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funatsufumiya/wktk_gpt2_aozora_tester_220220.ipynb

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},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/funatsufumiya/ea36bb6dd983783fef04044cec988c3a/wktk_gpt2_aozora_tester_220220.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive', force_remount=True)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "yOsj49J6MhjD",
"outputId": "e078389b-130d-4c40-9beb-442d797471dd"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Mounted at /content/drive\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## 前準備"
],
"metadata": {
"id": "TIQR_EDkMaxB"
}
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "VRK-IsaHfu1V",
"outputId": "63b7046a-489c-4731-e2cd-b97d78786303"
},
"source": [
"# pipのライブラリをインストール\n",
"!pip install git+https://github.com/huggingface/transformers\n",
"!pip install sentencepiece\n",
"!pip install datasets"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting git+https://github.com/huggingface/transformers\n",
" Cloning https://github.com/huggingface/transformers to /tmp/pip-req-build-nh0gr6iy\n",
" Running command git clone -q https://github.com/huggingface/transformers /tmp/pip-req-build-nh0gr6iy\n",
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
" Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n",
"Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (4.62.3)\n",
"Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (4.11.0)\n",
"Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (3.4.2)\n",
"Collecting pyyaml>=5.1\n",
" Downloading PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (596 kB)\n",
"\u001b[K |████████████████████████████████| 596 kB 5.1 MB/s \n",
"\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (1.21.5)\n",
"Collecting sacremoses\n",
" Downloading sacremoses-0.0.47-py2.py3-none-any.whl (895 kB)\n",
"\u001b[K |████████████████████████████████| 895 kB 77.5 MB/s \n",
"\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (2.23.0)\n",
"Collecting tokenizers!=0.11.3,>=0.11.1\n",
" Downloading tokenizers-0.11.5-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (6.8 MB)\n",
"\u001b[K |████████████████████████████████| 6.8 MB 83.2 MB/s \n",
"\u001b[?25hRequirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (21.3)\n",
"Collecting huggingface-hub<1.0,>=0.1.0\n",
" Downloading huggingface_hub-0.4.0-py3-none-any.whl (67 kB)\n",
"\u001b[K |████████████████████████████████| 67 kB 7.0 MB/s \n",
"\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (2019.12.20)\n",
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0,>=0.1.0->transformers==4.17.0.dev0) (3.10.0.2)\n",
"Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=20.0->transformers==4.17.0.dev0) (3.0.7)\n",
"Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->transformers==4.17.0.dev0) (3.7.0)\n",
"Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.17.0.dev0) (1.24.3)\n",
"Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.17.0.dev0) (2.10)\n",
"Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.17.0.dev0) (3.0.4)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.17.0.dev0) (2021.10.8)\n",
"Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.17.0.dev0) (1.15.0)\n",
"Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.17.0.dev0) (1.1.0)\n",
"Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.17.0.dev0) (7.1.2)\n",
"Building wheels for collected packages: transformers\n",
" Building wheel for transformers (PEP 517) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for transformers: filename=transformers-4.17.0.dev0-py3-none-any.whl size=3712360 sha256=63978bfd24928ac80ed913cc326d440b29dce16b4728f31aa47f665f5a9cb9e2\n",
" Stored in directory: /tmp/pip-ephem-wheel-cache-8ah1gvd2/wheels/35/2e/a7/d819e3310040329f0f47e57c9e3e7a7338aa5e74c49acfe522\n",
"Successfully built transformers\n",
"Installing collected packages: pyyaml, tokenizers, sacremoses, huggingface-hub, transformers\n",
" Attempting uninstall: pyyaml\n",
" Found existing installation: PyYAML 3.13\n",
" Uninstalling PyYAML-3.13:\n",
" Successfully uninstalled PyYAML-3.13\n",
"Successfully installed huggingface-hub-0.4.0 pyyaml-6.0 sacremoses-0.0.47 tokenizers-0.11.5 transformers-4.17.0.dev0\n",
"Collecting sentencepiece\n",
" Downloading sentencepiece-0.1.96-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB)\n",
"\u001b[K |████████████████████████████████| 1.2 MB 5.1 MB/s \n",
"\u001b[?25hInstalling collected packages: sentencepiece\n",
"Successfully installed sentencepiece-0.1.96\n",
"Collecting datasets\n",
" Downloading datasets-1.18.3-py3-none-any.whl (311 kB)\n",
