






import math

def    UpperCamelCase						(	_A			):






      """simple docstring"""







      __magic_name__      :       List[str]       						= []
      __magic_name__      :       Optional[int]       						= 2
      __magic_name__      :       Union[str, Any]       						= int(math.sqrt(_snake_case			)			)  # Size of every segment
      __magic_name__      :       int       						= [True] * (end + 1)
      __magic_name__      :       List[Any]       						= []

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

      __magic_name__      :       Union[str, Any]       						= end + 1
      __magic_name__      :       Optional[int]       						= min(2 * end,   _snake_case			)

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

                  for j in range(_snake_case,   high + 1,   _snake_case			):
                        __magic_name__      :       List[str]       						= False

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

            __magic_name__      :       List[str]       						= high + 1
            __magic_name__      :       Optional[int]       						= min(high + end,   _snake_case			)

      return prime

print(sieve(10**6))








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__magic_name__:					List[Any]							=     {
    "configuration_conditional_detr": [
        "CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ConditionalDetrConfig",
        "ConditionalDetrOnnxConfig",
    ]
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__:					List[str]							=     ["ConditionalDetrFeatureExtractor"]
		__magic_name__:					int							=     ["ConditionalDetrImageProcessor"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__:					List[Any]							=     [
		    "CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "ConditionalDetrForObjectDetection",
		    "ConditionalDetrForSegmentation",
		    "ConditionalDetrModel",
		    "ConditionalDetrPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_conditional_detr import (
		    CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ConditionalDetrConfig,
		    ConditionalDetrOnnxConfig,
		)

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
				from .image_processing_conditional_detr import ConditionalDetrImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_conditional_detr import (
				    CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ConditionalDetrForObjectDetection,
				    ConditionalDetrForSegmentation,
				    ConditionalDetrModel,
				    ConditionalDetrPreTrainedModel,
				)

else:
		import sys

		__magic_name__:					List[str]							=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
