from __future__ import annotations

from collections.abc import MutableSequence



class  SCREAMING_SNAKE_CASE_ :
  '''simple docstring'''


  def __init__(				self    :					int      ,	SCREAMING_SNAKE_CASE__    :					int      ,	SCREAMING_SNAKE_CASE__    :					MutableSequence[float]     )    ->				None:
         if len(SCREAMING_SNAKE_CASE__     ) != degree + 1:
                raise ValueError(
                    'The number of coefficients should be equal to the degree + 1.'     )

         A						:     list[float]         =list(SCREAMING_SNAKE_CASE__     )
         A						:     Union[str, Any]         =degree







  def __add__(				self    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					Polynomial     )    ->				Polynomial:

         if self.degree > polynomial_a.degree:
                A						:     Any         =self.coefficients[:]
                for i in range(polynomial_a.degree + 1     ):
                       coefficients[i] += polynomial_a.coefficients[i]
                return Polynomial(self.degree      ,	SCREAMING_SNAKE_CASE__     )
         else:
                A						:     str         =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    :					Optional[int]      ,	SCREAMING_SNAKE_CASE__    :					Polynomial     )    ->				Polynomial:
         return self + polynomial_a * Polynomial(0      ,	[-1]     )







  def __neg__(				self    :					Optional[int]     )    ->				Polynomial:
         return Polynomial(self.degree      ,	[-c for c in self.coefficients]     )







  def __mul__(				self    :					Union[str, Any]      ,	SCREAMING_SNAKE_CASE__    :					Polynomial     )    ->				Polynomial:
         A						:     list[float]         =[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 		SCREAMING_SNAKE_CASE_		(				self    :					Any      ,	SCREAMING_SNAKE_CASE__    :					int | float     )    ->				int | float:
         A						:     int | float         =0
         for i in range(self.degree + 1     ):
                result += self.coefficients[i] * (substitution**i)
         return result







  def __str__(				self    :					Tuple     )    ->				str:
         A						:     Tuple         =''
         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    :					Union[str, Any]     )    ->				str:
         return self.__str__()







  def 		SCREAMING_SNAKE_CASE_		(				self    :					str     )    ->				Polynomial:
         A						:     list[float]         =[0] * self.degree
         for i in range(self.degree     ):
                A						:     List[Any]         =self.coefficients[i + 1] * (i + 1)
         return Polynomial(self.degree - 1      ,	SCREAMING_SNAKE_CASE__     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					str      ,	SCREAMING_SNAKE_CASE__    :					int | float = 0     )    ->				Polynomial:
         A						:     list[float]         =[0] * (self.degree + 2)
         A						:     List[Any]         =constant
         for i in range(self.degree + 1     ):
                A						:     Dict         =self.coefficients[i] / (i + 1)
         return Polynomial(self.degree + 1      ,	SCREAMING_SNAKE_CASE__     )







  def __eq__(				self    :					int      ,	SCREAMING_SNAKE_CASE__    :					object     )    ->				bool:
         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    :					str      ,	SCREAMING_SNAKE_CASE__    :					object     )    ->				bool:
         return not self.__eq__(SCREAMING_SNAKE_CASE__     )







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


_lowercase							:      int      							=logging.get_logger(__name__)

_lowercase							:      Dict      							={
    '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/config.json''',
    # See all XGLM models at https://huggingface.co/models?filter=xglm
}



class  SCREAMING_SNAKE_CASE_ (					lowerCAmelCase_			):
  '''simple docstring'''


  lowercase		:     Optional[int]            =				"xglm"
  lowercase		:     Any            =				["past_key_values"]

  lowercase		:     Dict            =				{
      "num_attention_heads": "attention_heads",
      "hidden_size": "d_model",
      "num_hidden_layers": "num_layers",
  }







  def __init__(				self    :					int      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=25_60_08      ,	SCREAMING_SNAKE_CASE__    :					Dict=20_48      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=10_24      ,	SCREAMING_SNAKE_CASE__    :					str=40_96      ,	SCREAMING_SNAKE_CASE__    :					Optional[int]=24      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]=16      ,	SCREAMING_SNAKE_CASE__    :					Any="gelu"      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]=0.1      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]=0.1      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=0.0      ,	SCREAMING_SNAKE_CASE__    :					Tuple=0.0      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=0.0_2      ,	SCREAMING_SNAKE_CASE__    :					int=True      ,	SCREAMING_SNAKE_CASE__    :					Dict=True      ,	SCREAMING_SNAKE_CASE__    :					Any=2      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=1      ,	SCREAMING_SNAKE_CASE__    :					str=0      ,	SCREAMING_SNAKE_CASE__    :					List[str]=2      ,	**SCREAMING_SNAKE_CASE__    :					Dict      ,	)    ->				int:
         A						:     str         =vocab_size
         A						:     Union[str, Any]         =max_position_embeddings
         A						:     Optional[Any]         =d_model
         A						:     Optional[int]         =ffn_dim
         A						:     int         =num_layers
         A						:     Any         =attention_heads
         A						:     Dict         =activation_function
         A						:     List[Any]         =dropout
         A						:     str         =attention_dropout
         A						:     List[Any]         =activation_dropout
         A						:     List[Any]         =layerdrop
         A						:     List[Any]         =init_std
         A						:     Union[str, Any]         =scale_embedding  # scale factor will be sqrt(d_model) if True
         A						:     List[str]         =use_cache

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






