code: 
  
  
  
  
  """simple docstring"""
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
  
  
  __A 		=			{
      "configuration_flaubert": ["FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "FlaubertConfig", "FlaubertOnnxConfig"],
      "tokenization_flaubert": ["FlaubertTokenizer"],
  }
  
  try:
  							if not is_torch_available():
  														raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  							pass
  else:
  							__A 		=			[
  							    "FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
  							    "FlaubertForMultipleChoice",
  							    "FlaubertForQuestionAnswering",
  							    "FlaubertForQuestionAnsweringSimple",
  							    "FlaubertForSequenceClassification",
  							    "FlaubertForTokenClassification",
  							    "FlaubertModel",
  							    "FlaubertWithLMHeadModel",
  							    "FlaubertPreTrainedModel",
  							]
  
  try:
  							if not is_tf_available():
  														raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  							pass
  else:
  							__A 		=			[
  							    "TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
  							    "TFFlaubertForMultipleChoice",
  							    "TFFlaubertForQuestionAnsweringSimple",
  							    "TFFlaubertForSequenceClassification",
  							    "TFFlaubertForTokenClassification",
  							    "TFFlaubertModel",
  							    "TFFlaubertPreTrainedModel",
  							    "TFFlaubertWithLMHeadModel",
  							]
  
  
  if TYPE_CHECKING:
  							from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertOnnxConfig
  							from .tokenization_flaubert import FlaubertTokenizer
  
  							try:
  														if not is_torch_available():
  																					raise OptionalDependencyNotAvailable()
  							except OptionalDependencyNotAvailable:
  														pass
  							else:
  														from .modeling_flaubert import (
  														    FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
  														    FlaubertForMultipleChoice,
  														    FlaubertForQuestionAnswering,
  														    FlaubertForQuestionAnsweringSimple,
  														    FlaubertForSequenceClassification,
  														    FlaubertForTokenClassification,
  														    FlaubertModel,
  														    FlaubertPreTrainedModel,
  														    FlaubertWithLMHeadModel,
  														)
  
  							try:
  														if not is_tf_available():
  																					raise OptionalDependencyNotAvailable()
  							except OptionalDependencyNotAvailable:
  														pass
  							else:
  														from .modeling_tf_flaubert import (
  														    TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
  														    TFFlaubertForMultipleChoice,
  														    TFFlaubertForQuestionAnsweringSimple,
  														    TFFlaubertForSequenceClassification,
  														    TFFlaubertForTokenClassification,
  														    TFFlaubertModel,
  														    TFFlaubertPreTrainedModel,
  														    TFFlaubertWithLMHeadModel,
  														)
  
  else:
  							import sys
  
  							__A 		=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  def   UpperCamelCase__     (		lowercase__  :     int   ):
  		if not isinstance(lowercase__       ,     lowercase__   ):
  				snake_case		:						Optional[Any]								=				F'''Input value of [number={number}] must be an integer'''
  				raise TypeError(lowercase__   )
  		if number < 0 or number % 2 == 1:
  				return False
  		snake_case		:						str								=				int(number**0.5   )
  		return number == number_sqrt * (number_sqrt + 1)
  
  
  if __name__ == "__main__":
  							import doctest
  
  							doctest.testmod()
  
  