





'''simple docstring'''


from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

a__			:					Optional[int]       						=						{
    'facebook/s2t-small-librispeech-asr': (
        'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json'
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech_to_text
}






class     lowerCAmelCase__ (				UpperCAmelCase_    ):

       '''simple docstring'''
       _lowerCamelCase								="speech_to_text"
       _lowerCamelCase								=["past_key_values"]
       _lowerCamelCase								={"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}

       def __init__( self					:				Dict       ,     a__					:				Any=10000       ,     a__					:				Union[str, Any]=12       ,     a__					:				List[str]=2048       ,     a__					:				List[Any]=4       ,     a__					:				Optional[Any]=6       ,     a__					:				Dict=2048       ,     a__					:				Optional[int]=4       ,     a__					:				Dict=0.0       ,     a__					:				List[str]=0.0       ,     a__					:				Dict=True       ,     a__					:				str=True       ,     a__					:				Tuple="relu"       ,     a__					:				str=256       ,     a__					:				Tuple=0.1       ,     a__					:				Tuple=0.0       ,     a__					:				List[str]=0.0       ,     a__					:				Dict=0.02       ,     a__					:				List[Any]=2       ,     a__					:				Union[str, Any]=True       ,     a__					:				Optional[Any]=1       ,     a__					:				Tuple=0       ,     a__					:				Optional[int]=2       ,     a__					:				List[str]=6000       ,     a__					:				List[str]=1024       ,     a__					:				Dict=2       ,     a__					:				int=(5, 5)       ,     a__					:				Union[str, Any]=1024       ,     a__					:				Optional[Any]=80       ,     a__					:				Tuple=1       ,     **a__					:				Optional[int]       ,     ):
              UpperCAmelCase  =						vocab_size
              UpperCAmelCase  =						d_model
              UpperCAmelCase  =						encoder_ffn_dim
              UpperCAmelCase  =						encoder_layers
              UpperCAmelCase  =						encoder_attention_heads
              UpperCAmelCase  =						decoder_ffn_dim
              UpperCAmelCase  =						decoder_layers
              UpperCAmelCase  =						decoder_attention_heads
              UpperCAmelCase  =						dropout
              UpperCAmelCase  =						attention_dropout
              UpperCAmelCase  =						activation_dropout
              UpperCAmelCase  =						activation_function
              UpperCAmelCase  =						init_std
              UpperCAmelCase  =						encoder_layerdrop
              UpperCAmelCase  =						decoder_layerdrop
              UpperCAmelCase  =						use_cache
              UpperCAmelCase  =						encoder_layers
              UpperCAmelCase  =						scale_embedding  # scale factor will be sqrt(d_model) if True
              UpperCAmelCase  =						max_source_positions
              UpperCAmelCase  =						max_target_positions
              UpperCAmelCase  =						num_conv_layers
              UpperCAmelCase  =						list(a__						)
              UpperCAmelCase  =						conv_channels
              UpperCAmelCase  =						input_feat_per_channel
              UpperCAmelCase  =						input_channels

              if len(self.conv_kernel_sizes						) != self.num_conv_layers:
                     raise ValueError(
                         '''Configuration for convolutional module is incorrect. '''
                         '''It is required that `len(config.conv_kernel_sizes)` == `config.num_conv_layers` '''
                         f"but is `len(config.conv_kernel_sizes) = {len(self.conv_kernel_sizes						)}`, "
                         f"`config.num_conv_layers = {self.num_conv_layers}`."						)

              super().__init__(
                  pad_token_id=a__       ,     bos_token_id=a__       ,     eos_token_id=a__       ,     is_encoder_decoder=a__       ,     decoder_start_token_id=a__       ,     **a__       ,     )








from __future__ import annotations

from collections.abc import MutableSequence



class       a_       :





	def __init__(							self      ,     SCREAMING_SNAKE_CASE      ,     SCREAMING_SNAKE_CASE      )  ->					None:




