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# Licensed under the Apache License, Version 2.0 (the "License");
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import os
import pytest
import transformers

import import_helper
from tokenizer import build_megatron_tokenizer

base_dir = os.path.abspath(os.path.dirname(__file__))


@pytest.mark.ipus(0)
@pytest.mark.skip
def test_tokenzier():
    """
    Test that the GPT2Tokenizer from Huggingface and Megatron will give the same results.
    """
    tokenizer_a = transformers.GPT2Tokenizer.from_pretrained("gpt2")
    tokenizer_b = build_megatron_tokenizer(
        vocab_file=base_dir + "/../tokenizer/gpt2-vocab-50256.json",
        merge_file=base_dir + "/../tokenizer/gpt2-merges-50256.txt",
    )

    text = (
        "Generative Pre-trained Transformer 2 (GPT-2) is an open-source artificial intelligence created"
        "by OpenAI in February 2019.[1][2][3][4] GPT-2 translates text, answers questions, summarizes passages,"
        "[5] and generates text output on a level that, while sometimes indistinguishable from that of humans,[6]"
        "can become repetitive or nonsensical when generating long passages.[7] It is a general-purpose learner;"
        "it was not specifically trained to do any of these tasks, and its ability to perform them is an extension"
        "of its general ability to accurately synthesize the next item in an arbitrary sequence.[8][5] GPT-2 was"
        "created as a 'direct scale-up' of OpenAI's 2018 GPT model,[9] with a ten-fold increase in both its"
        "parameter count and the size of its training dataset.[4]"
    )

    tokens_a = tokenizer_a.encode(text)
    tokens_b = tokenizer_b.encode(text)

    assert tokens_a == tokens_b