



'''simple docstring'''





import functools
from typing import Any

def        a_     (							_lowerCAmelCase       ,_lowerCAmelCase       )      ->      bool:

  # Validation
  if not isinstance(_lowerCAmelCase       ,_lowerCAmelCase       ) or len(_lowerCAmelCase       ) == 0:
    raise ValueError('the string should be not empty string'       )

  if not isinstance(_lowerCAmelCase       ,_lowerCAmelCase       ) or not all(
      isinstance(_lowerCAmelCase       ,_lowerCAmelCase       ) and len(_lowerCAmelCase       ) > 0 for item in words       ):
    raise ValueError('the words should be a list of non-empty strings'       )

  # Build trie
  __lowerCamelCase       :       dict[str, Any]           = {}
  __lowerCamelCase       :       Union[str, Any]           = 'WORD_KEEPER'

  for word in words:
    __lowerCamelCase       :       List[str]           = trie
    for c in word:
      if c not in trie_node:
        __lowerCamelCase       :       Tuple           = {}

      __lowerCamelCase       :       Optional[Any]           = trie_node[c]

    __lowerCamelCase       :       Optional[Any]           = True

  __lowerCamelCase       :       Optional[Any]           = len(_lowerCAmelCase       )

  # Dynamic programming method
  @functools.cache
  def is_breakable(_lowerCAmelCase       ) -> bool:
    if index == len_string:
      return True

    __lowerCamelCase       :       Union[str, Any]           = trie
    for i in range(_lowerCAmelCase       ,_lowerCAmelCase       ):
      __lowerCamelCase       :       int           = trie_node.get(string[i]       ,_lowerCAmelCase       )

      if trie_node is None:
        return False

      if trie_node.get(_lowerCAmelCase       ,_lowerCAmelCase       ) and is_breakable(i + 1       ):
        return True

    return False

  return is_breakable(0       )


if __name__ == "__main__":
   import doctest

   doctest.testmod()











'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_UpperCamelCase											=						{
    'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
    'tokenization_biogpt': ['BioGptTokenizer'],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=						[
       'BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'BioGptForCausalLM',
       'BioGptForTokenClassification',
       'BioGptForSequenceClassification',
       'BioGptModel',
       'BioGptPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
   from .tokenization_biogpt import BioGptTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_biogpt import (
          BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
          BioGptForCausalLM,
          BioGptForSequenceClassification,
          BioGptForTokenClassification,
          BioGptModel,
          BioGptPreTrainedModel,
      )


else:
   import sys

   _UpperCamelCase											=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






