diff --git "a/MedicalAbstracts_multilabel_classification.ipynb" "b/MedicalAbstracts_multilabel_classification.ipynb" new file mode 100644--- /dev/null +++ "b/MedicalAbstracts_multilabel_classification.ipynb" @@ -0,0 +1,6665 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "JeFpEz-XyZTx" + }, + "source": [ + "##### This work was done by me as a part my academic project\n", + "##### *problem description and dataset used,* [*clic*](https://huggingface.co/datasets/owaiskha9654/PubMed_MultiLabel_Text_Classification_Dataset_MeSH)\n", + "[*link to github repo &colab*](https://github.com/hajar-hajji/2A-project-MinesNancy-Loria/blob/main/MedicalAbstracts_MultilabelClassification/MedicalAbstracts_multilabel_classification.ipynb)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "OD5qRiZBpmEd" + }, + "source": [ + "#### Loading our dataset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ylzZnhXGpf7E", + "outputId": "0d5848d0-c163-4cd1-e260-93cad5136164" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Collecting datasets\n", + " Downloading datasets-2.10.1-py3-none-any.whl (469 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m469.0/469.0 KB\u001b[0m \u001b[31m13.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: pyarrow>=6.0.0 in /usr/local/lib/python3.8/dist-packages (from datasets) (9.0.0)\n", + "Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (4.64.1)\n", + "Requirement already satisfied: fsspec[http]>=2021.11.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (2023.1.0)\n", + "Requirement already satisfied: aiohttp in /usr/local/lib/python3.8/dist-packages (from datasets) (3.8.4)\n", + "Collecting huggingface-hub<1.0.0,>=0.2.0\n", + " Downloading huggingface_hub-0.12.1-py3-none-any.whl (190 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m190.3/190.3 KB\u001b[0m \u001b[31m21.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hCollecting xxhash\n", + " Downloading xxhash-3.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (213 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m213.0/213.0 KB\u001b[0m \u001b[31m27.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from datasets) (1.22.4)\n", + "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.8/dist-packages (from datasets) (2.25.1)\n", + "Collecting multiprocess\n", + " Downloading multiprocess-0.70.14-py38-none-any.whl (132 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m132.0/132.0 KB\u001b[0m \u001b[31m17.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from datasets) (23.0)\n", + "Collecting responses<0.19\n", + " Downloading responses-0.18.0-py3-none-any.whl (38 kB)\n", + "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (6.0)\n", + "Collecting dill<0.3.7,>=0.3.0\n", + " Downloading dill-0.3.6-py3-none-any.whl (110 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m110.5/110.5 KB\u001b[0m \u001b[31m14.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.8/dist-packages (from datasets) (1.3.5)\n", + "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.8.2)\n", + "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (22.2.0)\n", + "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (6.0.4)\n", + "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.3.1)\n", + "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.3.3)\n", + "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (4.0.2)\n", + "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (3.0.1)\n", + "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from huggingface-hub<1.0.0,>=0.2.0->datasets) (3.9.0)\n", + "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub<1.0.0,>=0.2.0->datasets) (4.5.0)\n", + "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (2.10)\n", + "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (1.26.14)\n", + "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (4.0.0)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (2022.12.7)\n", + "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas->datasets) (2.8.2)\n", + "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas->datasets) (2022.7.1)\n", + "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.7.3->pandas->datasets) (1.15.0)\n", + "Installing collected packages: xxhash, dill, responses, multiprocess, huggingface-hub, datasets\n", + "Successfully installed datasets-2.10.1 dill-0.3.6 huggingface-hub-0.12.1 multiprocess-0.70.14 responses-0.18.0 xxhash-3.2.0\n" + ] + } + ], + "source": [ + "!pip install datasets" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TG9KdRLApVCH" + }, + "outputs": [], + "source": [ + "from datasets import load_dataset\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 233, + "referenced_widgets": [ + "7bb7b488912c41229c4f52c10acf418d", + "a491db0de6754701bec1ed0b1dee0b53", + "4db9a812ea484b5aae744d7f99daf213", + "8a7ea158d2324f5b922f83d9446fb11c", + "66482f353af940cca612735c6f148a71", + "b8ee6a5794b449e3bb949820c3101795", + "71404edcc0544537a68d4e375834a3fe", + "66269ad51da14492bf589f9e8ed3212a", + "2fd2f67e9bec4bbdb846b9168f64243c", + "ab40298ef8b64f9c81a4f59cf777a8a3", + "767d4718e0584a859937644ba1e6de65", + "29a4f5bb2f0f40a8862b03c1b592dc6e", + "e07cd85e9b3f4c77907804960cb1b7f7", + "12c3e050593c4cc5a519d613fa99c6c3", + "6357b53dd0e5494cbae0915bbb09d70d", + "085daa87d602495ba387505d7addcfd7", + "35630fa379304dbc9fafce769b68be46", + "e015adba4713426584761ca3617c6932", + "d347390f96784e75945cc51d68f39cec", + "6743d48d260f44648cc44f4b807900c3", + "949fc2a0e36542069885c352a52ddf2a", + "8c81c573a7ad4cad824281e9db0ae532", + "62746b245cc6426ca40e64b207f18764", + "717cb8d537464ad59192cae89d587cef", + "51f15e08de964d6588fee19136177005", + "48650c3259c646878aa245b564e74237", + "593e3dd323be4dd6881f0ebf16734c26", + "6dadd7a4140d46b6a101274a8560b1f3", + "b8960ed31e1f4b33b4bd37c144e19e7e", + "9f1ad8b2589b4810883cab1b8f3ff403", + "c118d1bf0f7b46ddbaf2edbe615357a3", + "ac62656c960d432f94c1ada2a1e6c3c8", + "b1aef87d7b104c458b3d52367e38c64b", + "79b5773782504dfca6d9cdbefbfe4c4b", + "323a7fff25e140ffa0a0797759e235f0", + "602718a0005d48bc8976a96e1220b91b", + "f4431575c50740828c194978237f83e6", + "55f38c1e1e1d42ba8dbc167dc25eacd1", + "548d6d1baf8d44cca7983b1e2fa30145", + "27bd13b7007443c0b80e240094c3548e", + "46507d61346844eeba74910e3fd17d30", + "e1357c899dfc4cc7b243675a5b28c0b9", + "a256244cf3f740fdbc9618136f426ed6", + "bea9ce0783b34ddd9fdb691342f65679", + "472d4c6210034dd8b2835f27894aee99", + "43136e63ca7348d1994eeb8fa86a16c2", + "eb9c53ff17334912be09fdd689fe2ba8", + "8d79552fcf554659822238a18c496be4", + "48a7dfd985684a6a86a3225ba58292eb", + "2a5e3f0bfd8c4ef5a1f8c400e249b806", + "87f6ca0755044889a48ecc4901ece749", + "afff27a60ead4540aeb63abca824a1c2", + "5c149ee82a1548da800df4ffe8412195", + "37d80c0a5bc14d9097112a5ff1c11b96", + "50d2844a0b124e8ea86b487d0e735f09", + "2949b640914841468038d426ba386dc8", + "91f98c2cbb66427c827450fe16a3b581", + "088ac21fdf7e4861b5ffb816c5f1f0cb", + "56e78a2746b440058bc13f4ef4e4e04e", + "62ede59767c94e27bbc50e759a6aad61", + "de93611cf1074616be5b92133210c630", + "92d7ffaf03c844028e5ec5222a586ab2", + "b1c53c27bfbd4ff18b676c43f58cde5b", + "9f800503050a4537ba2e2cac44662bbc", + "1302ca8fba494e8089548b5aa4e7c4bd", + "3e9041e4729d4c8d9cd1abcbf99fa215" + ] + }, + "id": "rIKtQ7c3wfxI", + "outputId": "2cf8f3e0-de81-492c-efe4-a3ecd0810264" + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "7bb7b488912c41229c4f52c10acf418d", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading readme: 0%| | 0.00/960 [00:00=0.11.1\n", + " Downloading tokenizers-0.13.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m107.