



'''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 lowerCAmelCase  (__A  ,	__A  ,	__A  ,	__A  ,	__A=True  ,	__A="pt"):



     """simple docstring"""



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




def lowerCAmelCase  (__A  ,	__A  ,	__A=None  ,	):



     """simple docstring"""



     _a      =  input_ids.ne(__A).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			(  A						):



 '''simple docstring'''







 def __init__(self ,   A ,   A ,   A ,   A ,   A="train" ,   A=None ,   A=None ,   A=None ,   A="" ,   )    ->     Dict:


      """simple docstring"""



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



 def __len__(self       )    ->     Optional[Any]:


      """simple docstring"""



      return len(self.src_lens       )



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


      """simple docstring"""



      _a      =  index + 1  # linecache starts at 1
      _a      =  self.prefix + linecache.getline(str(self.src_file       ) ,   A       ).rstrip('''\n'''       )
      _a      =  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      =  (
          self.tokenizer.question_encoder if isinstance(self.tokenizer ,   A       ) else self.tokenizer
      )
      _a      =  self.tokenizer.generator if isinstance(self.tokenizer ,   A       ) else self.tokenizer

      _a      =  encode_line(A ,   A ,   self.max_source_length ,   '''right'''       )
      _a      =  encode_line(A ,   A ,   self.max_target_length ,   '''right'''       )

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



 @staticmethod
 def 					a__  (A       )    ->     Optional[int]:


      """simple docstring"""



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



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


      """simple docstring"""



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





lowercase_		       =  getLogger(__name__)




def lowerCAmelCase  (__A):



     """simple docstring"""



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




def lowerCAmelCase  (__A):



     """simple docstring"""



     _a      =  get_git_info()
     save_json(__A  ,	os.path.join(__A  ,	'''git_log.json'''))




def lowerCAmelCase  (__A  ,	__A  ,	__A=4  ,	**__A):



     """simple docstring"""



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




def lowerCAmelCase  (__A):



     """simple docstring"""



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




def lowerCAmelCase  ():



     """simple docstring"""



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




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     return list(map(__A  ,	__A))




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



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




def lowerCAmelCase  (__A):



     """simple docstring"""



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

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

     def remove_punc(__A):
          _a      =  set(string.punctuation)
          return "".join(ch for ch in text if ch not in exclude)

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

     return white_space_fix(remove_articles(remove_punc(lower(__A))))




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



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




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     return normalize_answer(__A) == normalize_answer(__A)




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



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




def lowerCAmelCase  (__A):



     """simple docstring"""



     return model_prefix.startswith('''rag''')




def lowerCAmelCase  (__A  ,	__A  ,	__A):



     """simple docstring"""



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








'''simple docstring'''





def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     _a      =  int(__A)

     # Initialize Result
     _a      =  []

     # Traverse through all denomination
     for denomination in reversed(__A):
          # Find denominations
          while int(__A) >= int(__A):
               total_value -= int(__A)
               answer.append(__A)  # Append the "answers" array

     return answer


# Driver Code
if __name__ == "__main__":
  lowercase_		       =  []
  lowercase_		       =  "0"

  if (
      input("Do you want to enter your denominations ? (yY/n): ").strip().lower()
      == "y"
  ):
    lowercase_		       =  int(input("Enter the number of denominations you want to add: ").strip())

    for i in range(0, n):
      denominations.append(int(input(F"""Denomination {i}: """).strip()))
    lowercase_		       =  input("Enter the change you want to make in Indian Currency: ").strip()
  else:
    # All denominations of Indian Currency if user does not enter
    lowercase_		       =  [1, 2, 5, 10, 20, 50, 100, 500, 2_000]
    lowercase_		       =  input("Enter the change you want to make: ").strip()

  if int(value) == 0 or int(value) < 0:
    print("The total value cannot be zero or negative.")

  else:
    print(F"""Following is minimal change for {value}: """)
    lowercase_		       =  find_minimum_change(denominations, value)
    # Print result
    for i in range(len(answer)):
      print(answer[i], end=" ")



