Files
axolotl/tests/conftest.py
Wing Lian fc4e37920b transformers v5 upgrade (#3272)
* Prepare for transformers v5 upgrade

* fix hf cli

* update for hf hub changes

* fix tokenizer apply_chat_template args

* remap include_tokens_per_second

* fix tps

* handle migration for warmup

* use latest hf hub

* Fix scan -> ls

* fix import

* fix for renaming of mistral common tokenizer -> backend

* update for fixed tokenziation for llama

* Skip phi35 tests for now

* remove mistral patch fixed upstream in huggingface/transformers#41439

* use namespacing for patch

* don't rely on sdist for e2e tests for now

* run modal ci without waiting too

* Fix dep for ci

* fix imports

* Fix fp8 check

* fsdp2 fixes

* fix version handling

* update fsdp version tests for new v5 behavior

* Fail multigpu tests after 3 failures

* skip known v5 broken tests for now and cleanup

* bump deps

* unmark skipped test

* re-enable test_fsdp_qlora_prequant_packed test

* increase multigpu ci timeout

* skip broken gemma3 test

* reduce timout back to original 120min now that the hanging test is skipped

* fix for un-necessary collator for pretraining with bsz=1

* fix: safe_serialization deprecated in transformers v5 rc01 (#3318)

* torch_dtype deprecated

* load model in float32 for consistency with tests

* revert some test fixtures back

* use hf cache ls instead of scan

* don't strip fsdp_version

more fdsp_Version fixes for v5
fix version in fsdp_config
fix aliasing
fix fsdp_version check
check fsdp_version is 2 in both places

* Transformers v5 rc2 (#3347)

* bump dep

* use latest fbgemm, grab model config as part of fixture, un-skip test

* import AutoConfig

* don't need more problematic autoconfig when specifying config.json manually

* add fixtures for argilla ultrafeedback datasets

* download phi4-reasoning

* fix arg

* update tests for phi fast tokenizer changes

* use explicit model types for gemma3

---------

Co-authored-by: Wing Lian <wing@axolotl.ai>

* fix: AutoModelForVision2Seq -> AutoModelForImageTextToText

* chore: remove duplicate

* fix: attempt fix gemma3 text mode

* chore: lint

* ga release of v5

* need property setter for name_or_path for mistral tokenizer

* vllm not compatible with transformers v5

* setter for chat_template w mistral too

---------

Co-authored-by: NanoCode012 <nano@axolotl.ai>
Co-authored-by: salman <salman.mohammadi@outlook.com>
2026-01-27 17:08:24 -05:00

