{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import os, sys, math, json\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport skimage.io\n\nfrom skimage.transform import resize\nfrom imgaug import augmenters as iaa\nfrom tqdm import tqdm\nimport PIL\nfrom PIL import Image, ImageOps\nimport cv2\nfrom sklearn.utils import class_weight, shuffle\n\n%matplotlib inline\n\nimport scipy\nimport tensorflow as tf\n\nfrom tensorflow.keras.losses import binary_crossentropy\nfrom tensorflow.keras.applications.resnet50 import preprocess_input\nimport tensorflow.keras.backend as K\nfrom tensorflow.keras.utils import Sequence\nfrom tensorflow.keras.utils import to_categorical\n\nfrom tensorflow.keras import layers\nfrom tensorflow.keras.applications import DenseNet121\nfrom tensorflow.keras.callbacks import Callback, ModelCheckpoint\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.optimizers import Adam\n\nfrom sklearn.metrics import f1_score, fbeta_score\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import cohen_kappa_score, accuracy_score\n\n\nWORKERS = 2\nCHANNEL = 3\n\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\nnp.random.seed(42)\ntf.random.set_seed(42)\n\nIMG_SIZE = 512\nNUM_CLASSES = 5\nSEED = 42\nTRAIN_NUM = 1000 # use 1000 when you just want to explore new idea, use -1 for full train\n\n#### Starting with just 2019 data","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","id":"dYkTK1DIa3LL","executionInfo":{"status":"ok","timestamp":1666068569334,"user_tz":-330,"elapsed":5713,"user":{"displayName":"319126510168 LAKKOJU SAI REVANTH","userId":"09596795716125126162"}},"execution":{"iopub.status.busy":"2023-03-22T13:37:51.914234Z","iopub.execute_input":"2023-03-22T13:37:51.91514Z","iopub.status.idle":"2023-03-22T13:38:00.109475Z","shell.execute_reply.started":"2023-03-22T13:37:51.915013Z","shell.execute_reply":"2023-03-22T13:38:00.108421Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train = pd.read_csv('../input/diabetic-retinopathy-resized/trainLabels.csv')\ndf_test = pd.read_csv('../input/aptos2019-blindness-detection/test.csv')\n\nprint(df_train.shape)\nprint(df_test.shape)\nprint(df_train.head())\ndf_test","metadata":{"id":"iVi7Zrk0a3LU","executionInfo":{"status":"error","timestamp":1666068579080,"user_tz":-330,"elapsed":729,"user":{"displayName":"319126510168 LAKKOJU SAI REVANTH","userId":"09596795716125126162"}},"outputId":"4f11323a-1f27-4ced-f07e-aab5912c1960","execution":{"iopub.status.busy":"2023-03-22T13:38:00.111483Z","iopub.execute_input":"2023-03-22T13:38:00.1122Z","iopub.status.idle":"2023-03-22T13:38:00.176073Z","shell.execute_reply.started":"2023-03-22T13:38:00.112169Z","shell.execute_reply":"2023-03-22T13:38:00.175123Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train['level'].value_counts().plot(kind='bar')\ndf_train.level.value_counts()","metadata":{"id":"Zk2foVKNa3LW","execution":{"iopub.status.busy":"2023-03-22T13:38:00.177572Z","iopub.execute_input":"2023-03-22T13:38:00.178179Z","iopub.status.idle":"2023-03-22T13:38:00.402533Z","shell.execute_reply.started":"2023-03-22T13:38:00.178142Z","shell.execute_reply":"2023-03-22T13:38:00.401535Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class_weights = df_train['level'].value_counts()\ndfs = [df_train[df_train['level'] == i].sample(1200*(2 if i < 3 else 1),replace=True) for i in range(5)]\nresampled = pd.concat(dfs, axis = 