"""simple docstring"""







import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 	UpperCamelCase    (					lowercase   ,			unittest.TestCase		):
				UpperCAmelCase       :   str					=	RobertaTokenizer
				UpperCAmelCase       :   Tuple					=	RobertaTokenizerFast
				UpperCAmelCase       :   Optional[int]					=	True
				UpperCAmelCase       :   Optional[int]					=	{"""cls_token""": """<s>"""}



				def       _lowercase  (self       :   str)					->			Optional[int]:
					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					__snake_case    :							Optional[Any]   	=				[
					    'l',
					    'o',
					    'w',
					    'e',
					    'r',
					    's',
					    't',
					    'i',
					    'd',
					    'n',
					    '\u0120',
					    '\u0120l',
					    '\u0120n',
					    '\u0120lo',
					    '\u0120low',
					    'er',
					    '\u0120lowest',
					    '\u0120newer',
					    '\u0120wider',
					    '<unk>',
					]
					__snake_case    :							Union[str, Any]   	=				dict(zip(_A			,						range(len(_A))))
					__snake_case    :							str   	=				['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
					__snake_case    :							str   	=				{'unk_token': '<unk>'}

					__snake_case    :							Dict   	=				os.path.join(self.tmpdirname			,						VOCAB_FILES_NAMES['vocab_file'])
					__snake_case    :							Optional[int]   	=				os.path.join(self.tmpdirname			,						VOCAB_FILES_NAMES['merges_file'])
					with open(self.vocab_file			,						'w'			,						encoding='utf-8') as fp:
						fp.write(json.dumps(_A) + '\n')
					with open(self.merges_file			,						'w'			,						encoding='utf-8') as fp:
						fp.write('\n'.join(_A))



				def       _lowercase  (self       :   Dict			,						**_A       :   List[str])					->			str:
					kwargs.update(self.special_tokens_map)
					return self.tokenizer_class.from_pretrained(self.tmpdirname			,						**_A)



				def       _lowercase  (self       :   Optional[int]			,						**_A       :   Any)					->			Tuple:
					kwargs.update(self.special_tokens_map)
					return RobertaTokenizerFast.from_pretrained(self.tmpdirname			,						**_A)



				def       _lowercase  (self       :   Tuple			,						_A       :   int)					->			int:
					__snake_case    :							Optional[int]   	=				'lower newer'
					__snake_case    :							int   	=				'lower newer'
					return input_text, output_text



				def       _lowercase  (self       :   Optional[Any])					->			int:
					__snake_case    :							Optional[Any]   	=				self.tokenizer_class(self.vocab_file			,						self.merges_file			,						**self.special_tokens_map)
					__snake_case    :							str   	=				'lower newer'
					__snake_case    :							Union[str, Any]   	=				['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
					__snake_case    :							Tuple   	=				tokenizer.tokenize(_A)  # , add_prefix_space=True)
					self.assertListEqual(_A			,						_A)

					__snake_case    :							int   	=				tokens + [tokenizer.unk_token]
					__snake_case    :							Optional[Any]   	=				[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(_A)			,						_A)



				def       _lowercase  (self       :   List[Any])					->			List[Any]:
					__snake_case    :							int   	=				self.get_tokenizer()

					self.assertListEqual(tokenizer.encode('Hello world!'			,						add_special_tokens=_A)			,						[0, 3_14_14, 2_32, 3_28, 2])
					self.assertListEqual(
					    tokenizer.encode('Hello world! cécé herlolip 418'			,						add_special_tokens=_A)			,						[0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]			,						)



				@slow
				def       _lowercase  (self       :   int)					->			Dict:
					__snake_case    :							List[Any]   	=				self.tokenizer_class.from_pretrained('roberta-base')

					__snake_case    :							Union[str, Any]   	=				tokenizer.encode('sequence builders'			,						add_special_tokens=_A)
					__snake_case    :							Dict   	=				tokenizer.encode('multi-sequence build'			,						add_special_tokens=_A)

					__snake_case    :							List[Any]   	=				tokenizer.encode(
					    'sequence builders'			,						add_special_tokens=_A			,						add_prefix_space=_A)
					__snake_case    :							Optional[Any]   	=				tokenizer.encode(
					    'sequence builders'			,						'multi-sequence build'			,						add_special_tokens=_A			,						add_prefix_space=_A)

					__snake_case    :							Tuple   	=				tokenizer.build_inputs_with_special_tokens(_A)
					__snake_case    :							Union[str, Any]   	=				tokenizer.build_inputs_with_special_tokens(_A			,						_A)

					assert encoded_sentence == encoded_text_from_decode
					assert encoded_pair == encoded_pair_from_decode



				def       _lowercase  (self       :   List[str])					->			Tuple:
					__snake_case    :							Optional[Any]   	=				self.get_tokenizer()

					__snake_case    :							Union[str, Any]   	=				'Encode this sequence.'
					__snake_case    :							List[Any]   	=				tokenizer.byte_encoder[' '.encode('utf-8')[0]]