				"""simple docstring"""



				if len(SCREAMING_SNAKE_CASE      ) != degree + 1:
							raise ValueError(
							    'The number of coefficients should be equal to the degree + 1.'      )

				SCREAMING_SNAKE_CASE_								=						list(SCREAMING_SNAKE_CASE      )
				SCREAMING_SNAKE_CASE_								=						degree





	def __add__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					Polynomial:




				"""simple docstring"""



				if self.degree > polynomial_a.degree:
							SCREAMING_SNAKE_CASE_								=						self.coefficients[:]
							for i in range(polynomial_a.degree + 1      ):
										coefficients[i] += polynomial_a.coefficients[i]
							return Polynomial(self.degree      ,     SCREAMING_SNAKE_CASE      )
				else:
							SCREAMING_SNAKE_CASE_								=						polynomial_a.coefficients[:]
							for i in range(self.degree + 1      ):
										coefficients[i] += self.coefficients[i]
							return Polynomial(polynomial_a.degree      ,     SCREAMING_SNAKE_CASE      )





	def __sub__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					Polynomial:




				"""simple docstring"""



				return self + polynomial_a * Polynomial(0      ,     [-1]      )





	def __neg__(							self      )  ->					Polynomial:




				"""simple docstring"""



				return Polynomial(self.degree      ,     [-c for c in self.coefficients]      )





	def __mul__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					Polynomial:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						[0] * (self.degree + polynomial_a.degree + 1)
				for i in range(self.degree + 1      ):
							for j in range(polynomial_a.degree + 1      ):
										coefficients[i + j] += (
										    self.coefficients[i] * polynomial_a.coefficients[j]
										)

				return Polynomial(self.degree + polynomial_a.degree      ,     SCREAMING_SNAKE_CASE      )





	def 						A_(							self      ,     SCREAMING_SNAKE_CASE      )  ->					int | float:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						0
				for i in range(self.degree + 1      ):
							result += self.coefficients[i] * (substitution**i)
				return result





	def __str__(							self      )  ->					str:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						''
				for i in range(self.degree      ,     -1      ,     -1      ):
							if self.coefficients[i] == 0:
										continue
							elif self.coefficients[i] > 0:
										if polynomial:
													polynomial += " + "
							else:
										polynomial += " - "

							if i == 0:
										polynomial += str(abs(self.coefficients[i]      )      )
							elif i == 1:
										polynomial += str(abs(self.coefficients[i]      )      ) + "x"
							else:
										polynomial += str(abs(self.coefficients[i]      )      ) + "x^" + str(SCREAMING_SNAKE_CASE      )

				return polynomial





	def __repr__(							self      )  ->					str:




				"""simple docstring"""



				return self.__str__()





	def 						A_(							self      )  ->					Polynomial:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						[0] * self.degree
				for i in range(self.degree      ):
							SCREAMING_SNAKE_CASE_								=						self.coefficients[i + 1] * (i + 1)
				return Polynomial(self.degree - 1      ,     SCREAMING_SNAKE_CASE      )





	def 						A_(							self      ,     SCREAMING_SNAKE_CASE = 0      )  ->					Polynomial:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						[0] * (self.degree + 2)
				SCREAMING_SNAKE_CASE_								=						constant
				for i in range(self.degree + 1      ):
							SCREAMING_SNAKE_CASE_								=						self.coefficients[i] / (i + 1)
				return Polynomial(self.degree + 1      ,     SCREAMING_SNAKE_CASE      )





	def __eq__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					bool:




				"""simple docstring"""



				if not isinstance(SCREAMING_SNAKE_CASE      ,     SCREAMING_SNAKE_CASE      ):
							return False

				if self.degree != polynomial_a.degree:
							return False

				for i in range(self.degree + 1      ):
							if self.coefficients[i] != polynomial_a.coefficients[i]:
										return False

				return True





	def __ne__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					bool:




				"""simple docstring"""



				return not self.__eq__(SCREAMING_SNAKE_CASE      )
