


'''simple docstring'''

from math import factorial





class   snake_case					:





  """simple docstring"""




  def __init__(					self    ,						UpperCamelCase    ,						UpperCamelCase  ):







   """simple docstring"""
   lowerCamelCase_  				=						real
   if isinstance(UpperCamelCase    ,						UpperCamelCase  ):
    lowerCamelCase_  				=						[1] * rank
   else:
    lowerCamelCase_  				=						rank






  def __repr__(					self  ):







   """simple docstring"""
   return (
       f'''{self.real}+'''
       f'''{"+".join(str(UpperCamelCase  )+"E"+str(n+1  )for n,dual in enumerate(self.duals  )  )}'''
   )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.duals.copy()
   while cur[-1] == 0:
    cur.pop(-1  )
   return Dual(self.real    ,						UpperCamelCase  )






  def __add__(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   if not isinstance(UpperCamelCase    ,						UpperCamelCase  ):
    return Dual(self.real + other    ,						self.duals  )
   lowerCamelCase_  				=						self.duals.copy()
   lowerCamelCase_  				=						other.duals.copy()
   if len(UpperCamelCase  ) > len(UpperCamelCase  ):
    o_dual.extend([1] * (len(UpperCamelCase  ) - len(UpperCamelCase  ))  )
   elif len(UpperCamelCase  ) < len(UpperCamelCase  ):
    s_dual.extend([1] * (len(UpperCamelCase  ) - len(UpperCamelCase  ))  )
   lowerCamelCase_  				=						[]
   for i in range(len(UpperCamelCase  )  ):
    new_duals.append(s_dual[i] + o_dual[i]  )
   return Dual(self.real + other.real    ,						UpperCamelCase  )

  _lowerCamelCase						=						__add__






  def __sub__(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   return self + other * -1






  def __mul__(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   if not isinstance(UpperCamelCase    ,						UpperCamelCase  ):
    lowerCamelCase_  				=						[]
    for i in self.duals:
     new_duals.append(i * other  )
    return Dual(self.real * other    ,						UpperCamelCase  )
   lowerCamelCase_  				=						[0] * (len(self.duals  ) + len(other.duals  ) + 1)
   for i, item in enumerate(self.duals  ):
    for j, jtem in enumerate(other.duals  ):
     new_duals[i + j + 1] += item * jtem
   for k in range(len(self.duals  )  ):
    new_duals[k] += self.duals[k] * other.real
   for index in range(len(other.duals  )  ):
    new_duals[index] += other.duals[index] * self.real
   return Dual(self.real * other.real    ,						UpperCamelCase  )

  _lowerCamelCase						=						__mul__






  def __truediv__(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   if not isinstance(UpperCamelCase    ,						UpperCamelCase  ):
    lowerCamelCase_  				=						[]
    for i in self.duals:
     new_duals.append(i / other  )
    return Dual(self.real / other    ,						UpperCamelCase  )
   raise ValueError






  def __floordiv__(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   if not isinstance(UpperCamelCase    ,						UpperCamelCase  ):
    lowerCamelCase_  				=						[]
    for i in self.duals:
     new_duals.append(i // other  )
    return Dual(self.real // other    ,						UpperCamelCase  )
   raise ValueError







  def __pow__(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   if n < 0 or isinstance(UpperCamelCase    ,						UpperCamelCase  ):
    raise ValueError("power must be a positive integer"  )
   if n == 0:
    return 1
   if n == 1:
    return self
   lowerCamelCase_  				=						self
   for _ in range(n - 1  ):
    x *= self
   return x





def __snake_case      (   UpperCAmelCase_		:		Optional[int]      ,       UpperCAmelCase_		:		Tuple      ,       UpperCAmelCase_		:		Union[str, Any]	):
 if not callable(UpperCAmelCase_	):
  raise ValueError("differentiate() requires a function as input for func"	)
 if not isinstance(UpperCAmelCase_      ,       (float, int)	):
  raise ValueError("differentiate() requires a float as input for position"	)
 if not isinstance(UpperCAmelCase_      ,       UpperCAmelCase_	):
  raise ValueError("differentiate() requires an int as input for order"	)
 lowerCamelCase_  				=						Dual(UpperCAmelCase_      ,       1	)
 lowerCamelCase_  				=						func(UpperCAmelCase_	)
 if order == 0:
  return result.real
 return result.duals[order - 1] * factorial(UpperCAmelCase_	)


if __name__ == "__main__":
     import doctest

     doctest.testmod()





     def __snake_case      (   UpperCAmelCase_		:		Optional[Any]	):
      return y**2 * y**4







     print(differentiate(f, 9, 2))







