code: 
  
  
  '''simple docstring'''
  
  from copy import deepcopy
  from unittest.case import TestCase
  
  import pytest
  
  from datasets.arrow_dataset import Dataset
  from datasets.features import Audio, ClassLabel, Features, Image, Sequence, Value
  from datasets.info import DatasetInfo
  from datasets.tasks import (
      AudioClassification,
      AutomaticSpeechRecognition,
      ImageClassification,
      LanguageModeling,
      QuestionAnsweringExtractive,
      Summarization,
      TextClassification,
      task_template_from_dict,
  )
  from datasets.utils.py_utils import asdict
  
  
  lowerCamelCase							:     List[str]								=			{
      'id': '5733be284776f41900661182',
      'title': 'University_of_Notre_Dame',
      'context': 'Architecturally, the school has a Catholic character. Atop the Main Building\'s gold dome is a golden statue of the Virgin Mary. Immediately in front of the Main Building and facing it, is a copper statue of Christ with arms upraised with the legend \"Venite Ad Me Omnes\". Next to the Main Building is the Basilica of the Sacred Heart. Immediately behind the basilica is the Grotto, a Marian place of prayer and reflection. It is a replica of the grotto at Lourdes, France where the Virgin Mary reputedly appeared to Saint Bernadette Soubirous in 1858. At the end of the main drive (and in a direct line that connects through 3 statues and the Gold Dome), is a simple, modern stone statue of Mary.',
      'question': 'To whom did the Virgin Mary allegedly appear in 1858 in Lourdes France?',
      'answers': {'text': ['Saint Bernadette Soubirous'], 'answer_start': [515]},
  }
  
  @pytest.mark.parametrize(
      '''task_cls'''						,				[
          AudioClassification,
          AutomaticSpeechRecognition,
          ImageClassification,
          LanguageModeling,
          QuestionAnsweringExtractive,
          Summarization,
          TextClassification,
      ]						,				)
  def _SCREAMING_SNAKE_CASE   (A ) -> Optional[Any]:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				task_cls()
         lowercase__       =				asdict(A )
         lowercase__       =				task_template_from_dict(A )
         assert task == reloaded
  class 						__lowerCAmelCase		:
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Tuple				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				LanguageModeling(text_column='''input_text'''				)
               assert {"input_text": "text"} == task.column_mapping
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Tuple				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Features({'''text''': Value('''string'''				)}				)
               lowercase__       =				{'''text_column''': '''input_text'''}
               lowercase__       =				LanguageModeling.from_dict(UpperCamelCase__				)
               assert "language-modeling" == task.task
               assert input_schema == task.input_schema
  
  
  
  
  
  
  class 						__lowerCAmelCase		(_SCREAMING_SNAKE_CASE  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				sorted(['''pos''', '''neg''']				)
  
  
  
        def    UpperCamelCase__	(self					:					str				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				TextClassification(text_column='''input_text'''     ,		label_column='''input_label'''				)
               self.assertDictEqual({'''input_text''': '''text''', '''input_label''': '''labels'''}     ,		task.column_mapping				)
  
  
  
        def    UpperCamelCase__	(self					:					int				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Features({'''text''': Value('''string'''				)}				)
               # Labels are cast to tuple during `TextClassification.__post_init__`, so we do the same here
               lowercase__       =				Features({'''labels''': ClassLabel}				)
               lowercase__       =				{'''text_column''': '''input_text''', '''label_column''': '''input_labels'''}
               lowercase__       =				TextClassification.from_dict(UpperCamelCase__				)
               self.assertEqual('''text-classification'''     ,		task.task				)
               self.assertEqual(UpperCamelCase__     ,		task.input_schema				)
               self.assertEqual(UpperCamelCase__     ,		task.label_schema				)
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				TextClassification(text_column='''input_text'''     ,		label_column='''input_label'''				)
               self.assertEqual(task.label_schema['''labels''']     ,		UpperCamelCase__				)
               lowercase__       =				task.align_with_features(Features({'''input_label''': ClassLabel(names=self.labels				)}				)				)
               self.assertEqual(task.label_schema['''labels''']     ,		ClassLabel(names=self.labels				)				)
  
  
  
