




from typing import TYPE_CHECKING

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


UpperCAmelCase__            =							{
    '''configuration_layoutlm''': ['''LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LayoutLMConfig''', '''LayoutLMOnnxConfig'''],
    '''tokenization_layoutlm''': ['''LayoutLMTokenizer'''],
}

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

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__            =							[
      '''LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''LayoutLMForMaskedLM''',
      '''LayoutLMForSequenceClassification''',
      '''LayoutLMForTokenClassification''',
      '''LayoutLMForQuestionAnswering''',
      '''LayoutLMModel''',
      '''LayoutLMPreTrainedModel''',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__            =							[
      '''TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''TFLayoutLMForMaskedLM''',
      '''TFLayoutLMForSequenceClassification''',
      '''TFLayoutLMForTokenClassification''',
      '''TFLayoutLMForQuestionAnswering''',
      '''TFLayoutLMMainLayer''',
      '''TFLayoutLMModel''',
      '''TFLayoutLMPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig, LayoutLMOnnxConfig
  from .tokenization_layoutlm import LayoutLMTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_layoutlm_fast import LayoutLMTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_layoutlm import (
        LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        LayoutLMForMaskedLM,
        LayoutLMForQuestionAnswering,
        LayoutLMForSequenceClassification,
        LayoutLMForTokenClassification,
        LayoutLMModel,
        LayoutLMPreTrainedModel,
    )
  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_layoutlm import (
        TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFLayoutLMForMaskedLM,
        TFLayoutLMForQuestionAnswering,
        TFLayoutLMForSequenceClassification,
        TFLayoutLMForTokenClassification,
        TFLayoutLMMainLayer,
        TFLayoutLMModel,
        TFLayoutLMPreTrainedModel,
    )

else:
  import sys

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





from math import sqrt
def     UpperCAmelCase_ (							__snake_case						)					->      list[int]:







 """simple docstring"""


 _lowercase											=[1]
 for i in range(2					,						int(sqrt(__snake_case						)						) + 1					,						1						):
  if number % i == 0:
   values.append(__snake_case						)
   if int(number // i						) != i:
    values.append(int(number // i						)						)
 return sorted(__snake_case						)
def     UpperCAmelCase_ (							__snake_case						)					->      bool:







 """simple docstring"""


 return sum(factors(__snake_case						)						) > n
def     UpperCAmelCase_ (							__snake_case						)					->      bool:







 """simple docstring"""


 _lowercase											=factors(__snake_case						)
 _lowercase											=len(__snake_case						)
 _lowercase											=[[0 for i in range(number + 1						)] for j in range(r + 1						)]
 for i in range(r + 1						):
  _lowercase											=True

 for i in range(1					,						number + 1						):
  _lowercase											=False

 for i in range(1					,						r + 1						):
  for j in range(1					,						number + 1						):
   if j < values[i - 1]:
    _lowercase											=subset[i - 1][j]
   else:
    _lowercase											=subset[i - 1][j] or subset[i - 1][j - values[i - 1]]

 return subset[r][number] != 0
def     UpperCAmelCase_ (							__snake_case						)					->      bool:







 """simple docstring"""


 return abundant(__snake_case						) and not semi_perfect(__snake_case						)


if __name__ == "__main__":
  import doctest

  doctest.testmod(verbose=True)
  for number in (69, 70, 71):
    print(f'''{number} is {'' if weird(number) else 'not '}weird.''')

