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* Use initialize_device_settings in all nodes * Set StreamHandler level to INFO * Add latest docstring and tutorial changes * work in progress * Standardize device initialization * Add latest docstring and tutorial changes * Adapt device initialization in Reader's train method Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
30 lines
987 B
Python
30 lines
987 B
Python
import logging
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from haystack.modeling.model.adaptive_model import AdaptiveModel
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from haystack.modeling.model.language_model import LanguageModel
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from haystack.modeling.model.prediction_head import QuestionAnsweringHead
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from haystack.modeling.utils import set_all_seeds, initialize_device_settings
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def test_prediction_head_load_save(tmp_path, caplog=None):
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if caplog:
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caplog.set_level(logging.CRITICAL)
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set_all_seeds(seed=42)
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devices, n_gpu = initialize_device_settings(use_cuda=False)
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lang_model = "bert-base-german-cased"
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language_model = LanguageModel.load(lang_model)
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prediction_head = QuestionAnsweringHead()
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model = AdaptiveModel(
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language_model=language_model,
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prediction_heads=[prediction_head],
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embeds_dropout_prob=0.1,
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lm_output_types=["per_sequence"],
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device=devices[0])
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model.save(tmp_path)
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model_loaded = AdaptiveModel.load(tmp_path, device='cpu')
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assert model_loaded is not None
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