






"""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


_UpperCamelCase		:  Any						=		{
    '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': [5_1_5]},
}
@pytest.mark.parametrize(
    'task_cls'		, [
        AudioClassification,
        AutomaticSpeechRecognition,
        ImageClassification,
        LanguageModeling,
        QuestionAnsweringExtractive,
        Summarization,
        TextClassification,
    ]		, )
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Optional[int]   ):





  '''simple docstring'''





  lowercase							   =	task_cls()
  lowercase							   =	asdict(__snake_case   )
  lowercase							   =	task_template_from_dict(__snake_case   )
  assert task == reloaded

class 	a					:







    def       UpperCamelCase_				(      self	):
      lowercase							   =	LanguageModeling(text_column='input_text'	)
      assert {"input_text": "text"} == task.column_mapping







    def       UpperCamelCase_				(      self	):
      lowercase							   =	Features({'text': Value('string'	)}	)
      lowercase							   =	{'text_column': 'input_text'}
      lowercase							   =	LanguageModeling.from_dict(_lowerCamelCase	)
      assert "language-modeling" == task.task
      assert input_schema == task.input_schema


class 	a					(       a_     ):







    def       UpperCamelCase_				(      self	):
      lowercase							   =	sorted(['pos', 'neg']	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	TextClassification(text_column='input_text'							,		label_column='input_label'	)
      self.assertDictEqual({'input_text': 'text', 'input_label': 'labels'}							,		task.column_mapping	)







    def       UpperCamelCase_				(      self	):
      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(_lowerCamelCase	)
      self.assertEqual('text-classification'							,		task.task	)
      self.assertEqual(_lowerCamelCase							,		task.input_schema	)
      self.assertEqual(_lowerCamelCase							,		task.label_schema	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	TextClassification(text_column='input_text'							,		label_column='input_label'	)
      self.assertEqual(task.label_schema['labels']							,		_lowerCamelCase	)
      lowercase							   =	task.align_with_features(Features({'input_label': ClassLabel(names=self.labels	)}	)	)
      self.assertEqual(task.label_schema['labels']							,		ClassLabel(names=self.labels	)	)


class 	a					(       a_     ):







    def       UpperCamelCase_				(      self	):
      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	):
      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(_lowerCamelCase	)
      self.assertEqual('question-answering-extractive'							,		task.task	)
      self.assertEqual(_lowerCamelCase							,		task.input_schema	)
      self.assertEqual(_lowerCamelCase							,		task.label_schema	)


class 	a					(       a_     ):







    def       UpperCamelCase_				(      self	):
      lowercase							   =	Summarization(text_column='input_text'							,		summary_column='input_summary'	)
      self.assertDictEqual({'input_text': 'text', 'input_summary': 'summary'}							,		task.column_mapping	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	Features({'text': Value('string'	)}	)
      lowercase							   =	Features({'summary': Value('string'	)}	)
      lowercase							   =	{'text_column': 'input_text', 'summary_column': 'input_summary'}
      lowercase							   =	Summarization.from_dict(_lowerCamelCase	)
      self.assertEqual('summarization'							,		task.task	)
      self.assertEqual(_lowerCamelCase							,		task.input_schema	)
      self.assertEqual(_lowerCamelCase							,		task.label_schema	)


class 	a					(       a_     ):







    def       UpperCamelCase_				(      self	):
      lowercase							   =	AutomaticSpeechRecognition(audio_column='input_audio'							,		transcription_column='input_transcription'	)
      self.assertDictEqual({'input_audio': 'audio', 'input_transcription': 'transcription'}							,		task.column_mapping	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	Features({'audio': Audio()}	)
      lowercase							   =	Features({'transcription': Value('string'	)}	)
      lowercase							   =	{
          'audio_column': 'input_audio',
          'transcription_column': 'input_transcription',
      }
      lowercase							   =	AutomaticSpeechRecognition.from_dict(_lowerCamelCase	)
      self.assertEqual('automatic-speech-recognition'							,		task.task	)
      self.assertEqual(_lowerCamelCase							,		task.input_schema	)
      self.assertEqual(_lowerCamelCase							,		task.label_schema	)


class 	a					(       a_     ):







