{"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":"markdown","source":"# Intro\nInference notebook for [Hotel-ID starter - classification - traning](https://www.kaggle.com/code/michaln/hotel-id-starter-classification-traning)\n\n","metadata":{"id":"DAY5rHgTm7e8","papermill":{"duration":0.024896,"end_time":"2022-03-24T14:00:54.588459","exception":false,"start_time":"2022-03-24T14:00:54.563563","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# Setup","metadata":{}},{"cell_type":"code","source":"import sys\nsys.path.append('../input/timm-pytorch-image-models/pytorch-image-models-master')","metadata":{"executionInfo":{"elapsed":16271,"status":"ok","timestamp":1619310548121,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"alleged-legislation","outputId":"c6541e5f-ffb4-4609-d6c6-39784e6a07b1","papermill":{"duration":0.036572,"end_time":"2022-03-24T14:00:54.649254","exception":false,"start_time":"2022-03-24T14:00:54.612682","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:47:57.681626Z","iopub.execute_input":"2022-06-05T14:47:57.681893Z","iopub.status.idle":"2022-06-05T14:47:57.709652Z","shell.execute_reply.started":"2022-06-05T14:47:57.681810Z","shell.execute_reply":"2022-06-05T14:47:57.709016Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Imports","metadata":{"id":"cZoSOL9Qm-Yr","papermill":{"duration":0.023644,"end_time":"2022-03-24T14:00:54.696898","exception":false,"start_time":"2022-03-24T14:00:54.673254","status":"completed"},"tags":[]}},{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport random\nimport os\nimport math","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","executionInfo":{"elapsed":14459,"status":"ok","timestamp":1619310548121,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"expired-matter","papermill":{"duration":0.030271,"end_time":"2022-03-24T14:00:54.751131","exception":false,"start_time":"2022-03-24T14:00:54.72086","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:47:57.711002Z","iopub.execute_input":"2022-06-05T14:47:57.711308Z","iopub.status.idle":"2022-06-05T14:47:57.715976Z","shell.execute_reply.started":"2022-06-05T14:47:57.711271Z","shell.execute_reply":"2022-06-05T14:47:57.715080Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from PIL import Image as pil_image\nfrom tqdm import tqdm","metadata":{"executionInfo":{"elapsed":16003,"status":"ok","timestamp":1619310550014,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"extreme-problem","papermill":{"duration":3.220402,"end_time":"2022-03-24T14:00:57.995239","exception":false,"start_time":"2022-03-24T14:00:54.774837","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:47:57.720675Z","iopub.execute_input":"2022-06-05T14:47:57.720983Z","iopub.status.idle":"2022-06-05T14:47:57.726532Z","shell.execute_reply.started":"2022-06-05T14:47:57.720955Z","shell.execute_reply":"2022-06-05T14:47:57.725409Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader\n\nimport timm","metadata":{"executionInfo":{"elapsed":19672,"status":"ok","timestamp":1619310554099,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"angry-domain","papermill":{"duration":2.727834,"end_time":"2022-03-24T14:01:00.766951","exception":false,"start_time":"2022-03-24T14:00:58.039117","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:47:57.730825Z","iopub.execute_input":"2022-06-05T14:47:57.731426Z","iopub.status.idle":"2022-06-05T14:48:01.385023Z","shell.execute_reply.started":"2022-06-05T14:47:57.731383Z","shell.execute_reply":"2022-06-05T14:48:01.384102Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Global","metadata":{"id":"0B00pe7mnBTj","papermill":{"duration":0.023573,"end_time":"2022-03-24T14:01:00.814976","exception":false,"start_time":"2022-03-24T14:01:00.791403","status":"completed"},"tags":[]}},{"cell_type":"code","source":"SEED = 42\nIMG_SIZE = 256\n\nPROJECT_FOLDER = \"../input/hotel-id-to-combat-human-trafficking-2022-fgvc9/\"\nTEST_DATA_FOLDER = PROJECT_FOLDER + \"test_images/\"","metadata":{"executionInfo":{"elapsed":589,"status":"ok","timestamp":1619310979015,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"contained-brief","papermill":{"duration":0.03175,"end_time":"2022-03-24T14:01:00.871686","exception":false,"start_time":"2022-03-24T14:01:00.839936","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:01.387668Z","iopub.execute_input":"2022-06-05T14:48:01.388680Z","iopub.status.idle":"2022-06-05T14:48:01.392245Z","shell.execute_reply.started":"2022-06-05T14:48:01.388648Z","shell.execute_reply":"2022-06-05T14:48:01.391613Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(os.listdir(PROJECT_FOLDER))","metadata":{"executionInfo":{"elapsed":879,"status":"ok","timestamp":1619310979515,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"PZvmFng7ctO3","outputId":"dce0cc91-8e70-4acc-a0b8-6763ffffd5ca","papermill":{"duration":0.031651,"end_time":"2022-03-24T14:01:00.927239","exception":false,"start_time":"2022-03-24T14:01:00.895588","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:01.393401Z","iopub.execute_input":"2022-06-05T14:48:01.394078Z","iopub.status.idle":"2022-06-05T14:48:01.405155Z","shell.execute_reply.started":"2022-06-05T14:48:01.394040Z","shell.execute_reply":"2022-06-05T14:48:01.404365Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def seed_everything(seed):\n    random.seed(seed)\n    os.environ['PYTHONHASHSEED'] = str(seed)\n    np.random.seed(seed)\n    torch.manual_seed(seed)\n    torch.cuda.manual_seed(seed)\n    torch.backends.cudnn.deterministic = True","metadata":{"executionInfo":{"elapsed":600,"status":"ok","timestamp":1619310981653,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"eastern-content","papermill":{"duration":0.032105,"end_time":"2022-03-24T14:01:01.031949","exception":false,"start_time":"2022-03-24T14:01:00.999844","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:01.408616Z","iopub.execute_input":"2022-06-05T14:48:01.408798Z","iopub.status.idle":"2022-06-05T14:48:01.413727Z","shell.execute_reply.started":"2022-06-05T14:48:01.408775Z","shell.execute_reply":"2022-06-05T14:48:01.412774Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Dataset and transformations","metadata":{"id":"xaJKvvuKnW4k","papermill":{"duration":0.023988,"end_time":"2022-03-24T14:01:01.080488","exception":false,"start_time":"2022-03-24T14:01:01.0565","status":"completed"},"tags":[]}},{"cell_type":"code","source":"import albumentations as A\nimport albumentations.pytorch as APT\nimport cv2 \n\nbase_transform = A.Compose([\n    A.ToFloat(),\n    APT.transforms.ToTensorV2(),\n])","metadata":{"executionInfo":{"elapsed":1519,"status":"ok","timestamp":1619310984075,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"revolutionary-membership","papermill":{"duration":0.747421,"end_time":"2022-03-24T14:01:01.852072","exception":false,"start_time":"2022-03-24T14:01:01.104651","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:01.415613Z","iopub.execute_input":"2022-06-05T14:48:01.415929Z","iopub.status.idle":"2022-06-05T14:48:03.512563Z","shell.execute_reply.started":"2022-06-05T14:48:01.415829Z","shell.execute_reply":"2022-06-05T14:48:03.511864Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def pad_image(img):\n    w, h, c = np.shape(img)\n    if w > h:\n        pad = int((w - h) / 2)\n        img = cv2.copyMakeBorder(img, 0, 0, pad, pad, cv2.BORDER_CONSTANT, value=0)\n    else:\n        pad = int((h - w) / 2)\n        img = cv2.copyMakeBorder(img, pad, pad, 0, 0, cv2.BORDER_CONSTANT, value=0)\n        \n    return img\n\n\ndef open_and_preprocess_image(image_path):\n    img = cv2.imread(image_path)\n    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n    img = pad_image(img)\n    return cv2.resize(img, (IMG_SIZE, IMG_SIZE))","metadata":{"execution":{"iopub.status.busy":"2022-06-05T14:48:03.514577Z","iopub.execute_input":"2022-06-05T14:48:03.514762Z","iopub.status.idle":"2022-06-05T14:48:03.524839Z","shell.execute_reply.started":"2022-06-05T14:48:03.514738Z","shell.execute_reply":"2022-06-05T14:48:03.524075Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class