code: 
  
  
  
  def _lowercase   (  __A							,__A       ):
  
  
  
   '''simple docstring'''
  
  
  
   if n < 0:
    return 0
   # table[i] represents the number of ways to get to amount i
   __UpperCamelCase				      =  [0] * (n + 1)
  
   # There is exactly 1 way to get to zero(You pick no coins).
   __UpperCamelCase				      =  1
  
   # Pick all coins one by one and update table[] values
   # after the index greater than or equal to the value of the
   # picked coin
   for coin_val in s:
    for j in range(__A							,n + 1       ):
     table[j] += table[j - coin_val]
  
   return table[n]
  
  
  if __name__ == "__main__":
   import doctest
  
   doctest.testmod()
  
  
  
  
  
  
style_context: 
  
  
  
  '''simple docstring'''
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
  )
  
  
  a__						:			Optional[int]										=			{
      'configuration_bark': [
          'BARK_PRETRAINED_CONFIG_ARCHIVE_MAP',
          'BarkCoarseConfig',
          'BarkConfig',
          'BarkFineConfig',
          'BarkSemanticConfig',
      ],
      'processing_bark': ['BarkProcessor'],
  }
  
  try:
   if not is_torch_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   a__						:			Any										=			[
       'BARK_PRETRAINED_MODEL_ARCHIVE_LIST',
       'BarkFineModel',
       'BarkSemanticModel',
       'BarkCoarseModel',
       'BarkModel',
       'BarkPreTrainedModel',
       'BarkCausalModel',
   ]
  
  if TYPE_CHECKING:
   from .configuration_bark import (
       BARK_PRETRAINED_CONFIG_ARCHIVE_MAP,
       BarkCoarseConfig,
       BarkConfig,
       BarkFineConfig,
       BarkSemanticConfig,
   )
   from .processing_bark import BarkProcessor
  
   try:
    if not is_torch_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_bark import (
        BARK_PRETRAINED_MODEL_ARCHIVE_LIST,
        BarkCausalModel,
        BarkCoarseModel,
        BarkFineModel,
        BarkModel,
        BarkPreTrainedModel,
        BarkSemanticModel,
    )
  
  else:
   import sys
  
   a__						:			Tuple										=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  
  
  
  