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (2022.6.2)\n", + "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from transformers) (2.25.1)\n", + "Requirement already satisfied: huggingface-hub<1.0,>=0.11.0 in /usr/local/lib/python3.8/dist-packages (from transformers) (0.12.1)\n", + "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers) (23.0)\n", + "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (1.22.4)\n", + "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers) (3.9.0)\n", + "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.8/dist-packages (from transformers) (4.64.1)\n", + "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from transformers) (6.0)\n", + "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (4.5.0)\n", + "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (1.26.14)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2022.12.7)\n", + "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2.10)\n", + "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (4.0.0)\n", + "Installing collected packages: tokenizers, transformers\n", + "Successfully installed tokenizers-0.13.2 transformers-4.26.1\n" + ] + } + ], + "source": [ + "!pip install transformers" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 113, + "referenced_widgets": [ + "564a62ba9281479e992567a376ee17ce", + "8896238b49d24f648e23dd721612f7af", + "40622122a1574b53a03523ea8e49e45e", + "a7f5346743ab4ad2945ef4c575be0458", + "bd93707bd6bd41b991e8c50a0ece8baf", + "a806fe6733374a359662c6a989fc851e", + "5802634805bc4654935aed28cf4855a5", + "3b61f2e1772c4c83a569ca808b580150", + "d7554b81b5b040218b281079f606d95f", + "f4487664111b4061b00cf36390d5e119", + "c89946cdc0f54e0faad8859e28e17ed0", + "d4bc24dabf744f7197a00dc10c77a127", + "5b5b18a2a7b441b8aee438a4fac1574b", + "540c6cb0c9e6404da39bae3ea3be2d4d", + "f44dcab8ac4d4025a0399179be883b37", + "ae97967de0574604bcd2e0cc599fb0db", + "471b020ec53944b6827fe487657e135c", + "2d91a540467846a181dc1477044f6cf4", + "f0e742d9b2db40e8b57e084de9420c40", + "f6f9fb55c39a46529329d1620e7d6088", + "f754f438d35e421db9ccf52d0c228f0a", + "7abadd0359364223833b5809140c99db", + "a46f3a4d96f24d0daf6dab9e63cfa8a9", + "a477991f543949c7bb24569d6cbbe8d8", + "d51d0c1236334849b5fc6c3e547360f4", + "16aba8f9a11a459f9cf1059efdc12ec9", + "c6baaa24df4943f6a7b8be154ef9e18a", + "27302aee438f4637be2daa2c74c478c7", + "23812f0e09cf4e57b91df171f66d1f54", + "a5c81d14bd204b9fab508b7ae315b5d9", + "eb33df63f64e42a3933400de0d955bc3", + "d2e2ae1d9fd34ff6ae20235d20cac2d7", + "c41cad9f1efc4bbc80d8c3c4e6c776f8" + ] + }, + "id": "QA-rqvoVqI1v", + "outputId": "35dbd8aa-e8c6-49a2-e052-aef621fcbb53" + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "564a62ba9281479e992567a376ee17ce", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading (…)solve/main/vocab.txt: 0%| | 0.00/232k [00:00max_length:\n", + "# max_length=len(mydataset[\"train\"][\"fullText\"][i])\n", + "# max_sentence=sentence\n", + "# print(max_sentence)\n", + "# print(max_length)\n", + "\n", + "# \"\"\"ps. do not rerun this cell !!!!!! it takes so long to run and it's of no use for the study as i already chose max_len ;)\n", + "# \"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "f63Tldlq6UWF" + }, + "outputs": [], + "source": [ + "###now let's define a function that will apply these steps for a certain dataset\n", + "def preprocessing(sample):\n", + " #####Encode all texts###############\n", + " #i'll set max_length to 512\n", + " mytext=sample[\"fullText\"]\n", + " encoder=tokenizer(mytext,\n", + " is_split_into_words=False, #phrases non tokenisées\n", + " padding=\"max_length\", truncation=True, #assure all inputs have same len\n", + " max_length=512)\n", + " #returns dictionary : {\"input_ids\"}\n", + " \n", + " #####Encode all labels###############\n", + " #create dictionary that contains labels \n", + " dic_labels={key:sample[key] for key in sample.keys() if key in tags}\n", + " #create an empty matrix\n", + " columns=len(tags)\n", + " lines=len(sample[\"A\"])\n", + " mymatrix=np.zeros((lines,columns))\n", + "\n", + "\n", + " for i,k in enumerate(dic_labels.keys()):\n", + " mymatrix[:,i]=dic_labels[k]\n", + " #that way we'll have a matrix where each line of labels corresponds to a specific text, 1 if label and 0 else...\n", + "\n", + " #add labels to the main dictionary\n", + " encoder[\"labels\"]=mymatrix.tolist()\n", + " #delete token_type_ids bcs we won't need it\n", + " del encoder[\"token_type_ids\"] # if AutoModelForSequenceClassification model is used, it will ignore the token_type_ids argument anyway.\n", + "\n", + " return encoder" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 17, + "referenced_widgets": [ + "3ddc743a17cc42dfaddbd590417fd4f1", + "db68936431e842068b7378c75bff17f7", + "b8f8d75e04ba4ac49f48b868a93e56e3", + "0a5649e245804023953ad2114e65f933", + "82b865bb3b674a549e3b540c88ca7fd7", + "d2cfe948df1e4a56b61f50dd1823f682", + "9ee44e3b1e97457b812068f8ea6195aa", + "ddcd7fb8ec2f4b09871542c457983c59", + "2bb55e38536140888c3599621f39b928", + "35abfcc74487460695b92748599a6304", + "4cdc3407a49b42d1b776c6e8f943e543" + ] + }, + "id": "XkZyfXkwE7Zh", + "outputId": "c612d02e-3529-49da-f296-b12137d0babc" + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "3ddc743a17cc42dfaddbd590417fd4f1", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Map: 0%| | 0/50000 [00:00\n", + "\n" + ] + } + ], + "source": [ + "from datasets import Dataset\n", + "import torch\n", + "\n", + "#transform to dataset object\n", + "train_data_copy=Dataset.from_dict(train_data)\n", + "val_data_copy=Dataset.from_dict(val_data)\n", + "print(type(train_data_copy))\n", + "\n", + "# import copy\n", + "# train_data_copy2=copy.deepcopy(train_data_copy)\n", + "\n", + "###transform all datasets to tensors before feeding them to the model(ps: directly w/ affecting variables...!!)\n", + "train_data_copy.set_format(\"torch\")\n", + "print(type(train_data_copy))\n", + "val_data_copy.set_format(\"torch\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9jHpa155kfZr" + }, + "outputs": [], + "source": [ + "# from datasets import DatasetDict\n", + "\n", + "# train_data_copyy=DatasetDict(train_data)\n", + "# train_data_essai=train_data.copy()\n", + "# train_data_copy.set_format(\"torch\")\n", + "##\"\"--\n", + "# input_ids_train=train_data[\"input_ids\"]\n", + "# mask_train=train_data[\"attention_mask\"]\n", + "# labels_train=train_data[\"labels\"]\n", + "# tensor_train=TensorDataset(torch.tensor(input_ids_train),torch.tensor(mask_train),torch.tensor(labels_train))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9lqu68T1rzCf" + }, + "source": [ + "#### Introducing the model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 159, + "referenced_widgets": [ + "f50a069bf0b445a38f809c7872fc2153", + "d68e445c62ef4472a10212f8122fd10e", + "f15de53617b54f61a73069be93a2a56e", + "5ea87c870f124556a2da90e1dcd80d4d", + "a465b55b480444ed8cdb2d70ab50466d", + "49702ffa478b46f0a318fca7dac1f28c", + "e329dea9634647b2aa840ddbb93973bf", + "d67dcac374c74096b6811d04641f13dd", + "da0ffcc86fa1438aa0b4151a89bdcd0c", + "d434c7b3bd914bf79df5b8ee18c2045d", + "017e29c8f4ee42b0a6f54bf091c63f76" + ] + }, + "id": "xhWKzObAouwZ", + "outputId": "e1c6d2dd-0e44-4f02-b95f-bc32fd18a840" + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f50a069bf0b445a38f809c7872fc2153", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading (…)\"pytorch_model.bin\";: 0%| | 0.00/440M [00:00), logits=tensor([[-0.0321, 0.2688, 0.1807, -0.3697, 0.3948, -0.1747, -0.4591, -0.1441,\n", + " 0.2316, 0.4735, -0.1143, 0.5607, -0.8226, -0.3508]],\n", + " grad_fn=), hidden_states=None, attentions=None)" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#let's see what the model output looks like (initially)\n", + "output_1 = model(input_ids=train_data_copy[\"input_ids\"][0].unsqueeze(0),labels=train_data_copy[\"labels\"][0].unsqueeze(0))\n", + "output_1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "RCOYyZ4k8_LI", + "outputId": "cee941c6-95ce-42ab-fcb8-7cf85ba8016f" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tensor(0.7532, grad_fn=)\n", + "\n", + "tensor([[-0.0321, 0.2688, 0.1807, -0.3697, 0.3948, -0.1747, -0.4591, -0.1441,\n", + " 0.2316, 0.4735, -0.1143, 0.5607, -0.8226, -0.3508]],\n", + " grad_fn=)\n", + "\n", + "torch.Size([1, 14])\n" + ] + } + ], + "source": [ + "print(output_1[0]) #loss\n", + "print()\n", + "print(output_1[1]) #logits\n", + "#ps : not normalized, meaning that they're not necessarily between 0 and 1 and are not interpretable as probabilities...