
"""simple docstring"""






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

import sentencepiece as spm

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


__UpperCAmelCase       =  logging.get_logger(__name__)

__UpperCAmelCase       =  '▁'

__UpperCAmelCase       =  {'vocab_file': 'sentencepiece.bpe.model'}

__UpperCAmelCase       =  {
    'vocab_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'
        ),
    }
}

__UpperCAmelCase       =  {
    'xlm-roberta-base': 5_12,
    'xlm-roberta-large': 5_12,
    'xlm-roberta-large-finetuned-conll02-dutch': 5_12,
    'xlm-roberta-large-finetuned-conll02-spanish': 5_12,
    'xlm-roberta-large-finetuned-conll03-english': 5_12,
    'xlm-roberta-large-finetuned-conll03-german': 5_12,
}




class 			_SCREAMING_SNAKE_CASE					(			A__							):
			UpperCAmelCase_  :str				 =						VOCAB_FILES_NAMES
			UpperCAmelCase_  :int				 =						PRETRAINED_VOCAB_FILES_MAP
			UpperCAmelCase_  :Any				 =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCAmelCase_  :Optional[int]				 =						["input_ids", "attention_mask"]






			def __init__(					self       ,   __A       ,   __A="<s>"       ,   __A="</s>"       ,   __A="</s>"       ,   __A="<s>"       ,   __A="<unk>"       ,   __A="<pad>"       ,   __A="<mask>"       ,   __A = None       ,   **__A       ,   )			->     None:
						# Mask token behave like a normal word, i.e. include the space before it
						lowerCAmelCase_    :int			     =  AddedToken(__A       ,   lstrip=__A       ,   rstrip=__A       ) if isinstance(__A       ,   __A       ) else mask_token

						lowerCAmelCase_    :Dict			     =  {} if sp_model_kwargs is None else sp_model_kwargs

						super().__init__(
						    bos_token=__A       ,   eos_token=__A       ,   unk_token=__A       ,   sep_token=__A       ,   cls_token=__A       ,   pad_token=__A       ,   mask_token=__A       ,   sp_model_kwargs=self.sp_model_kwargs       ,   **__A       ,   )

						lowerCAmelCase_    :Optional[Any]			     =  spm.SentencePieceProcessor(**self.sp_model_kwargs       )
						self.sp_model.Load(str(__A       )       )
						lowerCAmelCase_    :Optional[Any]			     =  vocab_file

						# Original fairseq vocab and spm vocab must be "aligned":
						# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
						# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
						# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
						# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

						# Mimic fairseq token-to-id alignment for the first 4 token
						lowerCAmelCase_    :Dict			     =  {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

						# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
						lowerCAmelCase_    :List[str]			     =  1

						lowerCAmelCase_    :int			     =  len(self.sp_model       ) + self.fairseq_offset
						lowerCAmelCase_    :int			     =  {v: k for k, v in self.fairseq_tokens_to_ids.items()}






			def __getstate__(					self       )			->     Dict:
						lowerCAmelCase_    :List[str]			     =  self.__dict__.copy()
						lowerCAmelCase_    :Tuple			     =  None
						lowerCAmelCase_    :Dict			     =  self.sp_model.serialized_model_proto()
						return state






			def __setstate__(					self       ,   __A       )			->     Optional[int]:
						lowerCAmelCase_    :Union[str, Any]			     =  d

						# for backward compatibility
						if not hasattr(self       ,   """sp_model_kwargs"""       ):
									lowerCAmelCase_    :str			     =  {}

						lowerCAmelCase_    :List[str]			     =  spm.SentencePieceProcessor(**self.sp_model_kwargs       )
						self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )






			def  __lowerCAmelCase (					self       ,   __A       ,   __A = None       )			->     List[int]:

						if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						lowerCAmelCase_    :Union[str, Any]			     =  [self.cls_token_id]
						lowerCAmelCase_    :List[str]			     =  [self.sep_token_id]
						return cls + token_ids_a + sep + sep + token_ids_a + sep






			def  __lowerCAmelCase (					self       ,   __A       ,   __A = None       ,   __A = False       )			->     List[int]:

						if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=__A       ,   token_ids_a=__A       ,   already_has_special_tokens=__A       )

