


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__)





def        UpperCAmelCase_      (							__snake_case		)  ->    bool:







 """simple docstring"""


 if not isinstance(__snake_case  ,		__snake_case		):
  _lowercase							   =F"Input value of [number={number}] must be an integer"
  raise TypeError(__snake_case		)
 if number < 0 or number % 2 == 1:
  return False
 _lowercase							   =int(number**0.5		)
 return number == number_sqrt * (number_sqrt + 1)


if __name__ == "__main__":
  import doctest

  doctest.testmod()

