





import math
from typing import Optional

import numpy as np

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


UpperCAmelCase     :     List[Any]							=	logging.get_logger(__name__)

UpperCAmelCase     :     Optional[Any]							=	{
    """facebook/encodec_24khz""": """https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json""",
    """facebook/encodec_48khz""": """https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json""",
}







class     __lowerCAmelCase	(   UpperCamelCase__):
      _lowercase    : Any            =      """encodec"""







      def __init__(   self		,				lowerCAmelCase__=[1.5, 3.0, 6.0, 12.0, 24.0]		,				lowerCAmelCase__=2_4_0_0_0		,				lowerCAmelCase__=1		,				lowerCAmelCase__=False		,				lowerCAmelCase__=None		,				lowerCAmelCase__=None		,				lowerCAmelCase__=1_2_8		,				lowerCAmelCase__=3_2		,				lowerCAmelCase__=1		,				lowerCAmelCase__=[8, 5, 4, 2]		,				lowerCAmelCase__="weight_norm"		,				lowerCAmelCase__=7		,				lowerCAmelCase__=7		,				lowerCAmelCase__=3		,				lowerCAmelCase__=2		,				lowerCAmelCase__=True		,				lowerCAmelCase__="reflect"		,				lowerCAmelCase__=2		,				lowerCAmelCase__=2		,				lowerCAmelCase__=1.0		,				lowerCAmelCase__=1_0_2_4		,				lowerCAmelCase__=None		,				lowerCAmelCase__=True		,				**lowerCAmelCase__		,				)       ->						Optional[int]:



        '''simple docstring'''




        a__     : Optional[int]  =target_bandwidths
        a__     : List[Any]  =sampling_rate
        a__     : Optional[Any]  =audio_channels
        a__     : List[str]  =normalize
        a__     : Union[str, Any]  =chunk_length_s
        a__     : Any  =overlap
        a__     : Optional[Any]  =hidden_size
        a__     : List[Any]  =num_filters
        a__     : Optional[int]  =num_residual_layers
        a__     : Any  =upsampling_ratios
        a__     : Dict  =norm_type
        a__     : str  =kernel_size
        a__     : str  =last_kernel_size
        a__     : List[Any]  =residual_kernel_size
        a__     : Optional[int]  =dilation_growth_rate
        a__     : Dict  =use_causal_conv
        a__     : Union[str, Any]  =pad_mode
        a__     : List[str]  =compress
        a__     : Dict  =num_lstm_layers
        a__     : Union[str, Any]  =trim_right_ratio
        a__     : Any  =codebook_size
        a__     : List[str]  =codebook_dim if codebook_dim is not None else hidden_size
        a__     : Tuple  =use_conv_shortcut

        if self.norm_type not in ["weight_norm", "time_group_norm"]:
          raise ValueError(
              F'''self.norm_type must be one of `"weight_norm"`, `"time_group_norm"`), got {self.norm_type}'''							)

        super().__init__(**lowerCAmelCase__							)







      @property
      def        _lowercase  (   self							)       ->						Optional[int]:



        '''simple docstring'''




        if self.chunk_length_s is None:
          return None
        else:
          return int(self.chunk_length_s * self.sampling_rate							)







      @property
      def        _lowercase  (   self							)       ->						Optional[int]:



        '''simple docstring'''




        if self.chunk_length_s is None or self.overlap is None:
          return None
        else:
          return max(1		,				int((1.0 - self.overlap) * self.chunk_length							)							)







      @property
      def        _lowercase  (   self							)       ->						int:



        '''simple docstring'''




        a__     : List[Any]  =np.prod(self.upsampling_ratios							)
        return math.ceil(self.sampling_rate / hop_length							)







      @property
      def        _lowercase  (   self							)       ->						int:



        '''simple docstring'''




        return int(1_0_0_0 * self.target_bandwidths[-1] // (self.frame_rate * 1_0)							)













from __future__ import annotations

import math
def 					_A	(		SCREAMING_SNAKE_CASE					:       int						):





  """simple docstring"""



  if num <= 0:
    a__     : List[str]  =f'''{num}: Invalid input, please enter a positive integer.'''
    raise ValueError(SCREAMING_SNAKE_CASE						)

  a__     : Union[str, Any]  =[True] * (num + 1)
  a__     : Union[str, Any]  =[]
  a__     : str  =2
  a__     : Any  =int(math.sqrt(SCREAMING_SNAKE_CASE						)						)

  while start <= end:
    # If start is a prime
    if sieve[start] is True:
      prime.append(SCREAMING_SNAKE_CASE						)

      # Set multiples of start be False
      for i in range(start * start	,	num + 1	,	SCREAMING_SNAKE_CASE						):
        if sieve[i] is True:
          a__     : Optional[int]  =False

    start += 1

  for j in range(end + 1	,	num + 1						):
    if sieve[j] is True:
      prime.append(SCREAMING_SNAKE_CASE						)

  return prime


if __name__ == "__main__":
     print(prime_sieve(int(input("""Enter a positive integer: """).strip())))