620 lines
18 KiB
Python

"""Shared pytest fixtures"""
import functools
import importlib
import logging
import os
import shutil
import sys
import tempfile
import time
from pathlib import Path
from typing import Generator
import datasets
import pytest
import requests
import torch
from huggingface_hub import snapshot_download
from huggingface_hub.errors import LocalEntryNotFoundError
from tokenizers import AddedToken
from transformers import AutoTokenizer
from axolotl.utils.dict import DictDefault
from tests.hf_offline_utils import (
enable_hf_offline,
hf_offline_context,
)
logging.getLogger("filelock").setLevel(logging.CRITICAL)
def retry_on_request_exceptions(max_retries=3, delay=1):
def decorator(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
for attempt in range(max_retries):
try:
return func(*args, **kwargs)
except (
requests.exceptions.ReadTimeout,
requests.exceptions.ConnectionError,
requests.exceptions.HTTPError,
) as exc:
if attempt < max_retries - 1:
wait = 2**attempt * delay # in seconds
time.sleep(wait)
else:
raise exc
return wrapper
return decorator
@retry_on_request_exceptions(max_retries=3, delay=5)
def snapshot_download_w_retry(*args, **kwargs):
"""
download a model or dataset from HF Hub, retrying in requests failures. We also try to fetch it from the local
cache first using hf_hub_offline to avoid hitting HF Hub API rate limits. If it doesn't exist in the cache,
disable hf_hub_offline and actually fetch from the hub
"""
with hf_offline_context(True):
try:
return snapshot_download(*args, local_files_only=True, **kwargs)
except LocalEntryNotFoundError:
pass
with hf_offline_context(False):
return snapshot_download(*args, **kwargs)
@pytest.fixture(scope="session", autouse=True)
def download_ds_fixture_bundle():
ds_dir = snapshot_download_w_retry(
"axolotl-ai-internal/axolotl-oss-dataset-fixtures", repo_type="dataset"
)
return Path(ds_dir)
@pytest.fixture(scope="session", autouse=True)
def download_smollm2_135m_model():
# download the model
snapshot_download_w_retry("HuggingFaceTB/SmolLM2-135M", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
def download_smollm2_135m_instruct_model():
# download the model
snapshot_download_w_retry("HuggingFaceTB/SmolLM2-135M-Instruct", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
def download_smollm2_135m_gptq_model():
# download the model
snapshot_download_w_retry("lilmeaty/SmolLM2-135M-Instruct-GPTQ", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
def download_qwen_2_5_half_billion_model():
# download the model
snapshot_download_w_retry("Qwen/Qwen2.5-0.5B", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
def download_qwen3_half_billion_model():
# download the model
snapshot_download_w_retry("Qwen/Qwen3-0.6B", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
def download_tatsu_lab_alpaca_dataset():
# download the dataset
snapshot_download_w_retry("tatsu-lab/alpaca", repo_type="dataset")
@pytest.fixture(scope="session", autouse=True)
def download_mhenrichsen_alpaca_2k_dataset():
# download the dataset
snapshot_download_w_retry("mhenrichsen/alpaca_2k_test", repo_type="dataset")
@pytest.fixture(scope="session", autouse=True)
def download_mhenrichsen_alpaca_2k_w_revision_dataset():
# download the dataset
snapshot_download_w_retry(
"mhenrichsen/alpaca_2k_test", repo_type="dataset", revision="d05c1cb"
)
@pytest.fixture(scope="session", autouse=True)
def download_mlabonne_finetome_100k_dataset():
# download the dataset
snapshot_download_w_retry("mlabonne/FineTome-100k", repo_type="dataset")
@pytest.fixture(scope="session", autouse=True)
def download_argilla_distilabel_capybara_dpo_7k_binarized_dataset():
# download the dataset
snapshot_download_w_retry(
"argilla/distilabel-capybara-dpo-7k-binarized", repo_type="dataset"
)
@pytest.fixture(scope="session", autouse=True)
def download_argilla_distilabel_intel_orca_dpo_dataset():
# download the dataset
snapshot_download_w_retry(
"argilla/distilabel-intel-orca-dpo-pairs", repo_type="dataset"
)
@pytest.fixture(scope="session", autouse=True)
def download_argilla_ultrafeedback_binarized_preferences_cleaned_dataset():
# download the dataset
snapshot_download_w_retry(
"argilla/ultrafeedback-binarized-preferences-cleaned", repo_type="dataset"
)
@pytest.fixture(scope="session", autouse=True)
def download_argilla_ultrafeedback_binarized_preferences_cleaned_kto_dataset():
# download the dataset
snapshot_download_w_retry(
"argilla/ultrafeedback-binarized-preferences-cleaned-kto", repo_type="dataset"
)
# @pytest.fixture(scope="session", autouse=True)
# def download_fozzie_alpaca_dpo_dataset():
# # download the dataset
# snapshot_download_w_retry(
# "fozziethebeat/alpaca_messages_2k_dpo_test", repo_type="dataset"
# )
# snapshot_download_w_retry(
# "fozziethebeat/alpaca_messages_2k_dpo_test",
# repo_type="dataset",
# revision="ea82cff",
# )
# @pytest.fixture(scope="session")
# @disable_hf_offline
# def dataset_fozzie_alpaca_dpo_dataset(
# download_fozzie_alpaca_dpo_dataset,
# ):
# return load_dataset("fozziethebeat/alpaca_messages_2k_dpo_test", split="train")
#
#
# @pytest.fixture(scope="session")
# @disable_hf_offline
# def dataset_fozzie_alpaca_dpo_dataset_rev_ea82cff(
# download_fozzie_alpaca_dpo_dataset,
# ):
# return load_dataset(
# "fozziethebeat/alpaca_messages_2k_dpo_test", split="train", revision="ea82cff"
# )
@pytest.fixture(scope="session", autouse=True)
