code: 
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  __lowerCamelCase  				=					{
      '''configuration_realm''': ['''REALM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RealmConfig'''],
      '''tokenization_realm''': ['''RealmTokenizer'''],
  }
  
  try:
      if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
      pass
  else:
      __lowerCamelCase  				=					['''RealmTokenizerFast''']
  
  try:
      if not is_torch_available():
          raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
      pass
  else:
      __lowerCamelCase  				=					[
          '''REALM_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''RealmEmbedder''',
          '''RealmForOpenQA''',
          '''RealmKnowledgeAugEncoder''',
          '''RealmPreTrainedModel''',
          '''RealmReader''',
          '''RealmScorer''',
          '''load_tf_weights_in_realm''',
      ]
      __lowerCamelCase  				=					['''RealmRetriever''']
  
  
  if TYPE_CHECKING:
      from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
      from .tokenization_realm import RealmTokenizer
  
      try:
          if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
          pass
      else:
          from .tokenization_realm import RealmTokenizerFast
  
      try:
          if not is_torch_available():
              raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
          pass
      else:
          from .modeling_realm import (
              REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
              RealmEmbedder,
              RealmForOpenQA,
              RealmKnowledgeAugEncoder,
              RealmPreTrainedModel,
              RealmReader,
              RealmScorer,
              load_tf_weights_in_realm,
          )
          from .retrieval_realm import RealmRetriever
  
  
  else:
      import sys
  
      __lowerCamelCase  				=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
style_context: 
  
  
  
  def     UpperCAmelCase__ (							__snake_case						,				__snake_case						,				__snake_case						,				__snake_case						,				__snake_case							)   -> None:
    if target == 0:
      answer.append(path.copy()							)
    else:
      for index in range(__snake_case						,				len(__snake_case							)							):
        if target >= candidates[index]:
          path.append(candidates[index]							)
          backtrack(__snake_case						,				__snake_case						,				__snake_case						,				target - candidates[index]						,				__snake_case							)
          path.pop(len(__snake_case							) - 1							)
  
  
  
  
  def     UpperCAmelCase__ (							__snake_case						,				__snake_case							)   -> list:
    _A           =    []  # type: list[int]
    _A           =    []  # type: list[int]
    backtrack(__snake_case						,				__snake_case						,				__snake_case						,				__snake_case						,				0							)
    return answer
  
  
  
  
  def     UpperCAmelCase__ (							)   -> None:
    print(combination_sum([-8, 2.3, 0]						,				1							)							)
  
  
  if __name__ == "__main__":
      import doctest
  
      doctest.testmod()
      main()