





'''simple docstring'''

def 		UpperCamelCase       (							_lowerCamelCase      :      str		, _lowerCamelCase      :      Optional[int]		, _lowerCamelCase      :      Optional[Any] ):
    assert b != 0, "This cannot accept modulo that is == 0"
    if n == 0:
        return 1

    if n % 2 == 1:
        return (bin_exp_mod(_lowerCamelCase		, n - 1		, _lowerCamelCase ) * a) % b

    A__       =    bin_exp_mod(_lowerCamelCase		, n / 2		, _lowerCamelCase )
    return (r * r) % b


if __name__ == "__main__":
  try:
    __lowerCAmelCase							:			List[str]				=int(input("Enter Base : ").strip())
    __lowerCAmelCase							:			List[str]				=int(input("Enter Power : ").strip())
    __lowerCAmelCase							:			Union[str, Any]				=int(input("Enter Modulo : ").strip())
  except ValueError:
    print("Invalid literal for integer")

  print(bin_exp_mod(BASE, POWER, MODULO))










'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowerCAmelCase							:			int				={
    "configuration_layoutlm": ["LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMConfig", "LayoutLMOnnxConfig"],
    "tokenization_layoutlm": ["LayoutLMTokenizer"],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase							:			Any				=["LayoutLMTokenizerFast"]

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

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase							:			str				=[
      "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

  __lowerCAmelCase							:			int				=_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



