":1620280609386,"user_tz":-540,"elapsed":319616,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["def convert_dataset(input_data, text, label):\n","    list_of_example = [data.Example.fromlist(row.tolist(), fields=[('text', text), ('label', label)])  for _, row in input_data.iterrows()]\n","    dataset = data.Dataset(examples=list_of_example, fields=[('text', text), ('label', label)])\n","    return dataset"],"execution_count":13,"outputs":[]},{"cell_type":"code","metadata":{"id":"IR41A4m9OBJM","executionInfo":{"status":"ok","timestamp":1620280647705,"user_tz":-540,"elapsed":357363,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["train_data = convert_dataset(train_data,TEXT,LABEL)\n","valid_data = convert_dataset(valid_data, TEXT, LABEL)"],"execution_count":14,"outputs":[]},{"cell_type":"code","metadata":{"id":"e3CLzUr8DDkE","executionInfo":{"status":"ok","timestamp":1620280648633,"user_tz":-540,"elapsed":357644,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["TEXT.build_vocab(train_data, max_size=10000)\n","LABEL.build_vocab(train_data)"],"execution_count":15,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"nFQaqoPnDLaE","executionInfo":{"status":"ok","timestamp":1620280648634,"user_tz":-540,"elapsed":357077,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"dd68fd6d-3317-4ae9-84d4-e6c1ef10b1af"},"source":["print('단어 집합의 크기 : {}'.format(len(TEXT.vocab)))\n","print('label 의 크기 : {}'.format(len(LABEL.vocab)))"],"execution_count":16,"outputs":[{"output_type":"stream","text":["단어 집합의 크기 : 10002\n","label 의 크기 : 2\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"yeoY2_b4DS6E"},"source":["10000개 단어 + \\<unk> + \\<pad> 토큰이 들어감\n"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Kz5XeWKeEkwG","executionInfo":{"status":"ok","timestamp":1620280648634,"user_tz":-540,"elapsed":355518,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"5be3eb2d-9f9a-47f3-b0d6-1aea139ca631"},"source":["print(LABEL.vocab.stoi) #라벨 값이 "],"execution_count":17,"outputs":[{"output_type":"stream","text":["defaultdict(None, {0: 0, 1: 1})\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"NQhMoHCg0ZmN","executionInfo":{"status":"ok","timestamp":1620280661530,"user_tz":-540,"elapsed":367494,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["test_data = convert_dataset(test_data, TEXT, LABEL)"],"execution_count":18,"outputs":[]},{"cell_type":"code","metadata":{"id":"9gGUTpZ2DNvz","executionInfo":{"status":"ok","timestamp":1620280661530,"user_tz":-540,"elapsed":365998,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["batch_size = 5\n","train_iter, valid_iter, test_iter = data.Iterator.splits((train_data, valid_data, test_data), batch_size=batch_size, sort=False, device=device)"],"execution_count":19,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2Q8mve6nDg7_","executionInfo":{"status":"ok","timestamp":1620280661531,"user_tz":-540,"elapsed":365374,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"1741d559-b4e5-446e-e238-a885a73c6fb2"},"source":["print('훈련 데이터의 미니 배치 수 : {}'.format(len(train_iter)))\n","print('평가 데이터의 미니 배치 수 : {}'.format(len(valid_iter)))\n","print('테스트 데이터의 미니 배치 수 : {}'.format(len(test_iter)))"],"execution_count":20,"outputs":[{"output_type":"stream","text":["훈련 데이터의 미니 배치 수 : 21000\n","평가 데이터의 미니 배치 수 : 9000\n","테스트 데이터의 미니 배치 수 : 10000\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"L15OceFfFBbi","executionInfo":{"status":"ok","timestamp":1620281807375,"user_tz":-540,"elapsed":677,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["class biLSTM(nn.Module):\n","  def __init__(self, input_dim, hidden_dim, output_dim, embedding_dim, dropout):\n","    super().