


"""simple docstring"""


import os
from typing import Dict, List, Union

import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs

from .tokenization_gpta import GPTaTokenizer



class       lowerCamelCase__    ( tf.keras.layers.Layer      ):







						def __init__(				self :     List[Any]      ,      _lowercase :     Dict[str, int]      ,      _lowercase :     List[str]      ,      _lowercase :     int = None      ,      _lowercase :     int = None		):
								super().__init__()
								A       							=			pad_token_id
								A       							=			max_length
								A       							=			vocab
								A       							=			merges
								A       							=			BytePairTokenizer(lowercase__      ,      lowercase__      ,      sequence_length=lowercase__		)







						@classmethod
						def __a    (				cls :     List[Any]      ,      _lowercase :     GPTaTokenizer      ,      *_lowercase :     Optional[Any]      ,      **_lowercase :     int		):
								A       							=			[""" """.join(lowercase__		) for m in tokenizer.bpe_ranks.keys()]
								A       							=			tokenizer.get_vocab()
								return cls(lowercase__      ,      lowercase__      ,      *lowercase__      ,      **lowercase__		)







						@classmethod
						def __a    (				cls :     Dict      ,      _lowercase :     Union[str, os.PathLike]      ,      *_lowercase :     str      ,      **_lowercase :     Optional[int]		):
								A       							=			GPTaTokenizer.from_pretrained(lowercase__      ,      *lowercase__      ,      **lowercase__		)
								return cls.from_tokenizer(lowercase__      ,      *lowercase__      ,      **lowercase__		)







						@classmethod
						def __a    (				cls :     Dict      ,      _lowercase :     Optional[Any]		):
								return cls(**lowercase__		)







						def __a    (				self :     Optional[Any]		):
								return {
								    "vocab": self.vocab,
								    "merges": self.merges,
								    "max_length": self.max_length,
								    "pad_token_id": self.pad_token_id,
								}







						def __a    (				self :     Dict      ,      _lowercase :     Union[str, Any]      ,      _lowercase :     int = None		):
								A       							=			self.tf_tokenizer(lowercase__		)
								A       							=			tf.ones_like(lowercase__		)

								if self.pad_token_id is not None:
										# pad the tokens up to max length
										A       							=			max_length if max_length is not None else self.max_length

										if max_length is not None:
												A       							=			pad_model_inputs(
												    lowercase__      ,      max_seq_length=lowercase__      ,      pad_value=self.pad_token_id		)

								return {"attention_mask": attention_mask, "input_ids": input_ids}











'''simple docstring'''


def  _SCREAMING_SNAKE_CASE     (      UpperCamelCase__    :					list[int] ,    UpperCamelCase__    :					str				):




     """simple docstring"""


     a_     :							Tuple     						=  int(UpperCamelCase__				)

     # Initialize Result
     a_     :							Tuple     						=  []

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

     return answer


# Driver Code
if __name__ == "__main__":
 lowerCAmelCase_      :  List[str]				     =  []
 lowerCAmelCase_      :  Union[str, Any]				     =  '0'

 if (
     input('Do you want to enter your denominations ? (yY/n): ').strip().lower()
     == "y"
 ):
  lowerCAmelCase_      :  str				     =  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()))
  lowerCAmelCase_      :  Union[str, Any]				     =  input('Enter the change you want to make in Indian Currency: ').strip()
 else:
  # All denominations of Indian Currency if user does not enter
  lowerCAmelCase_      :  List[Any]				     =  [1, 2, 5, 10, 20, 50, 100, 500, 2000]
  lowerCAmelCase_      :  str				     =  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}: ")
  lowerCAmelCase_      :  Optional[int]				     =  find_minimum_change(denominations, value)
  # Print result
  for i in range(len(answer)):
   print(answer[i], end=' ')
