


import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


_SCREAMING_SNAKE_CASE     :					Dict      =       logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE     :					Tuple      =       {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

_SCREAMING_SNAKE_CASE     :					List[str]      =       {
    'vocab_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/vocab.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/vocab.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/vocab.json',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/merges.txt',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/merges.txt',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/merges.txt',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'
        ),
    },
    'tokenizer_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/tokenizer.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/tokenizer.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json',
        'roberta-base-openai-detector': (
            'https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json'
        ),
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json'
        ),
    },
}

_SCREAMING_SNAKE_CASE     :					Tuple      =       {
    'roberta-base': 5_12,
    'roberta-large': 5_12,
    'roberta-large-mnli': 5_12,
    'distilroberta-base': 5_12,
    'roberta-base-openai-detector': 5_12,
    'roberta-large-openai-detector': 5_12,
}

class     A__   (       snake_case__      ):







    """simple docstring"""

    __magic_name__         =						VOCAB_FILES_NAMES
    __magic_name__         =						PRETRAINED_VOCAB_FILES_MAP
    __magic_name__         =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __magic_name__         =						['input_ids', 'attention_mask']
    __magic_name__         =						RobertaTokenizer
    def __init__(			self     ,   __snake_case=None     ,   __snake_case=None     ,   __snake_case=None     ,   __snake_case="replace"     ,   __snake_case="<s>"     ,   __snake_case="</s>"     ,   __snake_case="</s>"     ,   __snake_case="<s>"     ,   __snake_case="<unk>"     ,   __snake_case="<pad>"     ,   __snake_case="<mask>"     ,   __snake_case=False     ,   __snake_case=True     ,   **__snake_case     ,   ):
         super().__init__(
             lowerCAmelCase__     ,   lowerCAmelCase__     ,   tokenizer_file=lowerCAmelCase__     ,   errors=lowerCAmelCase__     ,   bos_token=lowerCAmelCase__     ,   eos_token=lowerCAmelCase__     ,   sep_token=lowerCAmelCase__     ,   cls_token=lowerCAmelCase__     ,   unk_token=lowerCAmelCase__     ,   pad_token=lowerCAmelCase__     ,   mask_token=lowerCAmelCase__     ,   add_prefix_space=lowerCAmelCase__     ,   trim_offsets=lowerCAmelCase__     ,   **lowerCAmelCase__     ,   )

         snake_case											=							json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
         if pre_tok_state.get('''add_prefix_space'''     ,   lowerCAmelCase__       ) != add_prefix_space:
              snake_case											=							getattr(lowerCAmelCase__     ,   pre_tok_state.pop('''type'''       )       )
              snake_case											=							add_prefix_space
              snake_case											=							pre_tok_class(**lowerCAmelCase__       )

         snake_case											=							add_prefix_space

         snake_case											=							'''post_processor'''
         snake_case											=							getattr(self.backend_tokenizer     ,   lowerCAmelCase__     ,   lowerCAmelCase__       )
         if tokenizer_component_instance:
              snake_case											=							json.loads(tokenizer_component_instance.__getstate__()       )

              # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
              if "sep" in state:
                   snake_case											=							tuple(state['''sep''']       )
              if "cls" in state:
                   snake_case											=							tuple(state['''cls''']       )

              snake_case											=							False

              if state.get('''add_prefix_space'''     ,   lowerCAmelCase__       ) != add_prefix_space:
                   snake_case											=							add_prefix_space
                   snake_case											=							True

              if state.get('''trim_offsets'''     ,   lowerCAmelCase__       ) != trim_offsets:
                   snake_case											=							trim_offsets
                   snake_case											=							True

              if changes_to_apply:
                   snake_case											=							getattr(lowerCAmelCase__     ,   state.pop('''type'''       )       )
                   snake_case											=							component_class(**lowerCAmelCase__       )
                   setattr(self.backend_tokenizer     ,   lowerCAmelCase__     ,   lowerCAmelCase__       )
    @property
    def 						a_     (			self       ):




