



"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case_         = {"""configuration_qdqbert""": ["""QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """QDQBertConfig"""]}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case_         = [
				    """QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """QDQBertForMaskedLM""",
				    """QDQBertForMultipleChoice""",
				    """QDQBertForNextSentencePrediction""",
				    """QDQBertForQuestionAnswering""",
				    """QDQBertForSequenceClassification""",
				    """QDQBertForTokenClassification""",
				    """QDQBertLayer""",
				    """QDQBertLMHeadModel""",
				    """QDQBertModel""",
				    """QDQBertPreTrainedModel""",
				    """load_tf_weights_in_qdqbert""",
				]


if TYPE_CHECKING:
				from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_qdqbert import (
								    QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    QDQBertForMaskedLM,
								    QDQBertForMultipleChoice,
								    QDQBertForNextSentencePrediction,
								    QDQBertForQuestionAnswering,
								    QDQBertForSequenceClassification,
								    QDQBertForTokenClassification,
								    QDQBertLayer,
								    QDQBertLMHeadModel,
								    QDQBertModel,
								    QDQBertPreTrainedModel,
								    load_tf_weights_in_qdqbert,
								)


else:
				import sys

				snake_case_         = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










"""simple docstring"""


from math import exp

def 				_lowerCAmelCase   (     lowercase_		):
						return 8 * x - 2 * exp(-x		)

def 				_lowerCAmelCase   (     lowercase_	,			lowercase_	,			lowercase_		):
						UpperCAmelCase    =				lower_bound
						UpperCAmelCase    =				upper_bound
						for _ in range(0	,			lowercase_		):
												UpperCAmelCase   ,					UpperCAmelCase    =				xa, xa - (f(lowercase_		) * (xa - xa)) / (f(lowercase_		) - f(lowercase_		))
						return xa


if __name__ == "__main__":
				print(f'''Example: {secant_method(1, 3, 2)}''')





