


"""simple docstring"""
from math import factorial, radians

def 				_snake_case      (   __snake_case							:      int						, __snake_case							:      Any = 18						, __snake_case							:      Union[str, Any] = 10   ):




   """simple docstring"""







   _lowerCamelCase	:					Optional[int]   =		angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)

   # Converting from degrees to radians
   _lowerCamelCase	:					Optional[Any]   =		radians(__snake_case   )

   _lowerCamelCase	:					Any   =		angle_in_radians
   _lowerCamelCase	:					Any   =		3
   _lowerCamelCase	:					Dict   =		-1

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

      _lowerCamelCase	:					List[str]   =		-b  # One positive term and the next will be negative and so on...
      a += 2  # Increased by 2 for every term.

   return round(__snake_case						, __snake_case   )


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





'''simple docstring'''

from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging


if TYPE_CHECKING:
 from ...feature_extraction_utils import FeatureExtractionMixin
 from ...tokenization_utils_base import PreTrainedTokenizerBase
 from ...utils import TensorType

lowerCamelCase				:  Dict    		=      logging.get_logger(__name__)

lowerCamelCase				:  List[Any]    		=      {
    'openai/whisper-base': 'https://huggingface.co/openai/whisper-base/resolve/main/config.json',
}

# fmt: off
lowerCamelCase				:  Dict    		=      [
    1, 2, 7, 8, 9, 10, 14, 25,
    26, 27, 28, 29, 31, 58, 59, 60, 61, 62,
    63, 90, 91, 92, 93, 357, 366, 438, 532, 685,
    705, 796, 930, 1_058, 1_220, 1_267, 1_279, 1_303, 1_343, 1_377,
    1_391, 1_635, 1_782, 1_875, 2_162, 2_361, 2_488, 3_467, 4_008, 4_211,
    4_600, 4_808, 5_299, 5_855, 6_329, 7_203, 9_609, 9_959, 10_563, 10_786,
    11_420, 11_709, 11_907, 13_163, 13_697, 13_700, 14_808, 15_306, 16_410, 16_791,
    17_992, 19_203, 19_510, 20_724, 22_305, 22_935, 27_007, 30_109, 30_420, 33_409,
    34_949, 40_283, 40_493, 40_549, 47_282, 49_146, 50_257, 50_359, 50_360, 50_361
]
lowerCamelCase				:  str    		=      [
    1, 2, 7, 8, 9, 10, 14, 25,
    26, 27, 28, 29, 31, 58, 59, 60, 61, 62,
    63, 90, 91, 92, 93, 359, 503, 522, 542, 873,
    893, 902, 918, 922, 931, 1_350, 1_853, 1_982, 2_460, 2_627,
    3_246, 3_253, 3_268, 3_536, 3_846, 3_961, 4_183, 4_667, 6_585, 6_647,
    7_273, 9_061, 9_383, 10_428, 10_929, 11_938, 12_033, 12_331, 12_562, 13_793,
    14_157, 14_635, 15_265, 15_618, 16_553, 16_604, 18_362, 18_956, 20_075, 21_675,
    22_520, 26_130, 26_161, 26_435, 28_279, 29_464, 31_650, 32_302, 32_470, 36_865,
    42_863, 47_425, 49_870, 50_254, 50_258, 50_360, 50_361, 50_362
]
class     __lowerCAmelCase		(lowercase_	):





      '''simple docstring'''






      lowerCAmelCase__   :	List[str]       =				"""whisper"""
      lowerCAmelCase__   :	Dict       =				["""past_key_values"""]
      lowerCAmelCase__   :	Optional[int]       =				{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}



      def __init__(self       :       int  ,		UpperCamelCase       :       Optional[int]=51865  ,		UpperCamelCase       :       Any=80  ,		UpperCamelCase       :       Dict=6  ,		UpperCamelCase       :       str=4  ,		UpperCamelCase       :       Optional[Any]=6  ,		UpperCamelCase       :       List[Any]=4  ,		UpperCamelCase       :       Tuple=1536  ,		UpperCamelCase       :       Dict=1536  ,		UpperCamelCase       :       Any=0.0  ,		UpperCamelCase       :       Any=0.0  ,		UpperCamelCase       :       int=50257  ,		UpperCamelCase       :       List[str]=True  ,		UpperCamelCase       :       List[Any]=True  ,		UpperCamelCase       :       List[str]="gelu"  ,		UpperCamelCase       :       Dict=256  ,		UpperCamelCase       :       Optional[int]=0.0  ,		UpperCamelCase       :       str=0.0  ,		UpperCamelCase       :       str=0.0  ,		UpperCamelCase       :       Dict=0.02  ,		UpperCamelCase       :       List[Any]=False  ,		UpperCamelCase       :       int=1500  ,		UpperCamelCase       :       List[str]=448  ,		UpperCamelCase       :       int=50256  ,		UpperCamelCase       :       Optional[int]=50256  ,		UpperCamelCase       :       Optional[Any]=50256  ,		UpperCamelCase       :       Any=None  ,		UpperCamelCase       :       Tuple=[220, 50256]  ,		UpperCamelCase       :       Optional[Any]=False  ,		UpperCamelCase       :       int=256  ,		UpperCamelCase       :       Optional[int]=False  ,		UpperCamelCase       :       int=0.05  ,		UpperCamelCase       :       List[Any]=10  ,		UpperCamelCase       :       Optional[int]=2  ,		UpperCamelCase       :       Optional[int]=0.0  ,		UpperCamelCase       :       Dict=10  ,		UpperCamelCase       :       Union[str, Any]=0  ,		UpperCamelCase       :       Union[str, Any]=7  ,		**UpperCamelCase       :       Union[str, Any]  ,		):

