






from typing import TYPE_CHECKING

from ..utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available


a		:	str      					=			{
    '''configuration_utils''': ['''GenerationConfig'''],
    '''streamers''': ['''TextIteratorStreamer''', '''TextStreamer'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a		:	Tuple      					=			[
           '''Constraint''',
           '''ConstraintListState''',
           '''DisjunctiveConstraint''',
           '''PhrasalConstraint''',
       ]
       a		:	Dict      					=			[
           '''BeamHypotheses''',
           '''BeamScorer''',
           '''BeamSearchScorer''',
           '''ConstrainedBeamSearchScorer''',
       ]
       a		:	Any      					=			[
           '''EpsilonLogitsWarper''',
           '''EtaLogitsWarper''',
           '''ForcedBOSTokenLogitsProcessor''',
           '''ForcedEOSTokenLogitsProcessor''',
           '''HammingDiversityLogitsProcessor''',
           '''InfNanRemoveLogitsProcessor''',
           '''LogitsProcessor''',
           '''LogitsProcessorList''',
           '''LogitsWarper''',
           '''MinLengthLogitsProcessor''',
           '''MinNewTokensLengthLogitsProcessor''',
           '''NoBadWordsLogitsProcessor''',
           '''NoRepeatNGramLogitsProcessor''',
           '''PrefixConstrainedLogitsProcessor''',
           '''RepetitionPenaltyLogitsProcessor''',
           '''SequenceBiasLogitsProcessor''',
           '''EncoderRepetitionPenaltyLogitsProcessor''',
           '''TemperatureLogitsWarper''',
           '''TopKLogitsWarper''',
           '''TopPLogitsWarper''',
           '''TypicalLogitsWarper''',
           '''EncoderNoRepeatNGramLogitsProcessor''',
           '''ExponentialDecayLengthPenalty''',
           '''LogitNormalization''',
       ]
       a		:	str      					=			[
           '''MaxNewTokensCriteria''',
           '''MaxLengthCriteria''',
           '''MaxTimeCriteria''',
           '''StoppingCriteria''',
           '''StoppingCriteriaList''',
           '''validate_stopping_criteria''',
       ]
       a		:	Optional[int]      					=			[
           '''GenerationMixin''',
           '''top_k_top_p_filtering''',
           '''GreedySearchEncoderDecoderOutput''',
           '''GreedySearchDecoderOnlyOutput''',
           '''SampleEncoderDecoderOutput''',
           '''SampleDecoderOnlyOutput''',
           '''BeamSearchEncoderDecoderOutput''',
           '''BeamSearchDecoderOnlyOutput''',
           '''BeamSampleEncoderDecoderOutput''',
           '''BeamSampleDecoderOnlyOutput''',
           '''ContrastiveSearchEncoderDecoderOutput''',
           '''ContrastiveSearchDecoderOnlyOutput''',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a		:	List[Any]      					=			[
           '''TFForcedBOSTokenLogitsProcessor''',
           '''TFForcedEOSTokenLogitsProcessor''',
           '''TFLogitsProcessor''',
           '''TFLogitsProcessorList''',
           '''TFLogitsWarper''',
           '''TFMinLengthLogitsProcessor''',
           '''TFNoBadWordsLogitsProcessor''',
           '''TFNoRepeatNGramLogitsProcessor''',
           '''TFRepetitionPenaltyLogitsProcessor''',
           '''TFTemperatureLogitsWarper''',
           '''TFTopKLogitsWarper''',
           '''TFTopPLogitsWarper''',
           '''TFForceTokensLogitsProcessor''',
           '''TFSuppressTokensAtBeginLogitsProcessor''',
           '''TFSuppressTokensLogitsProcessor''',
       ]
       a		:	Tuple      					=			[
           '''TFGenerationMixin''',
           '''tf_top_k_top_p_filtering''',
           '''TFGreedySearchDecoderOnlyOutput''',
           '''TFGreedySearchEncoderDecoderOutput''',
           '''TFSampleEncoderDecoderOutput''',
           '''TFSampleDecoderOnlyOutput''',
           '''TFBeamSearchEncoderDecoderOutput''',
           '''TFBeamSearchDecoderOnlyOutput''',
           '''TFBeamSampleEncoderDecoderOutput''',
           '''TFBeamSampleDecoderOnlyOutput''',
           '''TFContrastiveSearchEncoderDecoderOutput''',
           '''TFContrastiveSearchDecoderOnlyOutput''',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a		:	Dict      					=			[
           '''FlaxForcedBOSTokenLogitsProcessor''',
           '''FlaxForcedEOSTokenLogitsProcessor''',
           '''FlaxLogitsProcessor''',
           '''FlaxLogitsProcessorList''',
           '''FlaxLogitsWarper''',
           '''FlaxMinLengthLogitsProcessor''',
           '''FlaxTemperatureLogitsWarper''',
           '''FlaxTopKLogitsWarper''',
           '''FlaxTopPLogitsWarper''',
       ]
       a		:	Tuple      					=			[
           '''FlaxGenerationMixin''',
           '''FlaxGreedySearchOutput''',
           '''FlaxSampleOutput''',
           '''FlaxBeamSearchOutput''',
       ]

