2023-12-18 02:20:08 -07:00
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import os
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import requests
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import tempfile
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2023-02-14 05:02:16 -07:00
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import pytest
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2023-12-18 02:20:08 -07:00
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import huggingface_hub.constants
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from huggingface_hub import hf_api
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import text_generation_server.utils.hub
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2023-03-07 10:52:22 -07:00
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from text_generation_server.utils.hub import (
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2023-02-14 05:02:16 -07:00
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weight_hub_files,
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download_weights,
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weight_files,
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EntryNotFoundError,
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LocalEntryNotFoundError,
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RevisionNotFoundError,
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)
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2023-12-18 02:20:08 -07:00
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@pytest.fixture()
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def offline():
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current_value = text_generation_server.utils.hub.HF_HUB_OFFLINE
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text_generation_server.utils.hub.HF_HUB_OFFLINE = True
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yield "offline"
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text_generation_server.utils.hub.HF_HUB_OFFLINE = current_value
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@pytest.fixture()
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def fresh_cache():
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with tempfile.TemporaryDirectory() as d:
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current_value = huggingface_hub.constants.HUGGINGFACE_HUB_CACHE
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huggingface_hub.constants.HUGGINGFACE_HUB_CACHE = d
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text_generation_server.utils.hub.HUGGINGFACE_HUB_CACHE = d
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2023-12-21 09:25:22 -07:00
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os.environ["HUGGINGFACE_HUB_CACHE"] = d
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yield
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huggingface_hub.constants.HUGGINGFACE_HUB_CACHE = current_value
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os.environ["HUGGINGFACE_HUB_CACHE"] = current_value
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text_generation_server.utils.hub.HUGGINGFACE_HUB_CACHE = current_value
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@pytest.fixture()
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def prefetched():
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model_id = "bert-base-uncased"
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huggingface_hub.snapshot_download(
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repo_id=model_id,
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revision="main",
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local_files_only=False,
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repo_type="model",
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allow_patterns=["*.safetensors"],
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2023-12-18 02:20:08 -07:00
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)
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yield model_id
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def test_weight_hub_files_offline_error(offline, fresh_cache):
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# If the model is not prefetched then it will raise an error
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with pytest.raises(EntryNotFoundError):
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weight_hub_files("gpt2")
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def test_weight_hub_files_offline_ok(prefetched, offline):
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# If the model is prefetched then we should be able to get the weight files from local cache
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filenames = weight_hub_files(prefetched)
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root = None
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assert len(filenames) == 1
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for f in filenames:
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curroot, filename = os.path.split(f)
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if root is None:
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root = curroot
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else:
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assert root == curroot
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assert filename == "model.safetensors"
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2023-02-14 05:02:16 -07:00
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def test_weight_hub_files():
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filenames = weight_hub_files("bigscience/bloom-560m")
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assert filenames == ["model.safetensors"]
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def test_weight_hub_files_llm():
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filenames = weight_hub_files("bigscience/bloom")
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assert filenames == [f"model_{i:05d}-of-00072.safetensors" for i in range(1, 73)]
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def test_weight_hub_files_empty():
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with pytest.raises(EntryNotFoundError):
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weight_hub_files("bigscience/bloom", extension=".errors")
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def test_download_weights():
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model_id = "bigscience/bloom-560m"
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filenames = weight_hub_files(model_id)
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files = download_weights(filenames, model_id)
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local_files = weight_files("bigscience/bloom-560m")
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assert files == local_files
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def test_weight_files_revision_error():
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with pytest.raises(RevisionNotFoundError):
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weight_files("bigscience/bloom-560m", revision="error")
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def test_weight_files_not_cached_error(fresh_cache):
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with pytest.raises(LocalEntryNotFoundError):
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weight_files("bert-base-uncased")
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