
from typing import TYPE_CHECKING

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


A  :			Tuple     				=				{'configuration_pegasus': ['PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusConfig']}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A  :			Optional[Any]     				=				['PegasusTokenizer']

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A  :			Union[str, Any]     				=				['PegasusTokenizerFast']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A  :			Union[str, Any]     				=				[
					    'PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'PegasusForCausalLM',
					    'PegasusForConditionalGeneration',
					    'PegasusModel',
					    'PegasusPreTrainedModel',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A  :			Any     				=				[
					    'TFPegasusForConditionalGeneration',
					    'TFPegasusModel',
					    'TFPegasusPreTrainedModel',
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A  :			Optional[int]     				=				[
					    'FlaxPegasusForConditionalGeneration',
					    'FlaxPegasusModel',
					    'FlaxPegasusPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_pegasus import PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_pegasus import PegasusTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_pegasus_fast import PegasusTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_pegasus import (
										    PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
										    PegasusForCausalLM,
										    PegasusForConditionalGeneration,
										    PegasusModel,
										    PegasusPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_pegasus import TFPegasusForConditionalGeneration, TFPegasusModel, TFPegasusPreTrainedModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_pegasus import (
										    FlaxPegasusForConditionalGeneration,
										    FlaxPegasusModel,
										    FlaxPegasusPreTrainedModel,
										)

else:
					import sys

					A  :			Tuple     				=				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

from itertools import compress, repeat
from math import ceil, sqrt


def 					__lowerCAmelCase    (    a__						) ->						list[int]:

				if num <= 2:
								return []
				if num == 3:
								return [2]

				# Odd sieve for numbers in range [3, num - 1]
				__a    							=					bytearray(B'''\x01'''						) * ((num >> 1) - 1)

				for i in range(3		,					int(sqrt(a__						)						) + 1		,					2						):
								if sieve[(i >> 1) - 1]:
												__a    							=					i**2
												__a    							=					repeat(
												    0		,					ceil((num - i_squared) / (i << 1)						)						)

				return [2] + list(compress(range(3		,					a__		,					2						)		,					a__						)						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()