code: 
  
  
  '''simple docstring'''
  
  import unittest
  from timeit import timeit
  
  
  
  def        SCREAMING_SNAKE_CASE__(		_UpperCamelCase      :				int    ,		_UpperCamelCase      :				int   )		->					int:
  
  
  
  
  
     '''simple docstring'''
  
  
  
  
  
  
  
     UpperCamelCase__ 						=						first_num if first_num >= second_num else second_num
     UpperCamelCase__ 						=						max_num
     while (common_mult % first_num > 0) or (common_mult % second_num > 0):
        common_mult += max_num
     return common_mult
  
  
  
  def        SCREAMING_SNAKE_CASE__(		_UpperCamelCase      :				int    ,		_UpperCamelCase      :				int   )		->					int:
  
  
  
  
  
     '''simple docstring'''
  
  
  
  
  
  
  
     return b if a == 0 else greatest_common_divisor(b % a    ,		_UpperCamelCase   )
  
  
  
  def        SCREAMING_SNAKE_CASE__(		_UpperCamelCase      :				int    ,		_UpperCamelCase      :				int   )		->					int:
  
  
  
  
  
     '''simple docstring'''
  
  
  
  
  
  
  
     return first_num // greatest_common_divisor(_UpperCamelCase    ,		_UpperCamelCase   ) * second_num
  
  
  
  def        SCREAMING_SNAKE_CASE__(		)		->					str:
  
  
  
  
  
     '''simple docstring'''
  
  
  
  
  
  
  
     UpperCamelCase__ 						=						(
         "from __main__ import least_common_multiple_slow, least_common_multiple_fast"
     )
     print(
         "least_common_multiple_slow():"    ,		timeit("least_common_multiple_slow(1000, 999)"    ,		setup=_UpperCamelCase   )    ,		)
     print(
         "least_common_multiple_fast():"    ,		timeit("least_common_multiple_fast(1000, 999)"    ,		setup=_UpperCamelCase   )    ,		)
  
  
  
  
  
  
  
  class  UpperCAmelCase (       unittest.TestCase):
   _lowerCamelCase :					str    					=					(
       (10, 20),
       (13, 15),
       (4, 31),
       (10, 42),
       (43, 34),
       (5, 12),
       (12, 25),
       (10, 25),
       (6, 9),
   )
   _lowerCamelCase :					int    					=					(20, 195, 124, 210, 1462, 60, 300, 50, 18)
  
   def 		lowercase_						( self :	List[Any]					):
  
  
  
  
  
      """simple docstring"""
  
  
  
      for i, (first_num, second_num) in enumerate(self.test_inputs					):
         UpperCamelCase__ 						=						least_common_multiple_slow(a_,					a_					)
         UpperCamelCase__ 						=						least_common_multiple_fast(a_,					a_					)
         with self.subTest(i=a_					):
            self.assertEqual(a_,					self.expected_results[i]					)
            self.assertEqual(a_,					self.expected_results[i]					)
  
  
  if __name__ == "__main__":
         benchmark()
         unittest.main()
style_context: 
  
  
  '''simple docstring'''
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_sentencepiece_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  __lowercase:		int							=     {
      "configuration_open_llama": ["OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "OpenLlamaConfig"],
  }
  
  try:
         if not is_sentencepiece_available():
                raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
         pass
  else:
         __lowercase:		str							=     ["LlamaTokenizer"]
  
  try:
         if not is_tokenizers_available():
                raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
         pass
  else:
         __lowercase:		List[Any]							=     ["LlamaTokenizerFast"]
  
  try:
         if not is_torch_available():
                raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
         pass
  else:
         __lowercase:		Union[str, Any]							=     [
             "OpenLlamaForCausalLM",
             "OpenLlamaModel",
             "OpenLlamaPreTrainedModel",
             "OpenLlamaForSequenceClassification",
         ]
  
  
  if TYPE_CHECKING:
         from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig
  
         try:
                if not is_sentencepiece_available():
                       raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
                pass
         else:
                from transformers import LlamaTokenizer
  
         try:
                if not is_tokenizers_available():
                       raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
                pass
         else:
                from transformers import LlamaTokenizerFast
  
         try:
                if not is_torch_available():
                       raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
                pass
         else:
                from .modeling_open_llama import (
                    OpenLlamaForCausalLM,
                    OpenLlamaForSequenceClassification,
                    OpenLlamaModel,
                    OpenLlamaPreTrainedModel,
                )
  
  
  else:
         import sys
  
         __lowercase:		Tuple							=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)