\n", + "print()\n", + "print(output_1[1].shape)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "PmqsMaDq_a1T", + "outputId": "f9d7cde3-920d-4674-cdef-9ed552dab307" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([[0.4920, 0.5668, 0.5451, 0.4086, 0.5974, 0.4564, 0.3872, 0.4640, 0.5576,\n", + " 0.6162, 0.4714, 0.6366, 0.3052, 0.4132]], grad_fn=)" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "probabilities=torch.sigmoid(output_1[1])\n", + "probabilities" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ccFat7uy_75B", + "outputId": "b7cfd76a-3d8e-4df6-d05d-182dd7f34ca9" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initial predictions :\n", + "[0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0]\n", + "['B', 'C', 'E', 'I', 'J', 'M']\n", + "['Organisms', 'Diseases', 'Analytical, Diagnostic and Therapeutic Techniques, and Equipment', 'Anthropology, Education, Sociology, and Social Phenomena', 'Technology, Industry, and Agriculture', 'Named Groups']\n", + "\n", + "\n", + "True labels :\n", + "tensor([1., 1., 0., 0., 1., 0., 1., 0., 0., 0., 1., 0., 1., 0.])\n", + "['A', 'B', 'E', 'G', 'L', 'N']\n", + "['Anatomy', 'Organisms', 'Analytical, Diagnostic and Therapeutic Techniques, and Equipment', 'Phenomena and Processes', 'Information Science', 'Health Care']\n" + ] + } + ], + "source": [ + "print(\"Initial predictions :\")\n", + "predictions=[1 if el>0.5 else 0 for el in probabilities.tolist()[0]]\n", + "print(predictions)\n", + "literal_predictions=[get_tag[i] for i,el in enumerate(predictions) if el==1]\n", + "print(literal_predictions)\n", + "interpreted_pred=[main_ref[tag] for tag in literal_predictions]\n", + "print(interpreted_pred)\n", + "print(\"\\n\")\n", + "print(\"True labels :\")\n", + "#real labels\n", + "labels=train_data_copy[\"labels\"][0]\n", + "print(labels)\n", + "lit=[get_tag[i] for i,el in enumerate(labels) if el==1]\n", + "print(lit)\n", + "ref=[main_ref[tag] for tag in lit]\n", + "print(ref)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "KokOLQdE6KwG", + "outputId": "9600787e-c9e8-4c39-a337-2f56bf89e4c0" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "SequenceClassifierOutput(loss=tensor(0.7798, grad_fn=), logits=tensor([[-0.0321, 0.2688, 0.1807, -0.3697, 0.3948, -0.1747, -0.4591, -0.1441,\n", + " 0.2316, 0.4735, -0.1143, 0.5607, -0.8226, -0.3508],\n", + " [-0.0610, 0.2731, 0.1877, -0.3594, 0.3711, -0.2088, -0.4294, -0.1975,\n", + " 0.2379, 0.4534, -0.0987, 0.5458, -0.7977, -0.2637]],\n", + " grad_fn=), hidden_states=None, attentions=None)" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "output_2 = model(input_ids=train_data_copy[\"input_ids\"][:2],labels=train_data_copy[\"labels\"][:2])\n", + "output_2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "wM4KgjLv9Oe1", + "outputId": "5a3e43da-5d27-405c-8fca-efe8f5acbade" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch.Size([2, 14])\n" + ] + } + ], + "source": [ + "print(output_2[1].shape) #dim: (batch_size,num_tags)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "TYeyNEqvsgkN" + }, + "outputs": [], + "source": [ + "from sklearn.metrics import precision_recall_fscore_support\n", + "from transformers import EvalPrediction\n", + "\n", + "\"\"\"\n", + "EvalPrediction class from the Hugging Face Transformers library\n", + "The EvalPrediction class has two main attributes: predictions and label_ids. \n", + "\n", + "1) predictions is a tensor of size (batch_size, num_labels) containing the model's output scores for each example in the batch.\n", + "2) label_ids is a tensor of the same size containing the actual labels for each example in the batch.\n", + "3) ...\n", + "\n", + "source : https://huggingface.co/docs/transformers/internal/trainer_utils\n", + "\"\"\"\n", + "\n", + "def function_metrics(p: EvalPrediction): #an instance of EvalPrediction\n", + "\n", + " logits=p.predictions\n", + " probabilities=torch.sigmoid(torch.tensor(logits)) #turn into probabilities using sigmoid activation function\n", + " predicted_labels=np.where(probabilities>=0.5,1,0) #set 1 if belongs to class 0 otherwise\n", + "\n", + " true_labels=p.label_ids\n", + " \n", + " #precision, recall, f1, _ = precision_recall_fscore_support(true_labels, predicted_labels, average=None)\n", + " precision_micro, recall_micro, f1_micro, _ = precision_recall_fscore_support(true_labels, predicted_labels, average='micro')\n", + " \n", + " return {\n", + " 'precision_micro': precision_micro,\n", + " 'recall_micro': recall_micro,\n", + " 'f1_micro': f1_micro,\n", + " }\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "DColzDI9sch1" + }, + "outputs": [], + "source": [ + "#fast trainer -> https://huggingface.co/docs/transformers/main_classes/trainer\n", + "trainer = Trainer(\n", + " model,\n", + " arguments,\n", + " train_dataset=train_data_copy,\n", + " eval_dataset=val_data_copy,\n", + " tokenizer=tokenizer,\n", + " compute_metrics=function_metrics\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "KFcyLc3cq5MA" + }, + "outputs": [], + "source": [ + "import gc\n", + "\n", + "gc.collect()\n", + "\n", + "torch.cuda.empty_cache()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vJ1Sg9rpmwxG" + }, + "outputs": [], + "source": [ + "import os\n", + "os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_cached_bytes=2147483648,max_split_size_mb=1024'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "xqMmF6gt4QYa", + "outputId": "109a86a7-413c-44d3-a3c4-198963c24dd7" + }, + "outputs": [ + { + "metadata": { + "tags": null + }, + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.8/dist-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n", + " warnings.warn(\n", + "***** Running training *****\n", + " Num examples = 40000\n", + " Num Epochs = 1\n", + " Instantaneous batch size per device = 16\n", + " Total train batch size (w. parallel, distributed & accumulation) = 16\n", + " Gradient Accumulation steps = 1\n", + " Total optimization steps = 2500\n", + " Number of trainable parameters = 109493006\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " \n", + " [ 517/2500 11:56 < 46:00, 0.72 it/s, Epoch 0.21/1]\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
EpochTraining LossValidation Loss

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "

\n", + " \n", + " \n", + " [2500/2500 58:00, Epoch 1/1]\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
EpochTraining LossValidation LossPrecision MicroRecall MicroF1 Micro
10.3085000.3043850.8565040.8337670.844983

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "***** Running Evaluation *****\n", + " Num examples = 10000\n", + " Batch size = 16\n", + "Saving model checkpoint to /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500\n", + "Configuration saved in /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500/config.json\n", + "Model weights saved in /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500/pytorch_model.bin\n", + "tokenizer config file saved in /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500/tokenizer_config.json\n", + "Special tokens file saved in /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500/special_tokens_map.json\n" + ] + }, + { + "ename": "KeyError", + "evalue": "ignored", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.8/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)\u001b[0m\n\u001b[1;32m 1541\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_inner_training_loop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_train_batch_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauto_find_batch_size\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1542\u001b[0m )\n\u001b[0;32m-> 1543\u001b[0;31m return inner_training_loop(\n\u001b[0m\u001b[1;32m 1544\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1545\u001b[0m \u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.8/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_inner_training_loop\u001b[0;34m(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m 