             '''simple docstring'''







             lowercase__      =					vocab_size
             lowercase__      =					num_mel_bins
             lowercase__      =					d_model
             lowercase__      =					encoder_layers
             lowercase__      =					encoder_attention_heads
             lowercase__      =					decoder_layers
             lowercase__      =					decoder_attention_heads
             lowercase__      =					decoder_ffn_dim
             lowercase__      =					encoder_ffn_dim
             lowercase__      =					dropout
             lowercase__      =					attention_dropout
             lowercase__      =					activation_dropout
             lowercase__      =					activation_function
             lowercase__      =					init_std
             lowercase__      =					encoder_layerdrop
             lowercase__      =					decoder_layerdrop
             lowercase__      =					use_cache
             lowercase__      =					encoder_layers
             lowercase__      =					scale_embedding  # scale factor will be sqrt(d_model) if True
             lowercase__      =					max_source_positions
             lowercase__      =					max_target_positions

             # Audio Classification-specific parameters. Feel free to ignore for other classes.
             lowercase__      =					classifier_proj_size
             lowercase__      =					use_weighted_layer_sum

             # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
             lowercase__      =					apply_spec_augment
             lowercase__      =					mask_time_prob
             lowercase__      =					mask_time_length
             lowercase__      =					mask_time_min_masks
             lowercase__      =					mask_feature_prob
             lowercase__      =					mask_feature_length
             lowercase__      =					mask_feature_min_masks

             lowercase__      =					median_filter_width

             super().__init__(
                 pad_token_id=UpperCamelCase  ,		bos_token_id=UpperCamelCase  ,		eos_token_id=UpperCamelCase  ,		is_encoder_decoder=UpperCamelCase  ,		decoder_start_token_id=UpperCamelCase  ,		suppress_tokens=UpperCamelCase  ,		begin_suppress_tokens=UpperCamelCase  ,		**UpperCamelCase  ,		)






class     __lowerCAmelCase		(lowercase_	):





      '''simple docstring'''






      @property
      def  UpperCamelCase__						(self       :       str					):

             '''simple docstring'''







             lowercase__      =					OrderedDict(
                 [
                     ('''input_features''', {0: '''batch''', 1: '''feature_size''', 2: '''encoder_sequence'''}),
                 ]					)
             if self.use_past:
                    lowercase__      =					{0: '''batch'''}
             else:
                    lowercase__      =					{0: '''batch''', 1: '''decoder_sequence'''}

             if self.use_past:
                    self.fill_with_past_key_values_(UpperCamelCase  ,		direction='''inputs'''					)

             return common_inputs



      def  UpperCamelCase__						(self       :       Union[str, Any]  ,		UpperCamelCase       :       Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]  ,		UpperCamelCase       :       int = -1  ,		UpperCamelCase       :       int = -1  ,		UpperCamelCase       :       bool = False  ,		UpperCamelCase       :       Optional["TensorType"] = None  ,		UpperCamelCase       :       int = 22050  ,		UpperCamelCase       :       float = 5.0  ,		UpperCamelCase       :       int = 220  ,		):

             '''simple docstring'''







             lowercase__      =					OrderedDict()
             lowercase__      =					OnnxConfig.generate_dummy_inputs(
                 self  ,		preprocessor=preprocessor.feature_extractor  ,		batch_size=UpperCamelCase  ,		framework=UpperCamelCase  ,		sampling_rate=UpperCamelCase  ,		time_duration=UpperCamelCase  ,		frequency=UpperCamelCase  ,		)
             lowercase__      =					encoder_inputs['''input_features'''].shape[2]
             lowercase__      =					encoder_sequence_length // 2 if self.use_past else seq_length

             lowercase__      =					super().generate_dummy_inputs(
                 preprocessor.tokenizer  ,		UpperCamelCase  ,		UpperCamelCase  ,		UpperCamelCase  ,		UpperCamelCase					)

             lowercase__      =					encoder_inputs.pop('''input_features'''					)
             lowercase__      =					decoder_inputs.pop('''decoder_input_ids'''					)

             if "past_key_values" in decoder_inputs:
                    lowercase__      =					decoder_inputs.pop('''past_key_values'''					)

             return dummy_inputs






      @property
      def  UpperCamelCase__						(self       :       Union[str, Any]					):

             '''simple docstring'''







             return 1E-3