         if self._mask_token is None:
              if self.verbose:
                   logger.error('''Using mask_token, but it is not set yet.'''       )
              return None
         return str(self._mask_token       )
    @mask_token.setter
    def 						a_     (			self     ,   __snake_case       ):
         snake_case											=							AddedToken(lowerCAmelCase__     ,   lstrip=lowerCAmelCase__     ,   rstrip=lowerCAmelCase__       ) if isinstance(lowerCAmelCase__     ,   lowerCAmelCase__       ) else value
         snake_case											=							value
    def 						a_     (			self     ,   *__snake_case     ,   **__snake_case       ):
         snake_case											=							kwargs.get('''is_split_into_words'''     ,   lowerCAmelCase__       )
         assert self.add_prefix_space or not is_split_into_words, (
             F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
             "to use it with pretokenized inputs."
         )

         return super()._batch_encode_plus(*lowerCAmelCase__     ,   **lowerCAmelCase__       )
    def 						a_     (			self     ,   *__snake_case     ,   **__snake_case       ):
         snake_case											=							kwargs.get('''is_split_into_words'''     ,   lowerCAmelCase__       )

         assert self.add_prefix_space or not is_split_into_words, (
             F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
             "to use it with pretokenized inputs."
         )

         return super()._encode_plus(*lowerCAmelCase__     ,   **lowerCAmelCase__       )
    def 						a_     (			self     ,   __snake_case     ,   __snake_case = None       ):
         snake_case											=							self._tokenizer.model.save(lowerCAmelCase__     ,   name=lowerCAmelCase__       )
         return tuple(lowerCAmelCase__       )
    def 						a_     (			self     ,   __snake_case     ,   __snake_case=None       ):
         snake_case											=							[self.bos_token_id] + token_ids_a + [self.eos_token_id]
         if token_ids_a is None:
              return output

         return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




    def 						a_     (			self     ,   __snake_case     ,   __snake_case = None       ):
         snake_case											=							[self.sep_token_id]
         snake_case											=							[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]











'''simple docstring'''

import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer







def    a__							(							lowercase   :	Tuple,   lowercase   :	List[str],   lowercase   :	Optional[int],   lowercase   :	List[str],   lowercase   :	List[str]=True,   lowercase   :	str="pt" )						->						Union[str, Any]:





     """simple docstring"""

     _UpperCamelCase							       =			{'''add_prefix_space''': True} if isinstance(lowercase,   lowercase ) and not line.startswith(''' ''' ) else {}
     _UpperCamelCase							       =			padding_side
     return tokenizer(
         [line],   max_length=lowercase,   padding='''max_length''' if pad_to_max_length else None,   truncation=lowercase,   return_tensors=lowercase,   add_special_tokens=lowercase,   **lowercase,   )







def    a__							(							lowercase   :	str,   lowercase   :	int,   lowercase   :	Tuple=None,   )						->						Union[str, Any]:





     """simple docstring"""

     _UpperCamelCase							       =			input_ids.ne(lowercase ).any(dim=0 )
     if attention_mask is None:
          return input_ids[:, keep_column_mask]
     else:
          return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])
class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""





       def __init__(				self  :						Optional[int]			,					lowerCAmelCase__  :						int			,					lowerCAmelCase__  :						int			,					lowerCAmelCase__  :						str			,					lowerCAmelCase__  :						Tuple			,					lowerCAmelCase__  :						str="train"			,					lowerCAmelCase__  :						List[str]=None			,					lowerCAmelCase__  :						Dict=None			,					lowerCAmelCase__  :						Optional[Any]=None			,					lowerCAmelCase__  :						Dict=""			,					)       ->	Any:

            '''simple docstring'''




            super().__init__()
            _UpperCamelCase							       =			Path(lowerCAmelCase__	).joinpath(type_path + '''.source'''	)
            _UpperCamelCase							       =			Path(lowerCAmelCase__	).joinpath(type_path + '''.target'''	)
            _UpperCamelCase							       =			self.get_char_lens(self.src_file	)
            _UpperCamelCase							       =			max_source_length
            _UpperCamelCase							       =			max_target_length
            assert min(self.src_lens	) > 0, f"""found empty line in {self.src_file}"""
            _UpperCamelCase							       =			tokenizer
            _UpperCamelCase							       =			prefix
            if n_obs is not None:
                 _UpperCamelCase							       =			self.src_lens[:n_obs]
            _UpperCamelCase							       =			src_lang
            _UpperCamelCase							       =			tgt_lang





       def __len__(				self  :						Optional[Any]	)       ->	List[Any]:

