


def 	__lowercase		(  _UpperCamelCase,			_UpperCamelCase   )			->List[Any]:







      """simple docstring"""

      if number < 0 or shift_amount < 0:
            raise ValueError('''both inputs must be positive integers'''   )

      lowercase	:      Optional[Any]          =						str(bin(_UpperCamelCase   )   )
      binary_number += "0" * shift_amount
      return binary_number




def 	__lowercase		(  _UpperCamelCase,			_UpperCamelCase   )			->str:







      """simple docstring"""

      if number < 0 or shift_amount < 0:
            raise ValueError('''both inputs must be positive integers'''   )

      lowercase	:      List[str]          =						str(bin(_UpperCamelCase   )   )[2:]
      if shift_amount >= len(_UpperCamelCase   ):
            return "0b0"
      lowercase	:      Tuple          =						binary_number[: len(_UpperCamelCase   ) - shift_amount]
      return "0b" + shifted_binary_number




def 	__lowercase		(  _UpperCamelCase,			_UpperCamelCase   )			->Union[str, Any]:







      """simple docstring"""

      if number >= 0:  # Get binary representation of positive number
            lowercase	:      Union[str, Any]          =						'''0''' + str(bin(_UpperCamelCase   )   ).strip('''-'''   )[2:]
      else:  # Get binary (2's complement) representation of negative number
            lowercase	:      int          =						len(bin(_UpperCamelCase   )[3:]   )  # Find 2's complement of number
            lowercase	:      Optional[Any]          =						bin(abs(_UpperCamelCase   ) - (1 << binary_number_length)   )[3:]
            lowercase	:      Dict          =						(
                '''1''' + '''0''' * (binary_number_length - len(_UpperCamelCase   )) + binary_number
            )

      if shift_amount >= len(_UpperCamelCase   ):
            return "0b" + binary_number[0] * len(_UpperCamelCase   )
      return (
          "0b"
          + binary_number[0] * shift_amount
          + binary_number[: len(_UpperCamelCase   ) - shift_amount]
      )


if __name__ == "__main__":
  import doctest

  doctest.testmod()


"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase__  :  str						     =	{
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						pass

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__  :  List[str]						     =	[
						    'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'RoCBertForCausalLM',
						    'RoCBertForMaskedLM',
						    'RoCBertForMultipleChoice',
						    'RoCBertForPreTraining',
						    'RoCBertForQuestionAnswering',
						    'RoCBertForSequenceClassification',
						    'RoCBertForTokenClassification',
						    'RoCBertLayer',
						    'RoCBertModel',
						    'RoCBertPreTrainedModel',
						    'load_tf_weights_in_roc_bert',
						]

if TYPE_CHECKING:
						from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
						from .tokenization_roc_bert import RoCBertTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												raise OptionalDependencyNotAvailable()

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_roc_bert import (
												    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RoCBertForCausalLM,
												    RoCBertForMaskedLM,
												    RoCBertForMultipleChoice,
												    RoCBertForPreTraining,
												    RoCBertForQuestionAnswering,
												    RoCBertForSequenceClassification,
												    RoCBertForTokenClassification,
												    RoCBertLayer,
												    RoCBertModel,
												    RoCBertPreTrainedModel,
												    load_tf_weights_in_roc_bert,
												)


else:
						import sys

						lowerCAmelCase__  :  str						     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