1881\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1882\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallback_handler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_epoch_end\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1883\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_log_save_evaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtr_loss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrial\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepoch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mignore_keys_for_eval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1884\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1885\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mDebugOption\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTPU_METRICS_DEBUG\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.8/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_maybe_log_save_evaluate\u001b[0;34m(self, tr_loss, model, trial, epoch, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m 2133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2134\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshould_save\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2135\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_save_checkpoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrial\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2136\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallback_handler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_save\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2137\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.8/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_save_checkpoint\u001b[0;34m(self, model, trial, metrics)\u001b[0m\n\u001b[1;32m 2236\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mmetric_to_check\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstartswith\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"eval_\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2237\u001b[0m \u001b[0mmetric_to_check\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mf\"eval_{metric_to_check}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2238\u001b[0;31m \u001b[0mmetric_value\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmetric_to_check\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2240\u001b[0m \u001b[0moperator\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgreater\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgreater_is_better\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mless\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: 'eval_f1'" + ] + } + ], + "source": [ + "%time trainer.train()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6jkMV-bEpau0" + }, + "source": [ + "####Evaluate the model\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 262 + }, + "id": "uvJL2ju4864f", + "outputId": "a711710f-5b6f-47ee-9467-37529e152533" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "***** Running Evaluation *****\n", + " Num examples = 10000\n", + " Batch size = 16\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "

\n", + " \n", + " \n", + " [2500/2500 58:00, Epoch 1/1]\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
EpochTraining LossValidation LossPrecision MicroRecall MicroF1 Micro
10.3085000.3043850.8565040.8337670.844983
10.3085000.3043850.8565040.8337670.844983

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "{'eval_loss': 0.3043845593929291,\n", + " 'eval_precision_micro': 0.8565042547843883,\n", + " 'eval_recall_micro': 0.8337673231855438,\n", + " 'eval_f1_micro': 0.8449828644297442}" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "trainer.evaluate()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3rjh-5c2WWPb" + }, + "source": [ + "####Save the model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "UAvHpyMGWYWi", + "outputId": "1db3dc9a-6e1b-4641-e408-b654b28aa8ea" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Configuration saved in /content/mymodels/Medical_classif_abstracts_1e/config.json\n", + "Model weights saved in /content/mymodels/Medical_classif_abstracts_1e/pytorch_model.bin\n" + ] + } + ], + "source": [ + "#save tokenizer\n", + "tokenizer.save_vocabulary(\"/content/mymodels/Medical_classif_abstracts_1e\")\n", + "#save trained model\n", + "model.save_pretrained(\"/content/mymodels/Medical_classif_abstracts_1e\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UhFTt29UabId" + }, + "source": [ + "####Continue training on +1 epoch" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BRPjU96CfLs1" + }, + "source": [ + "#####Reloading saved model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Z9zmqN2XXMQH", + "outputId": "29375be1-441c-4e11-f260-8b51b1c05495" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mounted at /content/drive\n" + ] + } + ], + "source": [ + "from google.colab import drive\n", + "drive.mount('/content/drive')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "o3OlggVlagEL" + }, + "outputs": [], + "source": [ + "model_path=\"/content/drive/MyDrive/mymodels/medical_multiL_abstracts_1e\"\n", + "\n", + "NEWtokenizer=BertTokenizer.from_pretrained(model_path)\n", + "NEWmodel=BertForSequenceClassification.from_pretrained(model_path)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Lc9SLxE-fXJg" + }, + "source": [ + "#####Continue training" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "CeojUUFKfTGe" + }, + "outputs": [], + "source": [ + "trainer = Trainer(\n", + " NEWmodel,\n", + " arguments,\n", + " train_dataset=train_data_copy,\n", + " eval_dataset=val_data_copy,\n", + " tokenizer=NEWtokenizer,\n", + " compute_metrics=function_metrics\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 877 + }, + "id": "8DFfqJyzgV-Y", + "outputId": "57198a4c-cc6a-4f94-b44b-3e13430dcfdf" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.8/dist-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n", + " warnings.warn(\n", + "***** Running training *****\n", + " Num examples = 40000\n", + " Num Epochs = 1\n", + " Instantaneous batch size per device = 16\n", + " Total train batch size (w. parallel, distributed & accumulation) = 16\n", + " Gradient Accumulation steps = 1\n", + " Total optimization steps = 2500\n", + " Number of trainable parameters = 109493006\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "

\n", + " \n", + " \n", + " [2500/2500 1:02:19, Epoch 1/1]\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
EpochTraining LossValidation LossPrecision MicroRecall MicroF1 Micro
10.2808000.2793470.8675470.8457910.856531

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "***** Running Evaluation *****\n", + " Num examples = 10000\n", + " Batch size = 16\n", + "Saving model checkpoint to /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500\n", + "Configuration saved in /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500/config.json\n", + "Model weights saved in /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500/pytorch_model.bin\n", + "tokenizer config file saved in /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500/tokenizer_config.json\n", + "Special tokens file saved in /content/drive/MyDrive/mymodels/med_classif_abstract/checkpoint-2500/special_tokens_map.json\n" + ] + }, + { + "ename": "KeyError", + "evalue": "ignored", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.8/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)\u001b[0m\n\u001b[1;32m 1541\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_inner_training_loop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_train_batch_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauto_find_batch_size\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1542\u001b[0m )\n\u001b[0;32m-> 1543\u001b[0;31m return inner_training_loop(\n\u001b[0m\u001b[1;32m 1544\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1545\u001b[0m \u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.8/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_inner_training_loop\u001b[0;34m(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m 