            '''simple docstring'''




            return len(self.src_lens	)





       def __getitem__(				self  :						Optional[Any]			,					lowerCAmelCase__  :						Any	)       ->	Dict[str, torch.Tensor]:

            '''simple docstring'''




            _UpperCamelCase							       =			index + 1  # linecache starts at 1
            _UpperCamelCase							       =			self.prefix + linecache.getline(str(self.src_file	)			,					lowerCAmelCase__	).rstrip('''\n'''	)
            _UpperCamelCase							       =			linecache.getline(str(self.tgt_file	)			,					lowerCAmelCase__	).rstrip('''\n'''	)
            assert source_line, f"""empty source line for index {index}"""
            assert tgt_line, f"""empty tgt line for index {index}"""

            # Need to add eos token manually for T5
            if isinstance(self.tokenizer			,					lowerCAmelCase__	):
                 source_line += self.tokenizer.eos_token
                 tgt_line += self.tokenizer.eos_token

            # Pad source and target to the right
            _UpperCamelCase							       =			(
                self.tokenizer.question_encoder if isinstance(self.tokenizer			,					lowerCAmelCase__	) else self.tokenizer
            )
            _UpperCamelCase							       =			self.tokenizer.generator if isinstance(self.tokenizer			,					lowerCAmelCase__	) else self.tokenizer

            _UpperCamelCase							       =			encode_line(lowerCAmelCase__			,					lowerCAmelCase__			,					self.max_source_length			,					'''right'''	)
            _UpperCamelCase							       =			encode_line(lowerCAmelCase__			,					lowerCAmelCase__			,					self.max_target_length			,					'''right'''	)

            _UpperCamelCase							       =			source_inputs['''input_ids'''].squeeze()
            _UpperCamelCase							       =			target_inputs['''input_ids'''].squeeze()
            _UpperCamelCase							       =			source_inputs['''attention_mask'''].squeeze()
            return {
                "input_ids": source_ids,
                "attention_mask": src_mask,
                "decoder_input_ids": target_ids,
            }





       @staticmethod
       def snake_case__		(				lowerCAmelCase__  :						List[Any]	)       ->	Optional[int]:

            '''simple docstring'''




            return [len(lowerCAmelCase__	) for x in Path(lowerCAmelCase__	).open().readlines()]







       def snake_case__		(				self  :						Dict			,					lowerCAmelCase__  :						List[str]	)       ->	Dict[str, torch.Tensor]:

            '''simple docstring'''




            _UpperCamelCase							       =			torch.stack([x['''input_ids'''] for x in batch]	)
            _UpperCamelCase							       =			torch.stack([x['''attention_mask'''] for x in batch]	)
            _UpperCamelCase							       =			torch.stack([x['''decoder_input_ids'''] for x in batch]	)
            _UpperCamelCase							       =			(
                self.tokenizer.generator.pad_token_id
                if isinstance(self.tokenizer			,					lowerCAmelCase__	)
                else self.tokenizer.pad_token_id
            )
            _UpperCamelCase							       =			(
                self.tokenizer.question_encoder.pad_token_id
                if isinstance(self.tokenizer			,					lowerCAmelCase__	)
                else self.tokenizer.pad_token_id
            )
            _UpperCamelCase							       =			trim_batch(lowerCAmelCase__			,					lowerCAmelCase__	)
            _UpperCamelCase       ,							_UpperCamelCase							       =			trim_batch(lowerCAmelCase__			,					lowerCAmelCase__			,					attention_mask=lowerCAmelCase__	)
            _UpperCamelCase							       =			{
                '''input_ids''': source_ids,
                '''attention_mask''': source_mask,
                '''decoder_input_ids''': y,
            }
            return batch

lowercase__		:     Union[str, Any]			=							getLogger(__name__)







def    a__							(							lowercase   :	List[List] )						->						Optional[int]:





     """simple docstring"""

     return list(itertools.chain.from_iterable(lowercase ) )







def    a__							(							lowercase   :	str )						->						None:





     """simple docstring"""

     _UpperCamelCase							       =			get_git_info()
     save_json(lowercase,   os.path.join(lowercase,   '''git_log.json''' ) )







def    a__							(							lowercase   :	Optional[int],   lowercase   :	List[str],   lowercase   :	str=4,   **lowercase   :	Optional[Any] )						->						Any:





