





from __future__ import annotations



def _a				(	lowerCamelCase:   str					,				lowerCamelCase:   list[str] | None = None )	->						list[list[str]]:







      '''simple docstring'''






      __A          =				word_bank or []
      # create a table
      __A          =				len(lowerCamelCase ) + 1

      __A          =				[]
      for _ in range(lowerCamelCase ):
            table.append([] )
      # seed value
      __A          =				[[]]  # 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:
                              __A          =				[
                                  [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


snake_case__					:							Optional[Any]													=     {'configuration_ibert': ['IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'IBertConfig', 'IBertOnnxConfig']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       snake_case__					:							List[str]													=     [
           'IBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'IBertForMaskedLM',
           'IBertForMultipleChoice',
           'IBertForQuestionAnswering',
           'IBertForSequenceClassification',
           'IBertForTokenClassification',
           'IBertModel',
           'IBertPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_ibert import (
                  IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  IBertForMaskedLM,
                  IBertForMultipleChoice,
                  IBertForQuestionAnswering,
                  IBertForSequenceClassification,
                  IBertForTokenClassification,
                  IBertModel,
                  IBertPreTrainedModel,
              )

else:
       import sys

       snake_case__					:							Dict													=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





