

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A__						=							{
    "configuration_squeezebert": [
        "SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SqueezeBertConfig",
        "SqueezeBertOnnxConfig",
    ],
    "tokenization_squeezebert": ["SqueezeBertTokenizer"],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__						=							["SqueezeBertTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__						=							[
						    "SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SqueezeBertForMaskedLM",
						    "SqueezeBertForMultipleChoice",
						    "SqueezeBertForQuestionAnswering",
						    "SqueezeBertForSequenceClassification",
						    "SqueezeBertForTokenClassification",
						    "SqueezeBertModel",
						    "SqueezeBertModule",
						    "SqueezeBertPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_squeezebert import (
						    SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SqueezeBertConfig,
						    SqueezeBertOnnxConfig,
						)
						from .tokenization_squeezebert import SqueezeBertTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_squeezebert import (
												    SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SqueezeBertForMaskedLM,
												    SqueezeBertForMultipleChoice,
												    SqueezeBertForQuestionAnswering,
												    SqueezeBertForSequenceClassification,
												    SqueezeBertForTokenClassification,
												    SqueezeBertModel,
												    SqueezeBertModule,
												    SqueezeBertPreTrainedModel,
												)

else:
						import sys

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







from math import factorial, radians




def 					_lowercase     (				a_				:					float					,a_				:					int = 1_8					,a_				:					int = 1_0				)				->	float:




					'''simple docstring'''







					__magic_name__							=    angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)

					# Converting from degrees to radians
					__magic_name__							=    radians(a_				)

					__magic_name__							=    angle_in_radians
					__magic_name__							=    3
					__magic_name__							=    -1

					for _ in range(a_				):
										result += (b * (angle_in_radians**a)) / factorial(a_				)

										__magic_name__							=    -b  # One positive term and the next will be negative and so on...
										a += 2  # Increased by 2 for every term.

					return round(a_					,a_				)


if __name__ == "__main__":
						__import__("doctest").testmod()




