{"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":"# About this notebook\n- PyTorch Resnet + LSTM with attention starter code\n- Preprocess notebook is [here](https://www.kaggle.com/yasufuminakama/inchi-preprocess-2)\n- Inference notebook is [here](https://www.kaggle.com/yasufuminakama/inchi-resnet-lstm-with-attention-inference)\n\nIf this notebook is helpful, feel free to upvote :)\n\n# References\n- https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning\n- https://github.com/dacon-ai/LG_SMILES_3rd\n- https://www.kaggle.com/kaushal2896/bms-mt-show-attend-and-tell-pytorch-baseline\n![%E3%82%B9%E3%82%AF%E3%83%AA%E3%83%BC%E3%83%B3%E3%82%B7%E3%83%A7%E3%83%83%E3%83%88%202021-03-13%202.27.05.png](attachment:%E3%82%B9%E3%82%AF%E3%83%AA%E3%83%BC%E3%83%B3%E3%82%B7%E3%83%A7%E3%83%83%E3%83%88%202021-03-13%202.27.05.png) (Figure from https://arxiv.org/pdf/1502.03044.pdf)","metadata":{"_kg_hide-input":true},"attachments":{"%E3%82%B9%E3%82%AF%E3%83%AA%E3%83%BC%E3%83%B3%E3%82%B7%E3%83%A7%E3%83%83%E3%83%88%202021-03-13%202.27.05.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"# Directory settings","metadata":{"papermill":{"duration":0.014737,"end_time":"2021-03-09T09:44:33.475921","exception":false,"start_time":"2021-03-09T09:44:33.461184","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# ====================================================\n# Directory settings\n# ====================================================\nimport os\n\nOUTPUT_DIR = './'\nif not os.path.exists(OUTPUT_DIR):\n    os.makedirs(OUTPUT_DIR)","metadata":{"papermill":{"duration":0.022561,"end_time":"2021-03-09T09:44:33.513503","exception":false,"start_time":"2021-03-09T09:44:33.490942","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:18.388375Z","iopub.execute_input":"2022-11-15T09:31:18.38946Z","iopub.status.idle":"2022-11-15T09:31:18.415582Z","shell.execute_reply.started":"2022-11-15T09:31:18.389345Z","shell.execute_reply":"2022-11-15T09:31:18.414657Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Data Loading","metadata":{"papermill":{"duration":0.015133,"end_time":"2021-03-09T09:44:33.543804","exception":false,"start_time":"2021-03-09T09:44:33.528671","status":"completed"},"tags":[]}},{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport torch\ntrain = pd.read_pickle('../input/molecular-preprocessed/train2.pkl')\n\ndef get_train_file_path(image_id):\n    return \"../input/bms-molecular-translation/train/{}/{}/{}/{}.png\".format(\n        image_id[0], image_id[1], image_id[2], image_id \n    )\n\ntrain['file_path'] = train['image_id'].apply(get_train_file_path)\n\nprint(f'train.shape: {train.shape}')\ndisplay(train.head())","metadata":{"papermill":{"duration":13.620951,"end_time":"2021-03-09T09:44:47.179832","exception":false,"start_time":"2021-03-09T09:44:33.558881","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:18.417453Z","iopub.execute_input":"2022-11-15T09:31:18.41791Z","iopub.status.idle":"2022-11-15T09:31:32.541132Z","shell.execute_reply.started":"2022-11-15T09:31:18.417871Z","shell.execute_reply":"2022-11-15T09:31:32.540052Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# print(image_id[0], image_id[1], image_id[2], image_id)","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class Tokenizer(object):\n    \n    def __init__(self):\n        self.stoi = {}\n        self.itos = {}\n\n    def __len__(self):\n        return len(self.stoi)\n    \n    def fit_on_texts(self, texts):\n        vocab = set()\n        for text in texts:\n            vocab.update(text.split(' '))\n        vocab = sorted(vocab)\n        vocab.append('<sos>')\n        vocab.append('<eos>')\n        vocab.append('<pad>')\n        for i, s in enumerate(vocab):\n            self.stoi[s] = i\n        self.itos = {item[1]: item[0] for item in self.stoi.items()}\n        \n    def text_to_sequence(self, text):\n        sequence = []\n        sequence.append(self.stoi['<sos>'])\n        for s in text.split(' '):\n            sequence.append(self.stoi[s])\n        sequence.append(self.stoi['<eos>'])\n        return sequence\n    \n    def texts_to_sequences(self, texts):\n        sequences = []\n        for text in texts:\n            sequence = self.text_to_sequence(text)\n            sequences.append(sequence)\n        return sequences\n\n    def sequence_to_text(self, sequence):\n        return ''.join(list(map(lambda i: self.itos[i], sequence)))\n    \n    def sequences_to_texts(self, sequences):\n        texts = []\n        for sequence in sequences:\n            text = self.sequence_to_text(sequence)\n            texts.append(text)\n        return texts\n    \n    def predict_caption(self, sequence):\n        caption = ''\n        for i in sequence:\n            if i == self.stoi['<eos>'] or i == self.stoi['<pad>']:\n                break\n            caption += self.itos[i]\n        return caption\n    \n    def predict_captions(self, sequences):\n        captions = []\n        for sequence in sequences:\n            caption = self.predict_caption(sequence)\n            captions.append(caption)\n        return captions\n\ntokenizer = torch.load('../input/molecular-preprocessed/tokenizer2.pth')\nprint(f\"tokenizer.stoi: {tokenizer.stoi}\")","metadata":{"papermill":{"duration":0.040687,"end_time":"2021-03-09T09:44:47.238213","exception":false,"start_time":"2021-03-09T09:44:47.197526","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:32.542721Z","iopub.execute_input":"2022-11-15T09:31:32.544746Z","iopub.status.idle":"2022-11-15T09:31:32.576234Z","shell.execute_reply.started":"2022-11-15T09:31:32.544703Z","shell.execute_reply":"2022-11-15T09:31:32.575373Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train['InChI_length'].max()","metadata":{"execution":{"iopub.status.busy":"2022-11-15T09:31:32.577902Z","iopub.execute_input":"2022-11-15T09:31:32.578183Z","iopub.status.idle":"2022-11-15T09:31:32.588222Z","shell.execute_reply.started":"2022-11-15T09:31:32.578157Z","shell.execute_reply":"2022-11-15T09:31:32.587004Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# CFG","metadata":{"papermill":{"duration":0.016241,"end_time":"2021-03-09T09:44:47.271137","exception":false,"start_time":"2021-03-09T09:44:47.254896","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# ====================================================\n# CFG\n# ====================================================\nclass