pad_test.py

from transformers import AutoTokenizer

# Sample tokenizer
tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')

data = [{'input_ids': [2, 892, 19647, 235307, 67444, 1452, 60059, 235292, 108, 41911, 692, 708, 25890, 11898, 235269, 861, 6911, 603, 577, 2027, 235283, 53013, 685, 25890, 11898, 1134, 235269, 11637, 575, 3403, 25890, 11898, 235303, 235256, 3127, 6789, 235265, 108, 2045, 798, 1717, 25890, 11898, 235303, 235256, 3824, 578, 6789, 575, 573, 777, 4858, 603, 573, 4807, 576, 573, 14584, 235303, 2725, 235265, 108, 5041, 674, 25890, 11898, 235303, 235256, 7401, 578, 6789, 603, 1297, 12918, 577, 692, 235265, 108, 2045, 1412, 3418, 861, 1963, 577, 7914, 25890, 11898, 235303, 235256, 6789, 575, 476, 1703, 674, 8661, 675, 1024, 3285, 29881, 235265, 108, 54051, 235269, 22522, 573, 12836, 235303, 235256, 4158, 1746, 578, 75712, 603, 8727, 591, 235249, 235265, 235264, 1173, 749, 780, 17399, 1212, 1156, 1461, 919, 3303, 1180, 1794, 846, 109, 4858, 603, 573, 4807, 576, 736, 14584, 235292, 108, 45475, 235292, 7020, 46903, 4664, 696, 476, 24981, 12279, 4591, 108, 37663, 235292, 25890, 11898, 578, 66135, 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data = [
    {
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        'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
        'labels': [9766, 2314, 235298, 1425, 1192, 664, 53013, 824, 664, 10952, 1192, 664]
    },
    {
        'input_ids': [2, 892, 19647, 235307, 67444, 1452, 60059, 235292, 108, 41911, 692, 708, 25890, 11898],
        'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
        'labels': [9766, 2314, 235298, 1425, 1192, 664, 53013, 824, 664, 10952, 1192, 664, 2045, 235303]
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]

pad_kwargs = {
    'padding': True,
    'max_length': 512,
    'pad_to_multiple_of': None,
    'return_tensors': 'pt'
}

padded = tokenizer.pad(data, **pad_kwargs)