


"""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    _snake_case  (  _snake_case :	Union[str, Any]       ,      _snake_case :	Dict       ,      _snake_case :	Union[str, Any]       ,      _snake_case :	List[str]       ,      _snake_case :	Any=True       ,      _snake_case :	Any="pt"	):
      lowerCAmelCase    :		Optional[int]				=      {'''add_prefix_space''': True} if isinstance(_snake_case       ,      _snake_case	) and not line.startswith(''' '''	) else {}
      lowerCAmelCase    :		List[Any]				=      padding_side
      return tokenizer(
          [line]       ,      max_length=_snake_case       ,      padding='''max_length''' if pad_to_max_length else None       ,      truncation=_snake_case       ,      return_tensors=_snake_case       ,      add_special_tokens=_snake_case       ,      **_snake_case       ,      )


def    _snake_case  (  _snake_case :	Tuple       ,      _snake_case :	Optional[int]       ,      _snake_case :	Optional[int]=None       ,      ):
      lowerCAmelCase    :		Any				=      input_ids.ne(_snake_case	).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 						snake_case_(				a__	):






     def __init__(		self     :    List[Any]    , UpperCamelCase_     :    Any    , UpperCamelCase_     :    Tuple    , UpperCamelCase_     :    List[Any]    , UpperCamelCase_     :    Optional[int]    , UpperCamelCase_     :    int="train"    , UpperCamelCase_     :    str=None    , UpperCamelCase_     :    int=None    , UpperCamelCase_     :    List[str]=None    , UpperCamelCase_     :    str=""    , ):
           super().__init__()
           lowerCAmelCase    :		Union[str, Any]				=      Path(UpperCamelCase_ ).joinpath(type_path + '''.source''' )
           lowerCAmelCase    :		Dict				=      Path(UpperCamelCase_ ).joinpath(type_path + '''.target''' )
           lowerCAmelCase    :		Optional[int]				=      self.get_char_lens(self.src_file )
           lowerCAmelCase    :		Union[str, Any]				=      max_source_length
           lowerCAmelCase    :		int				=      max_target_length
           assert min(self.src_lens ) > 0, F'''found empty line in {self.src_file}'''
           lowerCAmelCase    :		List[str]				=      tokenizer
           lowerCAmelCase    :		Dict				=      prefix
           if n_obs is not None:
                 lowerCAmelCase    :		Tuple				=      self.src_lens[:n_obs]
           lowerCAmelCase    :		Tuple				=      src_lang
           lowerCAmelCase    :		Tuple				=      tgt_lang






     def __len__(		self     :    Union[str, Any] ):
           return len(self.src_lens )






     def __getitem__(		self     :    Any    , UpperCamelCase_     :    Union[str, Any] ):
           lowerCAmelCase    :		Tuple				=      index + 1  # linecache starts at 1
           lowerCAmelCase    :		List[Any]				=      self.prefix + linecache.getline(str(self.src_file )    , UpperCamelCase_ ).rstrip('''\n''' )
           lowerCAmelCase    :		Union[str, Any]				=      linecache.getline(str(self.tgt_file )    , UpperCamelCase_ ).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    , UpperCamelCase_ ):
                 source_line += self.tokenizer.eos_token
                 tgt_line += self.tokenizer.eos_token

           # Pad source and target to the right
           lowerCAmelCase    :		Union[str, Any]				=      (
               self.tokenizer.question_encoder if isinstance(self.tokenizer    , UpperCamelCase_ ) else self.tokenizer
           )
           lowerCAmelCase    :		Union[str, Any]				=      self.tokenizer.generator if isinstance(self.tokenizer    , UpperCamelCase_ ) else self.tokenizer

           lowerCAmelCase    :		Optional[Any]				=      encode_line(UpperCamelCase_    , UpperCamelCase_    , self.max_source_length    , '''right''' )
           lowerCAmelCase    :		Dict				=      encode_line(UpperCamelCase_    , UpperCamelCase_    , self.max_target_length    , '''right''' )