__init__()\n","    self.embedding = nn.Embedding(input_dim, embedding_dim, padding_idx=0)\n","    self.rnn = nn.LSTM(embedding_dim, hidden_dim, num_layers=2, bidirectional=True, batch_first=True, dropout=dropout)\n","    self.linear = nn.Linear(hidden_dim*2, output_dim)\n","    self.dropout = nn.Dropout(dropout)\n","  \n","  def forward(self, x):\n","    embed = self.dropout(self.embedding(x))\n","    output, (hidden, cell) = self.rnn(embed)\n","    \n","    hidden = self.dropout(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))\n","    hidden = self.linear(hidden)\n","    return hidden\n","  \n","  def _init_state(self, batch_size=1):\n","    weight = next(self.parameters()).data\n","    return weight.new(self.n_layers, batch_size, self.hidden_dim).zero_()"],"execution_count":30,"outputs":[]},{"cell_type":"code","metadata":{"id":"hH0XYn65xqt5","executionInfo":{"status":"ok","timestamp":1620281203128,"user_tz":-540,"elapsed":730,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["def binary_accuracy(prediction, target):\n","  '''\n","from https://github.com/bentrevett/pytorch-sentiment-analysis/blob/master/1%20-%20Simple%20Sentiment%20Analysis.ipynb\n","  '''\n","  # round predictions to the closest integer (0 or 1)\n","  rounded_preds = torch.round(torch.sigmoid(prediction))\n","  \n","  #convert into float for division\n","  correct = (rounded_preds == target).float()\n","\n","  # rounded_preds = [ 1   0   0   1   1   1   0   1   1   1]\n","  # targets       = [ 1   0   1   1   1   1   0   1   1   0]\n","  # correct       = [1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 0.0]\n","  acc = correct.sum() / len(correct)\n","  return acc"],"execution_count":23,"outputs":[]},{"cell_type":"code","metadata":{"id":"9MgSjQr3sa5i","executionInfo":{"status":"ok","timestamp":1620285100393,"user_tz":-540,"elapsed":743,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["def train(model, train_iter):\n","  model.train()\n","\n","  epoch_loss, epoch_acc = 0, 0\n","  for batch in train_iter:\n","    optimizer.zero_grad()\n","    x, y = batch.text.to(device), batch.label.to(device)\n","    y_hat = model(x).squeeze(1)\n","\n","    loss = criterion(y_hat, y)\n","    acc = binary_accuracy(y_hat, y)\n","\n","    loss.backward()\n","    optimizer.step()\n","\n","    epoch_loss += loss.item()\n","    epoch_acc += acc.item()\n","\n","  return epoch_loss / len(train_iter), epoch_acc / len(train_iter)\n"],"execution_count":36,"outputs":[]},{"cell_type":"code","metadata":{"id":"ZkuKVVyCzTF8","executionInfo":{"status":"ok","timestamp":1620281209670,"user_tz":-540,"elapsed":818,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["def evaluate(model, valid_iter):\n","  model.eval()\n","  with torch.no_grad():\n","    eval_loss, eval_acc = 0, 0\n","    for batch in valid_iter:\n","      x,y = batch.text.to(device), batch.label.to(device)\n","      y_hat = model(x).squeeze(1)\n","      \n","      loss = criterion(y_hat, y)\n","      acc = binary_accuracy(y_hat, y)\n","\n","      eval_loss += loss.item()\n","      eval_acc += acc.item()\n","      \n","  return eval_loss / len(valid_iter), eval_acc / len(valid_iter)"],"execution_count":25,"outputs":[]},{"cell_type":"code","metadata":{"id":"ss8RYLuN3QWN","executionInfo":{"status":"ok","timestamp":1620281209671,"user_tz":-540,"elapsed":619,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["def inference(model, test_iter):\n","  model.eval()\n","  with torch.no_grad():\n","    test_loss, test_acc = 0, 0\n","    for batch in test_iter:\n","      x, y = batch.text.to(device), batch.label.to(device)\n","      y_hat = model(x).squeeze(1)\n","\n","      loss = criterion(y_hat, y)\n","      acc = binary_accuracy(y_hat, y)\n","      \n","      test_loss += loss.item()\n","      test_acc += acc.item()\n","\n","  return test_loss / len(test_iter), test_acc / len(test_iter)"],"execution_count":26,"outputs":[]},{"cell_type":"code","metadata":{"id":"ilZJ-N2M1dcD","executionInfo":{"status":"ok","timestamp":1620285156464,"user_tz":-540,"elapsed":647,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["model = biLSTM(len(TEXT.vocab), 256, len(LABEL.vocab)-1, 300, 0.3)\n","model.to(device)\n","optimizer = optim.Adam(model.parameters())\n","criterion = nn.BCEWithLogitsLoss()\n","criterion.to(device)\n","\n","scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=2)"],"execution_count":37,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"DShy6pep2BIO","executionInfo":{"status":"ok","timestamp":1620287827546,"user_tz":-540,"elapsed":2643600,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"a2bae18a-9703-4407-99a5-8e560d19e6a8"},"source":["best_val_loss = float('inf')\n","for _epoch in range(1,6): # 5 epoch\n","  train_loss, train_acc = train(model, train_iter)\n","  valid_loss, valid_acc = evaluate(model, valid_iter)\n","  print(\"[Epoch: %d] train loss : %5.2f | train accuracy : %5.2f\" % (_epoch, train_loss, train_acc))\n","  print(\"[Epoch: %d] val loss : %5.2f | val accuracy : %5.2f\" % (_epoch, valid_loss, valid_acc))\n","\n","  scheduler.step() #lr scheduler\n","  \n","    # 검증 오차가 가장 적은 최적의 모델을 저장\n","  if valid_loss < best_val_loss:\n","    best_val_loss = valid_loss\n","    #torch.save(model.state_dict(), 'biLSTMmodel.pt')"],"execution_count":38,"outputs":[{"output_type":"stream","text":["[Epoch: 1] train loss :  0.42 | train accuracy :  0.80\n","[Epoch: 1] val loss :  0.36 | val accuracy :  0.84\n","[Epoch: 2] train loss :  0.33 | train accuracy :  0.86\n","[Epoch: 2] val loss :  0.34 | val accuracy :  0.85\n","[Epoch: 3] train loss :  0.28 | train accuracy :  0.88\n","[Epoch: 3] val loss :  0.34 | val accuracy :  0.85\n","[Epoch: 4] train loss :  0.27 | train accuracy :  0.88\n","[Epoch: 4] val loss :  0.34 | val accuracy :  0.86\n","[Epoch: 5] train loss :  0.26 | train accuracy :  0.89\n","[Epoch: 5] val loss :  0.34 | val accuracy :  0.85\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"ZP8Lqf7n5CgO","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1620287881280,"user_tz":-540,"elapsed":53711,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"4787263d-adb4-4472-f3fe-1d42dad346b8"},"source":["test_loss, test_acc = inference(model, test_iter)\n","print('Test Loss: %5.2f | Test Acc: %5.2f '%(test_loss, test_acc*100))"],"execution_count":39,"outputs":[{"output_type":"stream","text":["Test Loss:  0.34 | Test Acc: 85.40 \n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"aFeqcwhpeIoV","executionInfo":{"status":"ok","timestamp":1620288256588,"user_tz":-540,"elapsed":771,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}}},"source":["def predict_sentiment(model, sentence):\n","  model.eval()\n","  tokenized = [token for token in tokenizer.morphs(sentence)]\n","  indexed = [TEXT.vocab.stoi[t] for t in tokenized]\n","  tensor = torch.LongTensor(indexed).to(device)\n","  tensor = tensor.unsqueeze(1)\n","  prediction = torch.sigmoid(model(tensor))\n","  return prediction"],"execution_count":52,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"i2VHVmhanIQK","executionInfo":{"status":"ok","timestamp":1620288256879,"user_tz":-540,"elapsed":708,"user":{"displayName":"­원혜진[컴퓨터공학과]","photoUrl":"","userId":"11688778515012300025"}},"outputId":"61271fb5-8042-429d-93a1-6c980f2f4cec"},"source":["predict_sentiment(model, \"This film is terrible\")"],"execution_count":53,"outputs":[{"output_type":"execute_result","data":{"text/plain":["tensor([[0.1770],\n","        [0.4699],\n","        [0.3685],\n","        [0.4699]], device='cuda:0', grad_fn=<SigmoidBackward>)"]},"metadata":{"tags":[]},"execution_count":53}]},{"cell_type":"code","metadata":{"id":"rhbOwPYutFKh"},"source":[""],"execution_count":null,"outputs":[]}]}