






'''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 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase=True						,		_UpperCamelCase="pt"							):


   """simple docstring"""




   lowercase_	:    Optional[Any]           =     {"add_prefix_space": True} if isinstance(_UpperCamelCase						,		_UpperCamelCase							) and not line.startswith(" "							) else {}
   lowercase_	:    Union[str, Any]           =     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 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase=None						,		):


   """simple docstring"""




   lowercase_	:    Optional[Any]           =     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        _UpperCAmelCase						(		a__			):




    def __init__(			self  :       List[str]  ,     a  :       Tuple  ,     a  :       str  ,     a  :       Tuple  ,     a  :       Any  ,     a  :       Any="train"  ,     a  :       Optional[int]=None  ,     a  :       Optional[Any]=None  ,     a  :       Tuple=None  ,     a  :       str=""  ,     ):






       '''simple docstring'''






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




    def __len__(			self  :       List[Any]			):






       '''simple docstring'''






       return len(self.src_lens			)




    def __getitem__(			self  :       Optional[Any]  ,     a  :       Optional[int]			):






       '''simple docstring'''






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

       lowercase_	:    str           =     encode_line(lowerCamelCase_  ,     lowerCamelCase_  ,     self.max_source_length  ,     "right"			)
       lowercase_	:    Union[str, Any]           =     encode_line(lowerCamelCase_  ,     lowerCamelCase_  ,     self.max_target_length  ,     "right"			)

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




    @staticmethod
    def 				lowerCAmelCase__				(			a  :       List[Any]			):






       '''simple docstring'''






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





    def 				lowerCAmelCase__				(			self  :       int  ,     a  :       List[str]			):






       '''simple docstring'''






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


UpperCamelCase__ =			getLogger(__name__)



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




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



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    Dict           =     get_git_info()
   save_json(_UpperCamelCase						,		os.path.join(_UpperCamelCase						,		"git_log.json"							)							)



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase=4						,		**_UpperCamelCase							):


   """simple docstring"""




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



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




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



def 		__SCREAMING_SNAKE_CASE					(  ):


   """simple docstring"""




   lowercase_	:    Union[str, Any]           =     git.Repo(search_parent_directories=_UpperCamelCase							)
   lowercase_	:    Optional[int]           =     {
       "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 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   return list(map(_UpperCamelCase						,		_UpperCamelCase							)							)



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




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



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




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

   def white_space_fix(_UpperCamelCase							):
      return " ".join(text.split()							)

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

   def lower(_UpperCamelCase							):
      return text.lower()

   return white_space_fix(remove_articles(remove_punc(lower(_UpperCamelCase							)							)							)							)



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




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



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   return normalize_answer(_UpperCamelCase							) == normalize_answer(_UpperCamelCase							)



def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   assert len(_UpperCamelCase							) == len(_UpperCamelCase							)
   lowercase_	:    Dict           =     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 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




   return model_prefix.startswith("rag"							)





def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




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












'''simple docstring'''
from __future__ import annotations

UpperCamelCase__ =			[-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
UpperCamelCase__ =			[-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    str           =     []
   lowercase_	:    List[str]           =     len(_UpperCamelCase							)

   for i in range(_UpperCamelCase							):
      lowercase_	:    float           =     -1
      for j in range(i + 1						,		_UpperCamelCase							):
         if arr[i] < arr[j]:
            lowercase_	:    Union[str, Any]           =     arr[j]
            break
      result.append(_UpperCamelCase							)
   return result




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    List[str]           =     []
   for i, outer in enumerate(_UpperCamelCase							):
      lowercase_	:    float           =     -1
      for inner in arr[i + 1 :]:
         if outer < inner:
            lowercase_	:    Optional[Any]           =     inner
            break
      result.append(_UpperCamelCase							)
   return result




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    List[str]           =     len(_UpperCamelCase							)
   lowercase_	:    list[float]           =     []
   lowercase_	:    list[float]           =     [-1] * arr_size

   for index in reversed(range(_UpperCamelCase							)							):
      if stack:
         while stack[-1] <= arr[index]:
            stack.pop()
            if not stack:
               break
      if stack:
         lowercase_	:    Optional[Any]           =     stack[-1]
      stack.append(arr[index]							)
   return result


if __name__ == "__main__":
 from doctest import testmod
 from timeit import timeit

 testmod()
 print(next_greatest_element_slow(arr))
 print(next_greatest_element_fast(arr))
 print(next_greatest_element(arr))

 UpperCamelCase__ =			(
     'from __main__ import arr, next_greatest_element_slow, '
     'next_greatest_element_fast, next_greatest_element'
 )
 print(
     'next_greatest_element_slow():',
     timeit('next_greatest_element_slow(arr)', setup=setup),
 )
 print(
     'next_greatest_element_fast():',
     timeit('next_greatest_element_fast(arr)', setup=setup),
 )
 print(
     '     next_greatest_element():',
     timeit('next_greatest_element(arr)', setup=setup),
 )




