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hf offline decorator for tests to workaround rate limits (#2452) [skip ci]

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* hf offline decorator for tests to workaround rate limits

* fail quicker so we can see logs

* try new cache name

* limit files downloaded

* phi mini predownload

* offline decorator for phi tokenizer

* handle meta llama 8b offline too

* make sure to return fixtures if they are wrapped too

* more fixes

* more things offline

* more offline things

* fix the env var

* fix the model name

* handle gemma also

* force reload of modules to recheck offline status

* prefetch mistral too

* use reset_sessions so hub picks up offline mode

* more fixes

* rename so it doesn't seem like a context manager

* fix backoff

* switch out tinyshakespeare dataset since it runs a py script to fetch data and doesn't work offline

* include additional dataset

* more fixes

* more fixes

* replace tiny shakespeaere dataset

* skip some tests for now

* use more robust check using snapshot download to determine if a dataset name is on the hub

* typo for skip reason

* use local_files_only

* more fixtures

* remove local only

* use tiny shakespeare as pretrain dataset and streaming can't be offline even if precached

* make sure fixtures aren't offline

improve the offline reset
try bumping version of datasets
reorder reloading and setting
prime a new cache
run the tests now with fresh cache
try with a static cache

* now run all the ci again with hopefully a correct cache

* skip wonky tests for now

* skip wonky tests for now

* handle offline mode for model card creation
This commit is contained in:
Wing Lian
2025-03-28 19:20:46 -04:00
committed by GitHub
parent a4e430e7c4
commit 05f03b541a
21 changed files with 381 additions and 50 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
.github/workflows/tests.yml vendored
View File

@@ -63,7 +63,7 @@ jobs:
path: |
/home/runner/.cache/huggingface/hub/datasets--*
/home/runner/.cache/huggingface/hub/models--*
key: ${{ runner.os }}-hf-hub-cache-${{ hashFiles('**/conftest.py') }}
key: ${{ runner.os }}-hf-hub-cache-v2
- name: Setup Python
uses: actions/setup-python@v5
@@ -137,7 +137,7 @@ jobs:
path: |
/home/runner/.cache/huggingface/hub/datasets--*
/home/runner/.cache/huggingface/hub/models--*
key: ${{ runner.os }}-hf-hub-cache-${{ hashFiles('**/conftest.py') }}
key: ${{ runner.os }}-hf-hub-cache-v2
- name: Setup Python
uses: actions/setup-python@v5

2
requirements.txt
View File

@@ -15,7 +15,7 @@ peft==0.15.0
transformers==4.50.0
tokenizers>=0.21.1
accelerate==1.5.2
datasets==3.4.1
datasets==3.5.0
deepspeed==0.16.4
trl==0.15.1

3
src/axolotl/train.py
View File

@@ -14,6 +14,7 @@ import transformers.modelcard
from accelerate.logging import get_logger
from accelerate.utils import save_fsdp_model
from datasets import Dataset
from huggingface_hub.errors import OfflineModeIsEnabled
from peft import PeftConfig, PeftModel
from transformers import PreTrainedModel, PreTrainedTokenizer, ProcessorMixin
from transformers.integrations.deepspeed import is_deepspeed_zero3_enabled
@@ -302,7 +303,7 @@ def create_model_card(cfg: DictDefault, trainer: Trainer):
model_card_kwarg["dataset_tags"] = dataset_tags
trainer.create_model_card(**model_card_kwarg)
except (AttributeError, UnicodeDecodeError):
except (AttributeError, UnicodeDecodeError, OfflineModeIsEnabled):
pass
elif cfg.hub_model_id:
# Defensively push to the hub to ensure the model card is updated