1881\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1882\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallback_handler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_epoch_end\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1883\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_log_save_evaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtr_loss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrial\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepoch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mignore_keys_for_eval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1884\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1885\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mDebugOption\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTPU_METRICS_DEBUG\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.8/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_maybe_log_save_evaluate\u001b[0;34m(self, tr_loss, model, trial, epoch, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m 2133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2134\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshould_save\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2135\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_save_checkpoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrial\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2136\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallback_handler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_save\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2137\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.8/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_save_checkpoint\u001b[0;34m(self, model, trial, metrics)\u001b[0m\n\u001b[1;32m 2236\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mmetric_to_check\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstartswith\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"eval_\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2237\u001b[0m \u001b[0mmetric_to_check\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mf\"eval_{metric_to_check}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2238\u001b[0;31m \u001b[0mmetric_value\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmetric_to_check\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2240\u001b[0m \u001b[0moperator\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgreater\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgreater_is_better\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mless\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: 'eval_f1'" + ] + } + ], + "source": [ + "#train on one more epoch\n", + "%time trainer.train()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 263 + }, + "id": "ExnQl6L_guis", + "outputId": "68ec6374-8822-45b6-9ad9-3cdeac6562a9" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "***** Running Evaluation *****\n", + " Num examples = 10000\n", + " Batch size = 16\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "

\n", + " \n", + " \n", + " [2500/2500 1:02:19, Epoch 1/1]\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
EpochTraining LossValidation LossPrecision MicroRecall MicroF1 Micro
10.2808000.2793470.8675470.8457910.856531
10.2808000.2793470.8675470.8457910.856531

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "{'eval_loss': 0.27934730052948,\n", + " 'eval_precision_micro': 0.8675474133295092,\n", + " 'eval_recall_micro': 0.8457908809702731,\n", + " 'eval_f1_micro': 0.856531011353279}" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "trainer.evaluate()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "JETO0LwgpmdH", + "outputId": "d275ee9d-6f6d-4cf2-cca9-18b41a2fd62b" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Configuration saved in /content/drive/MyDrive/mymodels/medical_multiL_abstracts_2e/config.json\n", + "Model weights saved in /content/drive/MyDrive/mymodels/medical_multiL_abstracts_2e/pytorch_model.bin\n" + ] + } + ], + "source": [ + "NEWtokenizer.save_vocabulary(\"/content/drive/MyDrive/mymodels/medical_multiL_abstracts_2e\")\n", + "NEWmodel.save_pretrained(\"/content/drive/MyDrive/mymodels/medical_multiL_abstracts_2e\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Y9qartlEpwII" + }, + "source": [ + "####Test on new abstracts" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MD80BKosH2bo" + }, + "source": [ + "#####First example" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "cwr3cUFXXhs4" + }, + "outputs": [], + "source": [ + "model=NEWmodel\n", + "tokenizer=NEWtokenizer" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fBLusTU5sId7" + }, + "outputs": [], + "source": [ + "abstract1=\"rokinase receptor : a molecular organizer in cellular communication .In a variety of cell types , the glycolipid - anchored urokinase receptor ( uPAR ) is colocalized pericellularly with components of the plasminogen activation system and endocytosis receptors . uPAR is also coexpressed with caveolin and members of the integrin adhesion receptor superfamily . The formation of functional units with these various proteins allows the uPAR to mediate the focused proteolysis required for cell migration and invasion and to contribute both directly and indirectly to cell adhesive processes in a non - proteolytic fashion .This dual activity , together with the initiation of signal transduction pathways by uPAR , is believed to influence cellular behaviour in angiogenesis , inflammation , wound repair and tumor progression / metastasis and open up the way for uPAR - based therapeutic approaches .\"\n", + "\n", + "#####Encoding######\n", + "encode=tokenizer(abstract1,is_split_into_words=False)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "collapsed": true, + "id": "Mn903JVq60Bu", + "outputId": "1ff9d5e7-2a87-4281-8562-ca952e148eb1" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'input_ids': [101, 20996, 4939, 11022, 10769, 1024, 1037, 8382, 19012, 1999, 12562, 4807, 1012, 1999, 1037, 3528, 1997, 3526, 4127, 1010, 1996, 1043, 2135, 25778, 11514, 3593, 1011, 14453, 24471, 23212, 11649, 2063, 10769, 1006, 2039, 2906, 1007, 2003, 8902, 24755, 28931, 2566, 6610, 3363, 7934, 2135, 2007, 6177, 1997, 1996, 20228, 3022, 10020, 23924, 13791, 2291, 1998, 2203, 10085, 22123, 12650, 13833, 1012, 2039, 2906, 2003, 2036, 24873, 2595, 19811, 2007, 5430, 18861, 1998, 2372, 1997, 1996, 20014, 13910, 6657, 4748, 21471, 10769, 24169, 1012, 1996, 4195, 1997, 8360, 3197, 2007, 2122, 2536, 8171, 4473, 1996, 2039, 2906, 2000, 2865, 2618, 1996, 4208, 4013, 2618, 4747, 20960, 3223, 2005, 3526, 9230, 1998, 5274, 1998, 2000, 9002, 2119, 3495, 1998, 17351, 2000, 3526, 4748, 21579, 6194, 1999, 1037, 2512, 1011, 4013, 2618, 4747, 21252, 4827, 1012, 2023, 7037, 4023, 1010, 2362, 2007, 1996, 17890, 1997, 4742, 9099, 16256, 16910, 2011, 2039, 2906, 1010, 2003, 3373, 2000, 3747, 12562, 9164, 1999, 17076, 3695, 23737, 1010, 21733, 1010, 6357, 7192, 1998, 13656, 14967, 1013, 18804, 9153, 6190, 1998, 2330, 2039, 1996, 2126, 2005, 2039, 2906, 1011, 2241, 17261, 8107, 1012, 102], 'token_type_ids': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\"\"\"AC with torch.no_grad():\n", + " input_ids = torch.tensor(encode.input_ids).to(device)\n", + " attention_mask = torch.tensor(encode.attention_mask).to(device)\n", + " output = model(input_ids, attention_mask=attention_mask)\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "5RG5cB0q91cH", + "outputId": "3cb12148-16e8-4b55-d05a-098c9f8c972e" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cuda\n" + ] + } + ], + "source": [ + "mydevice = torch.device(\"cuda\") if torch.cuda.is_available() else torch.device(\"cpu\")\n", + "print(mydevice)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NZTrTCi2-O9r" + }, + "outputs": [], + "source": [ + "#turn everything into pytorch tensors (don't forget to move to cuda...)