    def       UpperCamelCase_				(      self	):
      lowercase							   =	sorted(['pos', 'neg']	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	AudioClassification(audio_column='input_audio'							,		label_column='input_label'	)
      self.assertDictEqual({'input_audio': 'audio', 'input_label': 'labels'}							,		task.column_mapping	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	Features({'audio': Audio()}	)
      lowercase							   =	Features({'labels': ClassLabel}	)
      lowercase							   =	{
          'audio_column': 'input_image',
          'label_column': 'input_label',
      }
      lowercase							   =	AudioClassification.from_dict(_lowerCamelCase	)
      self.assertEqual('audio-classification'							,		task.task	)
      self.assertEqual(_lowerCamelCase							,		task.input_schema	)
      self.assertEqual(_lowerCamelCase							,		task.label_schema	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	AudioClassification(audio_column='input_audio'							,		label_column='input_label'	)
      self.assertEqual(task.label_schema['labels']							,		_lowerCamelCase	)
      lowercase							   =	task.align_with_features(Features({'input_label': ClassLabel(names=self.labels	)}	)	)
      self.assertEqual(task.label_schema['labels']							,		ClassLabel(names=self.labels	)	)


class 	a					(       a_     ):







    def       UpperCamelCase_				(      self	):
      lowercase							   =	sorted(['pos', 'neg']	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	ImageClassification(image_column='input_image'							,		label_column='input_label'	)
      self.assertDictEqual({'input_image': 'image', 'input_label': 'labels'}							,		task.column_mapping	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	Features({'image': Image()}	)
      lowercase							   =	Features({'labels': ClassLabel}	)
      lowercase							   =	{
          'image_column': 'input_image',
          'label_column': 'input_label',
      }
      lowercase							   =	ImageClassification.from_dict(_lowerCamelCase	)
      self.assertEqual('image-classification'							,		task.task	)
      self.assertEqual(_lowerCamelCase							,		task.input_schema	)
      self.assertEqual(_lowerCamelCase							,		task.label_schema	)







    def       UpperCamelCase_				(      self	):
      lowercase							   =	ImageClassification(image_column='input_image'							,		label_column='input_label'	)
      self.assertEqual(task.label_schema['labels']							,		_lowerCamelCase	)
      lowercase							   =	task.align_with_features(Features({'input_label': ClassLabel(names=self.labels	)}	)	)
      self.assertEqual(task.label_schema['labels']							,		ClassLabel(names=self.labels	)	)


class 	a					(       a_     ):







    def       UpperCamelCase_				(      self	):
      lowercase							   =	DatasetInfo(task_templates=QuestionAnsweringExtractive()	)
      lowercase							   =	Dataset.from_dict({k: [v] for k, v in SAMPLE_QUESTION_ANSWERING_EXTRACTIVE.items()}							,		info=_lowerCamelCase	)
      assert isinstance(dataset.info.task_templates							,		_lowerCamelCase	)
      assert len(dataset.info.task_templates	) == 1

      def keep_task(_lowerCamelCase	):
        return x

      def dont_keep_task(_lowerCamelCase	):
        lowercase							   =	deepcopy(_lowerCamelCase	)
        lowercase							   =	0
        return out

      lowercase							   =	dataset.map(_lowerCamelCase	)
      assert mapped_dataset.info.task_templates == dataset.info.task_templates
      # reload from cache
      lowercase							   =	dataset.map(_lowerCamelCase	)
      assert mapped_dataset.info.task_templates == dataset.info.task_templates

      lowercase							   =	dataset.map(_lowerCamelCase	)
      assert mapped_dataset.info.task_templates == []
      # reload from cache
      lowercase							   =	dataset.map(_lowerCamelCase	)
      assert mapped_dataset.info.task_templates == []







    def       UpperCamelCase_				(      self	):
      lowercase							   =	Features({'text': Value('string'	), 'label': ClassLabel(names=('pos', 'neg')	)}	)
      lowercase							   =	TextClassification(text_column='text'							,		label_column='label'	)
      lowercase							   =	DatasetInfo(features=_lowerCamelCase							,		task_templates=_lowerCamelCase	)
      lowercase							   =	Dataset.from_dict({'text': ['A sentence.'], 'label': ['pos']}							,		info=_lowerCamelCase	)

      def process(_lowerCamelCase	):
        return example

      lowercase							   =	dataset.remove_columns('label'	)
      lowercase							   =	modified_dataset.map(_lowerCamelCase	)
      assert mapped_dataset.info.task_templates == []










"""simple docstring"""



import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_UpperCamelCase		:  Optional[Any]						=		logging.get_logger(__name__)