  
  
  
  class 						__lowerCAmelCase		(_SCREAMING_SNAKE_CASE  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				QuestionAnsweringExtractive(
                   context_column='''input_context'''     ,		question_column='''input_question'''     ,		answers_column='''input_answers'''				)
               self.assertDictEqual(
                   {'''input_context''': '''context''', '''input_question''': '''question''', '''input_answers''': '''answers'''}     ,		task.column_mapping				)
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Tuple				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Features({'''question''': Value('''string'''				), '''context''': Value('''string'''				)}				)
               lowercase__       =				Features(
                   {
                       '''answers''': Sequence(
                           {
                               '''text''': Value('''string'''				),
                               '''answer_start''': Value('''int32'''				),
                           }				)
                   }				)
               lowercase__       =				{
                   '''context_column''': '''input_input_context''',
                   '''question_column''': '''input_question''',
                   '''answers_column''': '''input_answers''',
               }
               lowercase__       =				QuestionAnsweringExtractive.from_dict(UpperCamelCase__				)
               self.assertEqual('''question-answering-extractive'''     ,		task.task				)
               self.assertEqual(UpperCamelCase__     ,		task.input_schema				)
               self.assertEqual(UpperCamelCase__     ,		task.label_schema				)
  
  
  
  
  
  
  class 						__lowerCAmelCase		(_SCREAMING_SNAKE_CASE  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Optional[int]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Summarization(text_column='''input_text'''     ,		summary_column='''input_summary'''				)
               self.assertDictEqual({'''input_text''': '''text''', '''input_summary''': '''summary'''}     ,		task.column_mapping				)
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Features({'''text''': Value('''string'''				)}				)
               lowercase__       =				Features({'''summary''': Value('''string'''				)}				)
               lowercase__       =				{'''text_column''': '''input_text''', '''summary_column''': '''input_summary'''}
               lowercase__       =				Summarization.from_dict(UpperCamelCase__				)
               self.assertEqual('''summarization'''     ,		task.task				)
               self.assertEqual(UpperCamelCase__     ,		task.input_schema				)
               self.assertEqual(UpperCamelCase__     ,		task.label_schema				)
  
  
  
  
  
  
  class 						__lowerCAmelCase		(_SCREAMING_SNAKE_CASE  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					List[str]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				AutomaticSpeechRecognition(audio_column='''input_audio'''     ,		transcription_column='''input_transcription'''				)
               self.assertDictEqual({'''input_audio''': '''audio''', '''input_transcription''': '''transcription'''}     ,		task.column_mapping				)
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					int				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Features({'''audio''': Audio()}				)
               lowercase__       =				Features({'''transcription''': Value('''string'''				)}				)
               lowercase__       =				{
                   '''audio_column''': '''input_audio''',
                   '''transcription_column''': '''input_transcription''',
               }
               lowercase__       =				AutomaticSpeechRecognition.from_dict(UpperCamelCase__				)
               self.assertEqual('''automatic-speech-recognition'''     ,		task.task				)
               self.assertEqual(UpperCamelCase__     ,		task.input_schema				)
               self.assertEqual(UpperCamelCase__     ,		task.label_schema				)
  
  
  
  
  
  
  class 						__lowerCAmelCase		(_SCREAMING_SNAKE_CASE  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					int				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				sorted(['''pos''', '''neg''']				)
  
  
  
        def    UpperCamelCase__	(self					:					List[str]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				AudioClassification(audio_column='''input_audio'''     ,		label_column='''input_label'''				)
               self.assertDictEqual({'''input_audio''': '''audio''', '''input_label''': '''labels'''}     ,		task.column_mapping				)
  
  
  
        def    UpperCamelCase__	(self					:					int				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Features({'''audio''': Audio()}				)
               lowercase__       =				Features({'''labels''': ClassLabel}				)
               lowercase__       =				{
                   '''audio_column''': '''input_image''',
                   '''label_column''': '''input_label''',
               }
               lowercase__       =				AudioClassification.from_dict(UpperCamelCase__				)
               self.assertEqual('''audio-classification'''     ,		task.task				)
               self.assertEqual(UpperCamelCase__     ,		task.input_schema				)
               self.assertEqual(UpperCamelCase__     ,		task.label_schema				)
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					str				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				AudioClassification(audio_column='''input_audio'''     ,		label_column='''input_label'''				)
               self.assertEqual(task.label_schema['''labels''']     ,		UpperCamelCase__				)
               lowercase__       =				task.align_with_features(Features({'''input_label''': ClassLabel(names=self.labels				)}				)				)
               self.assertEqual(task.label_schema['''labels''']     ,		ClassLabel(names=self.labels				)				)
  