\n", + "enc_tensor={key:torch.tensor(value).to(mydevice) for key,value in encode.items()} #or simply specify in the previous line: return_tensors=\"pt\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "yrQOBxGg79bI", + "outputId": "2f0af86b-aac1-4e41-a657-78c94a7ac28d" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cuda:0\n" + ] + } + ], + "source": [ + "print(enc_tensor[\"input_ids\"].device)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "iIcsyrYizBAo", + "outputId": "edd910d4-d43d-4730-dca9-975f666e5975" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "SequenceClassifierOutput(loss=None, logits=tensor([[ 1.7043, 3.3786, -1.8283, 4.4831, -0.1790, -3.0194, 2.7721, -2.4975,\n", + " -4.7531, -3.3341, -2.1064, -5.0834, -3.4248, -5.3879]],\n", + " device='cuda:0'), hidden_states=None, attentions=None)" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "with torch.no_grad(): #optional when doing inference, but it's recommended to do it in order to disable gradient computation to save memory and computation time\n", + " output=model(enc_tensor[\"input_ids\"].unsqueeze(0),attention_mask=enc_tensor[\"attention_mask\"].unsqueeze(0))\n", + "output" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "hhfsGjB_2mux", + "outputId": "3653c274-eef1-48ba-df5d-56693022ec8a" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tensor([[0.8461, 0.9670, 0.1384, 0.9888, 0.4554, 0.0466, 0.9412, 0.0760, 0.0086,\n", + " 0.0344, 0.1085, 0.0062, 0.0315, 0.0046]])\n", + "[[1 1 0 1 0 0 1 0 0 0 0 0 0 0]]\n", + "['A', 'B', 'D', 'G']\n", + "['Anatomy', 'Organisms', 'Chemicals and Drugs', 'Phenomena and Processes']\n" + ] + } + ], + "source": [ + "logits=output.logits\n", + "probas=torch.sigmoid(logits.cpu())\n", + "print(probas)\n", + "pred=np.where(probas>=0.5,1,0)\n", + "print(pred)\n", + "\n", + "pred_tags=[get_tag[i] for i,tag in enumerate(pred.tolist()[0]) if tag==1]\n", + "print(pred_tags)\n", + "interpreted_tags=[main_ref[tag] for tag in pred_tags]\n", + "print(interpreted_tags)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gvn0lTLwD0Eo" + }, + "source": [ + "#####Second example" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "sWwPWQjEDbZH", + "outputId": "40d207dd-6c1e-47fc-cb09-ece2624f7989" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tensor([[0.7674, 0.9700, 0.1592, 0.9937, 0.5032, 0.0169, 0.9591, 0.0516, 0.0065,\n", + " 0.0300, 0.0977, 0.0090, 0.0354, 0.0054]])\n", + "[[1 1 0 1 1 0 1 0 0 0 0 0 0 0]]\n", + "['A', 'B', 'D', 'E', 'G']\n", + "['Anatomy', 'Organisms', 'Chemicals and Drugs', 'Analytical, Diagnostic and Therapeutic Techniques, and Equipment', 'Phenomena and Processes']\n" + ] + } + ], + "source": [ + "abstract2=\"Role of the interferon - inducible IFI16 gene in the induction of ICAM - 1 by TNF - alpha . The Interferon - inducible gene IFI16 , a member of the HIN200 family , is activated by oxidative stress and cell density , in addition to Interferons , and it is implicated in the regulation of endothelial cell proliferation and vessel formation in vitro . We have previously shown that IFI16 is required for proinflammatory gene stimulation by IFN - gamma through the NF - kappaB complex . To examine whether IFI16 induction might be extended to other proinflammatory cytokines such as tumor necrosis factor ( TNF ) - alpha , we used the strategy of the RNA interference to knock down IFI16 express i on , and analyze the capability of TNF - alpha to stimulate intercellular adhesion molecule - 1 ( ICAM - 1 or CD54 ) express i on in the absence of functional IFI16 . Our studies demonstrate that IFI16 mediates ICAM - 1 stimulation by TNF - alpha through the NF - kappaB pathway , thus reinforcing the role of the IFI16 molecule in the inflammation process .\"\n", + "\n", + "encode2=tokenizer(abstract2,is_split_into_words=False)\n", + "enc_tensor2={key:torch.tensor(value).to(mydevice) for key,value in encode2.items()} \n", + "\n", + "with torch.no_grad():\n", + " output2=model(enc_tensor2[\"input_ids\"].unsqueeze(0),attention_mask=enc_tensor2[\"attention_mask\"].unsqueeze(0))\n", + "\n", + "logits=output2.logits\n", + "probas=torch.sigmoid(logits.cpu())\n", + "print(probas)\n", + "pred=np.where(probas>=0.5,1,0)\n", + "print(pred)\n", + "\n", + "pred_tags=[get_tag[i] for i,tag in enumerate(pred.tolist()[0]) if tag==1]\n", + "print(pred_tags)\n", + "interpreted_tags=[main_ref[tag] for tag in pred_tags]\n", + "print(interpreted_tags)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "B1tsx9n9D37q" + }, + "outputs": [], + "source": [ + "###END" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "provenance": [] + }, + "gpuClass": "standard", + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.13" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "017e29c8f4ee42b0a6f54bf091c63f76": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "0580f0da75f74720b1635586b2274c4b": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": "hidden", + "width": null + } + }, + "085daa87d602495ba387505d7addcfd7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "088ac21fdf7e4861b5ffb816c5f1f0cb": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_b1c53c27bfbd4ff18b676c43f58cde5b", + "max": 1, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_9f800503050a4537ba2e2cac44662bbc", + "value": 1 + } + }, + "0a5649e245804023953ad2114e65f933": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_35abfcc74487460695b92748599a6304", + "placeholder": "​", + "style": "IPY_MODEL_4cdc3407a49b42d1b776c6e8f943e543", + "value": " 50000/50000 [08:18<00:00, 103.32 examples/s]" + } + }, + "12c3e050593c4cc5a519d613fa99c6c3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d347390f96784e75945cc51d68f39cec", + "max": 1, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_6743d48d260f44648cc44f4b807900c3", + "value": 1 + } + }, + "1302ca8fba494e8089548b5aa4e7c4bd": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "16aba8f9a11a459f9cf1059efdc12ec9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d2e2ae1d9fd34ff6ae20235d20cac2d7", + "placeholder": "​", + "style": "IPY_MODEL_c41cad9f1efc4bbc80d8c3c4e6c776f8", + "value": " 570/570 [00:00<00:00, 13.6kB/s]" + } + }, + "23812f0e09cf4e57b91df171f66d1f54": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "27302aee438f4637be2daa2c74c478c7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "27bd13b7007443c0b80e240094c3548e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "2949b640914841468038d426ba386dc8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_91f98c2cbb66427c827450fe16a3b581", + "IPY_MODEL_088ac21fdf7e4861b5ffb816c5f1f0cb", + "IPY_MODEL_56e78a2746b440058bc13f4ef4e4e04e" + ], + "layout": "IPY_MODEL_62ede59767c94e27bbc50e759a6aad61" + } + }, + "29a4f5bb2f0f40a8862b03c1b592dc6e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_e07cd85e9b3f4c77907804960cb1b7f7", + "IPY_MODEL_12c3e050593c4cc5a519d613fa99c6c3", + "IPY_MODEL_6357b53dd0e5494cbae0915bbb09d70d" + ], + "layout": "IPY_MODEL_085daa87d602495ba387505d7addcfd7" + } + }, + "2a5e3f0bfd8c4ef5a1f8c400e249b806": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "2bb55e38536140888c3599621f39b928": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "2d91a540467846a181dc1477044f6cf4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "2fd2f67e9bec4bbdb846b9168f64243c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "323a7fff25e140ffa0a0797759e235f0": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_548d6d1baf8d44cca7983b1e2fa30145", + "placeholder": "​", + "style": "IPY_MODEL_27bd13b7007443c0b80e240094c3548e", + "value": "Extracting data files: 100%" + } + }, + "35630fa379304dbc9fafce769b68be46": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "35abfcc74487460695b92748599a6304": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "37d80c0a5bc14d9097112a5ff1c11b96": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "3b61f2e1772c4c83a569ca808b580150": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "3ddc743a17cc42dfaddbd590417fd4f1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_db68936431e842068b7378c75bff17f7", + "IPY_MODEL_b8f8d75e04ba4ac49f48b868a93e56e3", + "IPY_MODEL_0a5649e245804023953ad2114e65f933" + ], + "layout": "IPY_MODEL_82b865bb3b674a549e3b540c88ca7fd7" + } + }, + "3e9041e4729d4c8d9cd1abcbf99fa215": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "40622122a1574b53a03523ea8e49e45e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_3b61f2e1772c4c83a569ca808b580150", + "max": 231508, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_d7554b81b5b040218b281079f606d95f", + "value": 231508 + } + }, + "43136e63ca7348d1994eeb8fa86a16c2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_2a5e3f0bfd8c4ef5a1f8c400e249b806", + "placeholder": "​", + "style": "IPY_MODEL_87f6ca0755044889a48ecc4901ece749", + "value": "Generating