bertviz_summary_my_bert.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bertviz import attention, visualization\n",
    "import torch\n",
    "from mptb.models.bert import Config\n",
    "from mptb.models.embed_projection_albert import EmbedProjectionAlbertModel\n",
    "from mptb.tokenization.tokenization_sp_pos import FullTokenizer\n",
    "from IPython.display import display\n",
    "\n",
    "tokenizer = FullTokenizer(vocab_file='data/wiki-ja_1003.vocab',model_file='data/wiki-ja_1003.model')\n",
    "model_cfg = Config.from_json('data/albert_base.json', len(tokenizer))\n",
    "model = EmbedProjectionAlbertModel(model_cfg)\n",
    "model.load_state_dict(torch.load('data/albert_base.pt', map_location='cpu'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%javascript\n",
    "require.config({\n",
    "  paths: {\n",
    "      d3: '//cdnjs.cloudflare.com/ajax/libs/d3/3.4.8/d3.min'\n",
    "  }\n",
    "});\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def call_html():\n",
    "  import IPython\n",
    "  display(IPython.core.display.HTML('''\n",
    "        <script src=\"/static/components/requirejs/require.js\"></script>\n",
    "        <script>\n",
    "          requirejs.config({\n",
    "            paths: {\n",
    "              base: '/static/base',\n",
    "              \"d3\": \"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.8/d3.min\",\n",
    "              jquery: '//ajax.googleapis.com/ajax/libs/jquery/2.0.0/jquery.min',\n",
    "            },\n",
    "          });\n",
    "        </script>\n",
    "        '''))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence_a = \"吾輩は猫である\"\n",
    "sentence_b = \"名前はまだ無い\"\n",
    "attention_visualizer = visualization.AttentionVisualizer(model, tokenizer)\n",
    "tokens_a, tokens_b, attn = attention_visualizer.get_viz_data(sentence_a, sentence_b)\n",
    "call_html()\n",
    "attention.show(tokens_a, tokens_b, attn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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