  
  
  
  
  
  class 						__lowerCAmelCase		(_SCREAMING_SNAKE_CASE  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Tuple				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				sorted(['''pos''', '''neg''']				)
  
  
  
        def    UpperCamelCase__	(self					:					Tuple				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				ImageClassification(image_column='''input_image'''     ,		label_column='''input_label'''				)
               self.assertDictEqual({'''input_image''': '''image''', '''input_label''': '''labels'''}     ,		task.column_mapping				)
  
  
  
        def    UpperCamelCase__	(self					:					Tuple				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Features({'''image''': Image()}				)
               lowercase__       =				Features({'''labels''': ClassLabel}				)
               lowercase__       =				{
                   '''image_column''': '''input_image''',
                   '''label_column''': '''input_label''',
               }
               lowercase__       =				ImageClassification.from_dict(UpperCamelCase__				)
               self.assertEqual('''image-classification'''     ,		task.task				)
               self.assertEqual(UpperCamelCase__     ,		task.input_schema				)
               self.assertEqual(UpperCamelCase__     ,		task.label_schema				)
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Optional[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				ImageClassification(image_column='''input_image'''     ,		label_column='''input_label'''				)
               self.assertEqual(task.label_schema['''labels''']     ,		UpperCamelCase__				)
               lowercase__       =				task.align_with_features(Features({'''input_label''': ClassLabel(names=self.labels				)}				)				)
               self.assertEqual(task.label_schema['''labels''']     ,		ClassLabel(names=self.labels				)				)
  
  
  
  
  
  
  class 						__lowerCAmelCase		(_SCREAMING_SNAKE_CASE  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Tuple				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				DatasetInfo(task_templates=QuestionAnsweringExtractive()				)
               lowercase__       =				Dataset.from_dict({k: [v] for k, v in SAMPLE_QUESTION_ANSWERING_EXTRACTIVE.items()}     ,		info=UpperCamelCase__				)
               assert isinstance(dataset.info.task_templates     ,		UpperCamelCase__				)
               assert len(dataset.info.task_templates				) == 1
  
               def keep_task(UpperCamelCase					:					Any				):
                      return x
  
               def dont_keep_task(UpperCamelCase					:					Union[str, Any]				):
                      lowercase__       =				deepcopy(UpperCamelCase__				)
                      lowercase__       =				0
                      return out
  
               lowercase__       =				dataset.map(UpperCamelCase__				)
               assert mapped_dataset.info.task_templates == dataset.info.task_templates
               # reload from cache
               lowercase__       =				dataset.map(UpperCamelCase__				)
               assert mapped_dataset.info.task_templates == dataset.info.task_templates
  
               lowercase__       =				dataset.map(UpperCamelCase__				)
               assert mapped_dataset.info.task_templates == []
               # reload from cache
               lowercase__       =				dataset.map(UpperCamelCase__				)
               assert mapped_dataset.info.task_templates == []
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				Features({'''text''': Value('''string'''				), '''label''': ClassLabel(names=('''pos''', '''neg''')				)}				)
               lowercase__       =				TextClassification(text_column='''text'''     ,		label_column='''label'''				)
               lowercase__       =				DatasetInfo(features=UpperCamelCase__     ,		task_templates=UpperCamelCase__				)
               lowercase__       =				Dataset.from_dict({'''text''': ['''A sentence.'''], '''label''': ['''pos''']}     ,		info=UpperCamelCase__				)
  
               def process(UpperCamelCase					:					Dict				):
                      return example
  
               lowercase__       =				dataset.remove_columns('''label'''				)
               lowercase__       =				modified_dataset.map(UpperCamelCase__				)
               assert mapped_dataset.info.task_templates == []
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  import json
  import os
  from functools import lru_cache
  from typing import TYPE_CHECKING, List, Optional, Tuple, Union
  
  import numpy as np
  import regex as re
  
  from ...utils import is_tf_available, is_torch_available, logging
  
  
  if TYPE_CHECKING:
   if is_torch_available():
    import torch
   if is_tf_available():
    import tensorflow as tf
  
