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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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34 lines
1.4 KiB
34 lines
1.4 KiB
from typing import Type
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from api.models import (DOCUMENT_CLASSIFICATION, IMAGE_CLASSIFICATION,
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INTENT_DETECTION_AND_SLOT_FILLING, SEQ2SEQ,
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SEQUENCE_LABELING, SPEECH2TEXT)
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from . import catalog, repositories, writers
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def create_repository(project) -> repositories.BaseRepository:
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mapping = {
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DOCUMENT_CLASSIFICATION: repositories.TextClassificationRepository,
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SEQUENCE_LABELING: repositories.SequenceLabelingRepository,
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SEQ2SEQ: repositories.Seq2seqRepository,
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IMAGE_CLASSIFICATION: repositories.FileRepository,
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SPEECH2TEXT: repositories.Speech2TextRepository,
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INTENT_DETECTION_AND_SLOT_FILLING: repositories.IntentDetectionSlotFillingRepository,
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}
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if project.project_type not in mapping:
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ValueError(f'Invalid project type: {project.project_type}')
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repository = mapping.get(project.project_type)(project)
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return repository
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def create_writer(file_format: str) -> Type[writers.BaseWriter]:
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mapping = {
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catalog.CSV.name: writers.CsvWriter,
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catalog.JSON.name: writers.JSONWriter,
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catalog.JSONL.name: writers.JSONLWriter,
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catalog.FastText.name: writers.FastTextWriter,
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catalog.IntentAndSlot.name: writers.IntentAndSlotWriter
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}
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if file_format not in mapping:
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ValueError(f'Invalid format: {file_format}')
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return mapping[file_format]
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