from transformers import pipeline

pipe = pipeline('text-classification', model="olczig/irony-polish-detection", tokenizer = "olczig/irony-polish-detection")

def irony_prediction(data):
    result = pipe(data)
    return result

def clear_data(data):
    data = [i.replace('#','').
            replace('@','').
            replace('\uf8ff','').
            replace('\t','').
            replace('\"','').
            replace('\U000fe329','').
            replace('\U000fe35b','').
            replace('\U000fe4ef','').
            replace('\U000fe341','')
            for i in data['sentences']]
    return data

def count_predictions(predictions):
    l0 = 0
    l1 = 0
    all = {}

    for i in predictions:
        if i['label'] == 'LABEL_0':
            l0 += 1
        if i['label'] == 'LABEL_1':
            l1 += 1

    all['irony'] = l1
    all['non_irony'] = l0

    return all