"""simple docstring"""
from ...processing_utils import ProcessorMixin



class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""
				_lowerCAmelCase     :    Any			  =						"""SpeechT5FeatureExtractor"""
				_lowerCAmelCase     :    str			  =						"""SpeechT5Tokenizer"""

				def __init__(				self		,    lowerCAmelCase		,    lowerCAmelCase    ):






										"""simple docstring"""

										super().__init__(lowerCAmelCase		,    lowerCAmelCase    )

				def __call__(				self		,    *lowerCAmelCase		,    **lowerCAmelCase    ):






										"""simple docstring"""

										snake_case								=			kwargs.pop('audio'		,    lowerCAmelCase    )
										snake_case								=			kwargs.pop('text'		,    lowerCAmelCase    )
										snake_case								=			kwargs.pop('text_target'		,    lowerCAmelCase    )
										snake_case								=			kwargs.pop('audio_target'		,    lowerCAmelCase    )
										snake_case								=			kwargs.pop('sampling_rate'		,    lowerCAmelCase    )

										if audio is not None and text is not None:
																raise ValueError(
																    'Cannot process both `audio` and `text` inputs. Did you mean `audio_target` or `text_target`?'    )
										if audio_target is not None and text_target is not None:
																raise ValueError(
																    'Cannot process both `audio_target` and `text_target` inputs. Did you mean `audio` or `text`?'    )
										if audio is None and audio_target is None and text is None and text_target is None:
																raise ValueError(
																    'You need to specify either an `audio`, `audio_target`, `text`, or `text_target` input to process.'    )

										if audio is not None:
																snake_case								=			self.feature_extractor(lowerCAmelCase		,    *lowerCAmelCase		,    sampling_rate=lowerCAmelCase		,    **lowerCAmelCase    )
										elif text is not None:
																snake_case								=			self.tokenizer(lowerCAmelCase		,    **lowerCAmelCase    )
										else:
																snake_case								=			None

										if audio_target is not None:
																snake_case								=			self.feature_extractor(audio_target=lowerCAmelCase		,    *lowerCAmelCase		,    sampling_rate=lowerCAmelCase		,    **lowerCAmelCase    )
																snake_case								=			targets['input_values']
										elif text_target is not None:
																snake_case								=			self.tokenizer(lowerCAmelCase		,    **lowerCAmelCase    )
																snake_case								=			targets['input_ids']
										else:
																snake_case								=			None

										if inputs is None:
																return targets

										if targets is not None:
																snake_case								=			labels

																snake_case								=			targets.get('attention_mask'    )
																if decoder_attention_mask is not None:
																						snake_case								=			decoder_attention_mask

										return inputs

				def 		snake_case (				self		,    *lowerCAmelCase		,    **lowerCAmelCase    ):






										"""simple docstring"""

										snake_case								=			kwargs.pop('input_values'		,    lowerCAmelCase    )
										snake_case								=			kwargs.pop('input_ids'		,    lowerCAmelCase    )
										snake_case								=			kwargs.pop('labels'		,    lowerCAmelCase    )

										if input_values is not None and input_ids is not None:
																raise ValueError('Cannot process both `input_values` and `input_ids` inputs.'    )
										if input_values is None and input_ids is None and labels is None:
																raise ValueError(
																    'You need to specify either an `input_values`, `input_ids`, or `labels` input to be padded.'    )

										if input_values is not None:
																snake_case								=			self.feature_extractor.pad(lowerCAmelCase		,    *lowerCAmelCase		,    **lowerCAmelCase    )
										elif input_ids is not None:
																snake_case								=			self.tokenizer.pad(lowerCAmelCase		,    **lowerCAmelCase    )
										else:
																snake_case								=			None

										if labels is not None:
																if "input_ids" in labels or (isinstance(lowerCAmelCase		,    lowerCAmelCase    ) and "input_ids" in labels[0]):
																						snake_case								=			self.tokenizer.pad(lowerCAmelCase		,    **lowerCAmelCase    )
																						snake_case								=			targets['input_ids']
																else:
																						snake_case								=			self.feature_extractor.feature_size
																						snake_case								=			self.feature_extractor.num_mel_bins
																						snake_case								=			self.feature_extractor.pad(lowerCAmelCase		,    *lowerCAmelCase		,    **lowerCAmelCase    )
																						snake_case								=			feature_size_hack
																						snake_case								=			targets['input_values']
										else:
																snake_case								=			None

										if inputs is None:
																return targets

										if targets is not None:
																snake_case								=			labels

																snake_case								=			targets.get('attention_mask'    )
																if decoder_attention_mask is not None:
																						snake_case								=			decoder_attention_mask

										return inputs

				def 		snake_case (				self		,    *lowerCAmelCase		,    **lowerCAmelCase    ):






										"""simple docstring"""

										return self.tokenizer.batch_decode(*lowerCAmelCase		,    **lowerCAmelCase    )

				def 		snake_case (				self		,    *lowerCAmelCase		,    **lowerCAmelCase    ):






										"""simple docstring"""

										return self.tokenizer.decode(*lowerCAmelCase		,    **lowerCAmelCase    )



"""simple docstring"""
import math





def    lowerCAmelCase__    (			_UpperCamelCase       :				float ,			_UpperCamelCase       :				float					)					->				float:





						"""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_6_0:
												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(_UpperCamelCase					)					) ** 2)


if __name__ == "__main__":
					import doctest

					doctest.testmod(name="malus_law")