0).reset_index(drop=True)\nresampled","metadata":{"id":"xPg2CiWta3LX","execution":{"iopub.status.busy":"2023-03-22T13:38:00.405187Z","iopub.execute_input":"2023-03-22T13:38:00.405542Z","iopub.status.idle":"2023-03-22T13:38:00.427427Z","shell.execute_reply.started":"2023-03-22T13:38:00.405501Z","shell.execute_reply":"2023-03-22T13:38:00.426388Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"resampled.level.value_counts()","metadata":{"id":"7PDlLUZ5a3LY","execution":{"iopub.status.busy":"2023-03-22T13:38:00.429094Z","iopub.execute_input":"2023-03-22T13:38:00.429452Z","iopub.status.idle":"2023-03-22T13:38:00.437112Z","shell.execute_reply.started":"2023-03-22T13:38:00.429417Z","shell.execute_reply":"2023-03-22T13:38:00.436082Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train=resampled","metadata":{"id":"TC3NiZRxa3LZ","execution":{"iopub.status.busy":"2023-03-22T13:38:00.438493Z","iopub.execute_input":"2023-03-22T13:38:00.438991Z","iopub.status.idle":"2023-03-22T13:38:00.445088Z","shell.execute_reply.started":"2023-03-22T13:38:00.438955Z","shell.execute_reply":"2023-03-22T13:38:00.44411Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def display_samples(df, columns=4, rows=3, gauss=False):\n    fig=plt.figure(figsize=(5*columns, 4*rows))\n\n    for i in range(columns*rows):\n        image_path = df.loc[i,'image']\n        image_id = df.loc[i,'level']\n#         img = cv2.imread(f'../input/aptos2019-blindness-detection/train_images/{image_path}.png')\n        img = cv2.imread(f'../input/diabetic-retinopathy-resized/resized_train/resized_train/{image_path}.jpeg')\n\n        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n        if gauss:\n            img = cv2.addWeighted (img,4, cv2.GaussianBlur( img , (0,0) , IMG_SIZE/10) ,-4 ,128) \n\n        fig.add_subplot(rows, columns, i+1)\n        plt.title(image_id)\n        plt.imshow(img)\n    \n    plt.tight_layout()\n    \ndisplay_samples(df_train)","metadata":{"id":"3ESi5NNxa3La","execution":{"iopub.status.busy":"2023-03-22T13:38:00.446531Z","iopub.execute_input":"2023-03-22T13:38:00.447305Z","iopub.status.idle":"2023-03-22T13:38:03.827096Z","shell.execute_reply.started":"2023-03-22T13:38:00.447198Z","shell.execute_reply":"2023-03-22T13:38:03.826113Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"display_samples(df_train, gauss=True)","metadata":{"id":"N77PO0J4a3Lc","execution":{"iopub.status.busy":"2023-03-22T13:38:03.828762Z","iopub.execute_input":"2023-03-22T13:38:03.829461Z","iopub.status.idle":"2023-03-22T13:38:15.192543Z","shell.execute_reply.started":"2023-03-22T13:38:03.829423Z","shell.execute_reply":"2023-03-22T13:38:15.190724Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def preprocess_image(image_path, desired_size=224, gauss=False):\n    im = cv2.imread(image_path)\n    im = cv2.resize(im, (desired_size, desired_size), interpolation = cv2.INTER_AREA)\n    if gauss:\n        im = cv2.addWeighted(im,4, cv2.GaussianBlur( im , (0,0) , desired_size/10) ,-4 ,128)\n    \n    return im","metadata":{"id":"eTgB9qrDa3Ld","execution":{"iopub.status.busy":"2023-03-22T13:38:15.193822Z","iopub.execute_input":"2023-03-22T13:38:15.194742Z","iopub.status.idle":"2023-03-22T13:38:15.200701Z","shell.execute_reply.started":"2023-03-22T13:38:15.194706Z","shell.execute_reply":"2023-03-22T13:38:15.199731Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"N = df_train.shape[0]\nx_train_array = np.empty((N, 224, 224, 3), dtype=np.uint8)\n\nfor i, image_id in enumerate(tqdm(df_train['image'])):\n    x_train_array[i, :, :, :] = preprocess_image(\n        f'../input/diabetic-retinopathy-resized/resized_train/resized_train/{image_id}.jpeg',\n#         f'../input/diabetic-retinopathy-resized/resized_train{image_id}.png',\n        gauss=True\n    )\n#     Image.fromarray(x_train_array[i, :, :, :]).save(f'/kaggle/working/2019_244_resized_gauss/test_images/{image_id}.jpeg')","metadata":{"id":"u-jrbcWGa3Lf","execution":{"iopub.status.busy":"2023-03-22T13:38:15.205532Z","iopub.execute_input":"2023-03-22T13:38:15.208435Z","iopub.status.idle":"2023-03-22T13:47:25.051723Z","shell.execute_reply.started":"2023-03-22T13:38:15.208385Z","shell.execute_reply":"2023-03-22T13:47:25.050726Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig=plt.figure(figsize=(4*4, 