"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__       =	{
    "configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"],
    "tokenization_bart": ["BartTokenizer"],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__       =	["BartTokenizerFast"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__       =	[
					    "BART_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "BartForCausalLM",
					    "BartForConditionalGeneration",
					    "BartForQuestionAnswering",
					    "BartForSequenceClassification",
					    "BartModel",
					    "BartPretrainedModel",
					    "PretrainedBartModel",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__       =	[
					    "TFBartForConditionalGeneration",
					    "TFBartForSequenceClassification",
					    "TFBartModel",
					    "TFBartPretrainedModel",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__       =	[
					    "FlaxBartDecoderPreTrainedModel",
					    "FlaxBartForCausalLM",
					    "FlaxBartForConditionalGeneration",
					    "FlaxBartForQuestionAnswering",
					    "FlaxBartForSequenceClassification",
					    "FlaxBartModel",
					    "FlaxBartPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
					from .tokenization_bart import BartTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_bart_fast import BartTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_bart import (
										    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BartForCausalLM,
										    BartForConditionalGeneration,
										    BartForQuestionAnswering,
										    BartForSequenceClassification,
										    BartModel,
										    BartPretrainedModel,
										    PretrainedBartModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_bart import (
										    TFBartForConditionalGeneration,
										    TFBartForSequenceClassification,
										    TFBartModel,
										    TFBartPretrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_bart import (
										    FlaxBartDecoderPreTrainedModel,
										    FlaxBartForCausalLM,
										    FlaxBartForConditionalGeneration,
										    FlaxBartForQuestionAnswering,
										    FlaxBartForSequenceClassification,
										    FlaxBartModel,
										    FlaxBartPreTrainedModel,
										)

else:
					import sys

					SCREAMING_SNAKE_CASE__       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



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





def  lowerCAmelCase__     (      _UpperCamelCase							:					int       )       ->					Generator[int, None, None]:





						"""simple docstring"""






						snake_case             =      (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			,      _UpperCamelCase       ):
																		if (i % j) == 0:
																								break
												else:
																		yield i





def  lowerCAmelCase__     (      _UpperCamelCase							:					int       )       ->					Generator[int, None, None]:





						"""simple docstring"""






						snake_case             =      (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)
												snake_case             =      int(math.sqrt(_UpperCamelCase       )       ) + 1
												for j in range(2			,      _UpperCamelCase       ):
																		if (i % j) == 0:
																								break
												else:
																		yield i





def  lowerCAmelCase__     (      _UpperCamelCase							:					int       )       ->					Generator[int, None, None]:





						"""simple docstring"""






						snake_case             =      (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):
												snake_case             =      int(math.sqrt(_UpperCamelCase       )       ) + 1
												for j in range(3			,      _UpperCamelCase			,      2       ):
																		# As we removed the even numbers, we don't need them now
																		if (i % j) == 0:
																								break
												else:
																		yield i





def  lowerCAmelCase__     (      )       ->					List[str]:





						"""simple docstring"""






						from timeit import timeit

						snake_case             =      'from __main__ import slow_primes, primes, fast_primes'
						print(timeit('slow_primes(1_000_000_000_000)'			,      setup=_UpperCamelCase			,      number=1_0_0_0_0_0_0       )       )
						print(timeit('primes(1_000_000_000_000)'			,      setup=_UpperCamelCase			,      number=1_0_0_0_0_0_0       )       )
						print(timeit('fast_primes(1_000_000_000_000)'			,      setup=_UpperCamelCase			,      number=1_0_0_0_0_0_0       )       )


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