27
src/axolotl/utils/data/shared.py
View File

@@ -6,8 +6,12 @@ from pathlib import Path
from typing import Optional, Union
from datasets import Dataset, DatasetDict, load_dataset, load_from_disk
from huggingface_hub import hf_hub_download
from huggingface_hub.errors import HFValidationError
from huggingface_hub import hf_hub_download, snapshot_download
from huggingface_hub.errors import (
HFValidationError,
RepositoryNotFoundError,
RevisionNotFoundError,
)
from axolotl.utils.dict import DictDefault
@@ -70,20 +74,25 @@ def load_dataset_w_config(
# pylint: disable=invalid-name
ds: Optional[Union[Dataset, DatasetDict]] = None # pylint: disable=invalid-name
ds_from_hub = False
ds_trust_remote_code = config_dataset.trust_remote_code
try:
# this is just a basic check to see if the path is a
# valid HF dataset that's loadable
load_dataset(
config_dataset.path,
name=config_dataset.name,
streaming=True,
snapshot_download(
repo_id=config_dataset.path,
repo_type="dataset",
token=use_auth_token,
revision=config_dataset.revision,
trust_remote_code=ds_trust_remote_code,
ignore_patterns=["*"],
)
ds_from_hub = True
except (FileNotFoundError, ConnectionError, HFValidationError, ValueError):
except (
RepositoryNotFoundError,
RevisionNotFoundError,
FileNotFoundError,
ConnectionError,
HFValidationError,
ValueError,
):
pass
ds_from_cloud = False

189
tests/conftest.py
View File

@@ -12,6 +12,7 @@ import time
import pytest
import requests
from huggingface_hub import snapshot_download
from utils import disable_hf_offline
def retry_on_request_exceptions(max_retries=3, delay=1):
@@ -25,9 +26,11 @@ def retry_on_request_exceptions(max_retries=3, delay=1):
except (
requests.exceptions.ReadTimeout,
requests.exceptions.ConnectionError,
requests.exceptions.HTTPError,
) as exc:
if attempt < max_retries - 1:
time.sleep(delay)
wait = 2**attempt * delay # in seconds
time.sleep(wait)
else:
raise exc
@@ -37,41 +40,47 @@ def retry_on_request_exceptions(max_retries=3, delay=1):
@retry_on_request_exceptions(max_retries=3, delay=5)
@disable_hf_offline
def snapshot_download_w_retry(*args, **kwargs):
return snapshot_download(*args, **kwargs)
@pytest.fixture(scope="session", autouse=True)
@disable_hf_offline
def download_smollm2_135m_model():
# download the model
snapshot_download_w_retry("HuggingFaceTB/SmolLM2-135M")
snapshot_download_w_retry("HuggingFaceTB/SmolLM2-135M", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
def download_llama_68m_random_model():
# download the model
snapshot_download_w_retry("JackFram/llama-68m")
snapshot_download_w_retry("JackFram/llama-68m", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
@disable_hf_offline
def download_qwen_2_5_half_billion_model():
# download the model
snapshot_download_w_retry("Qwen/Qwen2.5-0.5B")
snapshot_download_w_retry("Qwen/Qwen2.5-0.5B", repo_type="model")
@pytest.fixture(scope="session", autouse=True)
@disable_hf_offline
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)
@disable_hf_offline
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)
@disable_hf_offline
def download_mhenrichsen_alpaca_2k_w_revision_dataset():
# download the dataset
snapshot_download_w_retry(
@@ -80,6 +89,7 @@ def download_mhenrichsen_alpaca_2k_w_revision_dataset():
@pytest.fixture(scope="session", autouse=True)
@disable_hf_offline
def download_mlabonne_finetome_100k_dataset():
# download the dataset
snapshot_download_w_retry("mlabonne/FineTome-100k", repo_type="dataset")
@@ -101,6 +111,19 @@ def download_argilla_ultrafeedback_binarized_preferences_cleaned_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", autouse=True)
def download_arcee_ai_distilabel_intel_orca_dpo_pairs_dataset():
# download the dataset
@@ -109,10 +132,135 @@ def download_arcee_ai_distilabel_intel_orca_dpo_pairs_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("Trelis/tiny-shakespeare", repo_type="dataset")
snapshot_download_w_retry("winglian/tiny-shakespeare", 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)
@disable_hf_offline
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)
@disable_hf_offline
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)
@disable_hf_offline
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*"]
)
@pytest.fixture(scope="session", autouse=True)
@disable_hf_offline
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*"],
)
@pytest.fixture(scope="session", autouse=True)
@disable_hf_offline
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*"]
)
@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*"],
)
@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_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(scope="session", autouse=True)
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
@@ -178,3 +326,34 @@ def cleanup_monkeypatches():
module_globals = module_name_tuple[1]
for module_global in module_globals:
globals().pop(module_global, None)
# # pylint: disable=redefined-outer-name,unused-argument
# def test_load_fixtures(
# download_smollm2_135m_model,
# download_llama_68m_random_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_distilabel_capybara_dpo_7k_binarized_dataset,
# download_argilla_ultrafeedback_binarized_preferences_cleaned_dataset,
# download_fozzie_alpaca_dpo_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_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

