forked from moreo/QuaPy
48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
import quapy as qp
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from quapy.data import LabelledCollection
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from sklearn.feature_extraction.text import TfidfVectorizer
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from os.path import join
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import os
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import pickle
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from utils import *
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from tqdm import tqdm
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import shutil
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vector_generation = 'average'
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datapath = './data'
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domain = f'Books-roberta-base-finetuned/checkpoint-1188-{vector_generation}'
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outname = domain.replace('-finetuned', '-finetuned-pkl')
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protocol = 'app'
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print('pickling npy txt files')
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print('from:', join(datapath, domain))
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print('to', join(datapath, outname))
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print('for protocol:', protocol)
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os.makedirs(join(datapath, outname), exist_ok=True)
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os.makedirs(join(datapath, outname, protocol), exist_ok=True)
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os.makedirs(join(datapath, outname, protocol, 'dev_samples'), exist_ok=True)
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os.makedirs(join(datapath, outname, protocol, 'test_samples'), exist_ok=True)
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shutil.copyfile(join(datapath, domain, protocol, 'dev_prevalences.txt'), join(datapath, outname, protocol, 'dev_prevalences.txt'))
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shutil.copyfile(join(datapath, domain, protocol, 'test_prevalences.txt'), join(datapath, outname, protocol, 'test_prevalences.txt'))
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train = load_simple_sample_npytxt(join(datapath, domain), 'training_data', classes=np.arange(5))
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pickle.dump(train, open(join(datapath, outname, 'training_data.pkl'), 'wb'), pickle.HIGHEST_PROTOCOL)
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def transform_folder_samples(protocol, splitname):
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folder_dir=join(datapath, domain, protocol, splitname)
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for i, sample in tqdm(enumerate(load_samples_folder(folder_dir, filter=None, load_fn=load_simple_sample_npytxt, classes=train.classes_))):
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pickle.dump(sample, open(join(datapath, outname, protocol, splitname, f'{i}.pkl'), 'wb'), pickle.HIGHEST_PROTOCOL)
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transform_folder_samples(protocol, 'dev_samples')
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transform_folder_samples(protocol, 'test_samples')
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