




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      _SCREAMING_SNAKE_CASE     (				lowercase      :			Optional[Any]      ,				lowercase      :			List[str]      ,				lowercase      :			Dict      ,				lowercase      :			List[Any]      ,				lowercase      :			Dict=True      ,				lowercase      :			int="pt"	):


      '''simple docstring'''



      lowerCamelCase_							=       {'add_prefix_space': True} if isinstance(lowercase      ,				lowercase	) and not line.startswith(' '	) else {}
      lowerCamelCase_							=       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      _SCREAMING_SNAKE_CASE     (				lowercase      :			List[Any]      ,				lowercase      :			List[str]      ,				lowercase      :			Dict=None      ,				):


      '''simple docstring'''



      lowerCamelCase_							=       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     A(		UpperCamelCase  ):



 '''simple docstring'''


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

       """simple docstring"""






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

 def __len__(							self   :    int    )  ->      int:

       """simple docstring"""






       return len(self.src_lens    )

 def __getitem__(							self   :    Tuple		,				A_   :    Dict    )  ->      Dict[str, torch.Tensor]:

       """simple docstring"""






       lowerCamelCase_							=       index + 1  # linecache starts at 1
       lowerCamelCase_							=       self.prefix + linecache.getline(str(self.src_file    )		,				A_    ).rstrip('\n'    )
       lowerCamelCase_							=       linecache.getline(str(self.tgt_file    )		,				A_    ).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		,				A_    ):
             source_line += self.tokenizer.eos_token
             tgt_line += self.tokenizer.eos_token

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

       lowerCamelCase_							=       encode_line(A_		,				A_		,				self.max_source_length		,				'right'    )
       lowerCamelCase_							=       encode_line(A_		,				A_		,				self.max_target_length		,				'right'    )

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

 @staticmethod
 def 							a__					(							A_   :    Union[str, Any]    )  ->      Tuple:

       """simple docstring"""






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





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

       """simple docstring"""






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

lowerCamelCase							:						Optional[int]					       =  getLogger(__name__)

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			List[List]	):


      '''simple docstring'''



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

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			str	):


      '''simple docstring'''



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

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			Any      ,				lowercase      :			Tuple      ,				lowercase      :			str=4      ,				**lowercase      :			Optional[Any]	):


      '''simple docstring'''



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

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			str	):


      '''simple docstring'''



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

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_							=       git.Repo(search_parent_directories=lowercase	)
      lowerCamelCase_							=       {
          '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      _SCREAMING_SNAKE_CASE     (				lowercase      :			Callable      ,				lowercase      :			Iterable	):


      '''simple docstring'''



      return list(map(lowercase      ,				lowercase	)	)

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			Optional[Any]      ,				lowercase      :			Optional[int]	):


      '''simple docstring'''



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

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			Union[str, Any]	):


      '''simple docstring'''



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

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

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

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

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

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			str      ,				lowercase      :			List[str]	):


      '''simple docstring'''



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

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			List[str]      ,				lowercase      :			str	):


      '''simple docstring'''



      return normalize_answer(lowercase	) == normalize_answer(lowercase	)

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			List[str]      ,				lowercase      :			List[str]	):


      '''simple docstring'''



      assert len(lowercase	) == len(lowercase	)
      lowerCamelCase_							=       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      _SCREAMING_SNAKE_CASE     (				lowercase      :			Optional[int]	):


      '''simple docstring'''



      return model_prefix.startswith('rag'	)






def      _SCREAMING_SNAKE_CASE     (				lowercase      :			Dict      ,				lowercase      :			List[str]      ,				lowercase      :			Tuple	):


      '''simple docstring'''



      lowerCamelCase_							=       {p: p for p in extra_params}
      # T5 models don't have `dropout` param, they have `dropout_rate` instead
      lowerCamelCase_							=       '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
                  lowerCamelCase_							=       p if hasattr(lowercase      ,				lowercase	) else equivalent_param[p]
                  setattr(lowercase      ,				lowercase      ,				getattr(lowercase      ,				lowercase	)	)
                  delattr(lowercase      ,				lowercase	)
      return hparams, config











import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


A__      :     int       =					importlib.util.find_spec('s3fs') is not None

if _has_safs:
							from .safilesystem import SaFileSystem  # noqa: F401

A__      :     List[compression.BaseCompressedFileFileSystem]       =					[
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
							if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
														warnings.warn(F"A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.")
							fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				if "://" in dataset_path:
								lowercase__  					=     dataset_path.split('''://'''							)[1]
				return dataset_path






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				if fs is not None and fs.protocol != "file":
								return True
				else:
								return False






def     a     (		lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     not is_remote_filesystem(lowerCamelCase_							)
				if is_local:
								# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
								shutil.move(fs._strip_protocol(lowerCamelCase_							)						,  fs._strip_protocol(lowerCamelCase_							)							)
				else:
								fs.mv(lowerCamelCase_						,  lowerCamelCase_						,  recursive=lowerCamelCase_							)






def     a     (		):






				'''simple docstring'''
				if hasattr(fsspec.asyn						,  '''reset_lock'''							):
								# for future fsspec>2022.05.0
								fsspec.asyn.reset_lock()
				else:
								lowercase__  					=     None
								lowercase__  					=     None
								lowercase__  					=     threading.Lock()