"\u001b[K |████████████████████████████████| 311 kB 5.0 MB/s \n",
"\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from datasets) (1.3.5)\n",
"Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from datasets) (21.3)\n",
"Requirement already satisfied: dill in /usr/local/lib/python3.7/dist-packages (from datasets) (0.3.4)\n",
"Collecting xxhash\n",
" Downloading xxhash-2.0.2-cp37-cp37m-manylinux2010_x86_64.whl (243 kB)\n",
"\u001b[K |████████████████████████████████| 243 kB 75.6 MB/s \n",
"\u001b[?25hCollecting fsspec[http]>=2021.05.0\n",
" Downloading fsspec-2022.1.0-py3-none-any.whl (133 kB)\n",
"\u001b[K |████████████████████████████████| 133 kB 89.3 MB/s \n",
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"Requirement already satisfied: pyarrow!=4.0.0,>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (6.0.1)\n",
"Requirement already satisfied: multiprocess in /usr/local/lib/python3.7/dist-packages (from datasets) (0.70.12.2)\n",
"Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (2.23.0)\n",
"Collecting aiohttp\n",
" Downloading aiohttp-3.8.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB)\n",
"\u001b[K |████████████████████████████████| 1.1 MB 78.2 MB/s \n",
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"Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from datasets) (4.11.0)\n",
"Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from datasets) (1.21.5)\n",
"Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (3.4.2)\n",
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (3.10.0.2)\n",
"Requirement already satisfied: pyyaml in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (6.0)\n",
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"Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (2.0.11)\n",
"Collecting asynctest==0.13.0\n",
" Downloading asynctest-0.13.0-py3-none-any.whl (26 kB)\n",
"Collecting frozenlist>=1.1.1\n",
" Downloading frozenlist-1.3.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (144 kB)\n",
"\u001b[K |████████████████████████████████| 144 kB 80.5 MB/s \n",
"\u001b[?25hCollecting multidict<7.0,>=4.5\n",
" Downloading multidict-6.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (94 kB)\n",
"\u001b[K |████████████████████████████████| 94 kB 4.7 MB/s \n",
"\u001b[?25hCollecting yarl<2.0,>=1.0\n",
" Downloading yarl-1.7.2-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (271 kB)\n",
"\u001b[K |████████████████████████████████| 271 kB 89.4 MB/s \n",
"\u001b[?25hCollecting aiosignal>=1.1.2\n",
" Downloading aiosignal-1.2.0-py3-none-any.whl (8.2 kB)\n",
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" Downloading async_timeout-4.0.2-py3-none-any.whl (5.8 kB)\n",
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"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->datasets) (1.15.0)\n",
"Installing collected packages: multidict, frozenlist, yarl, asynctest, async-timeout, aiosignal, fsspec, aiohttp, xxhash, datasets\n",
"Successfully installed aiohttp-3.8.1 aiosignal-1.2.0 async-timeout-4.0.2 asynctest-0.13.0 datasets-1.18.3 frozenlist-1.3.0 fsspec-2022.1.0 multidict-6.0.2 xxhash-2.0.2 yarl-1.7.2\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "OBLk1eWvgx2E",
"outputId": "9b62fdbc-6218-4f1e-c0fd-2afdfd5124f0"
},
"source": [
"#必要なスクリプトを取得\n",
"\n",
"!git clone --depth=1 https://github.com/huggingface/transformers\n",
"!ls ./transformers/examples/pytorch/language-modeling/"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'transformers'...\n",
"remote: Enumerating objects: 2095, done.\u001b[K\n",
"remote: Counting objects: 100% (2095/2095), done.\u001b[K\n",
"remote: Compressing objects: 100% (1742/1742), done.\u001b[K\n",
"remote: Total 2095 (delta 617), reused 801 (delta 306), pack-reused 0\u001b[K\n",
"Receiving objects: 100% (2095/2095), 8.03 MiB | 12.29 MiB/s, done.\n",
"Resolving deltas: 100% (617/617), done.\n",
"README.md\t run_clm_no_trainer.py run_mlm_no_trainer.py\trun_plm.py\n",
"requirements.txt run_clm.py\t\t run_mlm.py\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#ベースモデルをダウンロード\n",
"\n",
"import torch\n",
"import os\n",
"from transformers import AutoModelForCausalLM, AutoTokenizer\n",
"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
"\n",
"print(\"initializing and downloading rinna/japanese-gpt2-medium...\", flush=True)\n",
"tokenizer = AutoTokenizer.from_pretrained(\"rinna/japanese-gpt2-medium\")\n",
"tokenizer.do_lower_case = True\n",
"model = AutoModelForCausalLM.from_pretrained(\"rinna/japanese-gpt2-medium\")\n",
"print(\"\", flush=True)\n",
"print(\"done\", flush=True)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 230,
"referenced_widgets": [
"3af9c6cc202540c38e035548b587264a",
