

"""simple docstring"""





def 						__SCREAMING_SNAKE_CASE						(   A_				):
	lowerCAmelCase__			:		Optional[int]						       =			9

	while num > 0:
		if num % 10 != digit:
			return False
		num //= 1_00
		digit -= 1

	return True

def 						__SCREAMING_SNAKE_CASE						(   ):
	lowerCAmelCase__			:		List[Any]						       =			1_38_90_26_63

	while not is_square_form(num * num				):
		if num % 10 == 3:
			num -= 6  # (3 - 6) % 10 = 7
		else:
			num -= 4  # (7 - 4) % 10 = 3

	return num * 10


if __name__ == "__main__":
							print(F'''{solution() = }''')







"""simple docstring"""





from typing import TYPE_CHECKING

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


__UpperCamelCase						:   Union[str, Any]							   =	{
    '''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						:   Union[str, Any]							   =	['''LayoutLMTokenizerFast''']

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

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase						:   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

							__UpperCamelCase						:   int							   =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