def download_arcee_ai_distilabel_intel_orca_dpo_pairs_dataset():
# download the dataset
snapshot_download_w_retry(
"arcee-ai/distilabel-intel-orca-dpo-pairs-binarized", repo_type="dataset"
)
@pytest.fixture(scope="session", autouse=True)
def download_argilla_dpo_pairs_dataset():
# download the dataset
snapshot_download_w_retry(
"argilla/distilabel-intel-orca-dpo-pairs", repo_type="dataset"
)
@pytest.fixture(scope="session", autouse=True)
def download_tiny_shakespeare_dataset():
# download the dataset
snapshot_download_w_retry("winglian/tiny-shakespeare", repo_type="dataset")
@pytest.fixture(scope="session", autouse=True)
def download_evolkit_kd_sample_dataset():
# download the dataset
snapshot_download_w_retry(
"axolotl-ai-co/evolkit-logprobs-pipeline-75k-v2-sample", repo_type="dataset"
)
@pytest.fixture(scope="session", autouse=True)
def download_deepseek_model_fixture():
snapshot_download_w_retry("axolotl-ai-co/DeepSeek-V3-11M", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
def download_huggyllama_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"huggyllama/llama-7b",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_llama33_70b_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"axolotl-ai-co/Llama-3.3-70B-Instruct-tokenizer",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_llama_1b_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"NousResearch/Llama-3.2-1B",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_llama3_8b_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"NousResearch/Meta-Llama-3-8B",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_llama3_8b_instruct_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"NousResearch/Meta-Llama-3-8B-Instruct",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_phi_35_mini_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"microsoft/Phi-3.5-mini-instruct",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_phi_4_reasoning_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"microsoft/Phi-4-reasoning",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_phi_3_medium_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"microsoft/Phi-3-medium-128k-instruct",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_mistral_7b_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"casperhansen/mistral-7b-instruct-v0.1-awq",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_gemma3_4b_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"mlx-community/gemma-3-4b-it-8bit",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_gemma_2b_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"unsloth/gemma-2b-it",
revision="703fb4a",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_gemma2_9b_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"mlx-community/gemma-2-9b-it-4bit",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_mlx_mistral_7b_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"mlx-community/Mistral-7B-Instruct-v0.3-4bit",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture
def download_llama2_model_fixture():
# download the tokenizer only
snapshot_download_w_retry(
"NousResearch/Llama-2-7b-hf",
repo_type="model",
allow_patterns=["*token*", "config.json"],
)
@pytest.fixture(scope="session", autouse=True)
def download_llama32_1b_model_fixture():
snapshot_download_w_retry(
"osllmai-community/Llama-3.2-1B",
repo_type="model",
)
@pytest.fixture
@enable_hf_offline
def tokenizer_huggyllama(
download_huggyllama_model_fixture,
):
tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
tokenizer.pad_token = "</s>"
return tokenizer
@pytest.fixture
@enable_hf_offline
def tokenizer_huggyllama_w_special_tokens(
tokenizer_huggyllama,
):
tokenizer_huggyllama.add_special_tokens(
{
"bos_token": "<s>",
"eos_token": "</s>",
"unk_token": "<unk>",
}
)
return tokenizer_huggyllama
@pytest.fixture
@enable_hf_offline
def tokenizer_llama2_7b(
download_llama2_model_fixture,
):
tokenizer = AutoTokenizer.from_pretrained("NousResearch/Llama-2-7b-hf")
return tokenizer
@pytest.fixture
@enable_hf_offline
def tokenizer_mistral_7b_instruct(
download_mlx_mistral_7b_model_fixture,
):
return AutoTokenizer.from_pretrained("casperhansen/mistral-7b-instruct-v0.1-awq")
@pytest.fixture
def tokenizer_mistral_7b_instruct_chatml(tokenizer_mistral_7b_instruct):
tokenizer_mistral_7b_instruct.add_special_tokens(
{
"eos_token": AddedToken(
"<|im_end|>", rstrip=False, lstrip=False, normalized=False
)
}
)
tokenizer_mistral_7b_instruct.add_tokens(
[
AddedToken("<|im_start|>", rstrip=False, lstrip=False, normalized=False),
]
)
