





'''simple docstring'''







from __future__ import annotations





def 				lowerCamelCase_					(     SCREAMING_SNAKE_CASE__					:	str,	SCREAMING_SNAKE_CASE__					:	list[str] | None = None      )       ->		list[list[str]]:
						UpperCAmelCase_	:					str     =     word_bank or []
						# create a table
						UpperCAmelCase_	:					Any     =     len(SCREAMING_SNAKE_CASE__      ) + 1

						UpperCAmelCase_	:					Dict     =     []
						for _ in range(SCREAMING_SNAKE_CASE__      ):
												table.append([]      )
						# seed value
						UpperCAmelCase_	:					List[str]     =     [[]]  # because empty string has empty combination

						# iterate through the indices
						for i in range(SCREAMING_SNAKE_CASE__      ):
												# condition
												if table[i] != []:
																		for word in word_bank:
																								# slice condition
																								if target[i : i + len(SCREAMING_SNAKE_CASE__      )] == word:
																														UpperCAmelCase_	:					List[Any]     =     [
																														    [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(SCREAMING_SNAKE_CASE__      )] += new_combinations

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

						return table[len(SCREAMING_SNAKE_CASE__      )]


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"],
					    )
					)












# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


snake_case__					:							List[str]													=     {
    'configuration_vivit': ['VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VivitConfig'],
}
try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       snake_case__					:							Tuple													=     ['VivitImageProcessor']


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       snake_case__					:							Any													=     [
           'VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'VivitModel',
           'VivitPreTrainedModel',
           'VivitForVideoClassification',
       ]


if TYPE_CHECKING:
       from .configuration_vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_vivit import VivitImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vivit import (
                  VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  VivitForVideoClassification,
                  VivitModel,
                  VivitPreTrainedModel,
              )


else:
       import sys

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