CFG:\n    debug=False\n    max_len=275\n    print_freq=1000\n    num_workers=4\n    model_name='resnet34'\n    layers=34\n    size=224\n    scheduler='CosineAnnealingLR' # ['CosineAnnealingLR'，ReduceLROnPlateau', 'CosineAnnealingLR', 'CosineAnnealingWarmRestarts']\n    epochs=20# not to exceed 9h\n    factor=0.2 # ReduceLROnPlateau\n    patience=4 # ReduceLROnPlateau\n    eps=1e-6 # ReduceLROnPlateau\n    T_max=4 # CosineAnnealingLR\n    #T_0=4 # CosineAnnealingWarmRestarts\n    encoder_lr=1e-4\n    decoder_lr=4e-4\n    min_lr=1e-4\n    batch_size=64\n    weight_decay=1e-6\n    gradient_accumulation_steps=1\n    max_grad_norm=5\n    attention_dim=256\n    embed_dim=256\n    decoder_dim=512\n    dropout=0.5\n    seed=42\n    n_fold=5\n    trn_fold=[0] # [0, 1, 2, 3, 4]\n    train=True","metadata":{"papermill":{"duration":0.027167,"end_time":"2021-03-09T09:44:47.315067","exception":false,"start_time":"2021-03-09T09:44:47.2879","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:32.589929Z","iopub.execute_input":"2022-11-15T09:31:32.59061Z","iopub.status.idle":"2022-11-15T09:31:32.598232Z","shell.execute_reply.started":"2022-11-15T09:31:32.59057Z","shell.execute_reply":"2022-11-15T09:31:32.59728Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"if CFG.debug:\n    CFG.epochs = 1\n    train = train.sample(n=10000, random_state=CFG.seed).reset_index(drop=True)","metadata":{"papermill":{"duration":1.223567,"end_time":"2021-03-09T09:44:48.555526","exception":false,"start_time":"2021-03-09T09:44:47.331959","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:32.599688Z","iopub.execute_input":"2022-11-15T09:31:32.600085Z","iopub.status.idle":"2022-11-15T09:31:32.611089Z","shell.execute_reply.started":"2022-11-15T09:31:32.600047Z","shell.execute_reply":"2022-11-15T09:31:32.609943Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Library","metadata":{"papermill":{"duration":0.016658,"end_time":"2021-03-09T09:44:48.589756","exception":false,"start_time":"2021-03-09T09:44:48.573098","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# ====================================================\n# Library\n# ====================================================\nimport sys\nsys.path.append('../input/pytorch-image-models/pytorch-image-models-master')\n\nimport os\nimport gc\nimport re\nimport math\nimport time\nimport random\nimport shutil\nimport pickle\nfrom pathlib import Path\nfrom contextlib import contextmanager\nfrom collections import defaultdict, Counter\n\nimport scipy as sp\nimport numpy as np\nimport pandas as pd\nfrom tqdm.auto import tqdm\n\nimport Levenshtein\nfrom sklearn import preprocessing\nfrom sklearn.model_selection import StratifiedKFold, GroupKFold, KFold\n\nfrom functools import partial\n\nimport cv2\nfrom PIL import Image\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.optim import Adam, SGD\nimport torchvision.models as models\nfrom torch.nn.parameter import Parameter\nfrom torch.utils.data import DataLoader, Dataset\nfrom torch.nn.utils.rnn import pad_sequence, pack_padded_sequence\nfrom torch.optim.lr_scheduler import CosineAnnealingWarmRestarts, CosineAnnealingLR, ReduceLROnPlateau\n\nfrom albumentations import (\n    Compose, OneOf, Normalize, Resize, RandomResizedCrop, RandomCrop, HorizontalFlip, VerticalFlip, \n    RandomBrightness, RandomContrast, RandomBrightnessContrast, Rotate, ShiftScaleRotate, Cutout, \n    IAAAdditiveGaussianNoise, Transpose, Blur\n    )\nfrom albumentations.pytorch import ToTensorV2\nfrom albumentations import ImageOnlyTransform\n\nimport timm\n\nimport warnings \nwarnings.filterwarnings('ignore')\n\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')","metadata":{"papermill":{"duration":3.23384,"end_time":"2021-03-09T09:44:51.840158","exception":false,"start_time":"2021-03-09T09:44:48.606318","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:32.614223Z","iopub.execute_input":"2022-11-15T09:31:32.614541Z","iopub.status.idle":"2022-11-15T09:31:36.700605Z","shell.execute_reply.started":"2022-11-15T09:31:32.614516Z","shell.execute_reply":"2022-11-15T09:31:36.699295Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Utils","metadata":{"papermill":{"duration":0.01895,"end_time":"2021-03-09T09:44:51.878779","exception":false,"start_time":"2021-03-09T09:44:51.859829","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# ====================================================\n# Utils\n# ====================================================\ndef get_score(y_true, y_pred):\n    scores = []\n    for true, pred in zip(y_true, y_pred):\n        score = Levenshtein.distance(true, pred)\n        scores.append(score)\n    avg_score = np.mean(scores)\n    return avg_score\n\ndef longestCommonSubsequence(text1: str, text2: str) -> int:\n    m, n = len(text1), len(text2)\n    dp = [[0] * (n + 1) for _ in range(m + 1)]\n\n    for i in range(1, m + 1):\n        for j in range(1, n + 1):\n            if text1[i - 1] == text2[j - 1]:\n                dp[i][j] = dp[i - 1][j - 1] + 1\n            else:\n                dp[i][j] = max(dp[i - 1][j], dp[i][j - 1])\n\n    return dp[m][n]\n\n\ndef get_lcs(y_true, y_pred):\n    lcss = []\n    for true, pred in zip(y_true, y_pred):\n        lcs = longestCommonSubsequence(true, pred)\n        lcss.append(lcs/len(true))\n    avg_lcs = np.mean(lcss)\n    return avg_lcs \n\ndef getCER(y_true, y_pred):\n    cers = []\n    for true, pred in zip(y_true, y_pred):\n        score = Levenshtein.distance(true, pred)\n        cer = float(score / len(true))\n        cers.append(cer)\n    return np.mean(cers)\n\ndef init_logger(log_file=OUTPUT_DIR+'train.log'):\n    from logging import getLogger, INFO, FileHandler,  Formatter,  StreamHandler\n    logger = getLogger(__name__)\n    logger.setLevel(INFO)\n    handler1 = StreamHandler()\n    handler1.setFormatter(Formatter(\"%(message)s\"))\n    handler2 = FileHandler(filename=log_file)\n    handler2.setFormatter(Formatter(\"%(message)s\"))\n    logger.addHandler(handler1)\n    logger.addHandler(handler2)\n    return logger\n\nLOGGER = init_logger()\n\n\ndef seed_torch(seed=42):\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\n\nseed_torch(seed=CFG.seed)","metadata":{"papermill":{"duration":0.037035,"end_time":"2021-03-09T09:44:51.934525","exception":false,"start_time":"2021-03-09T09:44:51.89749","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:36.704566Z","iopub.execute_input":"2022-11-15T09:31:36.704923Z","iopub.status.idle":"2022-11-15T09:31:36.725404Z","shell.execute_reply.started":"2022-11-15T09:31:36.704889Z","shell.execute_reply":"2022-11-15T09:31:36.7245Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# CV split","metadata":{"papermill":{"duration":0.019365,"end_time":"2021-03-09T09:44:51.973096","exception":false,"start_time":"2021-03-09T09:44:51.953731","status":"completed"},"tags":[]}},{"cell_type":"code","source":"folds = train.copy()\nFold = StratifiedKFold(n_splits=CFG.n_fold, shuffle=True, random_state=CFG.seed)\nfor n, (train_index, val_index) in enumerate(Fold.split(folds, folds['InChI_length'])):\n    folds.loc[val_index, 'fold'] = int(n)\nfolds['fold'] = folds['fold'].astype(int)\nprint(folds.groupby(['fold']).size())","metadata":{"papermill":{"duration":0.063587,"end_time":"2021-03-09T09:44:52.056037","exception":false,"start_time":"2021-03-09T09:44:51.99245","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:36.729389Z","iopub.execute_input":"2022-11-15T09:31:36.729697Z","iopub.status.idle":"2022-11-15T09:31:39.664025Z","shell.execute_reply.started":"2022-11-15T09:31:36.729672Z","shell.execute_reply":"2022-11-15T09:31:39.662823Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Dataset","metadata":{"papermill":{"duration":0.018688,"end_time":"2021-03-09T09:44:52.093619","exception":false,"start_time":"2021-03-09T09:44:52.074931","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# ====================================================\n# Dataset\n# ====================================================\nclass TrainDataset(Dataset):\n    def __init__(self, df, tokenizer, transform=None):\n        super().__init__()\n        self.df = df\n        self.tokenizer = tokenizer\n        self.file_paths = df['file_path'].values\n        self.labels = df['InChI_text'].values\n        self.transform = transform\n    \n    def __len__(self):\n        return len(self.df)\n    \n    def __getitem__(self, idx):\n        file_path = self.file_paths[idx]\n        image = cv2.imread(file_path)\n        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB).astype(np.float32)\n        if self.transform:\n            augmented = self.transform(image=image)\n            image = augmented['image']\n        label = self.labels[idx]\n        label = self.tokenizer.text_to_sequence(label)\n        label_length = len(label)\n        label_length = torch.LongTensor([label_length])\n        return image, torch.LongTensor(label), label_length\n    \n\nclass TestDataset(Dataset):\n    def __init__(self, df, transform=None):\n        super().__init__()\n        self.df = df\n        self.file_paths = df['file_path'].values\n        self.transform = transform\n    \n    def __len__(self):\n        return len(self.df)\n    \n    def __getitem__(self, idx):\n        file_path = self.file_paths[idx]\n        image = cv2.imread(file_path)\n        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB).astype(np.float32)\n        if self.transform:\n            augmented = self.transform(image=image)\n            image = augmented['image']\n        return image","metadata":{"papermill":{"duration":0.032248,"end_time":"2021-03-09T09:44:52.144808","exception":false,"start_time":"2021-03-09T09:44:52.11256","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:39.666193Z","iopub.execute_input":"2022-11-15T09:31:39.666822Z","iopub.status.idle":"2022-11-15T09:31:39.678748Z","shell.execute_reply.started":"2022-11-15T09:31:39.666783Z","shell.execute_reply":"2022-11-15T09:31:39.677691Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def bms_collate(batch):\n    imgs, labels, label_lengths = [], [], []\n    for data_point in batch:\n        imgs.append(data_point[0])\n        labels.append(data_point[1])\n        label_lengths.append(data_point[2])\n    labels = pad_sequence(labels, batch_first=True, padding_value=tokenizer.stoi[\"<pad>\"])\n    return torch.stack(imgs), labels, torch.stack(label_lengths).reshape(-1, 1)","metadata":{"papermill":{"duration":0.02994,"end_time":"2021-03-09T09:44:52.194849","exception":false,"start_time":"2021-03-09T09:44:52.164909","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:39.6813Z","iopub.execute_input":"2022-11-15T09:31:39.682005Z","iopub.status.idle":"2022-11-15T09:31:39.689261Z","shell.execute_reply.started":"2022-11-15T09:31:39.681968Z","shell.execute_reply":"2022-11-15T09:31:39.688257Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Transforms","metadata":{"papermill":{"duration":0.021319,"end_time":"2021-03-09T09:44:52.239264","exception":false,"start_time":"2021-03-09T09:44:52.217945","status":"completed"},"tags":[]}},{"cell_type":"code","source":"def get_transforms(*, data):\n    \n    if