_UpperCamelCase		:  Any						=		{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all MVP models at https://huggingface.co/models?filter=mvp
_UpperCamelCase		:  Optional[int]						=		{
    'vocab_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json',
    },
    'added_tokens.json': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json',
    },
    'merges_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt',
    },
}

_UpperCamelCase		:  Union[str, Any]						=		{
    'RUCAIBox/mvp': 1_0_2_4,
}
@lru_cache()
def 						_SCREAMING_SNAKE_CASE			(   ):





  '''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(__snake_case   )
      cs.append(2**8 + n   )
      n += 1
  lowercase							   =	[chr(__snake_case   ) for n in cs]
  return dict(zip(__snake_case		, __snake_case   )   )
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  int   ):





  '''simple docstring'''





  lowercase							   =	set()
  lowercase							   =	word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)   )
    lowercase							   =	char
  return pairs



class 	a					(       a_     ):
    UpperCAmelCase_			:					Tuple     					=VOCAB_FILES_NAMES
    UpperCAmelCase_			:					int     					=PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase_			:					Optional[int]     					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    UpperCAmelCase_			:					Any     					=["input_ids", "attention_mask"]







    def __init__(      self							,		_lowerCamelCase							,		_lowerCamelCase							,		_lowerCamelCase="replace"							,		_lowerCamelCase="<s>"							,		_lowerCamelCase="</s>"							,		_lowerCamelCase="</s>"							,		_lowerCamelCase="<s>"							,		_lowerCamelCase="<unk>"							,		_lowerCamelCase="<pad>"							,		_lowerCamelCase="<mask>"							,		_lowerCamelCase=False							,		**_lowerCamelCase							,		):
      lowercase							   =	AddedToken(_lowerCamelCase							,		lstrip=_lowerCamelCase							,		rstrip=_lowerCamelCase	) if isinstance(_lowerCamelCase							,		_lowerCamelCase	) else bos_token
      lowercase							   =	AddedToken(_lowerCamelCase							,		lstrip=_lowerCamelCase							,		rstrip=_lowerCamelCase	) if isinstance(_lowerCamelCase							,		_lowerCamelCase	) else eos_token
      lowercase							   =	AddedToken(_lowerCamelCase							,		lstrip=_lowerCamelCase							,		rstrip=_lowerCamelCase	) if isinstance(_lowerCamelCase							,		_lowerCamelCase	) else sep_token
      lowercase							   =	AddedToken(_lowerCamelCase							,		lstrip=_lowerCamelCase							,		rstrip=_lowerCamelCase	) if isinstance(_lowerCamelCase							,		_lowerCamelCase	) else cls_token
      lowercase							   =	AddedToken(_lowerCamelCase							,		lstrip=_lowerCamelCase							,		rstrip=_lowerCamelCase	) if isinstance(_lowerCamelCase							,		_lowerCamelCase	) else unk_token
      lowercase							   =	AddedToken(_lowerCamelCase							,		lstrip=_lowerCamelCase							,		rstrip=_lowerCamelCase	) if isinstance(_lowerCamelCase							,		_lowerCamelCase	) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      lowercase							   =	AddedToken(_lowerCamelCase							,		lstrip=_lowerCamelCase							,		rstrip=_lowerCamelCase	) if isinstance(_lowerCamelCase							,		_lowerCamelCase	) else mask_token

      super().__init__(
          errors=_lowerCamelCase							,		bos_token=_lowerCamelCase							,		eos_token=_lowerCamelCase							,		unk_token=_lowerCamelCase							,		sep_token=_lowerCamelCase							,		cls_token=_lowerCamelCase							,		pad_token=_lowerCamelCase							,		mask_token=_lowerCamelCase							,		add_prefix_space=_lowerCamelCase							,		**_lowerCamelCase							,		)
      with open(_lowerCamelCase							,		encoding='utf-8'	) as vocab_handle:
        lowercase							   =	json.load(_lowerCamelCase	)
      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(_lowerCamelCase							,		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(_lowerCamelCase							,		range(len(_lowerCamelCase	)	)	)	)
      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	):
      return len(self.encoder	)







    def       UpperCamelCase_				(      self	):
      return dict(self.encoder							,		**self.added_tokens_encoder	)







    def       UpperCamelCase_				(      self							,		_lowerCamelCase	):
      if token in self.cache:
        return self.cache[token]
      lowercase							   =	tuple(_lowerCamelCase	)
      lowercase							   =	get_pairs(_lowerCamelCase	)