3*3))\nfor i in range(12):\n    fig.add_subplot(4, 3, i+1)\n    plt.imshow(x_train_array[i])","metadata":{"id":"n2Pz6Hc9a3Lg","execution":{"iopub.status.busy":"2023-03-22T13:47:25.05327Z","iopub.execute_input":"2023-03-22T13:47:25.05389Z","iopub.status.idle":"2023-03-22T13:47:26.180221Z","shell.execute_reply.started":"2023-03-22T13:47:25.053849Z","shell.execute_reply":"2023-03-22T13:47:26.179371Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"N = df_test.shape[0]\nx_test = np.empty((N, 224, 224, 3), dtype=np.uint8)\nfor i, image_id in enumerate(tqdm(df_test['id_code'])):\n    x_test[i, :, :, :] = preprocess_image(\n        f'../input/aptos2019-blindness-detection/test_images/{image_id}.png',\n        gauss = True\n    )\n#     Image.fromarray(x_test_array[i, :, :, :]).save(f'/kaggle/working/2019_244_resized_gauss/test_images/{image_id}.jpeg')","metadata":{"id":"NY-4jQRLa3Lh","execution":{"iopub.status.busy":"2023-03-22T13:47:26.181781Z","iopub.execute_input":"2023-03-22T13:47:26.183314Z","iopub.status.idle":"2023-03-22T13:50:08.266407Z","shell.execute_reply.started":"2023-03-22T13:47:26.183274Z","shell.execute_reply":"2023-03-22T13:50:08.265487Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y_train = pd.get_dummies(df_train['level']).values\n\nprint(x_train_array.shape)\nprint(y_train.shape)\nprint(x_test.shape)","metadata":{"id":"8-hzA4Hxa3Li","execution":{"iopub.status.busy":"2023-03-22T13:50:08.267938Z","iopub.execute_input":"2023-03-22T13:50:08.268307Z","iopub.status.idle":"2023-03-22T13:50:08.276188Z","shell.execute_reply.started":"2023-03-22T13:50:08.26827Z","shell.execute_reply":"2023-03-22T13:50:08.275104Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y_train_multi = np.empty(y_train.shape, dtype=y_train.dtype)\ny_train_multi[:, 4] = y_train[:, 4]\n\nfor i in range(3, -1, -1):\n    y_train_multi[:, i] = np.logical_or(y_train[:, i], y_train_multi[:, i+1])\n\nprint(\"Original y_train:\", y_train.sum(axis=0))\nprint(\"Multilabel version:\", y_train_multi.sum(axis=0))","metadata":{"id":"ZCR6jKHTa3Lj","execution":{"iopub.status.busy":"2023-03-22T13:50:08.277821Z","iopub.execute_input":"2023-03-22T13:50:08.278228Z","iopub.status.idle":"2023-03-22T13:50:08.288174Z","shell.execute_reply.started":"2023-03-22T13:50:08.278186Z","shell.execute_reply":"2023-03-22T13:50:08.286871Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"x_train, x_val, y_train, y_val = train_test_split(\n    x_train_array, y_train_multi, \n    test_size=0.05, \n    random_state=2019\n)\n\nprint(x_train.shape, y_train.shape, x_val.shape, y_val.shape)","metadata":{"id":"XcsXOXDZa3Lj","execution":{"iopub.status.busy":"2023-03-22T13:50:08.289763Z","iopub.execute_input":"2023-03-22T13:50:08.290128Z","iopub.status.idle":"2023-03-22T13:50:08.703018Z","shell.execute_reply.started":"2023-03-22T13:50:08.290093Z","shell.execute_reply":"2023-03-22T13:50:08.701935Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"BATCH_SIZE = 16\n\ndef create_datagen():\n    return ImageDataGenerator(\n        zoom_range=0.15,  # set range for random zoom\n        # set mode for filling points outside the input boundaries\n        fill_mode='constant',\n        cval=0.,  # value used for fill_mode = \"constant\"\n        horizontal_flip=True,  # randomly flip images\n        vertical_flip=True,  # randomly flip images\n    )\n\n# Using original generator\ndata_generator = create_datagen().flow(x_train, y_train, batch_size=BATCH_SIZE, seed=2019)\n# Using Mixup\n# mixup_generator = MixupGenerator(x_train, y_train, batch_size=BATCH_SIZE, alpha=0.2, datagen=create_datagen())()","metadata":{"id":"1mo04rFia3Lk","execution":{"iopub.status.busy":"2023-03-22T13:50:08.704695Z","iopub.execute_input":"2023-03-22T13:50:08.70509Z","iopub.status.idle":"2023-03-22T13:50:10.68548Z","shell.execute_reply.started":"2023-03-22T13:50:08.705037Z","shell.execute_reply":"2023-03-22T13:50:10.684476Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"densenet = DenseNet121(\n    weights='../input/densenet-keras/DenseNet-BC-121-32-no-top.h5',\n    include_top=False,\n    input_shape=(224,224,3)\n)","metadata":{"id":"a6EeKRPTa3Ll","execution":{"iopub.status.busy":"2023-03-22T13:50:10.687093Z","iopub.execute_input":"2023-03-22T13:50:10.687728Z","iopub.status.idle":"2023-03-22T13:50:16.867469Z","shell.execute_reply.started":"2023-03-22T13:50:10.687682Z","shell.execute_reply":"2023-03-22T13:50:16.866474Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def build_densenet_model():\n    model = Sequential()\n    model.add(densenet)\n    model.add(layers.GlobalAveragePooling2D())\n    model.add(layers.Dropout(0.5))\n    model.add(layers.Dense(5, activation='sigmoid'))\n    \n    model.compile(\n        loss='binary_crossentropy',\n        optimizer=Adam(lr=0.00003),\n    )\n    \n    return model","metadata":{"id":"gXJvUUYQa3Ll","execution":{"iopub.status.busy":"2023-03-22T13:50:16.868879Z","iopub.execute_input":"2023-03-22T13:50:16.869248Z","iopub.status.idle":"2023-03-22T13:50:16.874826Z","shell.execute_reply.started":"2023-03-22T13:50:16.869212Z","shell.execute_reply":"2023-03-22T13:50:16.873923Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model_densenet = build_densenet_model()\nmodel_densenet.build()\nmodel_densenet.summary()","metadata":{"id":"jTh9__QWa3Lm","execution":{"iopub.status.busy":"2023-03-22T13:50:16.876857Z","iopub.execute_input":"2023-03-22T13:50:16.878272Z","iopub.status.idle":"2023-03-22T13:50:17.908394Z","shell.execute_reply.started":"2023-03-22T13:50:16.878244Z","shell.execute_reply":"2023-03-22T13:50:17.907356Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"history = model_densenet.fit_generator(\n    data_generator,\n    steps_per_epoch=x_train.shape[0] / BATCH_SIZE,\n    epochs=41,\n    validation_data=(x_val, y_val)\n)","metadata":{"id":"4afjES0aa3Ln","execution":{"iopub.status.busy":"2023-03-22T13:50:17.909615Z","iopub.execute_input":"2023-03-22T13:50:17.909958Z","iopub.status.idle":"2023-03-22T15:05:17.579103Z","shell.execute_reply.started":"2023-03-22T13:50:17.909922Z","shell.execute_reply":"2023-03-22T15:05:17.578101Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"with open('history.json', 'w') as f:\n    json.dump(history.history, f)\n\nhistory_df = pd.DataFrame(history.history)\nhistory_df[['loss', 'val_loss']].plot()","metadata":{"id":"tv2_N4nOa3Ln","execution":{"iopub.status.busy":"2023-03-22T15:05:17.582024Z","iopub.execute_input":"2023-03-22T15:05:17.582341Z","iopub.status.idle":"2023-03-22T15:05:17.821825Z","shell.execute_reply.started":"2023-03-22T15:05:17.582307Z","shell.execute_reply":"2023-03-22T15:05:17.820926Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y_test = model_densenet.predict(x_test) > 0.5\ny_test = y_test.astype(int).sum(axis=1) - 1\n\ndf_test['diagnosis'] = y_test\ndf_test.to_csv('submission.csv',index=False)","metadata":{"id":"F80AHw3na3Lo","execution":{"iopub.status.busy":"2023-03-22T15:05:17.823289Z","iopub.execute_input":"2023-03-22T15:05:17.823904Z","iopub.status.idle":"2023-03-22T15:05:23.044059Z","shell.execute_reply.started":"2023-03-22T15:05:17.823865Z","shell.execute_reply":"2023-03-22T15:05:23.043066Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"history_df.plot()","metadata":{"id":"fiNnUWGja3Lo","execution":{"iopub.status.busy":"2023-03-22T15:05:23.045663Z","iopub.execute_input":"2023-03-22T15:05:23.046027Z","iopub.status.idle":"2023-03-22T15:05:23.275855Z","shell.execute_reply.started":"2023-03-22T15:05:23.045989Z","shell.execute_reply":"2023-03-22T15:05:23.274937Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"x_train_pred = model_densenet.predict(x_train) > 0.5\nx_train_pred = x_train_pred.astype(int).sum(axis=1) - 1\n\nx_val_pred = model_densenet.predict(x_val) > 0.5\nx_val_pred = x_val_pred.astype(int).sum(axis=1) - 1","metadata":{"id":"ThbTgI_oa3Lp","execution":{"iopub.status.busy":"2023-03-22T15:05:23.277479Z","iopub.execute_input":"2023-03-22T15:05:23.278131Z","iopub.status.idle":"2023-03-22T15:05:42.009716Z","shell.execute_reply.started":"2023-03-22T15:05:23.27809Z","shell.execute_reply":"2023-03-22T15:05:42.00871Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"x_train_pred","metadata":{"id":"yQvTawKZa3Lq","execution":{"iopub.status.busy":"2023-03-22T15:05:42.013218Z","iopub.execute_input":"2023-03-22T15:05:42.013577Z","iopub.status.idle":"2023-03-22T15:05:42.020613Z","shell.execute_reply.started":"2023-03-22T15:05:42.01354Z","shell.execute_reply":"2023-03-22T15:05:42.019619Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y_true_train = np.sum(y_train, axis=1) - 1\ny_true_val = np.sum(y_val, axis=1) - 1","metadata":{"id":"j9u5JKdva3Lq","execution":{"iopub.status.busy":"2023-03-22T15:05:42.022177Z","iopub.execute_input":"2023-03-22T15:05:42.022858Z","iopub.status.idle":"2023-03-22T15:05:42.031141Z","shell.execute_reply.started":"2023-03-22T15:05:42.022766Z","shell.execute_reply":"2023-03-22T15:05:42.030198Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.metrics import confusion_matrix, recall_score, precision_score, f1_score, accuracy_score\n\nprint(confusion_matrix(y_true_train, x_train_pred))\nprint(recall_score(y_true_train, x_train_pred, average='macro'))\nprint(precision_score(y_true_train, x_train_pred, average='macro'))\nprint(f1_score(y_true_train, x_train_pred, average='macro'))\nprint(accuracy_score(y_true_train, x_train_pred))","metadata":{"id":"2FK-gfsoa3Lr","execution":{"iopub.status.busy":"2023-03-22T15:05:42.032753Z","iopub.execute_input":"2023-03-22T15:05:42.033155Z","iopub.status.idle":"2023-03-22T15:05:42.062397Z","shell.execute_reply.started":"2023-03-22T15:05:42.033097Z","shell.execute_reply":"2023-03-22T15:05:42.061391Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(confusion_matrix(y_true_val, x_val_pred))\nprint(recall_score(y_true_val, x_val_pred, average='macro'))\nprint(precision_score(y_true_val, x_val_pred, average='macro'))\nprint(f1_score(y_true_val, x_val_pred, average='macro'))\nprint(accuracy_score(y_true_val, x_val_pred))\nprint(y_true_val.shape)","metadata":{"id":"ZwtvKrH7a3Lr","executionInfo":{"status":"error","timestamp":1666068543173,"user_tz":-330,"elapsed":423,"user":{"displayName":"319126510168 LAKKOJU SAI REVANTH","userId":"09596795716125126162"}},"outputId":"0e617dad-6e19-49d4-8698-0bbac62f728d","execution":{"iopub.status.busy":"2023-03-22T15:05:42.068227Z","iopub.execute_input":"2023-03-22T15:05:42.068483Z","iopub.status.idle":"2023-03-22T15:05:42.080482Z","shell.execute_reply.started":"2023-03-22T15:05:42.068458Z","shell.execute_reply":"2023-03-22T15:05:42.079529Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_ans=pd.read_csv('submission.csv')\nresult=df_ans.head(10)\nprint(\"First 10 rows of DataFrame:\")\nprint(result)","metadata":{"id":"wPaWfBh-a3Ls","execution":{"iopub.status.busy":"2023-03-22T15:05:42.081885Z","iopub.execute_input":"2023-03-22T15:05:42.082243Z","iopub.status.idle":"2023-03-22T15:05:42.105815Z","shell.execute_reply.started":"2023-03-22T15:05:42.082207Z","shell.execute_reply":"2023-03-22T15:05:42.104779Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"id":"u99RWfO_a3Ls","executionInfo":{"status":"error","timestamp":1666068533014,"user_tz":-330,"elapsed":957,"user":{"displayName":"319126510168 LAKKOJU SAI REVANTH","userId":"09596795716125126162"}},"outputId":"f0c062aa-4e16-4d7d-d7d4-8ed6af9974d0","trusted":true},"execution_count":null,"outputs":[]}]}