data == 'train':\n        return Compose([\n            Resize(CFG.size, CFG.size),\n            Normalize(\n                mean=[0.485, 0.456, 0.406],\n                std=[0.229, 0.224, 0.225],\n            ),\n            ToTensorV2(),\n        ])\n    \n    elif data == 'valid':\n        return Compose([\n            Resize(CFG.size, CFG.size),\n            Normalize(\n                mean=[0.485, 0.456, 0.406],\n                std=[0.229, 0.224, 0.225],\n            ),\n            ToTensorV2(),\n        ])\n","metadata":{"papermill":{"duration":0.032726,"end_time":"2021-03-09T09:44:52.293401","exception":false,"start_time":"2021-03-09T09:44:52.260675","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:39.690739Z","iopub.execute_input":"2022-11-15T09:31:39.691232Z","iopub.status.idle":"2022-11-15T09:31:39.702829Z","shell.execute_reply.started":"2022-11-15T09:31:39.691192Z","shell.execute_reply":"2022-11-15T09:31:39.701874Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from matplotlib import pyplot as plt\n\ntrain_dataset = TrainDataset(train, tokenizer, transform=get_transforms(data='train'))\n\nfor i in range(1):\n    image, label, label_length = train_dataset[i]\n    text = tokenizer.sequence_to_text(label.numpy())\n    plt.imshow(image.transpose(0, 1).transpose(1, 2))\n    plt.title(f'label: {label}  text: {text}  label_length: {label_length}')\n    plt.show() ","metadata":{"papermill":{"duration":0.358665,"end_time":"2021-03-09T09:44:52.673441","exception":false,"start_time":"2021-03-09T09:44:52.314776","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:39.704116Z","iopub.execute_input":"2022-11-15T09:31:39.704545Z","iopub.status.idle":"2022-11-15T09:31:40.051088Z","shell.execute_reply.started":"2022-11-15T09:31:39.704509Z","shell.execute_reply":"2022-11-15T09:31:40.050069Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# MODEL","metadata":{"papermill":{"duration":0.022092,"end_time":"2021-03-09T09:44:52.71725","exception":false,"start_time":"2021-03-09T09:44:52.695158","status":"completed"},"tags":[]}},{"cell_type":"code","source":"class Encoder(nn.Module):\n    def __init__(self, model_name='resnet18', pretrained=False):\n        super().__init__()\n        self.cnn = timm.create_model(model_name, pretrained=pretrained)\n        self.n_features = self.cnn.fc.in_features\n        self.cnn.global_pool = nn.Identity()\n        self.cnn.fc = nn.Identity()\n\n    def forward(self, x):\n        bs = x.size(0)\n        features = self.cnn(x)\n        features = features.permute(0, 2, 3, 1)\n        return features","metadata":{"papermill":{"duration":0.033392,"end_time":"2021-03-09T09:44:52.772345","exception":false,"start_time":"2021-03-09T09:44:52.738953","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:40.052785Z","iopub.execute_input":"2022-11-15T09:31:40.053184Z","iopub.status.idle":"2022-11-15T09:31:40.062175Z","shell.execute_reply.started":"2022-11-15T09:31:40.053146Z","shell.execute_reply":"2022-11-15T09:31:40.059034Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class Attention(nn.Module):\n    \"\"\"\n    Attention network for calculate attention value\n    \"\"\"\n    def __init__(self, encoder_dim, decoder_dim, attention_dim):\n        \"\"\"\n        :param encoder_dim: input size of encoder network\n        :param decoder_dim: input size of decoder network\n        :param attention_dim: input size of attention network\n        \"\"\"\n        super(Attention, self).__init__()\n        self.encoder_att = nn.Linear(encoder_dim, attention_dim)  # linear layer to transform encoded image\n        self.decoder_att = nn.Linear(decoder_dim, attention_dim)  # linear layer to transform decoder's output\n        self.full_att = nn.Linear(attention_dim, 1)  # linear layer to calculate values to be softmax-ed\n        self.relu = nn.ReLU()\n        self.softmax = nn.Softmax(dim=1)  # softmax layer to calculate weights\n\n    def forward(self, encoder_out, decoder_hidden):\n        att1 = self.encoder_att(encoder_out)  # (batch_size, num_pixels, attention_dim)\n        att2 = self.decoder_att(decoder_hidden)  # (batch_size, attention_dim)\n        att = self.full_att(self.relu(att1 + att2.unsqueeze(1))).squeeze(2)  # (batch_size, num_pixels)\n        alpha = self.softmax(att)  # (batch_size, num_pixels)\n        attention_weighted_encoding = (encoder_out * alpha.unsqueeze(2)).sum(dim=1)  # (batch_size, encoder_dim)\n        return attention_weighted_encoding, alpha\n\n\nclass DecoderWithAttention(nn.Module):\n    \"\"\"\n    Decoder network with attention network used for training\n    \"\"\"\n\n    def __init__(self, attention_dim, embed_dim, decoder_dim, vocab_size, device, encoder_dim=512, dropout=0.5):\n        \"\"\"\n        :param attention_dim: input size of attention network\n        :param embed_dim: input size of embedding network\n        :param decoder_dim: input size of decoder network\n        :param vocab_size: total number of characters used in training\n        :param encoder_dim: input size of encoder network\n        :param dropout: dropout rate\n        \"\"\"\n        super(DecoderWithAttention, self).