      if not pairs:
        return token

      while True:
        lowercase							   =	min(_lowerCamelCase							,		key=lambda _lowerCamelCase	: self.bpe_ranks.get(_lowerCamelCase							,		float('inf'	)	)	)
        if bigram not in self.bpe_ranks:
          break
        lowercase   ,					lowercase							   =	bigram
        lowercase							   =	[]
        lowercase							   =	0
        while i < len(_lowerCamelCase	):
          try:
            lowercase							   =	word.index(_lowerCamelCase							,		_lowerCamelCase	)
          except ValueError:
            new_word.extend(word[i:]	)
            break
          else:
            new_word.extend(word[i:j]	)
            lowercase							   =	j

          if word[i] == first and i < len(_lowerCamelCase	) - 1 and word[i + 1] == second:
            new_word.append(first + second	)
            i += 2
          else:
            new_word.append(word[i]	)
            i += 1
        lowercase							   =	tuple(_lowerCamelCase	)
        lowercase							   =	new_word
        if len(_lowerCamelCase	) == 1:
          break
        else:
          lowercase							   =	get_pairs(_lowerCamelCase	)
      lowercase							   =	' '.join(_lowerCamelCase	)
      lowercase							   =	word
      return word







    def       UpperCamelCase_				(      self							,		_lowerCamelCase	):
      lowercase							   =	[]
      for token in re.findall(self.pat							,		_lowerCamelCase	):
        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(_lowerCamelCase	).split(' '	)	)
      return bpe_tokens







    def       UpperCamelCase_				(      self							,		_lowerCamelCase	):
      return self.encoder.get(_lowerCamelCase							,		self.encoder.get(self.unk_token	)	)







    def       UpperCamelCase_				(      self							,		_lowerCamelCase	):
      return self.decoder.get(_lowerCamelCase	)







    def       UpperCamelCase_				(      self							,		_lowerCamelCase	):
      lowercase							   =	''.join(_lowerCamelCase	)
      lowercase							   =	bytearray([self.byte_decoder[c] for c in text]	).decode('utf-8'							,		errors=self.errors	)
      return text







    def       UpperCamelCase_				(      self							,		_lowerCamelCase							,		_lowerCamelCase = None	):
      if not os.path.isdir(_lowerCamelCase	):
        logger.error(F'Vocabulary path ({save_directory}) should be a directory'	)
        return
      lowercase							   =	os.path.join(
          _lowerCamelCase							,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)
      lowercase							   =	os.path.join(
          _lowerCamelCase							,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']	)

      with open(_lowerCamelCase							,		'w'							,		encoding='utf-8'	) as f:
        f.write(json.dumps(self.encoder							,		indent=2							,		sort_keys=_lowerCamelCase							,		ensure_ascii=_lowerCamelCase	) + '\n'	)

      lowercase							   =	0
      with open(_lowerCamelCase							,		'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 _lowerCamelCase	: 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(_lowerCamelCase	) + '\n'	)
          index += 1

      return vocab_file, merge_file







    def       UpperCamelCase_				(      self							,		_lowerCamelCase							,		_lowerCamelCase = None	):
      if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      lowercase							   =	[self.cls_token_id]
      lowercase							   =	[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep







    def       UpperCamelCase_				(      self							,		_lowerCamelCase							,		_lowerCamelCase = None							,		_lowerCamelCase = False	):
      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=_lowerCamelCase							,		token_ids_a=_lowerCamelCase							,		already_has_special_tokens=_lowerCamelCase	)

      if token_ids_a is None:
        return [1] + ([0] * len(_lowerCamelCase	)) + [1]
      return [1] + ([0] * len(_lowerCamelCase	)) + [1, 1] + ([0] * len(_lowerCamelCase	)) + [1]







    def       UpperCamelCase_				(      self							,		_lowerCamelCase							,		_lowerCamelCase = None	):
      lowercase							   =	[self.sep_token_id]
      lowercase							   =	[self.cls_token_id]

      if token_ids_a is None:
        return len(cls + token_ids_a + sep	) * [0]
      return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]







    def       UpperCamelCase_				(      self							,		_lowerCamelCase							,		_lowerCamelCase=False							,		**_lowerCamelCase	):
      lowercase							   =	kwargs.pop('add_prefix_space'							,		self.add_prefix_space	)
      if (is_split_into_words or add_prefix_space) and (len(_lowerCamelCase	) > 0 and not text[0].isspace()):
        lowercase							   =	' ' + text
      return (text, kwargs)