train split: " + } + }, + "46507d61346844eeba74910e3fd17d30": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "471b020ec53944b6827fe487657e135c": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "472d4c6210034dd8b2835f27894aee99": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_43136e63ca7348d1994eeb8fa86a16c2", + "IPY_MODEL_eb9c53ff17334912be09fdd689fe2ba8", + "IPY_MODEL_8d79552fcf554659822238a18c496be4" + ], + "layout": "IPY_MODEL_48a7dfd985684a6a86a3225ba58292eb" + } + }, + "48650c3259c646878aa245b564e74237": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_ac62656c960d432f94c1ada2a1e6c3c8", + "placeholder": "​", + "style": "IPY_MODEL_b1aef87d7b104c458b3d52367e38c64b", + "value": " 120M/120M [00:03<00:00, 42.6MB/s]" + } + }, + "48a7dfd985684a6a86a3225ba58292eb": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": "hidden", + "width": null + } + }, + "49702ffa478b46f0a318fca7dac1f28c": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "4cdc3407a49b42d1b776c6e8f943e543": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "4db9a812ea484b5aae744d7f99daf213": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_66269ad51da14492bf589f9e8ed3212a", + "max": 960, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_2fd2f67e9bec4bbdb846b9168f64243c", + "value": 960 + } + }, + "50d2844a0b124e8ea86b487d0e735f09": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "51f15e08de964d6588fee19136177005": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_9f1ad8b2589b4810883cab1b8f3ff403", + "max": 119799320, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_c118d1bf0f7b46ddbaf2edbe615357a3", + "value": 119799320 + } + }, + "540c6cb0c9e6404da39bae3ea3be2d4d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_f0e742d9b2db40e8b57e084de9420c40", + "max": 28, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_f6f9fb55c39a46529329d1620e7d6088", + "value": 28 + } + }, + "548d6d1baf8d44cca7983b1e2fa30145": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "557cdf551504414db384b016a397e259": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "55f38c1e1e1d42ba8dbc167dc25eacd1": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "564a62ba9281479e992567a376ee17ce": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_8896238b49d24f648e23dd721612f7af", + "IPY_MODEL_40622122a1574b53a03523ea8e49e45e", + "IPY_MODEL_a7f5346743ab4ad2945ef4c575be0458" + ], + "layout": "IPY_MODEL_bd93707bd6bd41b991e8c50a0ece8baf" + } + }, + "56e78a2746b440058bc13f4ef4e4e04e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_1302ca8fba494e8089548b5aa4e7c4bd", + "placeholder": "​", + "style": "IPY_MODEL_3e9041e4729d4c8d9cd1abcbf99fa215", + "value": " 1/1 [00:00<00:00, 37.19it/s]" + } + }, + "574ccb2f3f214037b0bf91086b85bd63": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "5802634805bc4654935aed28cf4855a5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "593e3dd323be4dd6881f0ebf16734c26": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "5b5b18a2a7b441b8aee438a4fac1574b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_471b020ec53944b6827fe487657e135c", + "placeholder": "​", + "style": "IPY_MODEL_2d91a540467846a181dc1477044f6cf4", + "value": "Downloading (…)okenizer_config.json: 100%" + } + }, + "5c149ee82a1548da800df4ffe8412195": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "5d3c18f5fceb4eb2b282ca49712681e1": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "5ea87c870f124556a2da90e1dcd80d4d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d434c7b3bd914bf79df5b8ee18c2045d", + "placeholder": "​", + "style": "IPY_MODEL_017e29c8f4ee42b0a6f54bf091c63f76", + "value": " 440M/440M [00:02<00:00, 217MB/s]" + } + }, + "602718a0005d48bc8976a96e1220b91b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_46507d61346844eeba74910e3fd17d30", + "max": 1, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_e1357c899dfc4cc7b243675a5b28c0b9", + "value": 1 + } + }, + "62746b245cc6426ca40e64b207f18764": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_717cb8d537464ad59192cae89d587cef", + "IPY_MODEL_51f15e08de964d6588fee19136177005", + "IPY_MODEL_48650c3259c646878aa245b564e74237" + ], + "layout": "IPY_MODEL_593e3dd323be4dd6881f0ebf16734c26" + } + }, + "62ede59767c94e27bbc50e759a6aad61": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "6357b53dd0e5494cbae0915bbb09d70d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_949fc2a0e36542069885c352a52ddf2a", + "placeholder": "​", + "style": "IPY_MODEL_8c81c573a7ad4cad824281e9db0ae532", + "value": " 1/1 [00:04<00:00, 4.89s/it]" + } + }, + "66269ad51da14492bf589f9e8ed3212a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "66482f353af940cca612735c6f148a71": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "6743d48d260f44648cc44f4b807900c3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "6dadd7a4140d46b6a101274a8560b1f3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "71404edcc0544537a68d4e375834a3fe": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "717cb8d537464ad59192cae89d587cef": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_6dadd7a4140d46b6a101274a8560b1f3", + "placeholder": "​", + "style": "IPY_MODEL_b8960ed31e1f4b33b4bd37c144e19e7e", + "value": "Downloading data: 100%" + } + }, + "767d4718e0584a859937644ba1e6de65": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "79b5773782504dfca6d9cdbefbfe4c4b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_323a7fff25e140ffa0a0797759e235f0", + "IPY_MODEL_602718a0005d48bc8976a96e1220b91b", + "IPY_MODEL_f4431575c50740828c194978237f83e6" + ], + "layout": "IPY_MODEL_55f38c1e1e1d42ba8dbc167dc25eacd1" + } + }, + "7abadd0359364223833b5809140c99db": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "7bb7b488912c41229c4f52c10acf418d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_a491db0de6754701bec1ed0b1dee0b53", + "IPY_MODEL_4db9a812ea484b5aae744d7f99daf213", + "IPY_MODEL_8a7ea158d2324f5b922f83d9446fb11c" + ], + "layout": "IPY_MODEL_66482f353af940cca612735c6f148a71" + } + }, + "7c443b4f825a4d0ca4889262b4c53b06": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_557cdf551504414db384b016a397e259", + "max": 50000, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_eca21fafbb2d450f9b39baa1aaccabd2", + "value": 50000 + } + }, + "8135589bdccc4722b5038697565e0f90": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_dc46a5beefd049cb8a4f1dcf81a97db3", + "placeholder": "​", + "style": "IPY_MODEL_574ccb2f3f214037b0bf91086b85bd63", + "value": "Map: 100%" + } + }, + "82b865bb3b674a549e3b540c88ca7fd7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": "hidden", + "width": null + } + }, + "87f6ca0755044889a48ecc4901ece749": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "8896238b49d24f648e23dd721612f7af": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_a806fe6733374a359662c6a989fc851e", + "placeholder": "​", + "style": "IPY_MODEL_5802634805bc4654935aed28cf4855a5", + "value": "Downloading (…)solve/main/vocab.txt: 100%" + } + }, + "8a7ea158d2324f5b922f83d9446fb11c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_ab40298ef8b64f9c81a4f59cf777a8a3", + "placeholder": "​", + "style": "IPY_MODEL_767d4718e0584a859937644ba1e6de65", + "value": " 960/960 [00:00<00:00, 10.6kB/s]" + } + }, + "8c81c573a7ad4cad824281e9db0ae532": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "8d79552fcf554659822238a18c496be4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_37d80c0a5bc14d9097112a5ff1c11b96", + "placeholder": "​", + "style": "IPY_MODEL_50d2844a0b124e8ea86b487d0e735f09", + "value": " 50000/0 [00:01<00:00, 24662.09 