__init__()\n        self.encoder_dim = encoder_dim\n        self.attention_dim = attention_dim\n        self.embed_dim = embed_dim\n        self.decoder_dim = decoder_dim\n        self.vocab_size = vocab_size\n        self.dropout = dropout\n        self.device = device\n        self.attention = Attention(encoder_dim, decoder_dim, attention_dim)  # attention network\n        self.embedding = nn.Embedding(vocab_size, embed_dim)  # embedding layer\n        self.dropout = nn.Dropout(p=self.dropout)\n        self.decode_step = nn.LSTMCell(embed_dim + encoder_dim, decoder_dim, bias=True)  # decoding LSTMCell\n        self.init_h = nn.Linear(encoder_dim, decoder_dim)  # linear layer to find initial hidden state of LSTMCell\n        self.init_c = nn.Linear(encoder_dim, decoder_dim)  # linear layer to find initial cell state of LSTMCell\n        self.f_beta = nn.Linear(decoder_dim, encoder_dim)  # linear layer to create a sigmoid-activated gate\n        self.sigmoid = nn.Sigmoid()\n        self.fc = nn.Linear(decoder_dim, vocab_size)  # linear layer to find scores over vocabulary\n        self.init_weights()  # initialize some layers with the uniform distribution\n\n    def init_weights(self):\n        self.embedding.weight.data.uniform_(-0.1, 0.1)\n        self.fc.bias.data.fill_(0)\n        self.fc.weight.data.uniform_(-0.1, 0.1)\n\n    def load_pretrained_embeddings(self, embeddings):\n        self.embedding.weight = nn.Parameter(embeddings)\n\n    def fine_tune_embeddings(self, fine_tune=True):\n        for p in self.embedding.parameters():\n            p.requires_grad = fine_tune\n\n    def init_hidden_state(self, encoder_out):\n        mean_encoder_out = encoder_out.mean(dim=1)\n        h = self.init_h(mean_encoder_out)  # (batch_size, decoder_dim)\n        c = self.init_c(mean_encoder_out)\n        return h, c\n\n    def forward(self, encoder_out, encoded_captions, caption_lengths):\n        \"\"\"\n        :param encoder_out: output of encoder network\n        :param encoded_captions: transformed sequence from character to integer\n        :param caption_lengths: length of transformed sequence\n        \"\"\"\n        batch_size = encoder_out.size(0)\n        encoder_dim = encoder_out.size(-1)\n        vocab_size = self.vocab_size\n        encoder_out = encoder_out.view(batch_size, -1, encoder_dim)  # (batch_size, num_pixels, encoder_dim)\n        num_pixels = encoder_out.size(1)\n        caption_lengths, sort_ind = caption_lengths.squeeze(1).sort(dim=0, descending=True)\n        encoder_out = encoder_out[sort_ind]\n        encoded_captions = encoded_captions[sort_ind]\n        # embedding transformed sequence for vector\n        embeddings = self.embedding(encoded_captions)  # (batch_size, max_caption_length, embed_dim)\n        # initialize hidden state and cell state of LSTM cell\n        h, c = self.init_hidden_state(encoder_out)  # (batch_size, decoder_dim)\n        # set decode length by caption length - 1 because of omitting start token\n        decode_lengths = (caption_lengths - 1).tolist()\n        predictions = torch.zeros(batch_size, max(decode_lengths), vocab_size).to(self.device)\n        alphas = torch.zeros(batch_size, max(decode_lengths), num_pixels).to(self.device)\n        # predict sequence\n        for t in range(max(decode_lengths)):\n            batch_size_t = sum([l > t for l in decode_lengths])\n            attention_weighted_encoding, alpha = self.attention(encoder_out[:batch_size_t], h[:batch_size_t])\n            gate = self.sigmoid(self.f_beta(h[:batch_size_t]))  # gating scalar, (batch_size_t, encoder_dim)\n            attention_weighted_encoding = gate * attention_weighted_encoding\n            h, c = self.decode_step(\n                torch.cat([embeddings[:batch_size_t, t, :], attention_weighted_encoding], dim=1),\n                (h[:batch_size_t], c[:batch_size_t]))  # (batch_size_t, decoder_dim)\n            preds = self.fc(self.dropout(h))  # (batch_size_t, vocab_size)\n            predictions[:batch_size_t, t, :] = preds\n            alphas[:batch_size_t, t, :] = alpha\n        return predictions, encoded_captions, decode_lengths, alphas, sort_ind\n    \n    def predict(self, encoder_out, decode_lengths, tokenizer):\n        batch_size = encoder_out.size(0)\n        encoder_dim = encoder_out.size(-1)\n        vocab_size = self.vocab_size\n        encoder_out = encoder_out.view(batch_size, -1, encoder_dim)  # (batch_size, num_pixels, encoder_dim)\n        num_pixels = encoder_out.size(1)\n        # embed start tocken for LSTM input\n        start_tockens = torch.ones(batch_size, dtype=torch.long).to(self.device) * tokenizer.stoi[\"<sos>\"]\n        embeddings = self.embedding(start_tockens)\n        # initialize hidden state and cell state of LSTM cell\n        h, c = self.init_hidden_state(encoder_out)  # (batch_size, decoder_dim)\n        predictions = torch.zeros(batch_size, decode_lengths, vocab_size).to(self.device)\n        # predict sequence\n        for t in range(decode_lengths):\n            attention_weighted_encoding, alpha = self.attention(encoder_out, h)\n            gate = self.sigmoid(self.f_beta(h))  # gating scalar, (batch_size_t, encoder_dim)\n            attention_weighted_encoding = gate * attention_weighted_encoding\n            h, c = self.decode_step(\n                torch.cat([embeddings, attention_weighted_encoding], dim=1),\n                (h, c))  # (batch_size_t, decoder_dim)\n            preds = self.fc(self.dropout(h))  # (batch_size_t, vocab_size)\n            predictions[:, t, :] = preds\n            if np.argmax(preds.detach().cpu().numpy()) == tokenizer.stoi[\"<eos>\"]:\n                break\n            embeddings = self.embedding(torch.argmax(preds, -1))\n        return predictions","metadata":{"papermill":{"duration":0.049082,"end_time":"2021-03-09T09:44:52.843864","exception":false,"start_time":"2021-03-09T09:44:52.794782","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:40.064498Z","iopub.execute_input":"2022-11-15T09:31:40.065019Z","iopub.status.idle":"2022-11-15T09:31:40.092713Z","shell.execute_reply.started":"2022-11-15T09:31:40.064842Z","shell.execute_reply":"2022-11-15T09:31:40.091637Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Helper functions","metadata":{"papermill":{"duration":0.020597,"end_time":"2021-03-09T09:44:58.570358","exception":false,"start_time":"2021-03-09T09:44:58.549761","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# ====================================================\n# Helper functions\n# ====================================================\nclass