4
tests/core/chat/test_messages.py
View File

@@ -6,14 +6,16 @@ import unittest
import pytest
from transformers import AddedToken, AutoTokenizer
from utils import enable_hf_offline
from axolotl.core.chat.format.chatml import format_message
from axolotl.core.chat.messages import ChatFormattedChats, Chats
@pytest.fixture(scope="session", name="llama_tokenizer")
@enable_hf_offline
def llama_tokenizer_fixture():
return AutoTokenizer.from_pretrained("NousResearch/Meta-Llama-3.1-8B")
return AutoTokenizer.from_pretrained("NousResearch/Meta-Llama-3-8B")
@pytest.fixture(scope="session", name="chatml_tokenizer")

3
tests/e2e/test_deepseekv3.py
View File

@@ -7,6 +7,7 @@ import os
from pathlib import Path
import pytest
from utils import enable_hf_offline
from axolotl.cli.args import TrainerCliArgs
from axolotl.common.datasets import load_datasets
@@ -23,6 +24,7 @@ class TestDeepseekV3:
Test case for DeepseekV3 models
"""
@enable_hf_offline
@pytest.mark.parametrize(
"sample_packing",
[True, False],
@@ -80,6 +82,7 @@ class TestDeepseekV3:
train(cfg=cfg, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "adapter_model.safetensors").exists()
@enable_hf_offline
@pytest.mark.parametrize(
"sample_packing",
[True, False],

16
tests/prompt_strategies/conftest.py
View File

@@ -4,8 +4,8 @@ shared fixtures for prompt strategies tests
import pytest
from datasets import Dataset
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer
from utils import enable_hf_offline
from axolotl.prompt_strategies.jinja_template_analyzer import JinjaTemplateAnalyzer
from axolotl.utils.chat_templates import _CHAT_TEMPLATES
@@ -108,24 +108,15 @@ def fixture_toolcalling_dataset():
@pytest.fixture(name="llama3_tokenizer", scope="session", autouse=True)
@enable_hf_offline
def fixture_llama3_tokenizer():
hf_hub_download(
repo_id="NousResearch/Meta-Llama-3-8B-Instruct",
filename="special_tokens_map.json",
)
hf_hub_download(
repo_id="NousResearch/Meta-Llama-3-8B-Instruct",
filename="tokenizer_config.json",
)
hf_hub_download(
repo_id="NousResearch/Meta-Llama-3-8B-Instruct", filename="tokenizer.json"
)
tokenizer = AutoTokenizer.from_pretrained("NousResearch/Meta-Llama-3-8B-Instruct")
return tokenizer
@pytest.fixture(name="smollm2_tokenizer", scope="session", autouse=True)
@enable_hf_offline
def fixture_smollm2_tokenizer():
tokenizer = AutoTokenizer.from_pretrained("HuggingFaceTB/SmolLM2-135M")
return tokenizer
@@ -140,6 +131,7 @@ def fixture_mistralv03_tokenizer():
@pytest.fixture(name="phi35_tokenizer", scope="session", autouse=True)
@enable_hf_offline
def fixture_phi35_tokenizer():
tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3.5-mini-instruct")
return tokenizer

2
tests/prompt_strategies/test_alpaca.py
View File

@@ -6,6 +6,7 @@ import pytest
from datasets import Dataset
from tokenizers import AddedToken
from transformers import AutoTokenizer
from utils import enable_hf_offline
from axolotl.datasets import TokenizedPromptDataset
from axolotl.prompt_tokenizers import AlpacaPromptTokenizingStrategy
@@ -26,6 +27,7 @@ def fixture_alpaca_dataset():
@pytest.fixture(name="tokenizer")
@enable_hf_offline
def fixture_tokenizer():
# pylint: disable=all
tokenizer = AutoTokenizer.from_pretrained(

