





from __future__ import annotations






def     lowerCamelCase__			(__lowerCamelCase,       __lowerCamelCase = None	):
     _SCREAMING_SNAKE_CASE       :	List[str]						    =							word_bank or []
     # create a table
     _SCREAMING_SNAKE_CASE       :	int						    =							len(__lowerCamelCase	) + 1

     _SCREAMING_SNAKE_CASE       :	list[list[list[str]]]						    =							[]
     for _ in range(__lowerCamelCase	):
          table.append([]	)
     # seed value
     _SCREAMING_SNAKE_CASE       :	Any						    =							[[]]  # because empty string has empty combination

     # iterate through the indices
     for i in range(__lowerCamelCase	):
          # condition
          if table[i] != []:
               for word in word_bank:
                    # slice condition
                    if target[i : i + len(__lowerCamelCase	)] == word:
                         _SCREAMING_SNAKE_CASE       :	list[list[str]]						    =							[
                             [word, *way] for way in table[i]
                         ]
                         # adds the word to every combination the current position holds
                         # now,push that combination to the table[i+len(word)]
                         table[i + len(__lowerCamelCase	)] += new_combinations

    # combinations are in reverse order so reverse for better output
     for combination in table[len(__lowerCamelCase	)]:
          combination.reverse()

     return table[len(__lowerCamelCase	)]


if __name__ == "__main__":
       print(all_construct('jwajalapa', ['jwa', 'j', 'w', 'a', 'la', 'lapa']))
       print(all_construct('rajamati', ['s', 'raj', 'amat', 'raja', 'ma', 'i', 't']))
       print(
           all_construct(
               'hexagonosaurus',
               ['h', 'ex', 'hex', 'ag', 'ago', 'ru', 'auru', 'rus', 'go', 'no', 'o', 's'],
           )
       )






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__      ={
    'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__      =[
           'LILT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'LiltForQuestionAnswering',
           'LiltForSequenceClassification',
           'LiltForTokenClassification',
           'LiltModel',
           'LiltPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_lilt import (
                  LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  LiltForQuestionAnswering,
                  LiltForSequenceClassification,
                  LiltForTokenClassification,
                  LiltModel,
                  LiltPreTrainedModel,
              )

else:
       import sys

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