Files
axolotl/tests/test_tokenizers.py
Wing Lian cada93cee5 upgrade transformers==5.3.0 trl==0.29.0 kernels (#3459)
* upgrade transformers==5.3.0 trl==0.29.0 kernels

* use latest deepspeed fixes

* use corect image for cleanup

* fix test outputs for tokenizer fixes upstream

* fix import:

* keep trl at 0.28.0

* handle updated API

* use latest trl since 0.28.0 doesn't work with latest transformers

* use trl experimental for pad to length

* monkeypatch trl with ORPOTrainer so liger doesn't croak

* upgrade accelerate

* more fixes

* move patch for orpotrainer

* load the imports later

* remove use_logits_to_keep

* fix loss_type arg as a list

* fetch hf cache from s3

* just manually download the missing model for now

* lint for pre-commit update

* a few more missing models on disk

* fix: loss_type internally now list

* fix: remove deprecated code and raise deprecate

* fix: remove unneeded blocklist

* fix: remove reliance on transformers api to find package available

* chore: refactor shim for less sideeffect

* fix: silent trl experimental warning

---------

Co-authored-by: NanoCode012 <nano@axolotl.ai>
2026-03-06 09:11:20 -05:00

165 lines
5.1 KiB
Python

"""
Test cases for the tokenizer loading
"""
import unittest
import pytest
from axolotl.loaders import load_tokenizer
from axolotl.utils.dict import DictDefault
from tests.hf_offline_utils import enable_hf_offline
class TestTokenizers:
"""
test class for the load_tokenizer fn
"""
@pytest.mark.skip("LlamaTokenizer no longer has a Fast/Slow tokenizer")
@enable_hf_offline
def test_default_use_fast(self):
cfg = DictDefault(
{
"tokenizer_config": "huggyllama/llama-7b",
}
)
tokenizer = load_tokenizer(cfg)
assert "Fast" in tokenizer.__class__.__name__
@pytest.mark.skip("LlamaTokenizer no longer has a Fast/Slow tokenizer")
@enable_hf_offline
def test_dont_use_fast(self):
cfg = DictDefault(
{
"tokenizer_config": "huggyllama/llama-7b",
"tokenizer_use_fast": False,
}
)
tokenizer = load_tokenizer(cfg)
assert "Fast" not in tokenizer.__class__.__name__
@enable_hf_offline
def test_special_tokens_modules_to_save(self):
# setting special_tokens to new token
cfg = DictDefault(
{
"tokenizer_config": "huggyllama/llama-7b",
"adapter": "lora",
"special_tokens": {"bos_token": "[INST]"},
}
)
with pytest.raises(
ValueError,
match=r".*Please set lora_modules_to_save*",
):
load_tokenizer(cfg)
# setting special_tokens but not changing from default
cfg = DictDefault(
{
"tokenizer_config": "huggyllama/llama-7b",
"adapter": "lora",
"special_tokens": {"bos_token": "<s>"},
}
)
load_tokenizer(cfg)
# non-adapter setting special_tokens
cfg = DictDefault(
{
"tokenizer_config": "huggyllama/llama-7b",
"special_tokens": {"bos_token": "[INST]"},
}
)
load_tokenizer(cfg)
@enable_hf_offline
def test_add_additional_special_tokens(self):
cfg = DictDefault(
{
"tokenizer_config": "huggyllama/llama-7b",
"special_tokens": {"additional_special_tokens": ["<|im_start|>"]},
}
)
tokenizer = load_tokenizer(cfg)
assert "LlamaTokenizer" in tokenizer.__class__.__name__
assert tokenizer("<|im_start|>user")["input_ids"] == [1, 32000, 1792]
assert len(tokenizer) == 32001
# ensure reloading the tokenizer again from cfg results in same vocab length
tokenizer = load_tokenizer(cfg)
assert len(tokenizer) == 32001
@enable_hf_offline
def test_added_tokens_overrides(self, temp_dir):
cfg = DictDefault(
{
# use with tokenizer that has reserved_tokens in added_tokens
"tokenizer_config": "NousResearch/Llama-3.2-1B",
"added_tokens_overrides": {
128041: "RANDOM_OVERRIDE_1",
128042: "RANDOM_OVERRIDE_2",
},
"output_dir": temp_dir,
}
)
tokenizer = load_tokenizer(cfg)
assert tokenizer.encode("RANDOM_OVERRIDE_1", add_special_tokens=False) == [
128041
]
assert tokenizer.encode("RANDOM_OVERRIDE_2", add_special_tokens=False) == [
128042
]
assert (
tokenizer.decode([128041, 128042]) == "RANDOM_OVERRIDE_1RANDOM_OVERRIDE_2"
)
@pytest.mark.skip("FIXME slow test sdist py3.11 + torch2.8.0")
@enable_hf_offline
def test_added_tokens_overrides_gemma3(self, temp_dir):
cfg = DictDefault(
{
# use with tokenizer that has reserved_tokens in added_tokens
"tokenizer_config": "mlx-community/gemma-3-4b-it-8bit",
"added_tokens_overrides": {
256001: "RANDOM_OVERRIDE_1",
256002: "RANDOM_OVERRIDE_2",
},
"output_dir": temp_dir,
}
)
tokenizer = load_tokenizer(cfg)
assert tokenizer.encode("RANDOM_OVERRIDE_1", add_special_tokens=False) == [
256001
]
assert tokenizer.encode("RANDOM_OVERRIDE_2", add_special_tokens=False) == [
256002
]
assert (
tokenizer.decode([256001, 256002]) == "RANDOM_OVERRIDE_1RANDOM_OVERRIDE_2"
)
@enable_hf_offline
def test_added_tokens_overrides_with_toolargeid(self, temp_dir):
cfg = DictDefault(
{
# use with tokenizer that has reserved_tokens in added_tokens
"tokenizer_config": "HuggingFaceTB/SmolLM2-135M",
"added_tokens_overrides": {1000000: "BROKEN_RANDOM_OVERRIDE_1"},
"output_dir": temp_dir,
}
)
with pytest.raises(
ValueError, match=r".*Token ID 1000000 not found in added_tokens.*"
):
load_tokenizer(cfg)
if __name__ == "__main__":
unittest.main()