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https://github.com/deepset-ai/haystack.git
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a2be90b95a
* fix: Update device deserializtion for SentenceTransformersTextEmbedder * Add unit test * Fix unit test * Make same change to doc embedder * Add release notes * Add same change to Diversity Ranker and Named Entity Extractor * Add unit test * Add the same for whisper local * Update release notes
57 lines
2.1 KiB
Python
57 lines
2.1 KiB
Python
# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
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#
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# SPDX-License-Identifier: Apache-2.0
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import pytest
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from haystack import ComponentError, DeserializationError
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from haystack.components.extractors import NamedEntityExtractor, NamedEntityExtractorBackend
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from haystack.utils.device import ComponentDevice
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@pytest.mark.unit
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def test_named_entity_extractor_backend():
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_ = NamedEntityExtractor(backend=NamedEntityExtractorBackend.HUGGING_FACE, model="dslim/bert-base-NER")
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_ = NamedEntityExtractor(backend="hugging_face", model="dslim/bert-base-NER")
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_ = NamedEntityExtractor(backend=NamedEntityExtractorBackend.SPACY, model="en_core_web_sm")
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_ = NamedEntityExtractor(backend="spacy", model="en_core_web_sm")
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with pytest.raises(ComponentError, match=r"Invalid backend"):
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NamedEntityExtractor(backend="random_backend", model="dslim/bert-base-NER")
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@pytest.mark.unit
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def test_named_entity_extractor_serde():
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extractor = NamedEntityExtractor(
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backend=NamedEntityExtractorBackend.HUGGING_FACE,
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model="dslim/bert-base-NER",
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device=ComponentDevice.from_str("cuda:1"),
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)
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serde_data = extractor.to_dict()
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new_extractor = NamedEntityExtractor.from_dict(serde_data)
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assert type(new_extractor._backend) == type(extractor._backend)
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assert new_extractor._backend.model_name == extractor._backend.model_name
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assert new_extractor._backend.device == extractor._backend.device
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with pytest.raises(DeserializationError, match=r"Couldn't deserialize"):
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serde_data["init_parameters"].pop("backend")
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_ = NamedEntityExtractor.from_dict(serde_data)
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@pytest.mark.unit
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def test_named_entity_extractor_serde_none_device():
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extractor = NamedEntityExtractor(
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backend=NamedEntityExtractorBackend.HUGGING_FACE, model="dslim/bert-base-NER", device=None
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)
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serde_data = extractor.to_dict()
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new_extractor = NamedEntityExtractor.from_dict(serde_data)
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assert type(new_extractor._backend) == type(extractor._backend)
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assert new_extractor._backend.model_name == extractor._backend.model_name
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assert new_extractor._backend.device == extractor._backend.device
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