






"""simple docstring"""



import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 							__SCREAMING_SNAKE_CASE						(				UpperCamelCase       ,		unittest.TestCase		):
		snake_case_     =							LongformerTokenizer
		snake_case_     =							True
		snake_case_     =							LongformerTokenizerFast
		snake_case_     =							True


		def 						_UpperCamelCase       (			self      :						Optional[Any]							):
								'''simple docstring'''





								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								A__						:  Tuple		  =  [
								    """l""",
								    """o""",
								    """w""",
								    """e""",
								    """r""",
								    """s""",
								    """t""",
								    """i""",
								    """d""",
								    """n""",
								    """\u0120""",
								    """\u0120l""",
								    """\u0120n""",
								    """\u0120lo""",
								    """\u0120low""",
								    """er""",
								    """\u0120lowest""",
								    """\u0120newer""",
								    """\u0120wider""",
								    """<unk>""",
								]
								A__						:  Union[str, Any]		  =  dict(zip(snake_case			,    range(len(snake_case							)							)							)							)
								A__						:  Any		  =  ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
								A__						:  Tuple		  =  {"""unk_token""": """<unk>"""}

								A__						:  Optional[Any]		  =  os.path.join(self.tmpdirname			,    VOCAB_FILES_NAMES["""vocab_file"""]							)
								A__						:  Any		  =  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(snake_case							) + """\n"""							)
								with open(self.merges_file			,    """w"""			,    encoding="""utf-8"""							) as fp:
														fp.write("""\n""".join(snake_case							)							)


		def 						_UpperCamelCase       (			self      :						Dict			,    **snake_case      :						Union[str, Any]							):
								'''simple docstring'''





								kwargs.update(self.special_tokens_map							)
								return self.tokenizer_class.from_pretrained(self.tmpdirname			,    **snake_case							)


		def 						_UpperCamelCase       (			self      :						Optional[Any]			,    **snake_case      :						List[Any]							):
								'''simple docstring'''





								kwargs.update(self.special_tokens_map							)
								return self.rust_tokenizer_class.from_pretrained(self.tmpdirname			,    **snake_case							)


		def 						_UpperCamelCase       (			self      :						Dict			,    snake_case      :						Tuple							):
								'''simple docstring'''





								A__						:  int		  =  """lower newer"""
								A__						:  List[str]		  =  """lower newer"""
								return input_text, output_text


		def 						_UpperCamelCase       (			self      :						Optional[int]							):
								'''simple docstring'''





								A__						:  Optional[Any]		  =  self.tokenizer_class(self.vocab_file			,    self.merges_file			,    **self.special_tokens_map							)
								A__						:  Any		  =  """lower newer"""
								A__						:  int		  =  ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
								A__						:  Optional[Any]		  =  tokenizer.tokenize(snake_case							)  # , add_prefix_space=True)
								self.assertListEqual(snake_case			,    snake_case							)

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


		def 						_UpperCamelCase       (			self      :						Tuple							):
								'''simple docstring'''





								A__						:  Optional[Any]		  =  self.get_tokenizer()

								self.assertListEqual(tokenizer.encode("""Hello world!"""			,    add_special_tokens=snake_case							)			,    [0, 3_1414, 232, 328, 2]							)
								self.assertListEqual(
								    tokenizer.encode("""Hello world! cécé herlolip 418"""			,    add_special_tokens=snake_case							)			,    [0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]			,    )


		@slow
		def 						_UpperCamelCase       (			self      :						Optional[Any]							):
								'''simple docstring'''





								A__						:  Optional[int]		  =  self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""							)

								A__						:  Optional[Any]		  =  tokenizer.encode("""sequence builders"""			,    add_special_tokens=snake_case							)
								A__						:  Optional[Any]		  =  tokenizer.encode("""multi-sequence build"""			,    add_special_tokens=snake_case							)

								A__						:  List[str]		  =  tokenizer.encode(
								    """sequence builders"""			,    add_special_tokens=snake_case			,    add_prefix_space=snake_case							)
								A__						:  Dict		  =  tokenizer.encode(
								    """sequence builders"""			,    """multi-sequence build"""			,    add_special_tokens=snake_case			,    add_prefix_space=snake_case							)

								A__						:  Any		  =  tokenizer.build_inputs_with_special_tokens(snake_case							)
								A__						:  Tuple		  =  tokenizer.build_inputs_with_special_tokens(snake_case			,    snake_case							)

								assert encoded_sentence == encoded_text_from_decode
								assert encoded_pair == encoded_pair_from_decode


		def 						_UpperCamelCase       (			self      :						Optional[int]							):
								'''simple docstring'''





								A__						:  Any		  =  self.get_tokenizer()

								A__						:  Any		  =  """Encode this sequence."""
								A__						:  Tuple		  =  tokenizer.byte_encoder[""" """.encode("""utf-8"""							)[0]]

								# Testing encoder arguments
								A__						:  str		  =  tokenizer.encode(snake_case			,    add_special_tokens=snake_case			,    add_prefix_space=snake_case							)
								A__						:  Optional[int]		  =  tokenizer.convert_ids_to_tokens(encoded[0]							)[0]
								self.assertNotEqual(snake_case			,    snake_case							)