AverageMeter(object):\n    \"\"\"Computes and stores the average and current value\"\"\"\n    def __init__(self):\n        self.reset()\n\n    def reset(self):\n        self.val = 0\n        self.avg = 0\n        self.sum = 0\n        self.count = 0\n\n    def update(self, val, n=1):\n        self.val = val\n        self.sum += val * n\n        self.count += n\n        self.avg = self.sum / self.count\n\n\ndef asMinutes(s):\n    m = math.floor(s / 60)\n    s -= m * 60\n    return '%dm %ds' % (m, s)\n\n\ndef timeSince(since, percent):\n    now = time.time()\n    s = now - since\n    es = s / (percent)\n    rs = es - s\n    return '%s (remain %s)' % (asMinutes(s), asMinutes(rs))\n\n\ndef train_fn(train_loader, encoder, decoder, criterion, \n             encoder_optimizer, decoder_optimizer, epoch,\n             encoder_scheduler, decoder_scheduler, device):\n    batch_time = AverageMeter()\n    data_time = AverageMeter()\n    losses = AverageMeter()\n    # switch to train mode\n    encoder.train()\n    decoder.train()\n    start = end = time.time()\n    global_step = 0\n    for step, (images, labels, label_lengths) in enumerate(train_loader):\n        # measure data loading time\n        data_time.update(time.time() - end)\n        images = images.to(device)\n        labels = labels.to(device)\n        label_lengths = label_lengths.to(device)\n        batch_size = images.size(0)\n        features = encoder(images)\n        predictions, caps_sorted, decode_lengths, alphas, sort_ind = decoder(features, labels, label_lengths)\n        targets = caps_sorted[:, 1:]\n        predictions = pack_padded_sequence(predictions, decode_lengths, batch_first=True).data\n        targets = pack_padded_sequence(targets, decode_lengths, batch_first=True).data\n        loss = criterion(predictions, targets)\n        # record loss\n        losses.update(loss.item(), batch_size)\n        if CFG.gradient_accumulation_steps > 1:\n            loss = loss / CFG.gradient_accumulation_steps\n        loss.backward()\n        encoder_grad_norm = torch.nn.utils.clip_grad_norm_(encoder.parameters(), CFG.max_grad_norm)\n        decoder_grad_norm = torch.nn.utils.clip_grad_norm_(decoder.parameters(), CFG.max_grad_norm)\n        if (step + 1) % CFG.gradient_accumulation_steps == 0:\n            encoder_optimizer.step()\n            decoder_optimizer.step()\n            encoder_optimizer.zero_grad()\n            decoder_optimizer.zero_grad()\n            global_step += 1\n        # measure elapsed time\n        batch_time.update(time.time() - end)\n        end = time.time()\n        if step % CFG.print_freq == 0 or step == (len(train_loader)-1):\n            print('Epoch: [{0}][{1}/{2}] '\n                  'Data {data_time.val:.3f} ({data_time.avg:.3f}) '\n                  'Elapsed {remain:s} '\n                  'Loss: {loss.val:.4f}({loss.avg:.4f}) '\n                  'Encoder Grad: {encoder_grad_norm:.4f}  '\n                  'Decoder Grad: {decoder_grad_norm:.4f}  '\n                  #'Encoder LR: {encoder_lr:.6f}  '\n                  #'Decoder LR: {decoder_lr:.6f}  '\n                  .format(\n                   epoch+1, step, len(train_loader), batch_time=batch_time,\n                   data_time=data_time, loss=losses,\n                   remain=timeSince(start, float(step+1)/len(train_loader)),\n                   encoder_grad_norm=encoder_grad_norm,\n                   decoder_grad_norm=decoder_grad_norm,\n                   #encoder_lr=encoder_scheduler.get_lr()[0],\n                   #decoder_lr=decoder_scheduler.get_lr()[0],\n                   ))\n    return losses.avg\n\n\ndef valid_fn(valid_loader, encoder, decoder, tokenizer, criterion, device):\n    batch_time = AverageMeter()\n    data_time = AverageMeter()\n    # switch to evaluation mode\n    encoder.eval()\n    decoder.eval()\n    text_preds = []\n    start = end = time.time()\n    for step, (images) in enumerate(valid_loader):\n        # measure data loading time\n        data_time.update(time.time() - end)\n        images = images.to(device)\n        batch_size = images.size(0)\n        with torch.no_grad():\n            features = encoder(images)\n            predictions = decoder.predict(features, CFG.max_len, tokenizer)\n        predicted_sequence = torch.argmax(predictions.detach().cpu(), -1).numpy()\n        _text_preds = tokenizer.predict_captions(predicted_sequence)\n        text_preds.append(_text_preds)\n        # measure elapsed time\n        batch_time.update(time.time() - end)\n        end = time.time()\n        if step % CFG.print_freq == 0 or step == (len(valid_loader)-1):\n            print('EVAL: [{0}/{1}] '\n                  'Data {data_time.val:.3f} ({data_time.avg:.3f}) '\n                  'Elapsed {remain:s} '\n                  .format(\n                   step, len(valid_loader), batch_time=batch_time,\n                   data_time=data_time,\n                   remain=timeSince(start, float(step+1)/len(valid_loader)),\n                   ))\n    text_preds = np.concatenate(text_preds)\n    return text_preds","metadata":{"papermill":{"duration":0.044148,"end_time":"2021-03-09T09:44:58.635121","exception":false,"start_time":"2021-03-09T09:44:58.590973","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T09:31:40.094632Z","iopub.execute_input":"2022-11-15T09:31:40.094982Z","iopub.status.idle":"2022-11-15T09:31:40.118583Z","shell.execute_reply.started":"2022-11-15T09:31:40.094948Z","shell.execute_reply":"2022-11-15T09:31:40.117674Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Train loop","metadata":{"papermill":{"duration":0.021011,"end_time":"2021-03-09T09:44:58.676694","exception":false,"start_time":"2021-03-09T09:44:58.655683","status":"completed"},"tags":[]}},{"cell_type":"code","source":"from torch.utils.data.sampler import Sampler\n\nclass