  from ...tokenization_utils import AddedToken, PreTrainedTokenizer
  
  
  lowerCamelCase							:     Union[str, Any]								=			logging.get_logger(__name__)
  
  lowerCamelCase							:     Tuple								=			{
      'vocab_file': 'vocab.json',
      'merges_file': 'merges.txt',
  }
  
  lowerCamelCase							:     Tuple								=			{
      'vocab_file': {
          'Salesforce/codegen-350M-mono': 'https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/vocab.json',
      },
      'merges_file': {
          'Salesforce/codegen-350M-mono': 'https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/merges.txt',
      },
  }
  
  lowerCamelCase							:     Optional[int]								=			{
      'Salesforce/codegen-350M-mono': 2_048,
  }
  
  @lru_cache()
  def _SCREAMING_SNAKE_CASE   () -> Optional[int]:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				(
             list(range(ord('''!''' )						,				ord('''~''' ) + 1 ) ) + list(range(ord('''¡''' )						,				ord('''¬''' ) + 1 ) ) + list(range(ord('''®''' )						,				ord('''ÿ''' ) + 1 ) )
         )
         lowercase__       =				bs[:]
         lowercase__       =				0
         for b in range(2**8 ):
                if b not in bs:
                       bs.append(A )
                       cs.append(2**8 + n )
                       n += 1
         lowercase__       =				[chr(A ) for n in cs]
         return dict(zip(A						,				A ) )
  
  def _SCREAMING_SNAKE_CASE   (A ) -> Tuple:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				set()
         lowercase__       =				word[0]
         for char in word[1:]:
                pairs.add((prev_char, char) )
                lowercase__       =				char
         return pairs
  
  class 						__lowerCAmelCase		(lowercase_  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        lowerCAmelCase__      :  int						      =							VOCAB_FILES_NAMES
        lowerCAmelCase__      :  Union[str, Any]						      =							PRETRAINED_VOCAB_FILES_MAP
        lowerCAmelCase__      :  Optional[int]						      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
        lowerCAmelCase__      :  Tuple						      =							["""input_ids""", """attention_mask"""]
  
  
  
        def __init__(self					:					List[Any]     ,		UpperCamelCase					:					List[str]     ,		UpperCamelCase					:					List[Any]     ,		UpperCamelCase					:					Optional[int]="replace"     ,		UpperCamelCase					:					Optional[Any]="<|endoftext|>"     ,		UpperCamelCase					:					str="<|endoftext|>"     ,		UpperCamelCase					:					Optional[int]="<|endoftext|>"     ,		UpperCamelCase					:					Optional[int]=None     ,		UpperCamelCase					:					str=False     ,		UpperCamelCase					:					Any=False     ,		**UpperCamelCase					:					Dict     ,		):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				AddedToken(UpperCamelCase     ,		lstrip=UpperCamelCase     ,		rstrip=UpperCamelCase				) if isinstance(UpperCamelCase     ,		UpperCamelCase				) else bos_token
               lowercase__       =				AddedToken(UpperCamelCase     ,		lstrip=UpperCamelCase     ,		rstrip=UpperCamelCase				) if isinstance(UpperCamelCase     ,		UpperCamelCase				) else eos_token
               lowercase__       =				AddedToken(UpperCamelCase     ,		lstrip=UpperCamelCase     ,		rstrip=UpperCamelCase				) if isinstance(UpperCamelCase     ,		UpperCamelCase				) else unk_token
               lowercase__       =				AddedToken(UpperCamelCase     ,		lstrip=UpperCamelCase     ,		rstrip=UpperCamelCase				) if isinstance(UpperCamelCase     ,		UpperCamelCase				) else pad_token
               super().__init__(
                   errors=UpperCamelCase     ,		unk_token=UpperCamelCase     ,		bos_token=UpperCamelCase     ,		eos_token=UpperCamelCase     ,		pad_token=UpperCamelCase     ,		add_prefix_space=UpperCamelCase     ,		add_bos_token=UpperCamelCase     ,		**UpperCamelCase     ,		)
               lowercase__       =				add_bos_token
  