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






     @staticmethod
     def    lowerCamelCase__   (		UpperCamelCase_     :    Tuple ):
           return [len(UpperCamelCase_ ) for x in Path(UpperCamelCase_ ).open().readlines()]






     def    lowerCamelCase__   (		self     :    List[Any]    , UpperCamelCase_     :    Any ):
           lowerCAmelCase    :		int				=      torch.stack([x['''input_ids'''] for x in batch] )
           lowerCAmelCase    :		Any				=      torch.stack([x['''attention_mask'''] for x in batch] )
           lowerCAmelCase    :		Optional[int]				=      torch.stack([x['''decoder_input_ids'''] for x in batch] )
           lowerCAmelCase    :		Dict				=      (
               self.tokenizer.generator.pad_token_id
               if isinstance(self.tokenizer    , UpperCamelCase_ )
               else self.tokenizer.pad_token_id
           )
           lowerCAmelCase    :		List[str]				=      (
               self.tokenizer.question_encoder.pad_token_id
               if isinstance(self.tokenizer    , UpperCamelCase_ )
               else self.tokenizer.pad_token_id
           )
           lowerCAmelCase    :		List[Any]				=      trim_batch(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase,					lowerCAmelCase    :		Union[str, Any]				=      trim_batch(UpperCamelCase_    , UpperCamelCase_    , attention_mask=UpperCamelCase_ )
           lowerCAmelCase    :		int				=      {
               '''input_ids''': source_ids,
               '''attention_mask''': source_mask,
               '''decoder_input_ids''': y,
           }
           return batch



snake_case__						:   Any			 = getLogger(__name__)


def    _snake_case  (  _snake_case :	List[List]	):
      return list(itertools.chain.from_iterable(_snake_case	)	)


def    _snake_case  (  _snake_case :	str	):
      lowerCAmelCase    :		Dict				=      get_git_info()
      save_json(_snake_case       ,      os.path.join(_snake_case       ,      '''git_log.json'''	)	)


def    _snake_case  (  _snake_case :	Union[str, Any]       ,      _snake_case :	Dict       ,      _snake_case :	Dict=4       ,      **_snake_case :	Dict	):
      with open(_snake_case       ,      '''w'''	) as f:
            json.dump(_snake_case       ,      _snake_case       ,      indent=_snake_case       ,      **_snake_case	)


def    _snake_case  (  _snake_case :	Any	):
      with open(_snake_case	) as f:
            return json.load(_snake_case	)


def    _snake_case  (  ):
      lowerCAmelCase    :		List[str]				=      git.Repo(search_parent_directories=_snake_case	)
      lowerCAmelCase    :		Union[str, Any]				=      {
          '''repo_id''': str(_snake_case	),
          '''repo_sha''': str(repo.head.object.hexsha	),
          '''repo_branch''': str(repo.active_branch	),
          '''hostname''': str(socket.gethostname()	),
      }
      return repo_infos


def    _snake_case  (  _snake_case :	Callable       ,      _snake_case :	Iterable	):
      return list(map(_snake_case       ,      _snake_case	)	)


def    _snake_case  (  _snake_case :	Optional[int]       ,      _snake_case :	List[Any]	):
      with open(_snake_case       ,      '''wb'''	) as f:
            return pickle.dump(_snake_case       ,      _snake_case	)


def    _snake_case  (  _snake_case :	List[str]	):

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

      def white_space_fix(_snake_case :	Union[str, Any]	):
            return " ".join(text.split()	)

      def remove_punc(_snake_case :	List[Any]	):
            lowerCAmelCase    :		List[str]				=      set(string.punctuation	)
            return "".join(ch for ch in text if ch not in exclude	)

      def lower(_snake_case :	str	):
            return text.lower()

      return white_space_fix(remove_articles(remove_punc(lower(_snake_case	)	)	)	)


def    _snake_case  (  _snake_case :	Tuple       ,      _snake_case :	Optional[int]	):
      lowerCAmelCase    :		Union[str, Any]				=      normalize_answer(_snake_case	).split()
      lowerCAmelCase    :		str				=      normalize_answer(_snake_case	).split()
      lowerCAmelCase    :		Dict				=      Counter(_snake_case	) & Counter(_snake_case	)
      lowerCAmelCase    :		Optional[Any]				=      sum(common.values()	)
      if num_same == 0:
            return 0
      lowerCAmelCase    :		str				=      1.0 * num_same / len(_snake_case	)
      lowerCAmelCase    :		Dict				=      1.0 * num_same / len(_snake_case	)
      lowerCAmelCase    :		List[str]				=      (2 * precision * recall) / (precision + recall)
      return fa


def    _snake_case  (  _snake_case :	Optional[int]       ,      _snake_case :	Optional[int]	):
      return normalize_answer(_snake_case	) == normalize_answer(_snake_case	)


def    _snake_case  (  _snake_case :	List[str]       ,      _snake_case :	List[str]	):
      assert len(_snake_case	) == len(_snake_case	)
      lowerCAmelCase    :		int				=      0
      for hypo, pred in zip(_snake_case       ,      _snake_case	):
            em += exact_match_score(_snake_case       ,      _snake_case	)
      if len(_snake_case	) > 0:
            em /= len(_snake_case	)
      return {"em": em}


def    _snake_case  (  _snake_case :	Any	):
      return model_prefix.startswith('''rag'''	)