FixNumSampler(Sampler):\n    \"\"\"验集和测试集采样\n    生成固定长度的采样\n    \"\"\"\n    def __init__(self, dataset, length=-1, is_shuffle=False):\n        if length<=0:\n            length=len(dataset)\n\n        self.is_shuffle = is_shuffle\n        self.length = length\n\n\n    def __iter__(self):\n        index = np.arange(self.length)\n        if self.is_shuffle: random.shuffle(index)\n        return iter(index)\n\n    def __len__(self):\n        return self.length","metadata":{"execution":{"iopub.status.busy":"2022-11-15T09:31:40.120937Z","iopub.execute_input":"2022-11-15T09:31:40.121291Z","iopub.status.idle":"2022-11-15T09:31:40.131505Z","shell.execute_reply.started":"2022-11-15T09:31:40.121252Z","shell.execute_reply":"2022-11-15T09:31:40.130441Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"### ====================================================\n# Train loop\n# ====================================================\ndef train_loop(folds, fold):\n    \n    start_epoch = 0\n    LOGGER.info(f\"start_epoch: {start_epoch}\")\n\n    LOGGER.info(f\"========== fold: {fold} training ==========\")\n\n    # ====================================================\n    # loader\n    # ====================================================\n    trn_idx = folds[folds['fold'] != fold].index\n    val_idx = folds[folds['fold'] == fold].index\n\n    train_folds = folds.loc[trn_idx].reset_index(drop=True)\n    valid_folds = folds.loc[val_idx].reset_index(drop=True)\n    valid_labels = valid_folds['InChI'].values\n\n    train_dataset = TrainDataset(train_folds, tokenizer, transform=get_transforms(data='train'))\n    valid_dataset = TestDataset(valid_folds, transform=get_transforms(data='valid'))\n\n    train_loader = DataLoader(train_dataset, \n                              sampler=FixNumSampler(train_dataset, 100000),\n                              batch_size=CFG.batch_size, \n                              shuffle=False, \n                              num_workers=CFG.num_workers, \n                              pin_memory=True,\n                              drop_last=True, \n                              collate_fn=bms_collate)\n    valid_loader = DataLoader(valid_dataset, \n                              sampler=FixNumSampler(valid_dataset, 20000),\n                              batch_size=CFG.batch_size, \n                              shuffle=False, \n                              num_workers=CFG.num_workers,\n                              pin_memory=True, \n                              drop_last=False)\n    \n    # ====================================================\n    # scheduler \n    # ====================================================\n    def get_scheduler(optimizer):\n        if CFG.scheduler=='ReduceLROnPlateau':\n            scheduler = ReduceLROnPlateau(optimizer, mode='min', factor=CFG.factor, patience=CFG.patience, verbose=True, eps=CFG.eps)\n        elif CFG.scheduler=='CosineAnnealingLR':\n            scheduler = CosineAnnealingLR(optimizer, T_max=CFG.T_max, eta_min=CFG.min_lr, last_epoch=-1)\n        elif CFG.scheduler=='CosineAnnealingWarmRestarts':\n            scheduler = CosineAnnealingWarmRestarts(optimizer, T_0=CFG.T_0, T_mult=1, eta_min=CFG.min_lr, last_epoch=-1)\n        return scheduler\n\n    # ====================================================\n    # model & optimizer\n    # ====================================================\n    encoder = Encoder(CFG.model_name, pretrained=True)\n    if start_epoch > 0: \n        states = torch.load('../input/calr-lr05-epochs20/resnet34_fold0_epoch35.pth', map_location=torch.device('cpu'))\n#         states = torch.load('../input/1103epoch14/resnet34_fold0_epoch14.pth', map_location=torch.device('cpu'))\n        LOGGER.info(f\"load state, epoch{start_epoch}\")\n        encoder.load_state_dict(states['encoder'])\n#     if start_epoch == 0: \n#         states = torch.load('../input/weight30/resnet34_fold0_epoch30.pth.pth', map_location=torch.device('cpu'))\n# #         states = torch.load('../input/1103epoch14/resnet34_fold0_epoch14.pth', map_location=torch.device('cpu'))\n#         LOGGER.info(f\"load state, epoch{start_epoch}\")\n#         encoder.load_state_dict(states['encoder'])\n    encoder.to(device)\n    encoder_optimizer = Adam(encoder.parameters(), lr=CFG.encoder_lr, weight_decay=CFG.weight_decay, amsgrad=False)\n    encoder_scheduler = get_scheduler(encoder_optimizer)\n    \n    decoder = DecoderWithAttention(attention_dim=CFG.attention_dim,\n                                   embed_dim=CFG.embed_dim,\n                                   decoder_dim=CFG.decoder_dim,\n                                   vocab_size=len(tokenizer),\n                                   dropout=CFG.dropout,\n                                   device=device)\n    if start_epoch > 0:\n        decoder.load_state_dict(states['decoder'])\n    decoder.to(device)\n    decoder_optimizer = Adam(decoder.parameters(), lr=CFG.decoder_lr, weight_decay=CFG.weight_decay, amsgrad=False)\n    decoder_scheduler = get_scheduler(decoder_optimizer)\n\n    # ====================================================\n    # loop\n    # ====================================================\n    criterion = nn.CrossEntropyLoss(ignore_index=tokenizer.stoi[\"<pad>\"])\n\n    best_score = np.inf\n    best_loss = np.inf\n    for epoch in range(CFG.epochs-start_epoch):\n        \n        epoch = epoch+start_epoch\n        \n        start_time = time.time()\n        \n        # train\n        avg_loss = train_fn(train_loader, encoder, decoder, criterion, \n                            encoder_optimizer, decoder_optimizer, epoch, \n                            encoder_scheduler, decoder_scheduler, device)\n        \n\n        # eval\n        text_preds = valid_fn(valid_loader, encoder, decoder, tokenizer, criterion, device)\n        text_preds = [f\"InChI=1S/{text}\" for text in text_preds]\n        LOGGER.info(f\"labels: {valid_labels[:5]}\")\n        LOGGER.info(f\"preds: {text_preds[:5]}\")\n        \n        # scoring\n        score = get_score(valid_labels, text_preds)\n        lcs = get_lcs(valid_labels, text_preds)\n        cer = getCER(valid_labels, text_preds)\n        \n        f_name = f\"nlayers{CFG.layers}_lr{CFG.min_lr}_batch{CFG.batch_size}_attdim{CFG.attention_dim}_dropout{CFG.dropout}_opti{CFG.scheduler}.csv\"\n        with open(file=f_name, mode=\"a\") as f:\n            f.write(f\"{epoch},{score:.4f},{lcs:.4f},{cer:.4f}\\n\")\n        \n        if isinstance(encoder_scheduler, ReduceLROnPlateau):\n            encoder_scheduler.step(score)\n        elif isinstance(encoder_scheduler, CosineAnnealingLR):\n            encoder_scheduler.step()\n        elif isinstance(encoder_scheduler, CosineAnnealingWarmRestarts):\n            encoder_scheduler.step()\n            \n        if isinstance(decoder_scheduler, ReduceLROnPlateau):\n            decoder_scheduler.step(score)\n        elif isinstance(decoder_scheduler, CosineAnnealingLR):\n            decoder_scheduler.step()\n        elif isinstance(decoder_scheduler, CosineAnnealingWarmRestarts):\n            decoder_scheduler.step()\n\n        elapsed = time.time() - start_time\n\n        LOGGER.info(f'Epoch {epoch+1} - avg_train_loss: {avg_loss:.4f}  time: {elapsed:.0f}s')\n        LOGGER.info(f'Epoch {epoch+1} - Score: {score:.4f} - LCS: {lcs:.4f} - CER: {cer:.4f}')\n         \n        torch.save({'encoder': encoder.state_dict(), \n                    'encoder_optimizer': encoder_optimizer.state_dict(), \n                    'encoder_scheduler': encoder_scheduler.state_dict(), \n                    'decoder': decoder.state_dict(), \n                    'decoder_optimizer': decoder_optimizer.state_dict(), \n                    'decoder_scheduler': decoder_scheduler.state_dict(), \n                    'text_preds': text_preds,\n                       },   \n                   OUTPUT_DIR+f'{CFG.model_name}_fold{fold}_epoch{epoch+1}.pth')\n                                \n                            \n                            \n#         torch.save({'encoder': encoder.state_dict(), \n#                     'encoder_optimizer': encoder_optimizer.state_dict(), \n#                     'encoder_scheduler': encoder_scheduler.state_dict(), \n#                     'decoder': decoder.state_dict(), \n#                     'decoder_optimizer': decoder_optimizer.state_dict(), \n#                     'decoder_scheduler': decoder_scheduler.state_dict(), \n#                     'text_preds': text_preds,\n#                    },\n#                     OUTPUT_DIR+f'{CFG.model_name}_fold{fold}_epoch{epoch+1}.pth')\n        if score < best_score:\n            best_score = score\n            LOGGER.info(f'Epoch {epoch+1} - Save Best Score: {best_score:.4f} Model')\n            torch.save({'encoder': encoder.state_dict(), \n                        'encoder_optimizer': encoder_optimizer.state_dict(), \n                        'encoder_scheduler': encoder_scheduler.state_dict(), \n                        'decoder': decoder.state_dict(), \n                        'decoder_optimizer': decoder_optimizer.state_dict(), \n                        'decoder_scheduler': decoder_scheduler.state_dict(), \n                        'text_preds': text_preds,\n                       },\n                        OUTPUT_DIR+f'{CFG.model_name}_fold{fold}_best.pth')","metadata":{"papermill":{"duration":0.041299,"end_time":"2021-03-09T09:44:58.739015","exception":false,"start_time":"2021-03-09T09:44:58.697716","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T10:03:53.069287Z","iopub.execute_input":"2022-11-15T10:03:53.069913Z","iopub.status.idle":"2022-11-15T10:03:53.098178Z","shell.execute_reply.started":"2022-11-15T10:03:53.069872Z","shell.execute_reply":"2022-11-15T10:03:53.097177Z"}},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Main","metadata":{"papermill":{"duration":0.021144,"end_time":"2021-03-09T09:44:58.78128","exception":false,"start_time":"2021-03-09T09:44:58.760136","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# ====================================================\n# main\n# ====================================================\ndef main():\n\n    \"\"\"\n    Prepare: 1.train  2.folds\n    \"\"\"\n    f_name = f\"nlayers{CFG.layers}_lr{CFG.min_lr}_batch{CFG.batch_size}_attdim{CFG.attention_dim}_dropout{CFG.dropout}_opti{CFG.scheduler}.csv\"\n    with open(file=f_name, mode=\"a\") as f:\n        f.truncate()   #清空文件\n        f.write(\"epoch,score,lcs,cer\\n\")\n    \n    if CFG.train:\n        # train\n        oof_df = pd.DataFrame()\n        for fold in range(CFG.n_fold):\n            if fold in CFG.trn_fold:\n                train_loop(folds, fold)","metadata":{"papermill":{"duration":0.030114,"end_time":"2021-03-09T09:44:58.832368","exception":false,"start_time":"2021-03-09T09:44:58.802254","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T10:03:53.68547Z","iopub.execute_input":"2022-11-15T10:03:53.685832Z","iopub.status.idle":"2022-11-15T10:03:53.692146Z","shell.execute_reply.started":"2022-11-15T10:03:53.6858Z","shell.execute_reply":"2022-11-15T10:03:53.691204Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"if __name__ == '__main__':\n    main()","metadata":{"papermill":{"duration":2043.388258,"end_time":"2021-03-09T10:19:02.241899","exception":false,"start_time":"2021-03-09T09:44:58.853641","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-15T10:03:53.698319Z","iopub.execute_input":"2022-11-15T10:03:53.69928Z","iopub.status.idle":"2022-11-15T10:05:47.472176Z","shell.execute_reply.started":"2022-11-15T10:03:53.699245Z","shell.execute_reply":"2022-11-15T10:05:47.468765Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}