
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_     (						__SCREAMING_SNAKE_CASE						:  Optional[Any]			,     __SCREAMING_SNAKE_CASE						:  Union[str, Any]			,     __SCREAMING_SNAKE_CASE						:  List[str]			,     __SCREAMING_SNAKE_CASE						:  str			,     __SCREAMING_SNAKE_CASE						:  List[str]=True			,     __SCREAMING_SNAKE_CASE						:  str="pt" )				->       Tuple:





  """simple docstring"""

  __A		:     int												=		{"""add_prefix_space""": True} if isinstance(lowerCAmelCase__			,     lowerCAmelCase__ ) and not line.startswith(""" """ ) else {}
  __A		:     Any												=		padding_side
  return tokenizer(
      [line]			,     max_length=lowerCAmelCase__			,     padding="""max_length""" if pad_to_max_length else None			,     truncation=lowerCAmelCase__			,     return_tensors=lowerCAmelCase__			,     add_special_tokens=lowerCAmelCase__			,     **lowerCAmelCase__			,     )







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[str]			,     __SCREAMING_SNAKE_CASE						:  Optional[Any]			,     __SCREAMING_SNAKE_CASE						:  Optional[int]=None			,     )				->       Dict:





  """simple docstring"""

  __A		:     Any												=		input_ids.ne(lowerCAmelCase__ ).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				( __SCREAMING_SNAKE_CASE			):
 def __init__(   self			:    Union[str, Any]				,   lowerCamelCase			:    Union[str, Any]				,   lowerCamelCase			:    Tuple				,   lowerCamelCase			:    Tuple				,   lowerCamelCase			:    Union[str, Any]				,   lowerCamelCase			:    int="train"				,   lowerCamelCase			:    Optional[Any]=None				,   lowerCamelCase			:    Any=None				,   lowerCamelCase			:    Any=None				,   lowerCamelCase			:    Optional[Any]=""				,   ):



   """simple docstring"""





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



   """simple docstring"""





   return len(self.src_lens       )
 def __getitem__(   self			:    List[str]				,   lowerCamelCase			:    Optional[Any]       ):



   """simple docstring"""





   __A		:     Any												=		index + 1  # linecache starts at 1
   __A		:     int												=		self.prefix + linecache.getline(str(self.src_file       )				,   _a       ).rstrip("""\n"""       )
   __A		:     List[Any]												=		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
   __A		:     int												=		(
       self.tokenizer.question_encoder if isinstance(self.tokenizer				,   _a       ) else self.tokenizer
   )
   __A		:     Union[str, Any]												=		self.tokenizer.generator if isinstance(self.tokenizer				,   _a       ) else self.tokenizer

   __A		:     Any												=		encode_line(_a				,   _a				,   self.max_source_length				,   """right"""       )
   __A		:     List[str]												=		encode_line(_a				,   _a				,   self.max_target_length				,   """right"""       )

   __A		:     Optional[Any]												=		source_inputs["""input_ids"""].squeeze()
   __A		:     Dict												=		target_inputs["""input_ids"""].squeeze()
   __A		:     Tuple												=		source_inputs["""attention_mask"""].squeeze()
   return {
       "input_ids": source_ids,
       "attention_mask": src_mask,
       "decoder_input_ids": target_ids,
   }
 @staticmethod
 def 		lowercase_(   lowerCamelCase			:    List[str]       ):



   """simple docstring"""





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






 def 		lowercase_(   self			:    Any				,   lowerCamelCase			:    Optional[int]       ):



   """simple docstring"""





   __A		:     Dict												=		torch.stack([x["""input_ids"""] for x in batch]       )
   __A		:     Optional[Any]												=		torch.stack([x["""attention_mask"""] for x in batch]       )
   __A		:     List[str]												=		torch.stack([x["""decoder_input_ids"""] for x in batch]       )
   __A		:     Any												=		(
       self.tokenizer.generator.pad_token_id
       if isinstance(self.tokenizer				,   _a       )
       else self.tokenizer.pad_token_id
   )
   __A		:     List[Any]												=		(
       self.tokenizer.question_encoder.pad_token_id
       if isinstance(self.tokenizer				,   _a       )
       else self.tokenizer.pad_token_id
   )
   __A		:     str												=		trim_batch(_a				,   _a       )
   __A							,					__A		:     List[Any]												=		trim_batch(_a				,   _a				,   attention_mask=_a       )
   __A		:     Tuple												=		{
       """input_ids""": source_ids,
       """attention_mask""": source_mask,
       """decoder_input_ids""": y,
   }
   return batch

A__   :		Tuple 		=getLogger(__name__)







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[List] )				->       int:





  """simple docstring"""

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







def        A_     (						__SCREAMING_SNAKE_CASE						:  str )				->       None:





  """simple docstring"""

  __A		:     Any												=		get_git_info()
  save_json(lowerCAmelCase__			,     os.path.join(lowerCAmelCase__			,     """git_log.json""" ) )







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[str]			,     __SCREAMING_SNAKE_CASE						:  str			,     __SCREAMING_SNAKE_CASE						:  List[str]=4			,     **__SCREAMING_SNAKE_CASE						:  Any )				->       int:





  """simple docstring"""

  with open(lowerCAmelCase__			,     """w""" ) as f:
    json.dump(lowerCAmelCase__			,     lowerCAmelCase__			,     indent=lowerCAmelCase__			,     **lowerCAmelCase__ )







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[str] )				->       Union[str, Any]:





