'''simple docstring'''






import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Value
from .base import TaskTemplate

@dataclass(frozen=lowerCamelCase__     )
class 							a__( lowerCamelCase__     ):
    # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
    lowercase__			=   field(default="""text-classification"""		,			metadata={"""include_in_asdict_even_if_is_default""": True}     )
    lowercase__			=   Features({"""text""": Value("""string"""     )}     )
    lowercase__			=   Features({"""labels""": ClassLabel}     )
    lowercase__			=   """text"""
    lowercase__			=   """labels"""







    def       lowercase_	(				self			:  Optional[Any]						,      __snake_case			:  Optional[Any]     ):
      if self.label_column not in features:
        raise ValueError(F"""Column {self.label_column} is not present in features."""     )
      if not isinstance(features[self.label_column]						,      __snake_case     ):
        raise ValueError(F"""Column {self.label_column} is not a ClassLabel."""     )
      a						: List[Any]					       =					copy.deepcopy(self     )
      a						: str					       =					self.label_schema.copy()
      a						: List[Any]					       =					features[self.label_column]
      a						: Optional[Any]					       =					label_schema
      return task_template







    @property
    def       lowercase_	(				self			:  int     ):
      return {
          self.text_column: "text",
          self.label_column: "labels",
      }




'''simple docstring'''






import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin

class 							a__( lowerCamelCase__		,			unittest.TestCase     ):
    lowercase__			=   CTRLTokenizer
    lowercase__			=   False
    lowercase__			=   False







    def       lowercase_	(				self			:  Dict     ):
      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      a						: Tuple					       =					['adapt', 're@@', 'a@@', 'apt', 'c@@', 't', '<unk>']
      a						: Union[str, Any]					       =					dict(zip(__snake_case						,      range(len(__snake_case     )     )     )     )
      a						: Union[str, Any]					       =					['#version: 0.2', 'a p', 'ap t</w>', 'r e', 'a d', 'ad apt</w>', '']
      a						: Optional[Any]					       =					{'unk_token': '<unk>'}

      a						: Dict					       =					os.path.join(self.tmpdirname						,      VOCAB_FILES_NAMES['vocab_file']     )
      a						: Optional[Any]					       =					os.path.join(self.tmpdirname						,      VOCAB_FILES_NAMES['merges_file']     )
      with open(self.vocab_file						,      'w'						,      encoding='utf-8'     ) as fp:
        fp.write(json.dumps(__snake_case     ) + '\n'     )
      with open(self.merges_file						,      'w'						,      encoding='utf-8'     ) as fp:
        fp.write('\n'.join(__snake_case     )     )







    def       lowercase_	(				self			:  int						,      **__snake_case			:  str     ):
      kwargs.update(self.special_tokens_map     )
      return CTRLTokenizer.from_pretrained(self.tmpdirname						,      **__snake_case     )







    def       lowercase_	(				self			:  Optional[int]						,      __snake_case			:  Any     ):
      a						: int					       =					'adapt react readapt apt'
      a						: Any					       =					'adapt react readapt apt'
      return input_text, output_text







    def       lowercase_	(				self			:  Dict     ):
      a						: Dict					       =					CTRLTokenizer(self.vocab_file						,      self.merges_file						,      **self.special_tokens_map     )
      a						: List[str]					       =					'adapt react readapt apt'
      a						: Dict					       =					'adapt re@@ a@@ c@@ t re@@ adapt apt'.split()
      a						: Any					       =					tokenizer.tokenize(__snake_case     )
      self.assertListEqual(__snake_case						,      __snake_case     )

      a						: Dict					       =					tokens + [tokenizer.unk_token]

      a						: Optional[Any]					       =					[0, 1, 2, 4, 5, 1, 0, 3, 6]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case     )						,      __snake_case     )