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






			def  __lowerCAmelCase (					self       ,   __A       ,   __A = None       )			->     List[int]:
						lowerCAmelCase_    :Optional[Any]			     =  [self.sep_token_id]
						lowerCAmelCase_    :Optional[int]			     =  [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]






			@property
			def  __lowerCAmelCase (					self       )			->     Tuple:
						return len(self.sp_model       ) + self.fairseq_offset + 1  # Add the <mask> token






			def  __lowerCAmelCase (					self       )			->     Union[str, Any]:
						lowerCAmelCase_    :Any			     =  {self.convert_ids_to_tokens(__A       ): i for i in range(self.vocab_size       )}
						vocab.update(self.added_tokens_encoder       )
						return vocab






			def  __lowerCAmelCase (					self       ,   __A       )			->     List[str]:
						return self.sp_model.encode(__A       ,   out_type=__A       )






			def  __lowerCAmelCase (					self       ,   __A       )			->     Optional[int]:
						if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
						lowerCAmelCase_    :Optional[Any]			     =  self.sp_model.PieceToId(__A       )

						# Need to return unknown token if the SP model returned 0
						return spm_id + self.fairseq_offset if spm_id else self.unk_token_id






			def  __lowerCAmelCase (					self       ,   __A       )			->     Optional[Any]:
						if index in self.fairseq_ids_to_tokens:
									return self.fairseq_ids_to_tokens[index]
						return self.sp_model.IdToPiece(index - self.fairseq_offset       )






			def  __lowerCAmelCase (					self       ,   __A       )			->     Tuple:
						lowerCAmelCase_    :List[str]			     =  """""".join(__A       ).replace(__A       ,   """ """       ).strip()
						return out_string






			def  __lowerCAmelCase (					self       ,   __A       ,   __A = None       )			->     Tuple[str]:
						if not os.path.isdir(__A       ):
									logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""       )
									return
						lowerCAmelCase_    :Tuple			     =  os.path.join(
						    __A       ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )

						if os.path.abspath(self.vocab_file       ) != os.path.abspath(__A       ) and os.path.isfile(self.vocab_file       ):
									copyfile(self.vocab_file       ,   __A       )
						elif not os.path.isfile(self.vocab_file       ):
									with open(__A       ,   """wb"""       ) as fi:
												lowerCAmelCase_    :int			     =  self.sp_model.serialized_model_proto()
												fi.write(__A       )

						return (out_vocab_file,)












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

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Union[str, Any]			,			__UpperCAmelCase						:	Optional[Any]			,			__UpperCAmelCase						:	Dict=None			,			)					-> Optional[Any]:
      SCREAMING_SNAKE_CASE_							=			input_ids.ne(__UpperCAmelCase							).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_							(      _SCREAMING_SNAKE_CASE					):


 '''simple docstring'''







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



 def __len__(							self  :		Tuple						):
       return len(self.src_lens						)



 def __getitem__(							self  :		List[str]				,				_lowerCAmelCase  :		Any						):
       SCREAMING_SNAKE_CASE_							=			index + 1  # linecache starts at 1
       SCREAMING_SNAKE_CASE_							=			self.prefix + linecache.getline(str(self.src_file						)				,				_lowerCAmelCase						).rstrip('\n'						)
       SCREAMING_SNAKE_CASE_							=			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
       SCREAMING_SNAKE_CASE_							=			(
           self.tokenizer.question_encoder if isinstance(self.tokenizer				,				_lowerCAmelCase						) else self.tokenizer
       )
       SCREAMING_SNAKE_CASE_							=			self.tokenizer.generator if isinstance(self.tokenizer				,				_lowerCAmelCase						) else self.tokenizer

