Upload inferenceNotebook.ipynb

inferenceNotebook.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e12b9784-0a73-447c-bd95-5c4db12213ec",
+   "metadata": {},
+   "source": [
+    "## Load "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "94c34109-799b-4094-934b-85df33a3be99",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import transformers\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import torch\n",
+    "from transformers import BertTokenizer\n",
+    "\n",
+    "# Path of bert model\n",
+    "path = '/home/colombo_phd/ItalianLaws/Data/BERT-Domains/'\n",
+    "\n",
+    "# label df to convert token to string\n",
+    "label = pd.read_csv(path +'label_tokens.csv', sep = ';')\n",
+    "\n",
+    "# Load model\n",
+    "if torch.cuda.is_available():\n",
+    "    model = torch.load('bert_model')\n",
+    "else:\n",
+    "    model = torch.load(path +'bert_model', map_location=torch.device('cpu'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8df905b-9a7b-46ec-8aab-adb15b50aad5",
+   "metadata": {},
+   "source": [
+    "## String to evaluate - title of the law"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "5868b342-3161-4862-b269-1d4959359d48",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "title = 'Regolamento per il commercio di prodotti agricoli in europa'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3c2d173a-4702-4fb3-93f8-c1ea366bdc41",
+   "metadata": {},
+   "source": [
+    "## Run model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "d57af582-61bc-4be9-b305-63a40ede1311",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tokenizer = BertTokenizer.from_pretrained('bert-base-uncased', do_lower_case=True)\n",
+    "encoded_dict = tokenizer.encode_plus(\n",
+    "                    title,\n",
+    "                    add_special_tokens = True,\n",
+    "                    max_length = 389,\n",
+    "                    truncation=True,\n",
+    "                    pad_to_max_length = True,\n",
+    "                    return_attention_mask = True,\n",
+    "                    return_tensors = 'pt',\n",
+    "                )\n",
+    "test_input_ids = torch.cat([encoded_dict['input_ids']], dim=0)\n",
+    "test_attention_masks = torch.cat([encoded_dict['attention_mask']], dim=0)\n",
+    "\n",
+    "b_input_ids = test_input_ids.to(device)\n",
+    "b_input_mask = test_attention_masks.to(device)\n",
+    "with torch.no_grad():\n",
+    "    output= model(b_input_ids,\n",
+    "                            token_type_ids=None,\n",
+    "                            attention_mask=b_input_mask)\n",
+    "    logits = output.logits\n",
+    "    logits = logits.detach().cpu().numpy()\n",
+    "    pred_flat = np.argmax(logits, axis=1).flatten()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bbf3114a-c0ad-411c-b35b-1d7ec922035d",
+   "metadata": {},
+   "source": [
+    "## Derive domain"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "c2e3004b-d735-4462-bbda-6bdb02586102",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'economia'"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "label[label['label']== pred_flat[0]]['Ministries'].iloc[0]"
+   ]
+  }
+ ],
+ "metadata": {
+  "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": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}