





from __future__ import annotations

_lowerCamelCase			       =      [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
_lowerCamelCase			       =      [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]




def    __UpperCAmelCase(      lowercase_      ):
       _lowerCamelCase							:     Dict	=		[]
       _lowerCamelCase							:     Union[str, Any]	=		len(lowercase_      )

       for i in range(lowercase_      ):
              _lowerCamelCase							:     float	=		-1
              for j in range(i + 1 ,    lowercase_      ):
                     if arr[i] < arr[j]:
                            _lowerCamelCase							:     Optional[Any]	=		arr[j]
                            break
              result.append(lowercase_      )
       return result




def    __UpperCAmelCase(      lowercase_      ):
       _lowerCamelCase							:     Dict	=		[]
       for i, outer in enumerate(lowercase_      ):
              _lowerCamelCase							:     float	=		-1
              for inner in arr[i + 1 :]:
                     if outer < inner:
                            _lowerCamelCase							:     Tuple	=		inner
                            break
              result.append(lowercase_      )
       return result




def    __UpperCAmelCase(      lowercase_      ):
       _lowerCamelCase							:     List[str]	=		len(lowercase_      )
       _lowerCamelCase							:     list[float]	=		[]
       _lowerCamelCase							:     list[float]	=		[-1] * arr_size

       for index in reversed(range(lowercase_      )      ):
              if stack:
                     while stack[-1] <= arr[index]:
                            stack.pop()
                            if not stack:
                                   break
              if stack:
                     _lowerCamelCase							:     Optional[int]	=		stack[-1]
              stack.append(arr[index]      )
       return result


if __name__ == "__main__":
       from doctest import testmod
       from timeit import timeit

       testmod()
       print(next_greatest_element_slow(arr))
       print(next_greatest_element_fast(arr))
       print(next_greatest_element(arr))

       _lowerCamelCase			       =      (
           'from __main__ import arr, next_greatest_element_slow, '
           'next_greatest_element_fast, next_greatest_element'
       )
       print(
           'next_greatest_element_slow():',
           timeit('next_greatest_element_slow(arr)', setup=setup),
       )
       print(
           'next_greatest_element_fast():',
           timeit('next_greatest_element_fast(arr)', setup=setup),
       )
       print(
           '     next_greatest_element():',
           timeit('next_greatest_element(arr)', setup=setup),
       )








from typing import TYPE_CHECKING

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


_lowerCamelCase			       =      {
    'configuration_layoutlmv3': [
        'LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'LayoutLMv3Config',
        'LayoutLMv3OnnxConfig',
    ],
    'processing_layoutlmv3': ['LayoutLMv3Processor'],
    'tokenization_layoutlmv3': ['LayoutLMv3Tokenizer'],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      ['LayoutLMv3TokenizerFast']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      [
           'LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
           'LayoutLMv3ForQuestionAnswering',
           'LayoutLMv3ForSequenceClassification',
           'LayoutLMv3ForTokenClassification',
           'LayoutLMv3Model',
           'LayoutLMv3PreTrainedModel',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      [
           'TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
           'TFLayoutLMv3ForQuestionAnswering',
           'TFLayoutLMv3ForSequenceClassification',
           'TFLayoutLMv3ForTokenClassification',
           'TFLayoutLMv3Model',
           'TFLayoutLMv3PreTrainedModel',
       ]

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      ['LayoutLMv3FeatureExtractor']
       _lowerCamelCase			       =      ['LayoutLMv3ImageProcessor']


if TYPE_CHECKING:
       from .configuration_layoutlmva import (
           LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
           LayoutLMvaConfig,
           LayoutLMvaOnnxConfig,
       )
       from .processing_layoutlmva import LayoutLMvaProcessor
       from .tokenization_layoutlmva import LayoutLMvaTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_layoutlmva import (
                  LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
                  LayoutLMvaForQuestionAnswering,
                  LayoutLMvaForSequenceClassification,
                  LayoutLMvaForTokenClassification,
                  LayoutLMvaModel,
                  LayoutLMvaPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_layoutlmva import (
                  TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFLayoutLMvaForQuestionAnswering,
                  TFLayoutLMvaForSequenceClassification,
                  TFLayoutLMvaForTokenClassification,
                  TFLayoutLMvaModel,
                  TFLayoutLMvaPreTrainedModel,
              )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
              from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
       import sys

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

