66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
"""Module for testing dataset sequence packing"""
|
|
|
|
import unittest
|
|
from pathlib import Path
|
|
|
|
from datasets import Dataset, load_dataset
|
|
from transformers import AutoTokenizer
|
|
|
|
from axolotl.datasets import ConstantLengthDataset, TokenizedPromptDataset
|
|
from axolotl.prompt_tokenizers import AlpacaPromptTokenizingStrategy
|
|
from axolotl.prompters import AlpacaPrompter
|
|
|
|
|
|
class TestPacking(unittest.TestCase):
|
|
"""
|
|
Test class for packing dataset sequences
|
|
"""
|
|
|
|
def setUp(self) -> None:
|
|
# pylint: disable=duplicate-code
|
|
self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
|
|
self.tokenizer.add_special_tokens(
|
|
{
|
|
"bos_token": "<s>",
|
|
"eos_token": "</s>",
|
|
"unk_token": "<unk>",
|
|
}
|
|
)
|
|
|
|
def test_resets_attention(self):
|
|
prompter = AlpacaPrompter("chat")
|
|
strat = AlpacaPromptTokenizingStrategy(
|
|
prompter,
|
|
self.tokenizer,
|
|
False,
|
|
2048,
|
|
)
|
|
dateset = load_dataset(
|
|
"json",
|
|
data_files=str(Path(__file__).parent / "fixtures/alpaca/alpaca.json"),
|
|
)["train"]
|
|
dataset = Dataset.from_list(list(TokenizedPromptDataset(strat, dateset)))
|
|
|
|
constant_len_dataset = ConstantLengthDataset(
|
|
self.tokenizer,
|
|
[dataset],
|
|
seq_length=2048,
|
|
)
|
|
packed_dataset = Dataset.from_list(list(constant_len_dataset))
|
|
example = packed_dataset[0]
|
|
next_bos_index = (
|
|
example["input_ids"][1:].index(self.tokenizer.bos_token_id) + 1
|
|
) # add one since we sliced
|
|
|
|
# first example doesn't have mask reset
|
|
assert example["input_ids"][0] == self.tokenizer.bos_token_id
|
|
assert example["attention_mask"][0] == 1
|
|
|
|
# but subsequent one does
|
|
assert example["input_ids"][next_bos_index] == self.tokenizer.bos_token_id
|
|
assert example["attention_mask"][next_bos_index] == 0
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|