




"""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__)







"""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()