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






"""simple docstring"""





import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_fnet import FNetTokenizer
else:
 snake_case__						:   str			 = None

snake_case__						:   Optional[Any]			 = logging.get_logger(__name__)
snake_case__						:   Optional[int]			 = {'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case__						:   Dict			 = {
    '''vocab_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/spiece.model''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/spiece.model''',
    },
    '''tokenizer_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json''',
    },
}

snake_case__						:   Any			 = {
    '''google/fnet-base''': 512,
    '''google/fnet-large''': 512,
}

snake_case__						:   Dict			 = '''▁'''



class 						snake_case_(				a__	):
     __UpperCamelCase     =    VOCAB_FILES_NAMES
     __UpperCamelCase     =    PRETRAINED_VOCAB_FILES_MAP
     __UpperCamelCase     =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __UpperCamelCase     =    ['''input_ids''', '''token_type_ids''']
     __UpperCamelCase     =    FNetTokenizer






     def __init__(		self     :    Union[str, Any]    , UpperCamelCase_     :    Union[str, Any]=None    , UpperCamelCase_     :    Union[str, Any]=None    , UpperCamelCase_     :    Any=False    , UpperCamelCase_     :    Any=True    , UpperCamelCase_     :    Dict=True    , UpperCamelCase_     :    Tuple="<unk>"    , UpperCamelCase_     :    List[str]="[SEP]"    , UpperCamelCase_     :    List[Any]="<pad>"    , UpperCamelCase_     :    Union[str, Any]="[CLS]"    , UpperCamelCase_     :    int="[MASK]"    , **UpperCamelCase_     :    Optional[Any]    , ):
           # Mask token behave like a normal word, i.e. include the space before it and
           # is included in the raw text, there should be a match in a non-normalized sentence.
           lowerCAmelCase    :		int				=      (
               AddedToken(UpperCamelCase_    , lstrip=UpperCamelCase_    , rstrip=UpperCamelCase_    , normalized=UpperCamelCase_ )
               if isinstance(UpperCamelCase_    , UpperCamelCase_ )
               else mask_token
           )

           super().__init__(
               UpperCamelCase_    , tokenizer_file=UpperCamelCase_    , do_lower_case=UpperCamelCase_    , remove_space=UpperCamelCase_    , keep_accents=UpperCamelCase_    , unk_token=UpperCamelCase_    , sep_token=UpperCamelCase_    , pad_token=UpperCamelCase_    , cls_token=UpperCamelCase_    , mask_token=UpperCamelCase_    , **UpperCamelCase_    , )

           lowerCAmelCase    :		Optional[int]				=      do_lower_case
           lowerCAmelCase    :		str				=      remove_space
           lowerCAmelCase    :		Any				=      keep_accents
           lowerCAmelCase    :		int				=      vocab_file
           lowerCAmelCase    :		List[str]				=      False if not self.vocab_file else True






     def    lowerCamelCase__   (		self     :    List[Any]    , UpperCamelCase_     :    List[int]    , UpperCamelCase_     :    Optional[List[int]] = None ):
           lowerCAmelCase    :		Optional[int]				=      [self.sep_token_id]
           lowerCAmelCase    :		Optional[Any]				=      [self.cls_token_id]
           if token_ids_a is None:
                 return cls + token_ids_a + sep
           return cls + token_ids_a + sep + token_ids_a + sep






     def    lowerCamelCase__   (		self     :    List[str]    , UpperCamelCase_     :    List[int]    , UpperCamelCase_     :    Optional[List[int]] = None ):
           lowerCAmelCase    :		List[str]				=      [self.sep_token_id]
           lowerCAmelCase    :		Optional[Any]				=      [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 ) * [0] + len(token_ids_a + sep ) * [1]






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

           if os.path.abspath(self.vocab_file ) != os.path.abspath(UpperCamelCase_ ):
                 copyfile(self.vocab_file    , UpperCamelCase_ )

           return (out_vocab_file,)


