





"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


lowerCamelCase_          =	logging.get_logger(__name__)

lowerCamelCase_          =	{
    "uclanlp/plbart-base": "https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json",
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}






class       _SCREAMING_SNAKE_CASE(     A						):
       SCREAMING_SNAKE_CASE_     :   Tuple					=						'''plbart'''
       SCREAMING_SNAKE_CASE_     :   str					=						['''past_key_values''']
       SCREAMING_SNAKE_CASE_     :   Optional[int]					=						{'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}




       def __init__(		self	,SCREAMING_SNAKE_CASE__=5_00_05	,SCREAMING_SNAKE_CASE__=10_24	,SCREAMING_SNAKE_CASE__=6	,SCREAMING_SNAKE_CASE__=30_72	,SCREAMING_SNAKE_CASE__=12	,SCREAMING_SNAKE_CASE__=6	,SCREAMING_SNAKE_CASE__=30_72	,SCREAMING_SNAKE_CASE__=12	,SCREAMING_SNAKE_CASE__=0.0	,SCREAMING_SNAKE_CASE__=0.0	,SCREAMING_SNAKE_CASE__=True	,SCREAMING_SNAKE_CASE__=True	,SCREAMING_SNAKE_CASE__="gelu"	,SCREAMING_SNAKE_CASE__=7_68	,SCREAMING_SNAKE_CASE__=0.1	,SCREAMING_SNAKE_CASE__=0.1	,SCREAMING_SNAKE_CASE__=0.0	,SCREAMING_SNAKE_CASE__=0.0_2	,SCREAMING_SNAKE_CASE__=0.0	,SCREAMING_SNAKE_CASE__=True	,SCREAMING_SNAKE_CASE__=1	,SCREAMING_SNAKE_CASE__=0	,SCREAMING_SNAKE_CASE__=2	,SCREAMING_SNAKE_CASE__=2	,**SCREAMING_SNAKE_CASE__	,)    ->   Any:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :str	       =						vocab_size
             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						max_position_embeddings
             __SCREAMING_SNAKE_CASE     :Dict	       =						d_model
             __SCREAMING_SNAKE_CASE     :Tuple	       =						encoder_ffn_dim
             __SCREAMING_SNAKE_CASE     :int	       =						encoder_layers
             __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						encoder_attention_heads
             __SCREAMING_SNAKE_CASE     :str	       =						decoder_ffn_dim
             __SCREAMING_SNAKE_CASE     :List[Any]	       =						decoder_layers
             __SCREAMING_SNAKE_CASE     :Dict	       =						decoder_attention_heads
             __SCREAMING_SNAKE_CASE     :int	       =						dropout
             __SCREAMING_SNAKE_CASE     :Any	       =						attention_dropout
             __SCREAMING_SNAKE_CASE     :List[Any]	       =						activation_dropout
             __SCREAMING_SNAKE_CASE     :str	       =						activation_function
             __SCREAMING_SNAKE_CASE     :Dict	       =						init_std
             __SCREAMING_SNAKE_CASE     :Any	       =						encoder_layerdrop
             __SCREAMING_SNAKE_CASE     :str	       =						decoder_layerdrop
             __SCREAMING_SNAKE_CASE     :Tuple	       =						classifier_dropout
             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						use_cache
             __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						encoder_layers
             __SCREAMING_SNAKE_CASE     :Tuple	       =						scale_embedding  # scale factor will be sqrt(d_model) if True
             super().__init__(
                 pad_token_id=SCREAMING_SNAKE_CASE__	,bos_token_id=SCREAMING_SNAKE_CASE__	,eos_token_id=SCREAMING_SNAKE_CASE__	,is_encoder_decoder=SCREAMING_SNAKE_CASE__	,forced_eos_token_id=SCREAMING_SNAKE_CASE__	,**SCREAMING_SNAKE_CASE__	,)






class       _SCREAMING_SNAKE_CASE(     A						):




       @property
       def 					_UpperCamelCase  (		self							)    ->   Mapping[str, Mapping[int, str]]:





             """simple docstring"""






             return OrderedDict(
                 [
                     ('''input_ids''', {0: '''batch''', 1: '''sequence'''}),
                     ('''attention_mask''', {0: '''batch''', 1: '''sequence'''}),
                 ]							)




       @property
       def 					_UpperCamelCase  (		self							)    ->   Mapping[str, Mapping[int, str]]:





             """simple docstring"""






             if self.use_past:
                   return OrderedDict(
                       [
                           ('''last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
                           ('''past_keys''', {0: '''batch''', 2: '''sequence'''}),
                           ('''encoder_last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
                       ]							)
             else:
                   return OrderedDict(
                       [
                           ('''last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
                           ('''encoder_last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
                       ]							)






"""simple docstring"""
import math
from collections.abc import Generator



def   __lowerCamelCase     (							a_  :	int							)    ->   Generator[int, None, None]:
      __SCREAMING_SNAKE_CASE     :Generator	       =						(i for i in range(1				,     (max_n + 1)							))
      for i in (n for n in numbers if n > 1):
            for j in range(2				,     a_							):
                  if (i % j) == 0:
                        break
            else:
                  yield i



def   __lowerCamelCase     (							a_  :	int							)    ->   Generator[int, None, None]:
      __SCREAMING_SNAKE_CASE     :Generator	       =						(i for i in range(1				,     (max_n + 1)							))
      for i in (n for n in numbers if n > 1):
            # only need to check for factors up to sqrt(i)
            __SCREAMING_SNAKE_CASE     :Tuple	       =						int(math.sqrt(a_							)							) + 1
            for j in range(2				,     a_							):
                  if (i % j) == 0:
                        break
            else:
                  yield i



def   __lowerCamelCase     (							a_  :	int							)    ->   Generator[int, None, None]:
      __SCREAMING_SNAKE_CASE     :Generator	       =						(i for i in range(1				,     (max_n + 1)				,     2							))
      # It's useless to test even numbers as they will not be prime
      if max_n > 2:
            yield 2  # Because 2 will not be tested, it's necessary to yield it now
      for i in (n for n in numbers if n > 1):
            __SCREAMING_SNAKE_CASE     :int	       =						int(math.sqrt(a_							)							) + 1
            for j in range(3				,     a_				,     2							):
                  # As we removed the even numbers, we don't need them now
                  if (i % j) == 0:
                        break
            else:
                  yield i



def   __lowerCamelCase     (							)    ->   Union[str, Any]:
      from timeit import timeit

      __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						'''from __main__ import slow_primes, primes, fast_primes'''
      print(timeit('''slow_primes(1_000_000_000_000)'''				,     setup=a_				,     number=1_00_00_00							)							)
      print(timeit('''primes(1_000_000_000_000)'''				,     setup=a_				,     number=1_00_00_00							)							)
      print(timeit('''fast_primes(1_000_000_000_000)'''				,     setup=a_				,     number=1_00_00_00							)							)


if __name__ == "__main__":
  lowerCamelCase_          =	int(input("Calculate primes up to:\n>> ").strip())
  for ret in primes(number):
    print(ret)
  benchmark()