| |
| import keyring as kr |
| import os |
| import random |
| import json |
| import re |
| import sys |
| import time |
| from collections import defaultdict |
| from functools import reduce |
|
|
| import codefast as cf |
| import joblib |
| import numpy as np |
| import pandas as pd |
| from rich import print |
| from typing import List, Union, Callable, Set, Dict, Tuple, Optional, Any |
|
|
| from codefast.patterns.pipeline import Pipeline, BeeMaxin |
| |
| from datasets import load_dataset |
|
|
|
|
| class DataLoader(BeeMaxin): |
| def __init__(self) -> None: |
| super().__init__() |
|
|
| def process(self): |
| files = [] |
| for f in cf.io.walk('jsons/'): |
| files.append(f) |
| return files |
|
|
|
|
| class ToCsv(BeeMaxin): |
| def to_csv(self, json_file: str): |
| texts, labels = [], [] |
| with open(json_file, 'r') as f: |
| for line in f: |
| line = json.loads(line) |
| texts.append(line['text']) |
| _label = ' '.join(line['labels']) |
| labels.append(_label) |
| task_name = cf.io.basename(json_file).replace('.json', '') |
| return pd.DataFrame({'text': texts, 'labels': labels, |
| 'task_name': task_name}) |
|
|
| def process(self, files: List[str]): |
| """ Merge all ner data into a train.csv |
| """ |
| df = pd.DataFrame() |
| for f in files: |
| cf.info({ |
| 'message': f'processing {f}' |
| }) |
| newdf = self.to_csv(f) |
| df = pd.concat([df, newdf], axis=0) |
| df.to_csv('train.csv', index=False) |
| df.sample(10).to_csv('dev.csv', index=False) |
| df.sample(10).to_csv('test.csv', index=False) |
|
|
|
|
| if __name__ == '__main__': |
| pl = Pipeline( |
| [ |
| ('dloader', DataLoader()), |
| ('csv converter', ToCsv()) |
| ] |
| ) |
| pl.gather() |
|
|