if TYPE_CHECKING:
       from .configuration_utils import GenerationConfig
       from .streamers import TextIteratorStreamer, TextStreamer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .beam_constraints import Constraint, ConstraintListState, DisjunctiveConstraint, PhrasalConstraint
              from .beam_search import BeamHypotheses, BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
              from .logits_process import (
                  EncoderNoRepeatNGramLogitsProcessor,
                  EncoderRepetitionPenaltyLogitsProcessor,
                  EpsilonLogitsWarper,
                  EtaLogitsWarper,
                  ExponentialDecayLengthPenalty,
                  ForcedBOSTokenLogitsProcessor,
                  ForcedEOSTokenLogitsProcessor,
                  HammingDiversityLogitsProcessor,
                  InfNanRemoveLogitsProcessor,
                  LogitNormalization,
                  LogitsProcessor,
                  LogitsProcessorList,
                  LogitsWarper,
                  MinLengthLogitsProcessor,
                  MinNewTokensLengthLogitsProcessor,
                  NoBadWordsLogitsProcessor,
                  NoRepeatNGramLogitsProcessor,
                  PrefixConstrainedLogitsProcessor,
                  RepetitionPenaltyLogitsProcessor,
                  SequenceBiasLogitsProcessor,
                  TemperatureLogitsWarper,
                  TopKLogitsWarper,
                  TopPLogitsWarper,
                  TypicalLogitsWarper,
              )
              from .stopping_criteria import (
                  MaxLengthCriteria,
                  MaxNewTokensCriteria,
                  MaxTimeCriteria,
                  StoppingCriteria,
                  StoppingCriteriaList,
                  validate_stopping_criteria,
              )
              from .utils import (
                  BeamSampleDecoderOnlyOutput,
                  BeamSampleEncoderDecoderOutput,
                  BeamSearchDecoderOnlyOutput,
                  BeamSearchEncoderDecoderOutput,
                  ContrastiveSearchDecoderOnlyOutput,
                  ContrastiveSearchEncoderDecoderOutput,
                  GenerationMixin,
                  GreedySearchDecoderOnlyOutput,
                  GreedySearchEncoderDecoderOutput,
                  SampleDecoderOnlyOutput,
                  SampleEncoderDecoderOutput,
                  top_k_top_p_filtering,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tf_logits_process import (
                  TFForcedBOSTokenLogitsProcessor,
                  TFForcedEOSTokenLogitsProcessor,
                  TFForceTokensLogitsProcessor,
                  TFLogitsProcessor,
                  TFLogitsProcessorList,
                  TFLogitsWarper,
                  TFMinLengthLogitsProcessor,
                  TFNoBadWordsLogitsProcessor,
                  TFNoRepeatNGramLogitsProcessor,
                  TFRepetitionPenaltyLogitsProcessor,
                  TFSuppressTokensAtBeginLogitsProcessor,
                  TFSuppressTokensLogitsProcessor,
                  TFTemperatureLogitsWarper,
                  TFTopKLogitsWarper,
                  TFTopPLogitsWarper,
              )
              from .tf_utils import (
                  TFBeamSampleDecoderOnlyOutput,
                  TFBeamSampleEncoderDecoderOutput,
                  TFBeamSearchDecoderOnlyOutput,
                  TFBeamSearchEncoderDecoderOutput,
                  TFContrastiveSearchDecoderOnlyOutput,
                  TFContrastiveSearchEncoderDecoderOutput,
                  TFGenerationMixin,
                  TFGreedySearchDecoderOnlyOutput,
                  TFGreedySearchEncoderDecoderOutput,
                  TFSampleDecoderOnlyOutput,
                  TFSampleEncoderDecoderOutput,
                  tf_top_k_top_p_filtering,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .flax_logits_process import (
                  FlaxForcedBOSTokenLogitsProcessor,
                  FlaxForcedEOSTokenLogitsProcessor,
                  FlaxLogitsProcessor,
                  FlaxLogitsProcessorList,
                  FlaxLogitsWarper,
                  FlaxMinLengthLogitsProcessor,
                  FlaxTemperatureLogitsWarper,
                  FlaxTopKLogitsWarper,
                  FlaxTopPLogitsWarper,
              )
              from .flax_utils import FlaxBeamSearchOutput, FlaxGenerationMixin, FlaxGreedySearchOutput, FlaxSampleOutput
else:
       import sys

       a		:	Optional[int]      					=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










def     lowerCamelCase__				(   ):

  for a in range(300		):
    for b in range(a + 1  ,		400		):
      for c in range(b + 1  ,		500		):
        if (a + b + c) == 1000 and (a**2) + (b**2) == (c**2):
          return a * b * c

  return -1






def     lowerCamelCase__				(   ):

  for a in range(300		):
    for b in range(400		):
      __UpperCAmelCase							:     Optional[Any]									=  1000 - a - b
      if a < b < c and (a**2) + (b**2) == (c**2):
        return a * b * c

  return -1






def     lowerCamelCase__				(   ):
  import timeit

  print(
      timeit.timeit("""solution()"""  ,		setup="""from __main__ import solution"""  ,		number=1000		)		)
  print(
      timeit.timeit(
          """solution_fast()"""  ,		setup="""from __main__ import solution_fast"""  ,		number=1000		)		)


if __name__ == "__main__":
       print(f"""{solution() = }""")