"cc87b9a3435e4524af0a535dce6f073b",
"ef45dc2192a641c9ba03f58ddef4327b",
"1f4cd257742a449ca847e2de03b88f30",
"63afe29d77804ce4979266690e3ca3bc",
"3030ab6510f6461a820af628bd8fb5a6",
"a0e1be66ab2d44e6a6d14257958e28cd",
"228d3b26205f4aa49e3617852e28de1b",
"e513beb3d9054da5817ca84839a783df",
"5196d41e9eb748288f026b24ed3490e6",
"65cb19ce286d42a1832eed8fb96b75e5",
"56fa4515aabf43e5aff0dbd2c9b27d20",
"657cd28b7c864274a268debe64cfda93",
"8b17cf187a1c4d0a9b7bdfaad7db470d",
"00673bd667634490bf693b849d6590e1",
"6fab5dec29574bbaa7c80fd2f7745177",
"05e89cb6f71741ed867e3b76851e1666",
"6813904a75d44aee84f439bb6bbe17fd",
"cadfcbabdbc94dde9d3b25237407698b",
"05f61448cc3b488e8acb8ff80201e2ea",
"68e17ee4b3ac4a82a757b2a793832ba5",
"37954915724d4c239124b49e0ce39d79",
"d44d736165304d91bb094f22ef6633a4",
"77a00bb2a7b74c5d832abdddc10d2f45",
"eed15f0599b0422a96e7ebf1af73fffc",
"ea70c2bdfe78495794c66e164b6d7e91",
"96e7cd740e0e40b581743c48b77b5f76",
"e538959e45f949f481c30ce1d794ef13",
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"3fec08dfda4541db9e86ad497f6fb4ca",
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"88db92caeff24beab9e7452f3b62267f",
"5b7ae96e7b0c4357abcbd735c83a3d6c",
"f8ee757c678a45548c12449ca62e77e4",
"d343502468624bc48327a2103def148c",
"07ca6b5ec5c7431cba5d67c266f5b28c",
"b7508730478d406abba9d02b049a36e9",
"80623635be79457abf60e447c85712ea",
"b7480082e3674a378d7ca3cfd4e693db",
"493f9d0c0e4b4bd186b8d2e992e7cc40",
"b8bfefdff60c40f1925d27cb33821b08",
"cf8f87dfdbbe43aead0cf67ee3aa28d7",
"ffd6df51bbc54c7b8a6c20eeb84fcdd9"
]
},
"id": "7YCBRRsrJTeH",
"outputId": "5a0b4d5a-7707-448d-aab7-09188af03329"
},
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"initializing and downloading rinna/japanese-gpt2-medium...\n"
]
},
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3af9c6cc202540c38e035548b587264a",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"Downloading: 0%| | 0.00/282 [00:00<?, ?B/s]"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "56fa4515aabf43e5aff0dbd2c9b27d20",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"Downloading: 0%| | 0.00/787k [00:00<?, ?B/s]"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d44d736165304d91bb094f22ef6633a4",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"Downloading: 0%| | 0.00/153 [00:00<?, ?B/s]"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "32c605a57f5342968927758dbe8927ca",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"Downloading: 0%| | 0.00/799 [00:00<?, ?B/s]"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "5b7ae96e7b0c4357abcbd735c83a3d6c",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"Downloading: 0%| | 0.00/1.28G [00:00<?, ?B/s]"
]
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"done\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "rJS3Q1INKDsp"
},
"source": [
"## 推論"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "0gnHBNCQWBLC",
"outputId": "568a95c8-8170-4e27-f500-9f914aac56ac"
},
"source": [
"import torch\n",
"import os\n",
"import re\n",
"from transformers import AutoModelForCausalLM, AutoTokenizer\n",
"base_dir = \"/content/drive/Shareddrives/colab/wktk_aozora_220220/output/checkpoint-10000\"\n",
"print(\"base_dir:\", base_dir)\n",
"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
"\n",
"#words = \"ohygzms\"\n",
"#words = \"siebs\"\n",
"#words = \"dnknrnk\"\n",
"#words = \"knbh\"\n",
"#words = \"knbnh\"\n",
"words = \"kynghnhnnksr\"\n",
"\n",
"tokenizer = AutoTokenizer.from_pretrained(\"rinna/japanese-gpt2-medium\")\n",
"tokenizer.do_lower_case = True\n",
"model = AutoModelForCausalLM.from_pretrained(base_dir)\n",
"model.to(device)\n",
"input = tokenizer.encode(f\"===\\n{words}\\n\", return_tensors=\"pt\").to(device)\n",
"output = model.generate(input, do_sample=True, min_length=14, max_length=100, num_return_sequences=10)\n",
"\n",
"out_list = tokenizer.batch_decode(output)\n",
"out_list = list(map(lambda s: re.sub('(?:\\<\\/s\\>)+','', s),out_list))\n",
"out_list = list(map(lambda s: re.sub('(?:\\<unk\\>)+','', s),out_list))\n",
"print(\"\\n\".join(out_list))"
],
"execution_count": 24,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"base_dir: /content/drive/Shareddrives/colab/wktk_aozora_220220/output/checkpoint-10000\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"=== kynghnhnnksr きょうに御本船にはなくする\n",
"=== kynghnhnnksr 今夜のご法事にはいないかしら\n",
"=== kynghnhnnksr 今日の御飯の方に何かしら\n",
"=== kynghnhnnksr 今日の呉府には何か知らん\n",
"=== kynghnhnnksr 急の御方の日中に\n",
"=== kynghnhnnksr 今日の御褒美は何かしら\n",
"=== kynghnhnnksr 今夜の御法事には何かしら\n",
"=== kynghnhnnksr きょうの女は何くれ\n",
"=== kynghnhnnksr 今日の儀は何にか知らん\n",
"=== kynghnhnnksr 今日の御府へ避難なさらん)\n"
]
}
]
}
]
}
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