



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase__     							=						{
    '''configuration_blenderbot''': [
        '''BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlenderbotConfig''',
        '''BlenderbotOnnxConfig''',
    ],
    '''tokenization_blenderbot''': ['''BlenderbotTokenizer'''],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__     							=						['''BlenderbotTokenizerFast''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__     							=						[
				    '''BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''BlenderbotForCausalLM''',
				    '''BlenderbotForConditionalGeneration''',
				    '''BlenderbotModel''',
				    '''BlenderbotPreTrainedModel''',
				]


try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__     							=						[
				    '''TFBlenderbotForConditionalGeneration''',
				    '''TFBlenderbotModel''',
				    '''TFBlenderbotPreTrainedModel''',
				]


try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__     							=						[
				    '''FlaxBlenderbotForConditionalGeneration''',
				    '''FlaxBlenderbotModel''',
				    '''FlaxBlenderbotPreTrainedModel''',
				]


if TYPE_CHECKING:
				from .configuration_blenderbot import (
				    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    BlenderbotConfig,
				    BlenderbotOnnxConfig,
				)
				from .tokenization_blenderbot import BlenderbotTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_blenderbot import (
								    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BlenderbotForCausalLM,
								    BlenderbotForConditionalGeneration,
								    BlenderbotModel,
								    BlenderbotPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_blenderbot import (
								    TFBlenderbotForConditionalGeneration,
								    TFBlenderbotModel,
								    TFBlenderbotPreTrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_blenderbot import (
								    FlaxBlenderbotForConditionalGeneration,
								    FlaxBlenderbotModel,
								    FlaxBlenderbotPreTrainedModel,
								)

else:
				import sys

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








from __future__ import annotations






def      _A				(UpperCamelCase		:      str      ,			UpperCamelCase		:      list[str] | None = None )  ->list[list[str]]:



			'''simple docstring'''







			lowerCamelCase__ :      List[str]								=		word_bank or []
			# create a table
			lowerCamelCase__ :      int								=		len(UpperCamelCase ) + 1

			lowerCamelCase__ :      list[list[list[str]]]								=		[]
			for _ in range(UpperCamelCase ):
						table.append([] )
			# seed value
			lowerCamelCase__ :      Tuple								=		[[]]  # because empty string has empty combination

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

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

			return table[len(UpperCamelCase )]


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'''],
				    )
				)



