



"""simple docstring"""
from typing import TYPE_CHECKING

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


__a           =							{
    "configuration_utils": ["GenerationConfig"],
    "streamers": ["TextIteratorStreamer", "TextStreamer"],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a           =							[
						    "Constraint",
						    "ConstraintListState",
						    "DisjunctiveConstraint",
						    "PhrasalConstraint",
						]
						__a           =							[
						    "BeamHypotheses",
						    "BeamScorer",
						    "BeamSearchScorer",
						    "ConstrainedBeamSearchScorer",
						]
						__a           =							[
						    "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           =							[
						    "MaxNewTokensCriteria",
						    "MaxLengthCriteria",
						    "MaxTimeCriteria",
						    "StoppingCriteria",
						    "StoppingCriteriaList",
						    "validate_stopping_criteria",
						]
						__a           =							[
						    "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           =							[
						    "TFForcedBOSTokenLogitsProcessor",
						    "TFForcedEOSTokenLogitsProcessor",
						    "TFLogitsProcessor",
						    "TFLogitsProcessorList",
						    "TFLogitsWarper",
						    "TFMinLengthLogitsProcessor",
						    "TFNoBadWordsLogitsProcessor",
						    "TFNoRepeatNGramLogitsProcessor",
						    "TFRepetitionPenaltyLogitsProcessor",
						    "TFTemperatureLogitsWarper",
						    "TFTopKLogitsWarper",
						    "TFTopPLogitsWarper",
						    "TFForceTokensLogitsProcessor",
						    "TFSuppressTokensAtBeginLogitsProcessor",
						    "TFSuppressTokensLogitsProcessor",
						]
						__a           =							[
						    "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           =							[
						    "FlaxForcedBOSTokenLogitsProcessor",
						    "FlaxForcedEOSTokenLogitsProcessor",
						    "FlaxLogitsProcessor",
						    "FlaxLogitsProcessorList",
						    "FlaxLogitsWarper",
						    "FlaxMinLengthLogitsProcessor",
						    "FlaxTemperatureLogitsWarper",
						    "FlaxTopKLogitsWarper",
						    "FlaxTopPLogitsWarper",
						]
						__a           =							[
						    "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           =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)







class 		_lowerCAmelCase:

  """simple docstring"""







  def __init__(   self      )->   None:
     # numbermap keys are the number and its values are lists of indexes sorted
     # in ascending order
     __A    =  {}
     # indexmap keys are an index and it's values are the number at that index
     __A    =  {}

  def 						SCREAMING_SNAKE_CASE__			(   self    ,							UpperCAmelCase    ,							UpperCAmelCase      )->   list[int]:
     if isinstance(UpperCAmelCase    ,							(range, str)      ):
        __A    =  list(UpperCAmelCase      )
     elif not isinstance(UpperCAmelCase    ,							UpperCAmelCase      ):
        raise TypeError(
            '''binary_search_delete() only accepts either a list, range or str'''      )

     __A    =  0
     __A    =  len(UpperCAmelCase      ) - 1

     while low <= high:
        __A    =  (low + high) // 2
        if array[mid] == item:
           array.pop(UpperCAmelCase      )
           return array
        elif array[mid] < item:
           __A    =  mid + 1
        else:
           __A    =  mid - 1
     raise ValueError(
         '''Either the item is not in the array or the array was unsorted'''      )

  def 						SCREAMING_SNAKE_CASE__			(   self    ,							UpperCAmelCase    ,							UpperCAmelCase      )->   list[int]:
     if isinstance(UpperCAmelCase    ,							(range, str)      ):
        __A    =  list(UpperCAmelCase      )
     elif not isinstance(UpperCAmelCase    ,							UpperCAmelCase      ):
        raise TypeError(
            '''binary_search_insert() only accepts either a list, range or str'''      )

     __A    =  0
     __A    =  len(UpperCAmelCase      ) - 1

     while low <= high:
        __A    =  (low + high) // 2
        if array[mid] == index:
           # If the item already exists in the array,
           # insert it after the existing item
           array.insert(mid + 1    ,							UpperCAmelCase      )
           return array
        elif array[mid] < index:
           __A    =  mid + 1
        else:
           __A    =  mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
     array.insert(UpperCAmelCase    ,							UpperCAmelCase      )
     return array

  def 						SCREAMING_SNAKE_CASE__			(   self    ,							UpperCAmelCase    ,							UpperCAmelCase      )->   None:
     # Remove previous index
     if index in self.indexmap:
        __A    =  self.indexmap[index]
        if len(self.numbermap[n]      ) == 1:
           del self.numbermap[n]
        else:
           __A    =  self.binary_search_delete(self.numbermap[n]    ,							UpperCAmelCase      )

        # Set new index
     __A    =  number

     # Number not seen before or empty so insert number value
     if number not in self.numbermap:
        __A    =  [index]

     # Here we need to perform a binary search insertion in order to insert
     # The item in the correct place
     else:
        __A    =  self.binary_search_insert(
            self.numbermap[number]    ,							UpperCAmelCase      )





  def 						SCREAMING_SNAKE_CASE__			(   self    ,							UpperCAmelCase      )->   int:
     return self.numbermap.get(UpperCAmelCase    ,							[-1]      )[0]


if __name__ == "__main__":
    import doctest

    doctest.testmod()

