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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "87270bc7-2da0-490e-be8a-8cb06f38507b",
"metadata": {},
"outputs": [],
"source": [
"from flair.datasets.sequence_labeling import ColumnCorpus\n",
"\n",
"from pathlib import Path"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "08ebe948-4179-4a75-8c6b-0e2fcad293d7",
"metadata": {},
"outputs": [],
"source": [
"columns = {0: \"text\", 2: \"ner\"}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "af10c49b-002a-41f4-afde-172ac07251c0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2024-03-25 12:57:38,583 Reading data from .\n",
"2024-03-25 12:57:38,585 Train: train.tsv\n",
"2024-03-25 12:57:38,586 Dev: dev.tsv\n",
"2024-03-25 12:57:38,586 Test: test.tsv\n"
]
}
],
"source": [
"corpus = ColumnCorpus(\".\",\n",
" column_format=columns,\n",
" train_file=\"train.tsv\",\n",
" dev_file=\"dev.tsv\",\n",
" test_file=\"test.tsv\",\n",
" comment_symbol=None)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "efd08709-9308-4244-a730-0d51b738520c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Corpus: 758 train + 94 dev + 96 test sentences'"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"str(corpus)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "6d857c95-ae9f-4aab-803a-0a7e03ff632d",
"metadata": {},
"outputs": [],
"source": [
"base_path = Path(\"./prepared-data-and-code/\")\n",
"\n",
"indices_for_split = {\n",
" \"train\": base_path / \"train_indices.txt\",\n",
" \"dev\": base_path / \"valid_indices.txt\",\n",
" \"test\": base_path / \"test_indices.txt\",\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "2529666f-793f-4d8c-a7aa-9b7d83975310",
"metadata": {},
"outputs": [],
"source": [
"def get_number_of_total_indices(filename: str) -> int:\n",
" indices_counter = 0\n",
" with open(filename, \"rt\") as f_p:\n",
" for line in f_p:\n",
" line = line.strip()\n",
" if not line:\n",
" continue\n",
" indices_counter += 1\n",
" return indices_counter"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "49a69247-ef66-445b-b9e8-adcaac282e14",
"metadata": {},
"outputs": [],
"source": [
"train_indices = get_number_of_total_indices(indices_for_split[\"train\"])\n",
"dev_indices = get_number_of_total_indices(indices_for_split[\"dev\"])\n",
"test_indices = get_number_of_total_indices(indices_for_split[\"test\"])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "fb22489b-07d2-4403-a30c-6d92f00d252e",
"metadata": {},
"outputs": [],
"source": [
"assert len(corpus.train) == train_indices\n",
"assert len(corpus.dev) == dev_indices\n",
"assert len(corpus.test) == test_indices"
]
}
],
"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": "3.11.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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