return tokenizer_mistral_7b_instruct
@pytest.fixture
def temp_dir() -> Generator[str, None, None]:
# Create a temporary directory
_temp_dir = tempfile.mkdtemp()
yield _temp_dir
# Clean up the directory after the test
shutil.rmtree(_temp_dir)
@pytest.fixture(scope="function", autouse=True)
def torch_manual_seed():
torch.manual_seed(42)
@pytest.fixture(scope="function", autouse=True)
def cleanup_monkeypatches():
from transformers import Trainer
from transformers.models.llama.modeling_llama import ( # LlamaFlashAttention2,
LlamaAttention,
LlamaForCausalLM,
)
# original_fa2_forward = LlamaFlashAttention2.forward
original_llama_attn_forward = LlamaAttention.forward
original_llama_forward = LlamaForCausalLM.forward
original_trainer_inner_training_loop = Trainer._inner_training_loop
original_trainer_training_step = Trainer.training_step
# monkey patches can happen inside the tests
yield
# Reset LlamaFlashAttention2 forward
# LlamaFlashAttention2.forward = original_fa2_forward
LlamaAttention.forward = original_llama_attn_forward
LlamaForCausalLM.forward = original_llama_forward
Trainer._inner_training_loop = original_trainer_inner_training_loop
Trainer.training_step = original_trainer_training_step
# Reset other known monkeypatches
modules_to_reset: list[tuple[str, list[str]]] = [
("transformers.models.llama",),
(
"transformers.models.llama.modeling_llama",
[
# "LlamaFlashAttention2",
"LlamaAttention",
],
),
("transformers.trainer",),
("transformers", ["Trainer"]),
("transformers.loss.loss_utils",),
]
for module_name_tuple in modules_to_reset:
module_name = module_name_tuple[0]
spec = importlib.util.spec_from_file_location(
module_name, sys.modules[module_name].__file__
)
sys.modules[module_name] = importlib.util.module_from_spec(spec)
spec.loader.exec_module(sys.modules[module_name])
sys.modules[module_name] = importlib.reload(sys.modules[module_name])
if len(module_name_tuple) > 1:
module_globals = module_name_tuple[1]
for module_global in module_globals:
globals().pop(module_global, None)
@pytest.fixture
def dataset_winglian_tiny_shakespeare(
download_ds_fixture_bundle: Path,
):
ds_path = download_ds_fixture_bundle / "winglian__tiny-shakespeare"
return datasets.load_from_disk(ds_path)
@pytest.fixture
def dataset_tatsu_lab_alpaca(
download_ds_fixture_bundle: Path,
):
ds_path = download_ds_fixture_bundle / "tatsu-lab__alpaca"
return datasets.load_from_disk(ds_path)["train"]
@pytest.fixture
def dataset_mhenrichsen_alpaca_2k_test(
download_ds_fixture_bundle: Path,
):
ds_path = download_ds_fixture_bundle / "mhenrichsen__alpaca_2k_test"
return datasets.load_from_disk(ds_path)["train"]
@pytest.fixture
def dataset_argilla_ultrafeedback_binarized_preferences_cleaned(
download_ds_fixture_bundle: Path,
):
ds_path = (
download_ds_fixture_bundle
/ "argilla__ultrafeedback-binarized-preferences-cleaned"
)
return datasets.load_from_disk(ds_path)["train"]
@pytest.fixture
def dataset_fozziethebeat_alpaca_messages_2k_dpo_test(
download_ds_fixture_bundle: Path,
):
ds_path = download_ds_fixture_bundle / "fozziethebeat__alpaca_messages_2k_dpo_test"
return datasets.load_from_disk(ds_path)["train"]
@pytest.fixture
def dataset_fozziethebeat_alpaca_messages_2k_dpo_test_rev_ea82cff(
download_ds_fixture_bundle: Path,
):
ds_path = (
download_ds_fixture_bundle
/ "fozziethebeat__alpaca_messages_2k_dpo_test__rev_ea82cff"
)
return datasets.load_from_disk(ds_path)["train"]
@pytest.fixture(name="min_base_cfg")
def fixture_min_base_cfg():
return DictDefault(
base_model="HuggingFaceTB/SmolLM2-135M",
learning_rate=1e-3,
datasets=[
{
"path": "mhenrichsen/alpaca_2k_test",
"type": "alpaca",
},
],
micro_batch_size=1,
gradient_accumulation_steps=1,
)
#
@pytest.mark.skipif(
os.environ.get("AXOLOTL_IS_CI_CACHE_PRELOAD", "-1") != "1",
reason="Not running in CI cache preload",
)
def test_load_fixtures(
download_smollm2_135m_model,
download_qwen_2_5_half_billion_model,
download_tatsu_lab_alpaca_dataset,
download_mhenrichsen_alpaca_2k_dataset,
download_mhenrichsen_alpaca_2k_w_revision_dataset,
download_mlabonne_finetome_100k_dataset,
download_argilla_ultrafeedback_binarized_preferences_cleaned_dataset,
download_argilla_ultrafeedback_binarized_preferences_cleaned_kto_dataset,
download_argilla_distilabel_capybara_dpo_7k_binarized_dataset,
download_arcee_ai_distilabel_intel_orca_dpo_pairs_dataset,
download_argilla_dpo_pairs_dataset,
download_tiny_shakespeare_dataset,
download_deepseek_model_fixture,
download_huggyllama_model_fixture,
download_llama_1b_model_fixture,
download_llama3_8b_model_fixture,
download_llama3_8b_instruct_model_fixture,
download_phi_35_mini_model_fixture,
download_phi_3_medium_model_fixture,
download_phi_4_reasoning_model_fixture,
download_mistral_7b_model_fixture,
download_gemma_2b_model_fixture,
download_gemma2_9b_model_fixture,
download_mlx_mistral_7b_model_fixture,
download_llama2_model_fixture,
):
pass
@pytest.fixture(autouse=True)
def disable_telemetry(monkeypatch):
monkeypatch.setenv("AXOLOTL_DO_NOT_TRACK", "1")
yield