


"""simple docstring"""






from __future__ import annotations
def       A_   (   _lowerCAmelCase     :					list[int]       ):






     """simple docstring"""

     _a    	=				len(_lowerCAmelCase       ) // 2

     # choose the middle 3 elements
     _a    	=				lst[m - 1 : m + 2]

     # if middle element is peak
     if three[1] > three[0] and three[1] > three[2]:
          return three[1]

     # if increasing, recurse on right
     elif three[0] < three[2]:
          if len(lst[:m]       ) == 2:
               m -= 1
          return peak(lst[m:]       )

     # decreasing
     else:
          if len(lst[:m]       ) == 2:
               m += 1
          return peak(lst[:m]       )


if __name__ == "__main__":
   import doctest

   doctest.testmod()









"""simple docstring"""






from typing import TYPE_CHECKING

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


__snake_case		=       {
    '''configuration_lxmert''': ['''LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LxmertConfig'''],
    '''tokenization_lxmert''': ['''LxmertTokenizer'''],
}

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

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case		=       [
       '''LxmertEncoder''',
       '''LxmertForPreTraining''',
       '''LxmertForQuestionAnswering''',
       '''LxmertModel''',
       '''LxmertPreTrainedModel''',
       '''LxmertVisualFeatureEncoder''',
       '''LxmertXLayer''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case		=       [
       '''TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFLxmertForPreTraining''',
       '''TFLxmertMainLayer''',
       '''TFLxmertModel''',
       '''TFLxmertPreTrainedModel''',
       '''TFLxmertVisualFeatureEncoder''',
   ]


if TYPE_CHECKING:
   from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
   from .tokenization_lxmert import LxmertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_lxmert_fast import LxmertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_lxmert import (
          LxmertEncoder,
          LxmertForPreTraining,
          LxmertForQuestionAnswering,
          LxmertModel,
          LxmertPreTrainedModel,
          LxmertVisualFeatureEncoder,
          LxmertXLayer,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_lxmert import (
          TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFLxmertForPreTraining,
          TFLxmertMainLayer,
          TFLxmertModel,
          TFLxmertPreTrainedModel,
          TFLxmertVisualFeatureEncoder,
      )

else:
   import sys

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