HotelImageDataset:\n    def __init__(self, data, transform=None, data_folder=\"train_images/\"):\n        self.data = data\n        self.data_folder = data_folder\n        self.transform = transform\n\n    def __len__(self):\n        return len(self.data)\n    \n    def __getitem__(self, idx):\n        record = self.data.iloc[idx]\n        image_path = self.data_folder + record[\"image_id\"]\n        \n        image = np.array(open_and_preprocess_image(image_path)).astype(np.uint8)\n\n        if self.transform:\n            transformed = self.transform(image=image)\n            image = transformed[\"image\"]\n        \n        return {\n            \"image\" : image,\n        }","metadata":{"executionInfo":{"elapsed":1058,"status":"ok","timestamp":1619310984077,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"found-mouth","papermill":{"duration":0.037507,"end_time":"2022-03-24T14:01:01.914352","exception":false,"start_time":"2022-03-24T14:01:01.876845","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:03.527092Z","iopub.execute_input":"2022-06-05T14:48:03.527571Z","iopub.status.idle":"2022-06-05T14:48:03.535348Z","shell.execute_reply.started":"2022-06-05T14:48:03.527534Z","shell.execute_reply":"2022-06-05T14:48:03.534307Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Model","metadata":{"id":"NMDM4PwPnced","papermill":{"duration":0.023902,"end_time":"2022-03-24T14:01:01.962307","exception":false,"start_time":"2022-03-24T14:01:01.938405","status":"completed"},"tags":[]}},{"cell_type":"code","source":"class HotelIdModel(nn.Module):\n    def __init__(self, n_classes=100, backbone_name=\"efficientnet_b0\"):\n        super(HotelIdModel, self).__init__()\n        \n        self.backbone = timm.create_model(backbone_name, num_classes=n_classes, pretrained=False)\n\n    def forward(self, x):\n        return self.backbone(x)","metadata":{"papermill":{"duration":0.032166,"end_time":"2022-03-24T14:01:02.018479","exception":false,"start_time":"2022-03-24T14:01:01.986313","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:03.536870Z","iopub.execute_input":"2022-06-05T14:48:03.537170Z","iopub.status.idle":"2022-06-05T14:48:03.545263Z","shell.execute_reply.started":"2022-06-05T14:48:03.537134Z","shell.execute_reply":"2022-06-05T14:48:03.544399Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Model helper functions","metadata":{"id":"YMZYKhUSneMY","papermill":{"duration":0.024153,"end_time":"2022-03-24T14:01:02.067537","exception":false,"start_time":"2022-03-24T14:01:02.043384","status":"completed"},"tags":[]}},{"cell_type":"code","source":"def predict(loader, model, n_matches=5):\n    preds = []\n    with torch.no_grad():\n        t = tqdm(loader)\n        for i, sample in enumerate(t):\n            input = sample['image'].to(args.device)\n            outputs = model(input)\n            outputs = torch.sigmoid(outputs).detach().cpu().numpy()\n            preds.extend(outputs)\n    \n    # get 5 top predictions\n    preds = np.argsort(-np.array(preds), axis=1)[:, :5]\n    return preds","metadata":{"papermill":{"duration":0.034692,"end_time":"2022-03-24T14:01:02.127372","exception":false,"start_time":"2022-03-24T14:01:02.09268","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:03.547100Z","iopub.execute_input":"2022-06-05T14:48:03.547344Z","iopub.status.idle":"2022-06-05T14:48:03.555083Z","shell.execute_reply.started":"2022-06-05T14:48:03.547321Z","shell.execute_reply":"2022-06-05T14:48:03.554239Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Prepare data","metadata":{"id":"AwShW1wXniD6","papermill":{"duration":0.023807,"end_time":"2022-03-24T14:01:02.175822","exception":false,"start_time":"2022-03-24T14:01:02.152015","status":"completed"},"tags":[]}},{"cell_type":"code","source":"test_df = pd.DataFrame(data={\"image_id\": os.listdir(TEST_DATA_FOLDER), \"hotel_id\": \"\"}).sort_values(by=\"image_id\")","metadata":{"executionInfo":{"elapsed":3742,"status":"ok","timestamp":1619311036476,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"discrete-right","outputId":"c21ed589-3139-4919-b5d5-07bcf6f1df15","papermill":{"duration":0.103381,"end_time":"2022-03-24T14:01:02.453866","exception":false,"start_time":"2022-03-24T14:01:02.350485","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:03.558789Z","iopub.execute_input":"2022-06-05T14:48:03.559113Z","iopub.status.idle":"2022-06-05T14:48:03.574074Z","shell.execute_reply.started":"2022-06-05T14:48:03.559075Z","shell.execute_reply":"2022-06-05T14:48:03.573391Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# code hotel_id mapping created in training notebook by encoding hotel_ids\nhotel_id_code_df = pd.read_csv('../input/hotel-id-starter-classification-traning/hotel_id_code_mapping.csv')\nhotel_id_code_map = hotel_id_code_df.set_index('hotel_id_code').to_dict()[\"hotel_id\"]","metadata":{"execution":{"iopub.status.busy":"2022-06-05T14:48:03.576134Z","iopub.execute_input":"2022-06-05T14:48:03.576573Z","iopub.status.idle":"2022-06-05T14:48:03.595527Z","shell.execute_reply.started":"2022-06-05T14:48:03.576537Z","shell.execute_reply":"2022-06-05T14:48:03.594939Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Prepare model","metadata":{"id":"5JPdD2bpnniP","papermill":{"duration":0.023835,"end_time":"2022-03-24T14:01:02.502786","exception":false,"start_time":"2022-03-24T14:01:02.478951","status":"completed"},"tags":[]}},{"cell_type":"code","source":"def get_model(model_type, backbone_name, checkpoint_path, args):\n    model = HotelIdModel(args.n_classes, backbone_name)\n        \n    checkpoint = torch.load(checkpoint_path)\n    model.load_state_dict(checkpoint[\"model\"])\n    model = model.to(args.device)\n    \n    return model","metadata":{"papermill":{"duration":0.031082,"end_time":"2022-03-24T14:01:02.557921","exception":false,"start_time":"2022-03-24T14:01:02.526839","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:03.598090Z","iopub.execute_input":"2022-06-05T14:48:03.598268Z","iopub.status.idle":"2022-06-05T14:48:03.602461Z","shell.execute_reply.started":"2022-06-05T14:48:03.598245Z","shell.execute_reply":"2022-06-05T14:48:03.601645Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class args:\n    batch_size = 64\n    num_workers = 2\n    n_classes = hotel_id_code_df[\"hotel_id\"].nunique()\n    device = ('cuda' if torch.cuda.is_available() else 'cpu')\n    \n    \nseed_everything(seed=SEED)\n\ntest_dataset = HotelImageDataset(test_df, base_transform, data_folder=TEST_DATA_FOLDER)\ntest_loader = DataLoader(test_dataset, num_workers=args.num_workers, batch_size=args.batch_size, shuffle=False)","metadata":{"executionInfo":{"elapsed":450,"status":"ok","timestamp":1619311064188,"user":{"displayName":"Jeom Jin-Ho","photoUrl":"","userId":"00155613517919499503"},"user_tz":-120},"id":"appointed-machinery","papermill":{"duration":0.069839,"end_time":"2022-03-24T14:01:02.65177","exception":false,"start_time":"2022-03-24T14:01:02.581931","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:03.603699Z","iopub.execute_input":"2022-06-05T14:48:03.604228Z","iopub.status.idle":"2022-06-05T14:48:03.704659Z","shell.execute_reply.started":"2022-06-05T14:48:03.604188Z","shell.execute_reply":"2022-06-05T14:48:03.703815Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model = get_model(\"classification\", \"resnet18\",\n                  \"../input/resnet64256/checkpoint-classification-model-resnet18-256x256 (2).pt\", \n                  args)","metadata":{"papermill":{"duration":5.553999,"end_time":"2022-03-24T14:01:08.229948","exception":false,"start_time":"2022-03-24T14:01:02.675949","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T14:48:03.706347Z","iopub.execute_input":"2022-06-05T14:48:03.706807Z","iopub.status.idle":"2022-06-05T14:48:08.924429Z","shell.execute_reply.started":"2022-06-05T14:48:03.706768Z","shell.execute_reply":"2022-06-05T14:48:08.923665Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model2 = get_model(\"classification\", \"efficientnet_b1\",\n                  \"../input/effb132256/checkpoint-classification-model-efficientnet_b1-256x256.pt\", \n                  args)","metadata":{"execution":{"iopub.status.busy":"2022-06-05T14:48:08.926394Z","iopub.execute_input":"2022-06-05T14:48:08.926804Z","iopub.status.idle":"2022-06-05T14:48:10.374892Z","shell.execute_reply.started":"2022-06-05T14:48:08.926766Z","shell.execute_reply":"2022-06-05T14:48:10.374124Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model3 = get_model(\"classification\", \"efficientnet_b0\",\n                  \"../input/effb032256/checkpoint-classification-model-efficientnet_b0-256x256 (3).pt\", \n                  args)","metadata":{"execution":{"iopub.status.busy":"2022-06-05T15:01:10.847710Z","iopub.execute_input":"2022-06-05T15:01:10.848350Z","iopub.status.idle":"2022-06-05T15:01:13.011134Z","shell.execute_reply.started":"2022-06-05T15:01:10.848312Z","shell.execute_reply":"2022-06-05T15:01:13.010420Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def predict1(loader, model1, model2, model3, n_matches=5):\n    preds = []\n    with torch.no_grad():\n        t = tqdm(loader)\n        for i, sample in enumerate(t):\n            input = sample['image'].to(args.device)\n            outputs1 = model1(input)\n            outputs1 = torch.sigmoid(outputs1).detach().cpu().numpy()\n            outputs2 = model2(input)\n            outputs2 = torch.sigmoid(outputs2).detach().cpu().numpy()\n            outputs3 = model2(input)\n            outputs3 = torch.sigmoid(outputs3).detach().cpu().numpy()\n            outputs=outputs1+outputs2+outputs3\n            \n            preds.extend(outputs)\n    \n    # get 5 top predictions\n    preds = np.argsort(-np.array(preds), axis=1)[:, :5]\n    return preds","metadata":{"execution":{"iopub.status.busy":"2022-06-05T15:01:43.363732Z","iopub.execute_input":"2022-06-05T15:01:43.364015Z","iopub.status.idle":"2022-06-05T15:01:43.371921Z","shell.execute_reply.started":"2022-06-05T15:01:43.363986Z","shell.execute_reply":"2022-06-05T15:01:43.370921Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"preds = predict1(test_loader, model, model2, model3)","metadata":{"execution":{"iopub.status.busy":"2022-06-05T15:01:50.061564Z","iopub.execute_input":"2022-06-05T15:01:50.061813Z","iopub.status.idle":"2022-06-05T15:01:50.316410Z","shell.execute_reply.started":"2022-06-05T15:01:50.061786Z","shell.execute_reply":"2022-06-05T15:01:50.315059Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"preds","metadata":{"execution":{"iopub.status.busy":"2022-06-05T15:01:52.709552Z","iopub.execute_input":"2022-06-05T15:01:52.710286Z","iopub.status.idle":"2022-06-05T15:01:52.719234Z","shell.execute_reply.started":"2022-06-05T15:01:52.710249Z","shell.execute_reply":"2022-06-05T15:01:52.718314Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Submission","metadata":{"papermill":{"duration":0.024227,"end_time":"2022-03-24T14:01:08.278753","exception":false,"start_time":"2022-03-24T14:01:08.254526","status":"completed"},"tags":[]}},{"cell_type":"code","source":"%%time\n\n#preds = predict(test_loader, model)\n# replace classes with hotel_id using mapping created in trainig notebook\npreds = [[hotel_id_code_map[b] for b in a] for a in preds]\n# transform array of hotel_ids into string\ntest_df[\"hotel_id\"] = [str(list(l)).strip(\"[]\").replace(\",\", \"\") for l in preds]\n\ntest_df.to_csv(\"submission.csv\", index=False)\ntest_df.head()","metadata":{"papermill":{"duration":0.047156,"end_time":"2022-03-24T14:01:08.414557","exception":false,"start_time":"2022-03-24T14:01:08.367401","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-06-05T15:02:05.549121Z","iopub.execute_input":"2022-06-05T15:02:05.549392Z","iopub.status.idle":"2022-06-05T15:02:05.564754Z","shell.execute_reply.started":"2022-06-05T15:02:05.549341Z","shell.execute_reply":"2022-06-05T15:02:05.564068Z"},"trusted":true},"execution_count":null,"outputs":[]}]}