

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


a_     :    Dict     		=   logging.get_logger(__name__)

a_     :    Optional[int]     		=   {
    "google/vivit-b-16x2-kinetics400": (
        "https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}




class   UpperCamelCase			(  SCREAMING_SNAKE_CASE ):
    __UpperCamelCase    ="vivit"

    def __init__(      self			:   Tuple				,     snake_case__			:   str=2_2_4				,     snake_case__			:   Tuple=3_2				,     snake_case__			:   Any=[2, 1_6, 1_6]				,     snake_case__			:   List[str]=3				,     snake_case__			:   int=7_6_8				,     snake_case__			:   Union[str, Any]=1_2				,     snake_case__			:   Union[str, Any]=1_2				,     snake_case__			:   Dict=3_0_7_2				,     snake_case__			:   int="gelu_fast"				,     snake_case__			:   Optional[int]=0.0				,     snake_case__			:   str=0.0				,     snake_case__			:   Union[str, Any]=0.02				,     snake_case__			:   Tuple=1E-06				,     snake_case__			:   Any=True				,     **snake_case__			:   str				,     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      hidden_size
     SCREAMING_SNAKE_CASE		    =      num_hidden_layers
     SCREAMING_SNAKE_CASE		    =      num_attention_heads
     SCREAMING_SNAKE_CASE		    =      intermediate_size
     SCREAMING_SNAKE_CASE		    =      hidden_act
     SCREAMING_SNAKE_CASE		    =      hidden_dropout_prob
     SCREAMING_SNAKE_CASE		    =      attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE		    =      initializer_range
     SCREAMING_SNAKE_CASE		    =      layer_norm_eps

     SCREAMING_SNAKE_CASE		    =      image_size
     SCREAMING_SNAKE_CASE		    =      num_frames
     SCREAMING_SNAKE_CASE		    =      tubelet_size
     SCREAMING_SNAKE_CASE		    =      num_channels
     SCREAMING_SNAKE_CASE		    =      qkv_bias

     super().__init__(**snake_case__     )




import math


def 							__lowerCAmelCase     (							_UpperCamelCase		:	int						)		->				list[int]:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      []
 SCREAMING_SNAKE_CASE		    =      2
 SCREAMING_SNAKE_CASE		    =      int(math.sqrt(_UpperCamelCase						)						)  # Size of every segment
 SCREAMING_SNAKE_CASE		    =      [True] * (end + 1)
 SCREAMING_SNAKE_CASE		    =      []

 while start <= end:
  if temp[start] is True:
   in_prime.append(_UpperCamelCase						)
   for i in range(start * start		,				end + 1		,				_UpperCamelCase						):
    SCREAMING_SNAKE_CASE		    =      False
  start += 1
 prime += in_prime

 SCREAMING_SNAKE_CASE		    =      end + 1
 SCREAMING_SNAKE_CASE		    =      min(2 * end		,				_UpperCamelCase						)

 while low <= n:
  SCREAMING_SNAKE_CASE		    =      [True] * (high - low + 1)
  for each in in_prime:
   SCREAMING_SNAKE_CASE		    =      math.floor(low / each						) * each
   if t < low:
    t += each

   for j in range(_UpperCamelCase		,				high + 1		,				_UpperCamelCase						):
    SCREAMING_SNAKE_CASE		    =      False

  for j in range(len(_UpperCamelCase						)						):
   if temp[j] is True:
    prime.append(j + low						)

  SCREAMING_SNAKE_CASE		    =      high + 1
  SCREAMING_SNAKE_CASE		    =      min(high + end		,				_UpperCamelCase						)

 return prime




print(sieve(10**6))

