
from __future__ import annotations


def 			UpperCamelCase					(    __lowerCamelCase     : list[int]				,					__lowerCamelCase     : int    ):
       snake_case       :   list[list[int]]							=      []
       snake_case       :   list[int]							=      []
       snake_case       :   Optional[Any]							=      0
       snake_case       :   Optional[Any]							=      sum(__lowerCamelCase    )
       create_state_space_tree(__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase    )
       return result


def 			UpperCamelCase					(    __lowerCamelCase     : list[int]				,					__lowerCamelCase     : int				,					__lowerCamelCase     : int				,					__lowerCamelCase     : list[int]				,					__lowerCamelCase     : list[list[int]]				,					__lowerCamelCase     : int				,					):
       if sum(__lowerCamelCase    ) > max_sum or (remaining_nums_sum + sum(__lowerCamelCase    )) < max_sum:
              return
       if sum(__lowerCamelCase    ) == max_sum:
              result.append(__lowerCamelCase    )
              return
       for index in range(__lowerCamelCase				,					len(__lowerCamelCase    )    ):
              create_state_space_tree(
                  __lowerCamelCase				,					__lowerCamelCase				,					index + 1				,					[*path, nums[index]]				,					__lowerCamelCase				,					remaining_nums_sum - nums[index]				,					)
__lowerCamelCase							=       [3, 34, 4, 12, 5, 2]
__lowerCamelCase							=       9
__lowerCamelCase							=       generate_sum_of_subsets_soln(nums, max_sum)




print(*result)







from typing import TYPE_CHECKING

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


if is_sentencepiece_available():
   from ..ta.tokenization_ta import TaTokenizer
else:
   from ...utils.dummy_sentencepiece_objects import TaTokenizer

__lowerCamelCase							=       TaTokenizer

if is_tokenizers_available():
   from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
   from ...utils.dummy_tokenizers_objects import TaTokenizerFast

__lowerCamelCase							=       TaTokenizerFast

__lowerCamelCase							=       {"""configuration_mt5""": ["""MT5Config""", """MT5OnnxConfig"""]}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       [
       """MT5EncoderModel""",
       """MT5ForConditionalGeneration""",
       """MT5ForQuestionAnswering""",
       """MT5Model""",
       """MT5PreTrainedModel""",
       """MT5Stack""",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       ["""TFMT5EncoderModel""", """TFMT5ForConditionalGeneration""", """TFMT5Model"""]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       ["""FlaxMT5EncoderModel""", """FlaxMT5ForConditionalGeneration""", """FlaxMT5Model"""]


if TYPE_CHECKING:
   from .configuration_mta import MTaConfig, MTaOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mta import (
          MTaEncoderModel,
          MTaForConditionalGeneration,
          MTaForQuestionAnswering,
          MTaModel,
          MTaPreTrainedModel,
          MTaStack,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
   import sys

   __lowerCamelCase							=       _LazyModule(
       __name__,
       globals()["""__file__"""],
       _import_structure,
       extra_objects={"""MT5Tokenizer""": MTaTokenizer, """MT5TokenizerFast""": MTaTokenizerFast},
       module_spec=__spec__,
   )





