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Feat(test): Add tests for alpaca chatml prompt tokenizer #1088

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merged 13 commits into from
Jan 23, 2024
Merged

Feat(test): Add tests for alpaca chatml prompt tokenizer #1088

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draft for adding test for tokenizer
JohanWork Jan 10, 2024
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clean up
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clean up
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fix pre commit
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cd2cda3
fix pylint
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Revert "fix pylint"
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add pylint exception for pytest fixture
JohanWork Jan 14, 2024
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JohanWork Jan 15, 2024
59ce90f
update spelling and import promptstyle
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clean up
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add fmt:on
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343 changes: 343 additions & 0 deletions tests/prompt_strategies/test_alpacha.py
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Original file line number Diff line number Diff line change
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"""
Test module for alpacha integration w chatml
"""
import pytest
from datasets import Dataset
from tokenizers import AddedToken
from transformers import AutoTokenizer

from axolotl.datasets import TokenizedPromptDataset
from axolotl.prompt_tokenizers import AlpacaPromptTokenizingStrategy
from axolotl.prompters import AlpacaPrompter


@pytest.fixture(name="alpacha_dataset")
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def fixture_alpacha_dataset():
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return Dataset.from_list(
[
{
"instruction": "Evaluate this sentence for spelling and grammar mistakes",
"input": "He finnished his meal and left the resturant",
"output": "He finished his meal and left the restaurant.",
}
]
)


@pytest.fixture(name="tokenizer")
def fixture_tokenizer():
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
tokenizer.add_special_tokens(
{
"eos_token": AddedToken(
"<|im_end|>", rstrip=False, lstrip=False, normalized=False
)
}
)
tokenizer.add_tokens(
[
AddedToken("<|im_start|>", rstrip=False, lstrip=False, normalized=False),
]
)

return tokenizer


class TestAlpacha:
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"""
Test class for alpacha prompter
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"""

def test_no_double_im_end(self, alpacha_dataset, tokenizer):
strategy = AlpacaPromptTokenizingStrategy(
AlpacaPrompter(prompt_style="chatml"),
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tokenizer,
False, # train_on_inputs
2048, # sequence_len
)

dataset_wrapper = TokenizedPromptDataset(
strategy, alpacha_dataset, process_count=1
)

input_ids = dataset_wrapper[0]["input_ids"]

assert input_ids == [
1,
32001,
1587,
13,
20548,
336,
349,
396,
13126,
369,
13966,
264,
3638,
28725,
5881,
1360,
395,
396,
2787,
369,
5312,
3629,
2758,
28723,
12018,
264,
2899,
369,
6582,
1999,
2691,
274,
272,
2159,
28723,
32000,
28705,
13,
32001,
2188,
13,
16627,
11931,
456,
12271,
354,
668,
3572,
304,
18756,
3479,
17179,
13,
2428,
854,
28711,
1497,
516,
11314,
304,
1749,
272,
1846,
324,
440,
32000,
28705,
13,
32001,
13892,
13,
650,
5967,
516,
11314,
304,
1749,
272,
9926,
28723,
32000,
]

def test_no_train_on_input(self, alpacha_dataset, tokenizer):
strategy = AlpacaPromptTokenizingStrategy(
AlpacaPrompter(prompt_style="chatml"),
tokenizer,
False, # train_on_inputs
2048, # sequence_len
)

dataset_wrapper = TokenizedPromptDataset(
strategy, alpacha_dataset, process_count=1
)

labels = dataset_wrapper[0]["labels"]

assert labels == [
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
650,
5967,
516,
11314,
304,
1749,
272,
9926,
28723,
32000,
]

def test_w_train_on_input(self, alpacha_dataset, tokenizer):
strategy = AlpacaPromptTokenizingStrategy(
AlpacaPrompter(prompt_style="chatml"),
tokenizer,
True, # train_on_inputs
2048, # sequence_len
)

dataset_wrapper = TokenizedPromptDataset(
strategy, alpacha_dataset, process_count=1
)

labels = dataset_wrapper[0]["labels"]

assert labels == [
1,
32001,
1587,
13,
20548,
336,
349,
396,
13126,
369,
13966,
264,
3638,
28725,
5881,
1360,
395,
396,
2787,
369,
5312,
3629,
2758,
28723,
12018,
264,
2899,
369,
6582,
1999,
2691,
274,
272,
2159,
28723,
32000,
28705,
13,
32001,
2188,
13,
16627,
11931,
456,
12271,
354,
668,
3572,
304,
18756,
3479,
17179,
13,
2428,
854,
28711,
1497,
516,
11314,
304,
1749,
272,
1846,
324,
440,
32000,
28705,
13,
32001,
13892,
13,
650,
5967,
516,
11314,
304,
1749,
272,
9926,
28723,
32000,
]
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