2
tests/prompt_strategies/test_chat_template_utils.py
View File

@@ -6,6 +6,7 @@ import unittest
import pytest
from transformers import AutoTokenizer
from utils import enable_hf_offline
from axolotl.utils.chat_templates import (
_CHAT_TEMPLATES,
@@ -15,6 +16,7 @@ from axolotl.utils.chat_templates import (
@pytest.fixture(name="llama3_tokenizer")
@enable_hf_offline
def fixture_llama3_tokenizer():
tokenizer = AutoTokenizer.from_pretrained("NousResearch/Meta-Llama-3-8B")

11
tests/prompt_strategies/test_dpo_chat_templates.py
View File

@@ -7,6 +7,7 @@ import unittest
import pytest
from datasets import Dataset
from transformers import AutoTokenizer
from utils import enable_hf_offline
from axolotl.prompt_strategies.dpo.chat_template import default
from axolotl.utils.dict import DictDefault
@@ -78,15 +79,8 @@ def fixture_custom_assistant_dataset():
)
@pytest.fixture(name="llama3_tokenizer")
def fixture_llama3_tokenizer():
tokenizer = AutoTokenizer.from_pretrained("NousResearch/Meta-Llama-3-8B")
tokenizer.eos_token = "<|eot_id|>"
return tokenizer
@pytest.fixture(name="phi3_tokenizer")
@enable_hf_offline
def fixture_phi3_tokenizer():
tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-medium-128k-instruct")
@@ -94,6 +88,7 @@ def fixture_phi3_tokenizer():
@pytest.fixture(name="gemma_tokenizer")
@enable_hf_offline
def fixture_gemma_tokenizer():
tokenizer = AutoTokenizer.from_pretrained("unsloth/gemma-2b-it", revision="703fb4a")

3
tests/prompt_strategies/test_dpo_chatml.py
View File

@@ -5,6 +5,7 @@ Tests for loading DPO preference datasets with chatml formatting
import unittest
import pytest
from utils import enable_hf_offline
from axolotl.prompt_strategies.dpo import load as load_dpo
from axolotl.utils.data.rl import load_prepare_preference_datasets
@@ -34,6 +35,8 @@ class TestDPOChatml:
Test loading DPO preference datasets with chatml formatting
"""
@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
@enable_hf_offline
def test_default(self, minimal_dpo_cfg):
cfg = DictDefault(
{

2
tests/test_data.py
View File

@@ -5,6 +5,7 @@ test module for the axolotl.utils.data module
import unittest
from transformers import LlamaTokenizer
from utils import enable_hf_offline
from axolotl.utils.data import encode_pretraining, md5
@@ -14,6 +15,7 @@ class TestEncodePretraining(unittest.TestCase):
test class for encode pretraining and md5 helper
"""
@enable_hf_offline
def setUp(self):
self.tokenizer = LlamaTokenizer.from_pretrained("huggyllama/llama-7b")
self.tokenizer.add_special_tokens(

