doccano/backend/data_import/pipeline/factories.py

from api.models import (DOCUMENT_CLASSIFICATION, IMAGE_CLASSIFICATION,
                        INTENT_DETECTION_AND_SLOT_FILLING, SEQ2SEQ,
                        SEQUENCE_LABELING, SPEECH2TEXT)
from . import builders, catalog, cleaners, data, labels, parsers, readers


def get_data_class(project_type: str):
    text_projects = [
        DOCUMENT_CLASSIFICATION,
        SEQUENCE_LABELING,
        SEQ2SEQ,
        INTENT_DETECTION_AND_SLOT_FILLING
    ]
    if project_type in text_projects:
        return data.TextData
    else:
        return data.FileData


def create_parser(file_format: str, **kwargs):
    mapping = {
        catalog.TextFile.name: parsers.TextFileParser,
        catalog.TextLine.name: parsers.LineParser,
        catalog.CSV.name: parsers.CSVParser,
        catalog.JSONL.name: parsers.JSONLParser,
        catalog.JSON.name: parsers.JSONParser,
        catalog.FastText.name: parsers.FastTextParser,
        catalog.Excel.name: parsers.ExcelParser,
        catalog.CoNLL.name: parsers.CoNLLParser,
        catalog.ImageFile.name: parsers.PlainParser,
        catalog.AudioFile.name: parsers.PlainParser,
    }
    if file_format not in mapping:
        raise ValueError(f'Invalid format: {file_format}')
    return mapping[file_format](**kwargs)


def get_label_class(project_type: str):
    mapping = {
        DOCUMENT_CLASSIFICATION: labels.CategoryLabel,
        SEQUENCE_LABELING: labels.SpanLabel,
        SEQ2SEQ: labels.TextLabel,
        IMAGE_CLASSIFICATION: labels.CategoryLabel,
        SPEECH2TEXT: labels.TextLabel,
    }
    if project_type not in mapping:
        ValueError(f'Invalid project type: {project_type}')
    return mapping[project_type]


def create_cleaner(project):
    mapping = {
        DOCUMENT_CLASSIFICATION: cleaners.CategoryCleaner,
        SEQUENCE_LABELING: cleaners.SpanCleaner,
        IMAGE_CLASSIFICATION: cleaners.CategoryCleaner
    }
    if project.project_type not in mapping:
        ValueError(f'Invalid project type: {project.project_type}')
    cleaner_class = mapping.get(project.project_type, cleaners.Cleaner)
    return cleaner_class(project)


def create_bulder(project, **kwargs):
    data_column = builders.DataColumn(
        name=kwargs.get('column_data') or readers.DEFAULT_TEXT_COLUMN,
        value_class=get_data_class(project.project_type)
    )
    # If project is intent detection and slot filling,
    # column names are fixed: entities, cats
    if project.project_type == INTENT_DETECTION_AND_SLOT_FILLING:
        label_columns = [
            builders.LabelColumn(
                name='cats',
                value_class=labels.CategoryLabel
            ),
            builders.LabelColumn(
                name='entities',
                value_class=labels.SpanLabel
            )
        ]
    else:
        label_columns = [
            builders.LabelColumn(
                name=kwargs.get('column_label') or readers.DEFAULT_LABEL_COLUMN,
                value_class=get_label_class(project.project_type)
            )
        ]
    builder = builders.ColumnBuilder(
        data_column=data_column,
        label_columns=label_columns
    )
    return builder