               with open(UpperCamelCase     ,		encoding='''utf-8'''				) as vocab_handle:
                      lowercase__       =				json.load(UpperCamelCase				)
               lowercase__       =				{v: k for k, v in self.encoder.items()}
               lowercase__       =				errors  # how to handle errors in decoding
               lowercase__       =				bytes_to_unicode()
               lowercase__       =				{v: k for k, v in self.byte_encoder.items()}
               with open(UpperCamelCase     ,		encoding='''utf-8'''				) as merges_handle:
                      lowercase__       =				merges_handle.read().split('''\n'''				)[1:-1]
               lowercase__       =				[tuple(merge.split()				) for merge in bpe_merges]
               lowercase__       =				dict(zip(UpperCamelCase     ,		range(len(UpperCamelCase				)				)				)				)
               lowercase__       =				{}
               lowercase__       =				add_prefix_space
  
               # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
               lowercase__       =				re.compile(R'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''				)
  
  
  
        @property
        def    UpperCamelCase__	(self					:					Any				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               return len(self.encoder				)
  
  
  
        def    UpperCamelCase__	(self					:					Optional[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               return dict(self.encoder     ,		**self.added_tokens_encoder				)
  
  
  
        def    UpperCamelCase__	(self					:					Union[str, Any]     ,		UpperCamelCase					:					Optional[int]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if token in self.cache:
                      return self.cache[token]
               lowercase__       =				tuple(UpperCamelCase				)
               lowercase__       =				get_pairs(UpperCamelCase				)
  
               if not pairs:
                      return token
  
               while True:
                      lowercase__       =				min(UpperCamelCase     ,		key=lambda UpperCamelCase				: self.bpe_ranks.get(UpperCamelCase     ,		float('''inf'''				)				)				)
                      if bigram not in self.bpe_ranks:
                             break
                      lowercase__    ,lowercase__       =				bigram
                      lowercase__       =				[]
                      lowercase__       =				0
                      while i < len(UpperCamelCase				):
                             try:
                                    lowercase__       =				word.index(UpperCamelCase     ,		UpperCamelCase				)
                             except ValueError:
                                    new_word.extend(word[i:]				)
                                    break
                             else:
                                    new_word.extend(word[i:j]				)
                                    lowercase__       =				j
  
                             if word[i] == first and i < len(UpperCamelCase				) - 1 and word[i + 1] == second:
                                    new_word.append(first + second				)
                                    i += 2
                             else:
                                    new_word.append(word[i]				)
                                    i += 1
                      lowercase__       =				tuple(UpperCamelCase				)
                      lowercase__       =				new_word
                      if len(UpperCamelCase				) == 1:
                             break
                      else:
                             lowercase__       =				get_pairs(UpperCamelCase				)
               lowercase__       =				''' '''.join(UpperCamelCase				)
               lowercase__       =				word
               return word
  
  
  
        def    UpperCamelCase__	(self					:					Any     ,		UpperCamelCase					:					str     ,		UpperCamelCase					:					str=None				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if self.add_bos_token:
                      lowercase__       =				[self.bos_token_id]
               else:
                      lowercase__       =				[]
  
               lowercase__       =				bos_token_ids + token_ids_a
  
               if token_ids_a is None:
                      return output
  
               return output + bos_token_ids + token_ids_a
  
  
  
        def    UpperCamelCase__	(self					:					Optional[Any]     ,		UpperCamelCase					:					str				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				[]
               for token in re.findall(self.pat     ,		UpperCamelCase				):
                      lowercase__       =				''''''.join(
                          self.byte_encoder[b] for b in token.encode('''utf-8'''				)				)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
                      bpe_tokens.extend(bpe_token for bpe_token in self.bpe(UpperCamelCase				).split(''' '''				)				)
               return bpe_tokens
  
  
  
        def    UpperCamelCase__	(self					:					str     ,		UpperCamelCase					:					str				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               return self.encoder.get(UpperCamelCase     ,		self.encoder.get(self.unk_token				)				)
  
  
  
        def    UpperCamelCase__	(self					:					Any     ,		UpperCamelCase					:					Optional[int]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               return self.decoder.get(UpperCamelCase				)
  
  
  
        def    UpperCamelCase__	(self					:					List[Any]     ,		UpperCamelCase					:					Optional[int]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				''''''.join(UpperCamelCase				)
               lowercase__       =				bytearray([self.byte_decoder[c] for c in text]				).decode('''utf-8'''     ,		errors=self.errors				)
               return text
  
