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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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257 lines
6.0 KiB
257 lines
6.0 KiB
from collections import defaultdict
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from typing import Dict, List, Type
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from pydantic import BaseModel
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from typing_extensions import Literal
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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 examples
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encodings = Literal[
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'Auto',
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'ascii',
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'big5',
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'big5hkscs',
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'cp037',
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'cp273',
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'cp424',
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'cp437',
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'cp500',
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'cp720',
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'cp737',
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'cp775',
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'cp850',
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'cp852',
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'cp855',
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'cp856',
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'cp857',
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'cp858',
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'cp860',
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'cp861',
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'cp862',
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'cp863',
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'cp864',
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'cp865',
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'cp866',
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'cp869',
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'cp874',
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'cp875',
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'cp932',
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'cp949',
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'cp950',
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'cp1006',
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'cp1026',
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'cp1125',
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'cp1140',
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'cp1250',
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'cp1251',
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'cp1252',
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'cp1253',
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'cp1254',
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'cp1255',
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'cp1256',
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'cp1257',
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'cp1258',
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'cp65001',
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'euc_jp',
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'euc_jis_2004',
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'euc_jisx0213',
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'euc_kr',
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'gb2312',
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'gbk',
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'gb18030',
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'hz',
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'iso2022_jp',
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'iso2022_jp_1',
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'iso2022_jp_2',
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'iso2022_jp_2004',
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'iso2022_jp_3',
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'iso2022_jp_ext',
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'iso2022_kr',
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'latin_1',
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'iso8859_2',
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'iso8859_3',
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'iso8859_4',
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'iso8859_5',
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'iso8859_6',
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'iso8859_7',
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'iso8859_8',
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'iso8859_9',
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'iso8859_10',
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'iso8859_11',
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'iso8859_13',
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'iso8859_14',
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'iso8859_15',
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'iso8859_16',
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'johab',
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'koi8_r',
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'koi8_t',
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'koi8_u',
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'kz1048',
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'mac_cyrillic',
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'mac_greek',
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'mac_iceland',
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'mac_latin2',
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'mac_roman',
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'mac_turkish',
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'ptcp154',
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'shift_jis',
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'shift_jis_2004',
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'shift_jisx0213',
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'utf_32',
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'utf_32_be',
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'utf_32_le',
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'utf_16',
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'utf_16_be',
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'utf_16_le',
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'utf_7',
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'utf_8',
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'utf_8_sig'
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]
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class Format:
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name = ''
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accept_types = ''
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@classmethod
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def dict(cls):
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return {
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'name': cls.name,
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'accept_types': cls.accept_types
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}
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class CSV(Format):
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name = 'CSV'
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accept_types = 'text/csv'
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class FastText(Format):
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name = 'fastText'
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accept_types = 'text/plain'
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class JSON(Format):
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name = 'JSON'
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accept_types = 'application/json'
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class JSONL(Format):
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name = 'JSONL'
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accept_types = '*'
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class Excel(Format):
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name = 'Excel'
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accept_types = 'application/vnd.ms-excel, application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'
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class TextFile(Format):
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name = 'TextFile'
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accept_types = 'text/*'
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class TextLine(Format):
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name = 'TextLine'
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accept_types = 'text/*'
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class CoNLL(Format):
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name = 'CoNLL'
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accept_types = 'text/*'
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class ImageFile(Format):
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name = 'ImageFile'
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accept_types = 'image/png, image/jpeg, image/bmp, image/gif'
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class AudioFile(Format):
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name = 'AudioFile'
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accept_types = 'audio/ogg, audio/aac, audio/mpeg, audio/wav'
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class OptionColumn(BaseModel):
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encoding: encodings = 'utf_8'
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column_data: str = 'text'
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column_label: str = 'label'
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class OptionDelimiter(OptionColumn):
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encoding: encodings = 'utf_8'
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delimiter: Literal[',', '\t', ';', '|', ' '] = ','
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class OptionEncoding(BaseModel):
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encoding: encodings = 'utf_8'
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class OptionCoNLL(BaseModel):
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encoding: encodings = 'utf_8'
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scheme: Literal['IOB2', 'IOE2', 'IOBES', 'BILOU'] = 'IOB2'
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delimiter: Literal[' ', ''] = ' '
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class OptionNone(BaseModel):
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pass
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class Options:
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options: Dict[str, List] = defaultdict(list)
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@classmethod
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def filter_by_task(cls, task_name: str):
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options = cls.options[task_name]
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return [
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{
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**format.dict(),
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**option.schema(),
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'example': example
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} for format, option, example in options
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]
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@classmethod
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def register(cls,
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task: str,
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format: Type[Format],
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option: Type[BaseModel],
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example: str):
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cls.options[task].append((format, option, example))
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# Text Classification
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Options.register(DOCUMENT_CLASSIFICATION, TextFile, OptionEncoding, examples.Generic_TextFile)
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Options.register(DOCUMENT_CLASSIFICATION, TextLine, OptionEncoding, examples.Generic_TextLine)
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Options.register(DOCUMENT_CLASSIFICATION, CSV, OptionDelimiter, examples.Category_CSV)
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Options.register(DOCUMENT_CLASSIFICATION, FastText, OptionEncoding, examples.Category_fastText)
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Options.register(DOCUMENT_CLASSIFICATION, JSON, OptionColumn, examples.Category_JSON)
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Options.register(DOCUMENT_CLASSIFICATION, JSONL, OptionColumn, examples.Category_JSONL)
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Options.register(DOCUMENT_CLASSIFICATION, Excel, OptionColumn, examples.Category_CSV)
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# Sequence Labeling
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Options.register(SEQUENCE_LABELING, TextFile, OptionEncoding, examples.Generic_TextFile)
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Options.register(SEQUENCE_LABELING, TextLine, OptionEncoding, examples.Generic_TextLine)
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Options.register(SEQUENCE_LABELING, JSONL, OptionColumn, examples.Offset_JSONL)
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Options.register(SEQUENCE_LABELING, CoNLL, OptionCoNLL, examples.Offset_CoNLL)
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# Sequence to sequence
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Options.register(SEQ2SEQ, TextFile, OptionEncoding, examples.Generic_TextFile)
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Options.register(SEQ2SEQ, TextLine, OptionEncoding, examples.Generic_TextLine)
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Options.register(SEQ2SEQ, CSV, OptionDelimiter, examples.Text_CSV)
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Options.register(SEQ2SEQ, JSON, OptionColumn, examples.Text_JSON)
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Options.register(SEQ2SEQ, JSONL, OptionColumn, examples.Text_JSONL)
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Options.register(SEQ2SEQ, Excel, OptionColumn, examples.Text_CSV)
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# Intent detection and slof filling
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Options.register(INTENT_DETECTION_AND_SLOT_FILLING, TextFile, OptionEncoding, examples.Generic_TextFile)
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Options.register(INTENT_DETECTION_AND_SLOT_FILLING, TextLine, OptionEncoding, examples.Generic_TextLine)
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Options.register(INTENT_DETECTION_AND_SLOT_FILLING, JSONL, OptionNone, examples.IDSF_JSONL)
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# Image classification
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Options.register(IMAGE_CLASSIFICATION, ImageFile, OptionNone, examples.Generic_ImageFile)
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# Speech to Text
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Options.register(SPEECH2TEXT, AudioFile, OptionNone, examples.Generic_AudioFile)
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