					# Testing encoder arguments
					__snake_case    :							Union[str, Any]   	=				tokenizer.encode(_A			,						add_special_tokens=_A			,						add_prefix_space=_A)
					__snake_case    :							int   	=				tokenizer.convert_ids_to_tokens(encoded[0])[0]
					self.assertNotEqual(_A			,						_A)

					__snake_case    :							Union[str, Any]   	=				tokenizer.encode(_A			,						add_special_tokens=_A			,						add_prefix_space=_A)
					__snake_case    :							Any   	=				tokenizer.convert_ids_to_tokens(encoded[0])[0]
					self.assertEqual(_A			,						_A)

					tokenizer.add_special_tokens({'bos_token': '<s>'})
					__snake_case    :							Dict   	=				tokenizer.encode(_A			,						add_special_tokens=_A)
					__snake_case    :							Any   	=				tokenizer.convert_ids_to_tokens(encoded[1])[0]
					self.assertNotEqual(_A			,						_A)

					# Testing spaces after special tokens
					__snake_case    :							List[Any]   	=				'<mask>'
					tokenizer.add_special_tokens(
					    {'mask_token': AddedToken(_A			,						lstrip=_A			,						rstrip=_A)})  # mask token has a left space
					__snake_case    :							Any   	=				tokenizer.convert_tokens_to_ids(_A)

					__snake_case    :							Union[str, Any]   	=				'Encode <mask> sequence'
					__snake_case    :							int   	=				'Encode <mask>sequence'

					__snake_case    :							Tuple   	=				tokenizer.encode(_A)
					__snake_case    :							Optional[int]   	=				encoded.index(_A)
					__snake_case    :							Union[str, Any]   	=				tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
					self.assertEqual(_A			,						_A)

					__snake_case    :							Optional[Any]   	=				tokenizer.encode(_A)
					__snake_case    :							Optional[Any]   	=				encoded.index(_A)
					__snake_case    :							Union[str, Any]   	=				tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
					self.assertNotEqual(_A			,						_A)



				def       _lowercase  (self       :   Optional[int])					->			int:
					pass



				def       _lowercase  (self       :   Tuple)					->			str:
					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
							__snake_case    :							Tuple   	=				self.rust_tokenizer_class.from_pretrained(_A			,						**_A)
							__snake_case    :							Optional[Any]   	=				self.tokenizer_class.from_pretrained(_A			,						**_A)
							__snake_case    :							Any   	=				'A, <mask> AllenNLP sentence.'
							__snake_case    :							Any   	=				tokenizer_r.encode_plus(_A			,						add_special_tokens=_A			,						return_token_type_ids=_A)
							__snake_case    :							Dict   	=				tokenizer_p.encode_plus(_A			,						add_special_tokens=_A			,						return_token_type_ids=_A)

							# token_type_ids should put 0 everywhere
							self.assertEqual(sum(tokens_r['token_type_ids'])			,						sum(tokens_p['token_type_ids']))

							# attention_mask should put 1 everywhere, so sum over length should be 1
							self.assertEqual(
							    sum(tokens_r['attention_mask']) / len(tokens_r['attention_mask'])			,						sum(tokens_p['attention_mask']) / len(tokens_p['attention_mask'])			,						)

							__snake_case    :							Union[str, Any]   	=				tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids'])
							__snake_case    :							int   	=				tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids'])

							# Rust correctly handles the space before the mask while python doesnt
							self.assertSequenceEqual(tokens_p['input_ids']			,						[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2])
							self.assertSequenceEqual(tokens_r['input_ids']			,						[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2])

							self.assertSequenceEqual(
							    _A			,						['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'])
							self.assertSequenceEqual(
							    _A			,						['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'])



				def       _lowercase  (self       :   Tuple)					->			str:
					for trim_offsets, add_prefix_space in itertools.product([True, False]			,						repeat=2):
						__snake_case    :							Any   	=				self.rust_tokenizer_class.from_pretrained(
						    self.tmpdirname			,						use_fast=_A			,						add_prefix_space=_A			,						trim_offsets=_A)

						__snake_case    :							Optional[int]   	=				json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__())
						__snake_case    :							List[Any]   	=				json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__())

						self.assertEqual(pre_tokenizer_state['add_prefix_space']			,						_A)

						self.assertEqual(post_processor_state['add_prefix_space']			,						_A)
						self.assertEqual(post_processor_state['trim_offsets']			,						_A)






				def       _lowercase  (self       :   Union[str, Any])					->			Optional[Any]:
					# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
					# `trim_offsets`
					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
							__snake_case    :							Union[str, Any]   	=				'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
							__snake_case    :							List[str]   	=				f"{text_of_1_token} {text_of_1_token}"

							__snake_case    :							List[Any]   	=				self.rust_tokenizer_class.from_pretrained(
							    _A			,						use_fast=_A			,						add_prefix_space=_A			,						trim_offsets=_A)
							__snake_case    :							int   	=				tokenizer_r(_A			,						return_offsets_mapping=_A			,						add_special_tokens=_A)
							self.assertEqual(encoding.offset_mapping[0]			,						(0, len(_A)))
							self.assertEqual(
							    encoding.offset_mapping[1]			,						(len(_A) + 1, len(_A) + 1 + len(_A))			,						)