33
tests/test_datasets.py
View File

@@ -7,14 +7,16 @@ import tempfile
import unittest
from pathlib import Path
from conftest import snapshot_download_w_retry
import pytest
from constants import (
ALPACA_MESSAGES_CONFIG_OG,
ALPACA_MESSAGES_CONFIG_REVISION,
SPECIAL_TOKENS,
)
from datasets import Dataset
from huggingface_hub import snapshot_download
from transformers import AutoTokenizer
from utils import enable_hf_offline
from axolotl.utils.data import load_tokenized_prepared_datasets
from axolotl.utils.data.rl import load_prepare_preference_datasets
@@ -24,6 +26,7 @@ from axolotl.utils.dict import DictDefault
class TestDatasetPreparation(unittest.TestCase):
"""Test a configured dataloader."""
@enable_hf_offline
def setUp(self) -> None:
self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
self.tokenizer.add_special_tokens(SPECIAL_TOKENS)
@@ -38,6 +41,8 @@ class TestDatasetPreparation(unittest.TestCase):
]
)
@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
@enable_hf_offline
def test_load_hub(self):
"""Core use case. Verify that processing data from the hub works"""
with tempfile.TemporaryDirectory() as tmp_dir:
@@ -64,16 +69,21 @@ class TestDatasetPreparation(unittest.TestCase):
assert "attention_mask" in dataset.features
assert "labels" in dataset.features
@enable_hf_offline
@pytest.mark.skip("datasets bug with local datasets when offline")
def test_load_local_hub(self):
"""Niche use case. Verify that a local copy of a hub dataset can be loaded"""
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_ds_path = Path(tmp_dir) / "mhenrichsen/alpaca_2k_test"
tmp_ds_path.mkdir(parents=True, exist_ok=True)
snapshot_download_w_retry(
snapshot_path = snapshot_download(
repo_id="mhenrichsen/alpaca_2k_test",
repo_type="dataset",
local_dir=tmp_ds_path,
)
# offline mode doesn't actually copy it to local_dir, so we
# have to copy all the contents in the dir manually from the returned snapshot_path
shutil.copytree(snapshot_path, tmp_ds_path, dirs_exist_ok=True)
prepared_path = Path(tmp_dir) / "prepared"
# Right now a local copy that doesn't fully conform to a dataset
@@ -106,6 +116,7 @@ class TestDatasetPreparation(unittest.TestCase):
assert "labels" in dataset.features
shutil.rmtree(tmp_ds_path)
@enable_hf_offline
def test_load_from_save_to_disk(self):
"""Usual use case. Verify datasets saved via `save_to_disk` can be loaded."""
with tempfile.TemporaryDirectory() as tmp_dir:
@@ -135,6 +146,7 @@ class TestDatasetPreparation(unittest.TestCase):
assert "attention_mask" in dataset.features
assert "labels" in dataset.features
@enable_hf_offline
def test_load_from_dir_of_parquet(self):
"""Usual use case. Verify a directory of parquet files can be loaded."""
with tempfile.TemporaryDirectory() as tmp_dir:
@@ -171,6 +183,7 @@ class TestDatasetPreparation(unittest.TestCase):
assert "attention_mask" in dataset.features
assert "labels" in dataset.features
@enable_hf_offline
def test_load_from_dir_of_json(self):
"""Standard use case. Verify a directory of json files can be loaded."""
with tempfile.TemporaryDirectory() as tmp_dir:
@@ -207,6 +220,7 @@ class TestDatasetPreparation(unittest.TestCase):
assert "attention_mask" in dataset.features
assert "labels" in dataset.features
@enable_hf_offline
def test_load_from_single_parquet(self):
"""Standard use case. Verify a single parquet file can be loaded."""
with tempfile.TemporaryDirectory() as tmp_dir:
@@ -237,6 +251,7 @@ class TestDatasetPreparation(unittest.TestCase):
assert "attention_mask" in dataset.features
assert "labels" in dataset.features
@enable_hf_offline
def test_load_from_single_json(self):
"""Standard use case. Verify a single json file can be loaded."""
with tempfile.TemporaryDirectory() as tmp_dir:
@@ -267,6 +282,8 @@ class TestDatasetPreparation(unittest.TestCase):
assert "attention_mask" in dataset.features
assert "labels" in dataset.features
@pytest.mark.skip(reason="TODO: fix hf offline mode for CI rate limits")
@enable_hf_offline
def test_load_hub_with_dpo(self):
"""Verify that processing dpo data from the hub works"""
@@ -285,6 +302,8 @@ class TestDatasetPreparation(unittest.TestCase):
assert len(train_dataset) == 1800
assert "conversation" in train_dataset.features
@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
@enable_hf_offline
def test_load_hub_with_revision(self):
"""Verify that processing data from the hub works with a specific revision"""
with tempfile.TemporaryDirectory() as tmp_dir:
@@ -316,6 +335,7 @@ class TestDatasetPreparation(unittest.TestCase):
assert "attention_mask" in dataset.features
assert "labels" in dataset.features
@enable_hf_offline
def test_load_hub_with_revision_with_dpo(self):
"""Verify that processing dpo data from the hub works with a specific revision"""
@@ -334,17 +354,20 @@ class TestDatasetPreparation(unittest.TestCase):
assert len(train_dataset) == 1800
assert "conversation" in train_dataset.features
@enable_hf_offline
@pytest.mark.skip("datasets bug with local datasets when offline")
def test_load_local_hub_with_revision(self):
"""Verify that a local copy of a hub dataset can be loaded with a specific revision"""
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_ds_path = Path(tmp_dir) / "mhenrichsen/alpaca_2k_test"
tmp_ds_path.mkdir(parents=True, exist_ok=True)
snapshot_download_w_retry(
snapshot_path = snapshot_download(
repo_id="mhenrichsen/alpaca_2k_test",
repo_type="dataset",
local_dir=tmp_ds_path,
revision="d05c1cb",
)
shutil.copytree(snapshot_path, tmp_ds_path, dirs_exist_ok=True)
prepared_path = Path(tmp_dir) / "prepared"
cfg = DictDefault(
@@ -375,17 +398,19 @@ class TestDatasetPreparation(unittest.TestCase):
assert "labels" in dataset.features
shutil.rmtree(tmp_ds_path)
@enable_hf_offline
def test_loading_local_dataset_folder(self):
"""Verify that a dataset downloaded to a local folder can be loaded"""
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_ds_path = Path(tmp_dir) / "mhenrichsen/alpaca_2k_test"
tmp_ds_path.mkdir(parents=True, exist_ok=True)
snapshot_download_w_retry(
snapshot_path = snapshot_download(
repo_id="mhenrichsen/alpaca_2k_test",
repo_type="dataset",
local_dir=tmp_ds_path,
)
shutil.copytree(snapshot_path, tmp_ds_path, dirs_exist_ok=True)
prepared_path = Path(tmp_dir) / "prepared"
cfg = DictDefault(