								A__						:  Any		  =  tokenizer.encode(snake_case			,    add_special_tokens=snake_case			,    add_prefix_space=snake_case							)
								A__						:  List[Any]		  =  tokenizer.convert_ids_to_tokens(encoded[0]							)[0]
								self.assertEqual(snake_case			,    snake_case							)

								tokenizer.add_special_tokens({"""bos_token""": """<s>"""}							)
								A__						:  Optional[int]		  =  tokenizer.encode(snake_case			,    add_special_tokens=snake_case							)
								A__						:  str		  =  tokenizer.convert_ids_to_tokens(encoded[1]							)[0]
								self.assertNotEqual(snake_case			,    snake_case							)

								# Testing spaces after special tokens
								A__						:  Optional[int]		  =  """<mask>"""
								tokenizer.add_special_tokens(
								    {"""mask_token""": AddedToken(snake_case			,    lstrip=snake_case			,    rstrip=snake_case							)}							)  # mask token has a left space
								A__						:  Any		  =  tokenizer.convert_tokens_to_ids(snake_case							)

								A__						:  List[Any]		  =  """Encode <mask> sequence"""
								A__						:  Tuple		  =  """Encode <mask>sequence"""

								A__						:  List[str]		  =  tokenizer.encode(snake_case							)
								A__						:  str		  =  encoded.index(snake_case							)
								A__						:  Tuple		  =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]							)[0]
								self.assertEqual(snake_case			,    snake_case							)

								A__						:  Optional[int]		  =  tokenizer.encode(snake_case							)
								A__						:  Optional[int]		  =  encoded.index(snake_case							)
								A__						:  List[str]		  =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]							)[0]
								self.assertNotEqual(snake_case			,    snake_case							)


		def 						_UpperCamelCase       (			self      :						Optional[int]							):
								'''simple docstring'''





								pass


		def 						_UpperCamelCase       (			self      :						List[str]							):
								'''simple docstring'''





								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
														with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'							):
																				A__						:  Optional[Any]		  =  self.rust_tokenizer_class.from_pretrained(snake_case			,    **snake_case							)
																				A__						:  Dict		  =  self.tokenizer_class.from_pretrained(snake_case			,    **snake_case							)
																				A__						:  Dict		  =  """A, <mask> AllenNLP sentence."""
																				A__						:  List[Any]		  =  tokenizer_r.encode_plus(snake_case			,    add_special_tokens=snake_case			,    return_token_type_ids=snake_case							)
																				A__						:  Tuple		  =  tokenizer_p.encode_plus(snake_case			,    add_special_tokens=snake_case			,    return_token_type_ids=snake_case							)

																				# 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"""]							)			,    )

																				A__						:  Optional[Any]		  =  tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]							)
																				A__						:  str		  =  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, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]							)
																				self.assertSequenceEqual(tokens_r["""input_ids"""]			,    [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]							)

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


		def 						_UpperCamelCase       (			self      :						str							):
								'''simple docstring'''





								for trim_offsets, add_prefix_space in itertools.product([True, False]			,    repeat=2							):
														A__						:  Union[str, Any]		  =  self.rust_tokenizer_class.from_pretrained(
														    self.tmpdirname			,    use_fast=snake_case			,    add_prefix_space=snake_case			,    trim_offsets=snake_case							)

														A__						:  List[str]		  =  json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()							)
														A__						:  List[str]		  =  json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()							)

														self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]			,    snake_case							)

														self.assertEqual(post_processor_state["""add_prefix_space"""]			,    snake_case							)
														self.assertEqual(post_processor_state["""trim_offsets"""]			,    snake_case							)


		def 						_UpperCamelCase       (			self      :						Any							):
								'''simple docstring'''





								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
														with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'							):
																				A__						:  Optional[int]		  =  """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
																				A__						:  Tuple		  =  F'{text_of_1_token} {text_of_1_token}'

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

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

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

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

																				A__						:  str		  =  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)),
																				# )

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

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

																				A__						:  Optional[int]		  =  self.rust_tokenizer_class.from_pretrained(
																				    snake_case			,    use_fast=snake_case			,    add_prefix_space=snake_case			,    trim_offsets=snake_case							)
																				A__						:  str		  =  tokenizer_r(snake_case			,    return_offsets_mapping=snake_case			,    add_special_tokens=snake_case							)
																				self.assertEqual(encoding.offset_mapping[0]			,    (0, 1 + len(snake_case							))							)
																				self.assertEqual(
																				    encoding.offset_mapping[1]			,    (1 + len(snake_case							), 1 + len(snake_case							) + 1 + len(snake_case							))			,    )














"""simple docstring"""



def      _lowerCAmelCase		(							UpperCAmelCase__       :					int = 1_0_0_0      )		->int:
						A__						:  Optional[int]		  =  2**power
						A__						:  Dict		  =  0
						while n:
												A__  ,  A__						:  Tuple		  =  r + n % 1_0, n // 1_0
						return r


if __name__ == "__main__":
						print(solution(int(str(input()).strip())))