'''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

a_						:       Optional[int]      			=				logging.get_logger(__name__)

a_						:       Optional[int]      			=				{
    """openai/whisper-base""": """https://huggingface.co/openai/whisper-base/resolve/main/config.json""",
}

# fmt: off
a_						:       List[str]      			=				[
    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, 1058, 1220, 1267, 1279, 1303, 1343, 1377,
    1391, 1635, 1782, 1875, 2162, 2361, 2488, 3467, 4008, 4211,
    4600, 4808, 5299, 5855, 6329, 7203, 9609, 9959, 10563, 10786,
    11420, 11709, 11907, 13163, 13697, 13700, 14808, 15306, 16410, 16791,
    17992, 19203, 19510, 20724, 22305, 22935, 27007, 30109, 30420, 33409,
    34949, 40283, 40493, 40549, 47282, 49146, 50257, 50359, 50360, 50361
]
a_						:       Tuple      			=				[
    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, 1350, 1853, 1982, 2460, 2627,
    3246, 3253, 3268, 3536, 3846, 3961, 4183, 4667, 6585, 6647,
    7273, 9061, 9383, 10428, 10929, 11938, 12033, 12331, 12562, 13793,
    14157, 14635, 15265, 15618, 16553, 16604, 18362, 18956, 20075, 21675,
    22520, 26130, 26161, 26435, 28279, 29464, 31650, 32302, 32470, 36865,
    42863, 47425, 49870, 50254, 50258, 50360, 50361, 50362
]





class   snake_case					(					lowercase    ):





  """simple docstring"""




  _lowerCamelCase						=						"whisper"
  _lowerCamelCase						=						["past_key_values"]
  _lowerCamelCase						=						{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}






  def __init__(					self    ,						UpperCamelCase=5_1865    ,						UpperCamelCase=80    ,						UpperCamelCase=6    ,						UpperCamelCase=4    ,						UpperCamelCase=6    ,						UpperCamelCase=4    ,						UpperCamelCase=1536    ,						UpperCamelCase=1536    ,						UpperCamelCase=0.0    ,						UpperCamelCase=0.0    ,						UpperCamelCase=5_0257    ,						UpperCamelCase=True    ,						UpperCamelCase=True    ,						UpperCamelCase="gelu"    ,						UpperCamelCase=256    ,						UpperCamelCase=0.0    ,						UpperCamelCase=0.0    ,						UpperCamelCase=0.0    ,						UpperCamelCase=0.02    ,						UpperCamelCase=False    ,						UpperCamelCase=1500    ,						UpperCamelCase=448    ,						UpperCamelCase=5_0256    ,						UpperCamelCase=5_0256    ,						UpperCamelCase=5_0256    ,						UpperCamelCase=None    ,						UpperCamelCase=[220, 5_0256]    ,						UpperCamelCase=False    ,						UpperCamelCase=256    ,						UpperCamelCase=False    ,						UpperCamelCase=0.05    ,						UpperCamelCase=10    ,						UpperCamelCase=2    ,						UpperCamelCase=0.0    ,						UpperCamelCase=10    ,						UpperCamelCase=0    ,						UpperCamelCase=7    ,						**UpperCamelCase    ,						):







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

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

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

   lowerCamelCase_  				=						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   snake_case					(					lowercase    ):





  """simple docstring"""




  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						OrderedDict(
       [
           ("input_features", {0: "batch", 1: "feature_size", 2: "encoder_sequence"}),
       ]  )
   if self.use_past:
    lowerCamelCase_  				=						{0: "batch"}
   else:
    lowerCamelCase_  				=						{0: "batch", 1: "decoder_sequence"}

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

   return common_inputs






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase = -1    ,						UpperCamelCase = -1    ,						UpperCamelCase = False    ,						UpperCamelCase = None    ,						UpperCamelCase = 2_2050    ,						UpperCamelCase = 5.0    ,						UpperCamelCase = 220    ,						):







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

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

   lowerCamelCase_  				=						encoder_inputs.pop("input_features"  )
   lowerCamelCase_  				=						decoder_inputs.pop("decoder_input_ids"  )

   if "past_key_values" in decoder_inputs:
    lowerCamelCase_  				=						decoder_inputs.pop("past_key_values"  )

   return dummy_inputs







  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   return 1e-3



