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f9d2f786ca
* Replace FARM import statements; add dependencies * Add InferenceProc., TextCl.Proc., TextPairCl.Proc. * Remove FARMRanker, add type annotations, rename max_sample * Add sample_to_features_text for InferenceProc. * Fix type annotations: model_name_or_path is str not Path * Fix mypy errors: implement _create_dataset in TextCl.Proc. * Add task_type "embeddings" in Inferencer * Allow loading AdaptiveModel for embedding task * Add SQuAD eval metrics; enable InferenceProc for embedding task * Add baskets as param to log_samples and handle empty basket list in log_samples * Remove unused dependencies * Remove FARMClassifier (doc classificer) due to ref to TextClassificationHead * Remove FARMRanker and Classifier from doc generation scripts Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
20 lines
822 B
Python
20 lines
822 B
Python
import logging
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# Change log-levels before modules are loaded to avoid verbose log messages.
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logging.getLogger('haystack.modeling').setLevel(logging.WARNING)
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logging.getLogger('haystack.modeling.utils').setLevel(logging.INFO)
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logging.getLogger('haystack.modeling.infer').setLevel(logging.INFO)
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logging.getLogger('transformers').setLevel(logging.WARNING)
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logging.getLogger('haystack.modeling.evaluation.eval').setLevel(logging.INFO)
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logging.getLogger('haystack.modeling.model.optimization').setLevel(logging.INFO)
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logging.getLogger('faiss.loader').setLevel(logging.WARNING)
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import pandas as pd
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from haystack.schema import Document, Label, MultiLabel, BaseComponent
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from haystack.pipeline import Pipeline
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from haystack._version import __version__
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pd.options.display.max_colwidth = 80
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logger = logging.getLogger(__name__)
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