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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
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16
tests/prompt_strategies/conftest.py
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@@ -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