11
tests/test_exact_deduplication.py
View File

@@ -8,9 +8,11 @@ import hashlib
import unittest
from unittest.mock import patch
import pytest
from constants import ALPACA_MESSAGES_CONFIG_REVISION, SPECIAL_TOKENS
from datasets import Dataset
from transformers import AutoTokenizer
from utils import enable_hf_offline
from axolotl.utils.config import normalize_config
from axolotl.utils.data import prepare_dataset
@@ -234,6 +236,8 @@ class TestDeduplicateRLDataset(unittest.TestCase):
}
)
@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
@enable_hf_offline
def test_load_with_deduplication(self):
"""Verify that loading with deduplication removes duplicates."""
@@ -258,6 +262,7 @@ class TestDeduplicateRLDataset(unittest.TestCase):
class TestDeduplicateNonRL(unittest.TestCase):
"""Test prepare_dataset function with different configurations."""
@enable_hf_offline
def setUp(self) -> None:
self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
self.tokenizer.add_special_tokens(SPECIAL_TOKENS)
@@ -286,6 +291,8 @@ class TestDeduplicateNonRL(unittest.TestCase):
)
normalize_config(self.cfg_1)
@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
@enable_hf_offline
def test_prepare_dataset_with_deduplication_train(self):
"""Verify that prepare_dataset function processes the dataset correctly with deduplication."""
self.cfg_1.dataset_exact_deduplication = True
@@ -311,6 +318,8 @@ class TestDeduplicateNonRL(unittest.TestCase):
"Train dataset should have 2000 samples after deduplication.",
)
@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
@enable_hf_offline
def test_prepare_dataset_with_deduplication_eval(self):
"""Verify that prepare_dataset function processes the dataset correctly with deduplication."""
self.cfg_1.dataset_exact_deduplication = True
@@ -336,6 +345,8 @@ class TestDeduplicateNonRL(unittest.TestCase):
"Eval dataset should have 2000 samples after deduplication.",
)
@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
@enable_hf_offline
def test_prepare_dataset_without_deduplication(self):
"""Verify that prepare_dataset function processes the dataset correctly without deduplication."""
self.cfg_1.dataset_exact_deduplication = False

5
tests/test_packed_batch_sampler.py
View File

@@ -4,6 +4,7 @@ import pytest
from datasets import concatenate_datasets, load_dataset
from torch.utils.data import DataLoader, RandomSampler
from transformers import AutoTokenizer
from utils import enable_hf_offline
from axolotl.datasets import TokenizedPromptDataset
from axolotl.prompt_strategies.completion import load
@@ -25,6 +26,7 @@ class TestBatchedSamplerPacking:
Test class for packing streaming dataset sequences
"""
@pytest.mark.skip(reason="TODO: fix hf offline mode for CI rate limits")
@pytest.mark.parametrize(
"batch_size, num_workers",
[
@@ -35,11 +37,12 @@ class TestBatchedSamplerPacking:
],
)
@pytest.mark.parametrize("max_seq_length", [4096, 512])
@enable_hf_offline
def test_packing(self, batch_size, num_workers, tokenizer, max_seq_length):
import axolotl.monkeypatch.data.batch_dataset_fetcher # pylint: disable=unused-import # noqa: F401
dataset = load_dataset(
"Trelis/tiny-shakespeare",
"winglian/tiny-shakespeare",
split="train",
)

