
"""simple docstring"""




import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin

class 		a__						(      a_,			unittest.TestCase						):
   __lowerCAmelCase            =				BioGptTokenizer
   __lowerCAmelCase            =				False
   def 			__magic_name__			(			self				):
          super().setUp()

          # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
          lowercase    :				Optional[int]       		=							[
              "l",
              "o",
              "w",
              "e",
              "r",
              "s",
              "t",
              "i",
              "d",
              "n",
              "w</w>",
              "r</w>",
              "t</w>",
              "lo",
              "low",
              "er</w>",
              "low</w>",
              "lowest</w>",
              "newer</w>",
              "wider</w>",
              "<unk>",
          ]
          lowercase    :				Union[str, Any]       		=							dict(zip(_a	,    range(len(_a				)				)				)				)
          lowercase    :				Optional[int]       		=							["l o 123", "lo w 1456", "e r</w> 1789", ""]

          lowercase    :				Optional[Any]       		=							os.path.join(self.tmpdirname	,    VOCAB_FILES_NAMES["vocab_file"]				)
          lowercase    :				Dict       		=							os.path.join(self.tmpdirname	,    VOCAB_FILES_NAMES["merges_file"]				)
          with open(self.vocab_file	,    "w"				) as fp:
                 fp.write(json.dumps(_a				)				)
          with open(self.merges_file	,    "w"				) as fp:
                 fp.write("\n".join(_a				)				)
   def 			__magic_name__			(			self	,    _a				):
          lowercase    :				Optional[Any]       		=							"lower newer"
          lowercase    :				str       		=							"lower newer"
          return input_text, output_text
   def 			__magic_name__			(			self				):
          lowercase    :				int       		=							BioGptTokenizer(self.vocab_file	,    self.merges_file				)

          lowercase    :				Any       		=							"lower"
          lowercase    :				List[Any]       		=							["low", "er</w>"]
          lowercase    :				Optional[int]       		=							tokenizer.tokenize(_a				)
          self.assertListEqual(_a	,    _a				)

          lowercase    :				Union[str, Any]       		=							tokens + ["<unk>"]
          lowercase    :				Optional[Any]       		=							[14, 15, 20]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_a				)	,    _a				)

   @slow
   def 			__magic_name__			(			self				):
          lowercase    :				Optional[int]       		=							BioGptTokenizer.from_pretrained("microsoft/biogpt"				)

          lowercase    :				List[Any]       		=							tokenizer.encode("sequence builders"	,    add_special_tokens=_a				)
          lowercase    :				Any       		=							tokenizer.encode("multi-sequence build"	,    add_special_tokens=_a				)

          lowercase    :				List[Any]       		=							tokenizer.build_inputs_with_special_tokens(_a				)
          lowercase    :				int       		=							tokenizer.build_inputs_with_special_tokens(_a	,    _a				)

          self.assertTrue(encoded_sentence == [2] + text				)
          self.assertTrue(encoded_pair == [2] + text + [2] + text_a				)




"""simple docstring"""




from __future__ import annotations

from functools import lru_cache
from math import ceil

_A			:       Optional[Any]   		=       1_00

_A			:       Optional[int]   		=       set(range(3, NUM_PRIMES, 2))
primes.add(2)
_A			:       int

for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
   if prime not in primes:
      continue
   primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))


@lru_cache(maxsize=100  )
def   __magic_name__	(      __snake_case				:       int  ) ->				set[int]:
       if number_to_partition < 0:
              return set()
       elif number_to_partition == 0:
              return {1}

       lowercase    :				set[int]       		=							set()
       lowercase    :				int
       lowercase    :				int

       for prime in primes:
              if prime > number_to_partition:
                     continue
              for sub in partition(number_to_partition - prime  ):
                     ret.add(sub * prime  )

       return ret


def   __magic_name__	(      __snake_case				:       int = 5000  ) ->				int | None:
       for number_to_partition in range(1     , __snake_case  ):
              if len(partition(__snake_case  )  ) > number_unique_partitions:
                     return number_to_partition
       return None


if __name__ == "__main__":
   print(F"{solution() = }")


