import os import requests import tempfile import pytest import huggingface_hub.constants from huggingface_hub import hf_api import text_generation_server.utils.hub from text_generation_server.utils.hub import ( weight_hub_files, download_weights, weight_files, EntryNotFoundError, LocalEntryNotFoundError, RevisionNotFoundError, ) @pytest.fixture() def offline(): current_value = text_generation_server.utils.hub.HF_HUB_OFFLINE text_generation_server.utils.hub.HF_HUB_OFFLINE = True yield "offline" text_generation_server.utils.hub.HF_HUB_OFFLINE = current_value @pytest.fixture() def fresh_cache(): with tempfile.TemporaryDirectory() as d: current_value = huggingface_hub.constants.HUGGINGFACE_HUB_CACHE huggingface_hub.constants.HUGGINGFACE_HUB_CACHE = d text_generation_server.utils.hub.HUGGINGFACE_HUB_CACHE = d os.environ["HUGGINGFACE_HUB_CACHE"] = d yield huggingface_hub.constants.HUGGINGFACE_HUB_CACHE = current_value os.environ["HUGGINGFACE_HUB_CACHE"] = current_value text_generation_server.utils.hub.HUGGINGFACE_HUB_CACHE = current_value @pytest.fixture() def prefetched(): model_id = "bert-base-uncased" huggingface_hub.snapshot_download( repo_id=model_id, revision="main", local_files_only=False, repo_type="model", allow_patterns=["*.safetensors"], ) yield model_id def test_weight_hub_files_offline_error(offline, fresh_cache): # If the model is not prefetched then it will raise an error with pytest.raises(EntryNotFoundError): weight_hub_files("gpt2") def test_weight_hub_files_offline_ok(prefetched, offline): # If the model is prefetched then we should be able to get the weight files from local cache filenames = weight_hub_files(prefetched) root = None assert len(filenames) == 1 for f in filenames: curroot, filename = os.path.split(f) if root is None: root = curroot else: assert root == curroot assert filename == "model.safetensors" def test_weight_hub_files(): filenames = weight_hub_files("bigscience/bloom-560m") assert filenames == ["model.safetensors"] def test_weight_hub_files_llm(): filenames = weight_hub_files("bigscience/bloom") assert filenames == [f"model_{i:05d}-of-00072.safetensors" for i in range(1, 73)] def test_weight_hub_files_empty(): with pytest.raises(EntryNotFoundError): weight_hub_files("bigscience/bloom", extension=".errors") def test_download_weights(): model_id = "bigscience/bloom-560m" filenames = weight_hub_files(model_id) files = download_weights(filenames, model_id) local_files = weight_files("bigscience/bloom-560m") assert files == local_files def test_weight_files_revision_error(): with pytest.raises(RevisionNotFoundError): weight_files("bigscience/bloom-560m", revision="error") def test_weight_files_not_cached_error(fresh_cache): with pytest.raises(LocalEntryNotFoundError): weight_files("bert-base-uncased")