       SCREAMING_SNAKE_CASE_							=			encode_line(_lowerCAmelCase				,				_lowerCAmelCase				,				self.max_source_length				,				'right'						)
       SCREAMING_SNAKE_CASE_							=			encode_line(_lowerCAmelCase				,				_lowerCAmelCase				,				self.max_target_length				,				'right'						)

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



 @staticmethod
 def       lowerCAmelCase_  (							_lowerCAmelCase  :		Optional[int]						):
       return [len(_lowerCAmelCase						) for x in Path(_lowerCAmelCase						).open().readlines()]




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


lowerCamelCase__ :   List[str]					=							getLogger(__name__)

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[List]							)					-> Tuple:
      return list(itertools.chain.from_iterable(__UpperCAmelCase							)							)

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	str							)					-> None:
      SCREAMING_SNAKE_CASE_							=			get_git_info()
      save_json(__UpperCAmelCase			,			os.path.join(__UpperCAmelCase			,			'git_log.json'							)							)

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict			,			__UpperCAmelCase						:	Tuple			,			__UpperCAmelCase						:	Optional[int]=4			,			**__UpperCAmelCase						:	Tuple							)					-> str:
      with open(__UpperCAmelCase			,			'w'							) as f:
            json.dump(__UpperCAmelCase			,			__UpperCAmelCase			,			indent=__UpperCAmelCase			,			**__UpperCAmelCase							)

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[str]							)					-> int:
      with open(__UpperCAmelCase							) as f:
            return json.load(__UpperCAmelCase							)

def 					UpperCAmelCase_							(      )					-> Tuple:
      SCREAMING_SNAKE_CASE_							=			git.Repo(search_parent_directories=__UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_							=			{
          'repo_id': str(__UpperCAmelCase							),
          'repo_sha': str(repo.head.object.hexsha							),
          'repo_branch': str(repo.active_branch							),
          'hostname': str(socket.gethostname()							),
      }
      return repo_infos

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Callable			,			__UpperCAmelCase						:	Iterable							)					-> List:
      return list(map(__UpperCAmelCase			,			__UpperCAmelCase							)							)

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	str			,			__UpperCAmelCase						:	Dict							)					-> Dict:
      with open(__UpperCAmelCase			,			'wb'							) as f:
            return pickle.dump(__UpperCAmelCase			,			__UpperCAmelCase							)

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[Any]							)					-> Any:

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

      def white_space_fix(__UpperCAmelCase						:	List[str]							):
            return " ".join(text.split()							)

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

      def lower(__UpperCAmelCase						:	Union[str, Any]							):
            return text.lower()

      return white_space_fix(remove_articles(remove_punc(lower(__UpperCAmelCase							)							)							)							)

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	int			,			__UpperCAmelCase						:	Any							)					-> List[str]:
      SCREAMING_SNAKE_CASE_							=			normalize_answer(__UpperCAmelCase							).split()
      SCREAMING_SNAKE_CASE_							=			normalize_answer(__UpperCAmelCase							).split()
      SCREAMING_SNAKE_CASE_							=			Counter(__UpperCAmelCase							) & Counter(__UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_							=			sum(common.values()							)
      if num_same == 0:
            return 0
      SCREAMING_SNAKE_CASE_							=			1.0 * num_same / len(__UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_							=			1.0 * num_same / len(__UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_							=			(2 * precision * recall) / (precision + recall)
      return fa

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	str			,			__UpperCAmelCase						:	Optional[int]							)					-> Any:
      return normalize_answer(__UpperCAmelCase							) == normalize_answer(__UpperCAmelCase							)

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[str]			,			__UpperCAmelCase						:	List[str]							)					-> Dict:
      assert len(__UpperCAmelCase							) == len(__UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_							=			0
      for hypo, pred in zip(__UpperCAmelCase			,			__UpperCAmelCase							):
            em += exact_match_score(__UpperCAmelCase			,			__UpperCAmelCase							)
      if len(__UpperCAmelCase							) > 0:
            em /= len(__UpperCAmelCase							)
      return {"em": em}

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Union[str, Any]							)					-> Dict:
      return model_prefix.startswith('rag'							)





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