2
tests/test_packed_dataset.py
View File

@@ -5,6 +5,7 @@ from pathlib import Path
from datasets import Dataset, load_dataset
from transformers import AutoTokenizer
from utils import enable_hf_offline
from axolotl.datasets import ConstantLengthDataset, TokenizedPromptDataset
from axolotl.prompt_tokenizers import AlpacaPromptTokenizingStrategy
@@ -16,6 +17,7 @@ class TestPacking(unittest.TestCase):
Test class for packing dataset sequences
"""
@enable_hf_offline
def setUp(self) -> None:
# pylint: disable=duplicate-code
self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")

11
tests/test_packed_pretraining.py
View File

@@ -8,6 +8,7 @@ import torch
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from utils import disable_hf_offline, enable_hf_offline
from axolotl.utils.data import get_dataset_wrapper, wrap_pretraining_dataset
from axolotl.utils.dict import DictDefault
@@ -18,17 +19,18 @@ class TestPretrainingPacking(unittest.TestCase):
Test class for packing streaming dataset sequences
"""
@enable_hf_offline
def setUp(self) -> None:
# pylint: disable=duplicate-code
self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
self.tokenizer.pad_token = "</s>"
@pytest.mark.flaky(retries=3, delay=5)
@pytest.mark.flaky(retries=1, delay=5)
@disable_hf_offline
def test_packing_stream_dataset(self):
# pylint: disable=duplicate-code
dataset = load_dataset(
"allenai/c4",
"en",
"winglian/tiny-shakespeare",
streaming=True,
)["train"]
@@ -36,8 +38,7 @@ class TestPretrainingPacking(unittest.TestCase):
{
"pretraining_dataset": [
{
"path": "allenai/c4",
"name": "en",
"path": "winglian/tiny-shakespeare",
"type": "pretrain",
}
],

7
tests/test_prompt_tokenizers.py
View File

@@ -5,8 +5,10 @@ import logging
import unittest
from pathlib import Path
import pytest
from datasets import load_dataset
from transformers import AddedToken, AutoTokenizer, LlamaTokenizer
from utils import enable_hf_offline
from axolotl.prompt_strategies.alpaca_chat import NoSystemPrompter
from axolotl.prompt_strategies.alpaca_w_system import (
@@ -63,6 +65,7 @@ class TestPromptTokenizationStrategies(unittest.TestCase):
Test class for prompt tokenization strategies.
"""
@enable_hf_offline
def setUp(self) -> None:
# pylint: disable=duplicate-code
self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
@@ -119,6 +122,7 @@ class InstructionWSystemPromptTokenizingStrategyTest(unittest.TestCase):
Test class for prompt tokenization strategies with sys prompt from the dataset
"""
@enable_hf_offline
def setUp(self) -> None:
# pylint: disable=duplicate-code
self.tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
@@ -160,6 +164,7 @@ class Llama2ChatTokenizationTest(unittest.TestCase):
Test class for prompt tokenization strategies with sys prompt from the dataset
"""
@enable_hf_offline
def setUp(self) -> None:
# pylint: disable=duplicate-code
self.tokenizer = LlamaTokenizer.from_pretrained("NousResearch/Llama-2-7b-hf")
@@ -238,6 +243,7 @@ If a question does not make any sense, or is not factually coherent, explain why
class OrpoTokenizationTest(unittest.TestCase):
"""test case for the ORPO tokenization"""
@enable_hf_offline
def setUp(self) -> None:
# pylint: disable=duplicate-code
tokenizer = LlamaTokenizer.from_pretrained(
@@ -262,6 +268,7 @@ class OrpoTokenizationTest(unittest.TestCase):
"argilla/ultrafeedback-binarized-preferences-cleaned", split="train"
).select([0])
@pytest.mark.skip(reason="TODO: fix hf hub offline to work with HF rate limits")
def test_orpo_integration(self):
strat = load(
self.tokenizer,