							__snake_case    :							Union[str, Any]   	=				self.rust_tokenizer_class.from_pretrained(
							    _A			,						use_fast=_A			,						add_prefix_space=_A			,						trim_offsets=_A)
							__snake_case    :							Optional[Any]   	=				tokenizer_r(_A			,						return_offsets_mapping=_A			,						add_special_tokens=_A)
							self.assertEqual(encoding.offset_mapping[0]			,						(0, len(_A)))
							self.assertEqual(
							    encoding.offset_mapping[1]			,						(len(_A) + 1, len(_A) + 1 + len(_A))			,						)

							__snake_case    :							Optional[int]   	=				self.rust_tokenizer_class.from_pretrained(
							    _A			,						use_fast=_A			,						add_prefix_space=_A			,						trim_offsets=_A)
							__snake_case    :							List[Any]   	=				tokenizer_r(_A			,						return_offsets_mapping=_A			,						add_special_tokens=_A)
							self.assertEqual(encoding.offset_mapping[0]			,						(0, len(_A)))
							self.assertEqual(
							    encoding.offset_mapping[1]			,						(len(_A), len(_A) + 1 + len(_A))			,						)

							__snake_case    :							str   	=				self.rust_tokenizer_class.from_pretrained(
							    _A			,						use_fast=_A			,						add_prefix_space=_A			,						trim_offsets=_A)
							__snake_case    :							List[Any]   	=				tokenizer_r(_A			,						return_offsets_mapping=_A			,						add_special_tokens=_A)
							self.assertEqual(encoding.offset_mapping[0]			,						(0, len(_A)))
							self.assertEqual(
							    encoding.offset_mapping[1]			,						(len(_A), len(_A) + 1 + len(_A))			,						)

							__snake_case    :							List[Any]   	=				f" {text}"

							# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
							#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
							# )
							# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
							# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
							# self.assertEqual(
							#     encoding.offset_mapping[1],
							#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
							# )

							__snake_case    :							Tuple   	=				self.rust_tokenizer_class.from_pretrained(
							    _A			,						use_fast=_A			,						add_prefix_space=_A			,						trim_offsets=_A)
							__snake_case    :							Optional[Any]   	=				tokenizer_r(_A			,						return_offsets_mapping=_A			,						add_special_tokens=_A)
							self.assertEqual(encoding.offset_mapping[0]			,						(1, 1 + len(_A)))
							self.assertEqual(
							    encoding.offset_mapping[1]			,						(1 + len(_A) + 1, 1 + len(_A) + 1 + len(_A))			,						)

							__snake_case    :							int   	=				self.rust_tokenizer_class.from_pretrained(
							    _A			,						use_fast=_A			,						add_prefix_space=_A			,						trim_offsets=_A)
							__snake_case    :							Any   	=				tokenizer_r(_A			,						return_offsets_mapping=_A			,						add_special_tokens=_A)
							self.assertEqual(encoding.offset_mapping[0]			,						(0, 1 + len(_A)))
							self.assertEqual(
							    encoding.offset_mapping[1]			,						(1 + len(_A), 1 + len(_A) + 1 + len(_A))			,						)

							__snake_case    :							Any   	=				self.rust_tokenizer_class.from_pretrained(
							    _A			,						use_fast=_A			,						add_prefix_space=_A			,						trim_offsets=_A)
							__snake_case    :							Union[str, Any]   	=				tokenizer_r(_A			,						return_offsets_mapping=_A			,						add_special_tokens=_A)
							self.assertEqual(encoding.offset_mapping[0]			,						(0, 1 + len(_A)))
							self.assertEqual(
							    encoding.offset_mapping[1]			,						(1 + len(_A), 1 + len(_A) + 1 + len(_A))			,						)






"""simple docstring"""







def 						__UpperCAmelCase       (					UpperCAmelCase_					:       list[int]    ,							UpperCAmelCase_					:       str						)							->    list[int]:

	'''simple docstring'''





	__snake_case    :							Union[str, Any]   	=				int(UpperCAmelCase_						)

	# Initialize Result
	__snake_case    :							int   	=				[]

	# 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__":
	_a  :  Optional[int]=				[]
	_a  :  Optional[int]=				"0"

	if (
	    input("Do you want to enter your denominations ? (yY/n): ").strip().lower()
	    == "y"
	):
		_a  :  int=				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()))
		_a  :  Optional[int]=				input("Enter the change you want to make in Indian Currency: ").strip()
	else:
		# All denominations of Indian Currency if user does not enter
		_a  :  Tuple=				[1, 2, 5, 10, 20, 50, 100, 500, 2_000]
		_a  :  List[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}: ''')
		_a  :  List[Any]=				find_minimum_change(denominations, value)
		# Print result
		for i in range(len(answer)):
			print(answer[i], end=" ")





