
from typing import TYPE_CHECKING

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


lowerCamelCase__        =						{
    '''configuration_deformable_detr''': ['''DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeformableDetrConfig'''],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase__        =						['''DeformableDetrFeatureExtractor''']
					lowerCamelCase__        =						['''DeformableDetrImageProcessor''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase__        =						[
					    '''DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''DeformableDetrForObjectDetection''',
					    '''DeformableDetrModel''',
					    '''DeformableDetrPreTrainedModel''',
					]


if TYPE_CHECKING:
					from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
										from .image_processing_deformable_detr import DeformableDetrImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_deformable_detr import (
										    DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DeformableDetrForObjectDetection,
										    DeformableDetrModel,
										    DeformableDetrPreTrainedModel,
										)

else:
					import sys

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





from __future__ import annotations

import random







class 		__UpperCAmelCase:





     """simple docstring"""



     __UpperCAmelCase						:			Optional[int]							=     6

     def __init__(   self			:							int     )      ->      Optional[Any]:






         """simple docstring"""
         a__  			=							list(range(1    ,					Dice.NUM_SIDES + 1     )     )






     def 					__SCREAMING_SNAKE_CASE		(   self			:							Union[str, Any]     )      ->      List[str]:






         """simple docstring"""
         return random.choice(self.sides     )






def 							__lowerCAmelCase			(UpperCAmelCase_ ,     UpperCAmelCase_ = 2		):
    a__  			=							[Dice() for i in range(UpperCAmelCase_		)]
    a__  			=							[0] * (len(UpperCAmelCase_		) * Dice.NUM_SIDES + 1)
    for _ in range(UpperCAmelCase_		):
        count_of_sum[sum(dice.roll() for dice in dices		)] += 1
    a__  			=							[round((count * 100) / num_throws ,     2		) for count in count_of_sum]
    return probability[num_dice:]  # remove probability of sums that never appear


if __name__ == "__main__":
 import doctest

 doctest.testmod()