9
tests/test_tokenizers.py
View File

@@ -5,6 +5,7 @@ Test cases for the tokenizer loading
import unittest
import pytest
from utils import enable_hf_offline
from axolotl.utils.dict import DictDefault
from axolotl.utils.models import load_tokenizer
@@ -15,6 +16,7 @@ class TestTokenizers:
test class for the load_tokenizer fn
"""
@enable_hf_offline
def test_default_use_fast(self):
cfg = DictDefault(
{
@@ -24,6 +26,7 @@ class TestTokenizers:
tokenizer = load_tokenizer(cfg)
assert "Fast" in tokenizer.__class__.__name__
@enable_hf_offline
def test_dont_use_fast(self):
cfg = DictDefault(
{
@@ -34,6 +37,7 @@ class TestTokenizers:
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(
@@ -68,6 +72,7 @@ class TestTokenizers:
)
load_tokenizer(cfg)
@enable_hf_offline
def test_add_additional_special_tokens(self):
cfg = DictDefault(
{
@@ -83,6 +88,7 @@ class TestTokenizers:
tokenizer = load_tokenizer(cfg)
assert len(tokenizer) == 32001
@enable_hf_offline
def test_added_tokens_overrides(self, temp_dir):
cfg = DictDefault(
{
@@ -104,11 +110,12 @@ class TestTokenizers:
128042
]
@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": "NousResearch/Llama-3.2-1B",
"tokenizer_config": "HuggingFaceTB/SmolLM2-135M",
"added_tokens_overrides": {1000000: "BROKEN_RANDOM_OVERRIDE_1"},
"output_dir": temp_dir,
}

85
tests/utils/__init__.py Normal file
View File

@@ -0,0 +1,85 @@
"""
test utils for helpers and decorators
"""
import os
from functools import wraps
from huggingface_hub.utils import reset_sessions
def reload_modules(hf_hub_offline):
# Force reload of the modules that check this variable
import importlib
import datasets
import huggingface_hub.constants
# Reload the constants module first, as others depend on it
importlib.reload(huggingface_hub.constants)
huggingface_hub.constants.HF_HUB_OFFLINE = hf_hub_offline
importlib.reload(datasets.config)
datasets.config.HF_HUB_OFFLINE = hf_hub_offline
reset_sessions()
def enable_hf_offline(test_func):
"""
test decorator that sets HF_HUB_OFFLINE environment variable to True and restores it after the test even if the test fails.
:param test_func:
:return:
"""
@wraps(test_func)
def wrapper(*args, **kwargs):
# Save the original value of HF_HUB_OFFLINE environment variable
original_hf_offline = os.getenv("HF_HUB_OFFLINE")
# Set HF_OFFLINE environment variable to True
os.environ["HF_HUB_OFFLINE"] = "1"
reload_modules(True)
try:
# Run the test function
return test_func(*args, **kwargs)
finally:
# Restore the original value of HF_HUB_OFFLINE environment variable
if original_hf_offline is not None:
os.environ["HF_HUB_OFFLINE"] = original_hf_offline
reload_modules(bool(original_hf_offline))
else:
del os.environ["HF_HUB_OFFLINE"]
reload_modules(False)
return wrapper
def disable_hf_offline(test_func):
"""
test decorator that sets HF_HUB_OFFLINE environment variable to False and restores it after the wrapped func
:param test_func:
:return:
"""
@wraps(test_func)
def wrapper(*args, **kwargs):
# Save the original value of HF_HUB_OFFLINE environment variable
original_hf_offline = os.getenv("HF_HUB_OFFLINE")
# Set HF_OFFLINE environment variable to True
os.environ["HF_HUB_OFFLINE"] = "0"
reload_modules(False)
try:
# Run the test function
return test_func(*args, **kwargs)
finally:
# Restore the original value of HF_HUB_OFFLINE environment variable
if original_hf_offline is not None:
os.environ["HF_HUB_OFFLINE"] = original_hf_offline
reload_modules(bool(original_hf_offline))
else:
del os.environ["HF_HUB_OFFLINE"]
reload_modules(False)
return wrapper