examples/s]" + } + }, + "91f98c2cbb66427c827450fe16a3b581": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_de93611cf1074616be5b92133210c630", + "placeholder": "​", + "style": "IPY_MODEL_92d7ffaf03c844028e5ec5222a586ab2", + "value": "100%" + } + }, + "92d7ffaf03c844028e5ec5222a586ab2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "944379ef1c624513a7572815bffa57e0": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "949fc2a0e36542069885c352a52ddf2a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "9ee44e3b1e97457b812068f8ea6195aa": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "9f1ad8b2589b4810883cab1b8f3ff403": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "9f800503050a4537ba2e2cac44662bbc": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "a256244cf3f740fdbc9618136f426ed6": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a465b55b480444ed8cdb2d70ab50466d": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a46f3a4d96f24d0daf6dab9e63cfa8a9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_a477991f543949c7bb24569d6cbbe8d8", + "IPY_MODEL_d51d0c1236334849b5fc6c3e547360f4", + "IPY_MODEL_16aba8f9a11a459f9cf1059efdc12ec9" + ], + "layout": "IPY_MODEL_c6baaa24df4943f6a7b8be154ef9e18a" + } + }, + "a477991f543949c7bb24569d6cbbe8d8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_27302aee438f4637be2daa2c74c478c7", + "placeholder": "​", + "style": "IPY_MODEL_23812f0e09cf4e57b91df171f66d1f54", + "value": "Downloading (…)lve/main/config.json: 100%" + } + }, + "a491db0de6754701bec1ed0b1dee0b53": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_b8ee6a5794b449e3bb949820c3101795", + "placeholder": "​", + "style": "IPY_MODEL_71404edcc0544537a68d4e375834a3fe", + "value": "Downloading readme: 100%" + } + }, + "a5c81d14bd204b9fab508b7ae315b5d9": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a7f5346743ab4ad2945ef4c575be0458": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_f4487664111b4061b00cf36390d5e119", + "placeholder": "​", + "style": "IPY_MODEL_c89946cdc0f54e0faad8859e28e17ed0", + "value": " 232k/232k [00:00<00:00, 789kB/s]" + } + }, + "a806fe6733374a359662c6a989fc851e": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a99d00ab43454462a01844238ddade8c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_8135589bdccc4722b5038697565e0f90", + "IPY_MODEL_7c443b4f825a4d0ca4889262b4c53b06", + "IPY_MODEL_b382fd8e12664423b8b77ddc63e38020" + ], + "layout": "IPY_MODEL_0580f0da75f74720b1635586b2274c4b" + } + }, + "ab40298ef8b64f9c81a4f59cf777a8a3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "ac62656c960d432f94c1ada2a1e6c3c8": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "ae97967de0574604bcd2e0cc599fb0db": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "afff27a60ead4540aeb63abca824a1c2": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": "20px" + } + }, + "b1aef87d7b104c458b3d52367e38c64b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "b1c53c27bfbd4ff18b676c43f58cde5b": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b382fd8e12664423b8b77ddc63e38020": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_5d3c18f5fceb4eb2b282ca49712681e1", + "placeholder": "​", + "style": "IPY_MODEL_944379ef1c624513a7572815bffa57e0", + "value": " 50000/50000 [00:14<00:00, 3500.22 examples/s]" + } + }, + "b8960ed31e1f4b33b4bd37c144e19e7e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "b8ee6a5794b449e3bb949820c3101795": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b8f8d75e04ba4ac49f48b868a93e56e3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_ddcd7fb8ec2f4b09871542c457983c59", + "max": 50000, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_2bb55e38536140888c3599621f39b928", + "value": 50000 + } + }, + "bd93707bd6bd41b991e8c50a0ece8baf": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "bea9ce0783b34ddd9fdb691342f65679": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "c118d1bf0f7b46ddbaf2edbe615357a3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "c41cad9f1efc4bbc80d8c3c4e6c776f8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "c6baaa24df4943f6a7b8be154ef9e18a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "c89946cdc0f54e0faad8859e28e17ed0": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "d2cfe948df1e4a56b61f50dd1823f682": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d2e2ae1d9fd34ff6ae20235d20cac2d7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d347390f96784e75945cc51d68f39cec": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d434c7b3bd914bf79df5b8ee18c2045d": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d4bc24dabf744f7197a00dc10c77a127": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_5b5b18a2a7b441b8aee438a4fac1574b", + "IPY_MODEL_540c6cb0c9e6404da39bae3ea3be2d4d", + "IPY_MODEL_f44dcab8ac4d4025a0399179be883b37" + ], + "layout": "IPY_MODEL_ae97967de0574604bcd2e0cc599fb0db" + } + }, + "d51d0c1236334849b5fc6c3e547360f4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_a5c81d14bd204b9fab508b7ae315b5d9", + "max": 570, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_eb33df63f64e42a3933400de0d955bc3", + "value": 570 + } + }, + "d67dcac374c74096b6811d04641f13dd": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d68e445c62ef4472a10212f8122fd10e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_49702ffa478b46f0a318fca7dac1f28c", + "placeholder": "​", + "style": "IPY_MODEL_e329dea9634647b2aa840ddbb93973bf", + "value": "Downloading (…)"pytorch_model.bin";: 100%" + } + }, + "d7554b81b5b040218b281079f606d95f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "da0ffcc86fa1438aa0b4151a89bdcd0c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "db68936431e842068b7378c75bff17f7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d2cfe948df1e4a56b61f50dd1823f682", + "placeholder": "​", + "style": "IPY_MODEL_9ee44e3b1e97457b812068f8ea6195aa", + "value": "Map: 100%" + } + }, + "dc46a5beefd049cb8a4f1dcf81a97db3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "ddcd7fb8ec2f4b09871542c457983c59": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "de93611cf1074616be5b92133210c630": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "e015adba4713426584761ca3617c6932": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "e07cd85e9b3f4c77907804960cb1b7f7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_35630fa379304dbc9fafce769b68be46", + "placeholder": "​", + "style": "IPY_MODEL_e015adba4713426584761ca3617c6932", + "value": "Downloading data files: 100%" + } + }, + "e1357c899dfc4cc7b243675a5b28c0b9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "e329dea9634647b2aa840ddbb93973bf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "eb33df63f64e42a3933400de0d955bc3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "eb9c53ff17334912be09fdd689fe2ba8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "info", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_afff27a60ead4540aeb63abca824a1c2", + "max": 1, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_5c149ee82a1548da800df4ffe8412195", + "value": 1 + } + }, + "eca21fafbb2d450f9b39baa1aaccabd2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "f0e742d9b2db40e8b57e084de9420c40": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "f15de53617b54f61a73069be93a2a56e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d67dcac374c74096b6811d04641f13dd", + "max": 440473133, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_da0ffcc86fa1438aa0b4151a89bdcd0c", + "value": 440473133 + } + }, + "f4431575c50740828c194978237f83e6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_a256244cf3f740fdbc9618136f426ed6", + "placeholder": "​", + "style": "IPY_MODEL_bea9ce0783b34ddd9fdb691342f65679", + "value": " 1/1 [00:00<00:00, 40.42it/s]" + } + }, + "f4487664111b4061b00cf36390d5e119": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "f44dcab8ac4d4025a0399179be883b37": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_f754f438d35e421db9ccf52d0c228f0a", + "placeholder": "​", + "style": "IPY_MODEL_7abadd0359364223833b5809140c99db", + "value": " 28.0/28.0 [00:00<00:00, 444B/s]" + } + }, + "f50a069bf0b445a38f809c7872fc2153": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_d68e445c62ef4472a10212f8122fd10e", + "IPY_MODEL_f15de53617b54f61a73069be93a2a56e", + "IPY_MODEL_5ea87c870f124556a2da90e1dcd80d4d" + ], + "layout": "IPY_MODEL_a465b55b480444ed8cdb2d70ab50466d" + } + }, + "f6f9fb55c39a46529329d1620e7d6088": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "f754f438d35e421db9ccf52d0c228f0a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + } + } + } + }, + "nbformat": 4, + "nbformat_minor": 1 +}