  
  
        def    UpperCamelCase__	(self					:					int     ,		UpperCamelCase					:					str     ,		UpperCamelCase					:					Optional[str] = None				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if not os.path.isdir(UpperCamelCase				):
                      logger.error(f"Vocabulary path ({save_directory}) should be a directory"				)
                      return
               lowercase__       =				os.path.join(
                   UpperCamelCase     ,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)
               lowercase__       =				os.path.join(
                   UpperCamelCase     ,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']				)
  
               with open(UpperCamelCase     ,		'''w'''     ,		encoding='''utf-8'''				) as f:
                      f.write(json.dumps(self.encoder     ,		indent=2     ,		sort_keys=UpperCamelCase     ,		ensure_ascii=UpperCamelCase				) + '''\n'''				)
  
               lowercase__       =				0
               with open(UpperCamelCase     ,		'''w'''     ,		encoding='''utf-8'''				) as writer:
                      writer.write('''#version: 0.2\n'''				)
                      for bpe_tokens, token_index in sorted(self.bpe_ranks.items()     ,		key=lambda UpperCamelCase				: kv[1]				):
                             if index != token_index:
                                    logger.warning(
                                        f"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
                                        ''' Please check that the tokenizer is not corrupted!'''				)
                                    lowercase__       =				token_index
                             writer.write(''' '''.join(UpperCamelCase				) + '''\n'''				)
                             index += 1
  
               return vocab_file, merge_file
  
  
  
        def    UpperCamelCase__	(self					:					str     ,		UpperCamelCase					:					List[Any]     ,		UpperCamelCase					:					int=False     ,		**UpperCamelCase					:					Optional[int]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				kwargs.pop('''add_prefix_space'''     ,		self.add_prefix_space				)
               if is_split_into_words or add_prefix_space:
                      lowercase__       =				''' ''' + text
               return (text, kwargs)
  
  
  
        def    UpperCamelCase__	(self					:					Tuple     ,		UpperCamelCase					:					Union[int, List[int], "np.ndarray", "torch.Tensor", "tf.Tensor"]     ,		UpperCamelCase					:					bool = False     ,		UpperCamelCase					:					bool = None     ,		UpperCamelCase					:					Optional[List[str]] = None     ,		**UpperCamelCase					:					Optional[Any]     ,		):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				super()._decode(
                   token_ids=UpperCamelCase     ,		skip_special_tokens=UpperCamelCase     ,		clean_up_tokenization_spaces=UpperCamelCase     ,		**UpperCamelCase     ,		)
  
               if truncate_before_pattern is not None and len(UpperCamelCase				) > 0:
                      lowercase__       =				self.truncate(UpperCamelCase     ,		UpperCamelCase				)
  
               return decoded_text
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					str     ,		UpperCamelCase					:					List[str]     ,		UpperCamelCase					:					Union[str, Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               def find_re(UpperCamelCase					:					Dict     ,		UpperCamelCase					:					Dict     ,		UpperCamelCase					:					Optional[Any]				):
                      lowercase__       =				pattern.search(UpperCamelCase     ,		UpperCamelCase				)
                      return m.start() if m else -1
  
               lowercase__       =				[re.compile(UpperCamelCase     ,		re.MULTILINE				) for pattern in truncate_before_pattern]
  
               lowercase__       =				list(re.finditer('''^print'''     ,		UpperCamelCase     ,		re.MULTILINE				)				)
  
               if len(UpperCamelCase				) > 1:
                      lowercase__       =				completion[: prints[1].start()]
  
               lowercase__       =				list(re.finditer('''^def'''     ,		UpperCamelCase     ,		re.MULTILINE				)				)
  
               if len(UpperCamelCase				) > 1:
                      lowercase__       =				completion[: defs[1].start()]
  
               lowercase__       =				0
  
               lowercase__       =				[
                   pos for pos in [find_re(UpperCamelCase     ,		UpperCamelCase     ,		UpperCamelCase				) for terminal in terminals] if pos != -1
               ]
  
               if len(UpperCamelCase				) > 0:
                      return completion[: min(UpperCamelCase				)]
               else:
                      return completion
  
  
  
  
  