


import math
def      _a					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		if initial_intensity < 0:
				raise ValueError('''The value of intensity cannot be negative'''	)
				# handling of negative values of initial intensity
		if angle < 0 or angle > 3_60:
				raise ValueError('''In Malus Law, the angle is in the range 0-360 degrees'''	)
				# handling of values out of allowed range
		return initial_intensity * (math.cos(math.radians(SCREAMING_SNAKE_CASE	)	) ** 2)


if __name__ == "__main__":
			import doctest

			doctest.testmod(name='malus_law')








'''simple docstring'''
import os
import sys

_SCREAMING_SNAKE_CASE			=						os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


_SCREAMING_SNAKE_CASE			=						[
    "torch",
    "numpy",
    "tokenizers",
    "filelock",
    "requests",
    "tqdm",
    "regex",
    "sentencepiece",
    "sacremoses",
    "importlib_metadata",
    "huggingface_hub",
]





@add_start_docstrings(AutoConfig.__doc__     )
def 			lowerCamelCase(							*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )		->		int:
			return AutoConfig.from_pretrained(*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )





@add_start_docstrings(AutoTokenizer.__doc__     )
def 			lowerCamelCase(							*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )		->		List[str]:
			return AutoTokenizer.from_pretrained(*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )





@add_start_docstrings(AutoModel.__doc__     )
def 			lowerCamelCase(							*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )		->		Union[str, Any]:
			return AutoModel.from_pretrained(*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )





@add_start_docstrings(AutoModelForCausalLM.__doc__     )
def 			lowerCamelCase(							*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )		->		Optional[int]:
			return AutoModelForCausalLM.from_pretrained(*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )





@add_start_docstrings(AutoModelForMaskedLM.__doc__     )
def 			lowerCamelCase(							*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )		->		Dict:
			return AutoModelForMaskedLM.from_pretrained(*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )





@add_start_docstrings(AutoModelForSequenceClassification.__doc__     )
def 			lowerCamelCase(							*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )		->		Union[str, Any]:
			return AutoModelForSequenceClassification.from_pretrained(*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )






@add_start_docstrings(AutoModelForQuestionAnswering.__doc__     )
def 			lowerCamelCase(							*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )		->		str:
			return AutoModelForQuestionAnswering.from_pretrained(*SCREAMING_SNAKE_CASE_       ,**SCREAMING_SNAKE_CASE_     )