  """simple docstring"""

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







def        A_     (						)				->       Optional[int]:





  """simple docstring"""

  __A		:     str												=		git.Repo(search_parent_directories=lowerCAmelCase__ )
  __A		:     Tuple												=		{
      """repo_id""": str(lowerCAmelCase__ ),
      """repo_sha""": str(repo.head.object.hexsha ),
      """repo_branch""": str(repo.active_branch ),
      """hostname""": str(socket.gethostname() ),
  }
  return repo_infos







def        A_     (						__SCREAMING_SNAKE_CASE						:  Callable			,     __SCREAMING_SNAKE_CASE						:  Iterable )				->       List:





  """simple docstring"""

  return list(map(lowerCAmelCase__			,     lowerCAmelCase__ ) )







def        A_     (						__SCREAMING_SNAKE_CASE						:  Optional[Any]			,     __SCREAMING_SNAKE_CASE						:  Union[str, Any] )				->       Dict:





  """simple docstring"""

  with open(lowerCAmelCase__			,     """wb""" ) as f:
    return pickle.dump(lowerCAmelCase__			,     lowerCAmelCase__ )







def        A_     (						__SCREAMING_SNAKE_CASE						:  Dict )				->       Union[str, Any]:





  """simple docstring"""

  def remove_articles(__SCREAMING_SNAKE_CASE						:  Dict ):
    return re.sub(R"""\b(a|an|the)\b"""			,     """ """			,     lowerCAmelCase__ )

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

  def remove_punc(__SCREAMING_SNAKE_CASE						:  Tuple ):
    __A		:     Union[str, Any]												=		set(string.punctuation )
    return "".join(ch for ch in text if ch not in exclude )

  def lower(__SCREAMING_SNAKE_CASE						:  Optional[Any] ):
    return text.lower()

  return white_space_fix(remove_articles(remove_punc(lower(lowerCAmelCase__ ) ) ) )







def        A_     (						__SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  Tuple )				->       Optional[Any]:





  """simple docstring"""

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







def        A_     (						__SCREAMING_SNAKE_CASE						:  Optional[Any]			,     __SCREAMING_SNAKE_CASE						:  Tuple )				->       int:





  """simple docstring"""

  return normalize_answer(lowerCAmelCase__ ) == normalize_answer(lowerCAmelCase__ )







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[str]			,     __SCREAMING_SNAKE_CASE						:  List[str] )				->       Dict:





  """simple docstring"""

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







def        A_     (						__SCREAMING_SNAKE_CASE						:  int )				->       Tuple:





  """simple docstring"""

  return model_prefix.startswith("""rag""" )







def        A_     (						__SCREAMING_SNAKE_CASE						:  Tuple			,     __SCREAMING_SNAKE_CASE						:  Optional[Any]			,     __SCREAMING_SNAKE_CASE						:  List[Any] )				->       List[str]:





  """simple docstring"""

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





'''simple docstring'''
def        A_     (						__SCREAMING_SNAKE_CASE						:  Dict )				->       Optional[Any]:





  """simple docstring"""

  if not head:
    return True
  # split the list to two parts
  __A							,					__A		:     Any												=		head.next, head
  while fast and fast.next:
    __A		:     List[str]												=		fast.next.next
    __A		:     List[Any]												=		slow.next
  __A		:     int												=		slow.next
  __A		:     List[str]												=		None  # Don't forget here! But forget still works!
  # reverse the second part
  __A		:     Dict												=		None
  while second:
    __A		:     Dict												=		second.next
    __A		:     str												=		node
    __A		:     int												=		second
    __A		:     Optional[int]												=		nxt
  # compare two parts
  # second part has the same or one less node
  while node:
    if node.val != head.val:
      return False
    __A		:     List[Any]												=		node.next
    __A		:     Tuple												=		head.next
  return True







def        A_     (						__SCREAMING_SNAKE_CASE						:  Union[str, Any] )				->       Optional[int]:





  """simple docstring"""

  if not head or not head.next:
    return True

  # 1. Get the midpoint (slow)
  __A		:     int												=		head
  while fast and fast.next:
    __A							,					__A		:     Optional[int]												=		fast.next.next, slow.next

  # 2. Push the second half into the stack
  __A		:     Union[str, Any]												=		[slow.val]
  while slow.next:
    __A		:     List[str]												=		slow.next
    stack.append(slow.val )

  # 3. Comparison
  while stack:
    if stack.pop() != cur.val:
      return False
    __A		:     Tuple												=		cur.next

  return True







def        A_     (						__SCREAMING_SNAKE_CASE						:  Dict )				->       Any:





  """simple docstring"""

  if not head or not head.next:
    return True
  __A		:     List[Any]												=		{}
  __A		:     Optional[int]												=		0
  while head:
    if head.val in d:
      d[head.val].append(__SCREAMING_SNAKE_CASE )
    else:
      __A		:     Tuple												=		[pos]
    __A		:     List[Any]												=		head.next
    pos += 1
  __A		:     List[Any]												=		pos - 1
  __A		:     List[str]												=		0
  for v in d.values():
    if len(__SCREAMING_SNAKE_CASE ) % 2 != 0:
      middle += 1
    else:
      __A		:     List[Any]												=		0
      for i in range(0			,     len(__SCREAMING_SNAKE_CASE ) ):
        if v[i] + v[len(__SCREAMING_SNAKE_CASE ) - 1 - step] != checksum:
          return False
        step += 1
    if middle > 1:
      return False
  return True