     """simple docstring"""

     with open(lowercase,   '''w''' ) as f:
          json.dump(lowercase,   lowercase,   indent=lowercase,   **lowercase )







def    a__							(							lowercase   :	Union[str, Any] )						->						Optional[int]:





     """simple docstring"""

     with open(lowercase ) as f:
          return json.load(lowercase )







def    a__							(							)						->						List[Any]:





     """simple docstring"""

     _UpperCamelCase							       =			git.Repo(search_parent_directories=lowercase )
     _UpperCamelCase							       =			{
         '''repo_id''': str(lowercase ),
         '''repo_sha''': str(repo.head.object.hexsha ),
         '''repo_branch''': str(repo.active_branch ),
         '''hostname''': str(socket.gethostname() ),
     }
     return repo_infos







def    a__							(							lowercase   :	Callable,   lowercase   :	Iterable )						->						List:





     """simple docstring"""

     return list(map(lowercase,   lowercase ) )







def    a__							(							lowercase   :	List[Any],   lowercase   :	Dict )						->						Optional[int]:





     """simple docstring"""

     with open(lowercase,   '''wb''' ) as f:
          return pickle.dump(lowercase,   lowercase )







def    a__							(							lowercase   :	Tuple )						->						Tuple:





     """simple docstring"""

     def remove_articles(lowercase   :	Tuple ):
          return re.sub(r'''\b(a|an|the)\b''',   ''' ''',   lowercase )

     def white_space_fix(lowercase   :	Tuple ):
          return " ".join(text.split() )

     def remove_punc(lowercase   :	Optional[int] ):
          _UpperCamelCase							       =			set(string.punctuation )
          return "".join(ch for ch in text if ch not in exclude )

     def lower(lowercase   :	Tuple ):
          return text.lower()

     return white_space_fix(remove_articles(remove_punc(lower(lowercase ) ) ) )







def    a__							(							lowercase   :	Tuple,   lowercase   :	Union[str, Any] )						->						Dict:





     """simple docstring"""

     _UpperCamelCase							       =			normalize_answer(lowercase ).split()
     _UpperCamelCase							       =			normalize_answer(lowercase ).split()
     _UpperCamelCase							       =			Counter(lowercase ) & Counter(lowercase )
     _UpperCamelCase							       =			sum(common.values() )
     if num_same == 0:
          return 0
     _UpperCamelCase							       =			1.0 * num_same / len(lowercase )
     _UpperCamelCase							       =			1.0 * num_same / len(lowercase )
     _UpperCamelCase							       =			(2 * precision * recall) / (precision + recall)
     return fa







def    a__							(							lowercase   :	Tuple,   lowercase   :	Any )						->						List[str]:





     """simple docstring"""

     return normalize_answer(lowercase ) == normalize_answer(lowercase )







def    a__							(							lowercase   :	List[str],   lowercase   :	List[str] )						->						Dict:





     """simple docstring"""

     assert len(lowercase ) == len(lowercase )
     _UpperCamelCase							       =			0
     for hypo, pred in zip(lowercase,   lowercase ):
          em += exact_match_score(lowercase,   lowercase )
     if len(lowercase ) > 0:
          em /= len(lowercase )
     return {"em": em}







def    a__							(							lowercase   :	Tuple )						->						Union[str, Any]:





     """simple docstring"""

     return model_prefix.startswith('''rag''' )







def    a__							(							lowercase   :	int,   lowercase   :	List[Any],   lowercase   :	List[Any] )						->						Optional[int]:





     """simple docstring"""

     _UpperCamelCase							       =			{p: p for p in extra_params}
     # T5 models don't have `dropout` param, they have `dropout_rate` instead
     _UpperCamelCase							       =			'''dropout_rate'''
     for p in extra_params:
          if getattr(lowercase,   lowercase,   lowercase ):
               if not hasattr(lowercase,   lowercase ) and not hasattr(lowercase,   equivalent_param[p] ):
                    logger.info('''config doesn\'t have a `{}` attribute'''.format(lowercase ) )
                    delattr(lowercase,   lowercase )
                    continue
               _UpperCamelCase							       =			p if hasattr(lowercase,   lowercase ) else equivalent_param[p]
               setattr(lowercase,   lowercase,   getattr(lowercase,   lowercase ) )
               delattr(lowercase,   lowercase )
     return hparams, config



