

from typing import TYPE_CHECKING

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


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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__		   =    [
        '''Constraint''',
        '''ConstraintListState''',
        '''DisjunctiveConstraint''',
        '''PhrasalConstraint''',
    ]
    UpperCamelCase__		   =    [
        '''BeamHypotheses''',
        '''BeamScorer''',
        '''BeamSearchScorer''',
        '''ConstrainedBeamSearchScorer''',
    ]
    UpperCamelCase__		   =    [
        '''EpsilonLogitsWarper''',
        '''EtaLogitsWarper''',
        '''ForcedBOSTokenLogitsProcessor''',
        '''ForcedEOSTokenLogitsProcessor''',
        '''HammingDiversityLogitsProcessor''',
        '''InfNanRemoveLogitsProcessor''',
        '''LogitsProcessor''',
        '''LogitsProcessorList''',
        '''LogitsWarper''',
        '''MinLengthLogitsProcessor''',
        '''MinNewTokensLengthLogitsProcessor''',
        '''NoBadWordsLogitsProcessor''',
        '''NoRepeatNGramLogitsProcessor''',
        '''PrefixConstrainedLogitsProcessor''',
        '''RepetitionPenaltyLogitsProcessor''',
        '''SequenceBiasLogitsProcessor''',
        '''EncoderRepetitionPenaltyLogitsProcessor''',
        '''TemperatureLogitsWarper''',
        '''TopKLogitsWarper''',
        '''TopPLogitsWarper''',
        '''TypicalLogitsWarper''',
        '''EncoderNoRepeatNGramLogitsProcessor''',
        '''ExponentialDecayLengthPenalty''',
        '''LogitNormalization''',
    ]
    UpperCamelCase__		   =    [
        '''MaxNewTokensCriteria''',
        '''MaxLengthCriteria''',
        '''MaxTimeCriteria''',
        '''StoppingCriteria''',
        '''StoppingCriteriaList''',
        '''validate_stopping_criteria''',
    ]
    UpperCamelCase__		   =    [
        '''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:
    UpperCamelCase__		   =    [
        '''TFForcedBOSTokenLogitsProcessor''',
        '''TFForcedEOSTokenLogitsProcessor''',
        '''TFLogitsProcessor''',
        '''TFLogitsProcessorList''',
        '''TFLogitsWarper''',
        '''TFMinLengthLogitsProcessor''',
        '''TFNoBadWordsLogitsProcessor''',
        '''TFNoRepeatNGramLogitsProcessor''',
        '''TFRepetitionPenaltyLogitsProcessor''',
        '''TFTemperatureLogitsWarper''',
        '''TFTopKLogitsWarper''',
        '''TFTopPLogitsWarper''',
        '''TFForceTokensLogitsProcessor''',
        '''TFSuppressTokensAtBeginLogitsProcessor''',
        '''TFSuppressTokensLogitsProcessor''',
    ]
    UpperCamelCase__		   =    [
        '''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:
    UpperCamelCase__		   =    [
        '''FlaxForcedBOSTokenLogitsProcessor''',
        '''FlaxForcedEOSTokenLogitsProcessor''',
        '''FlaxLogitsProcessor''',
        '''FlaxLogitsProcessorList''',
        '''FlaxLogitsWarper''',
        '''FlaxMinLengthLogitsProcessor''',
        '''FlaxTemperatureLogitsWarper''',
        '''FlaxTopKLogitsWarper''',
        '''FlaxTopPLogitsWarper''',
    ]
    UpperCamelCase__		   =    [
        '''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

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




from __future__ import annotations

class 						__snake_case						:
       """simple docstring"""







       def __init__(		self			,   _UpperCamelCase      )			->       None:






              """simple docstring"""


              __snake_case					  =       value
              __snake_case					  =       None
              __snake_case					  =       None






class 						__snake_case						:
       """simple docstring"""







       __SCREAMING_SNAKE_CASE													=       42


       def __init__(		self      )			->       None:






              """simple docstring"""


              __snake_case					  =       0


       def  a		(		self			,   _UpperCamelCase			,   _UpperCamelCase      )			->       None:






              """simple docstring"""


              if node is None:
                     return

              if path_sum == self.target:
                     self.paths += 1

              if node.left:
                     self.depth_first_search(node.left			,   path_sum + node.left.value      )
              if node.right:
                     self.depth_first_search(node.right			,   path_sum + node.right.value      )






       def  a		(		self			,   _UpperCamelCase			,   _UpperCamelCase = None      )			->       int:






              """simple docstring"""


              if node is None:
                     return 0
              if target is not None:
                     __snake_case					  =       target

              self.depth_first_search(_UpperCamelCase			,   node.value      )
              self.path_sum(node.left      )
              self.path_sum(node.right      )

              return self.paths


if __name__ == "__main__":
    import doctest

    doctest.testmod()

