
'''simple docstring'''







_snake_case					: List[str]     			=					[0.33, 0.44, 0.55, 0.44, 0.33]
_snake_case					: int     			=					3
_snake_case					: str     			=					5

# Buffer Space (with Parameters Space)
_snake_case					: str     			=					[]
_snake_case					: int     			=					[]

# Machine Time
_snake_case					: int     			=					0



def       _a		(						_SCREAMING_SNAKE_CASE		: Tuple	):
						global buffer_space, params_space, machine_time, K, m, t

						# Choosing Dynamical Systems (All)
						for key, value in enumerate(lowercase__	):
												# Evolution Parameter
												_SCREAMING_SNAKE_CASE					=			float(seed / value	)

												# Control Theory: Orbit Change
												_SCREAMING_SNAKE_CASE					=			(buffer_space[(key + 1) % m] + e) % 1

												# Control Theory: Trajectory Change
												_SCREAMING_SNAKE_CASE					=			(params_space[key] + e) % 1 + 3

												# Modification (Transition Function) - Jumps
												_SCREAMING_SNAKE_CASE					=			round(float(r * value * (1 - value)	)						,      10	)
												_SCREAMING_SNAKE_CASE					=			r  # Saving to Parameters Space

						# Logistic Map
						assert max(lowercase__	) < 1
						assert max(lowercase__	) < 4

						# Machine Time
						machine_time += 1



def       _a		(						):
						global buffer_space, params_space, machine_time, K, m, t

						# PRNG (Xorshift by George Marsaglia)
						def xorshift(_SCREAMING_SNAKE_CASE		: Dict						,      _SCREAMING_SNAKE_CASE		: Optional[Any]	):
												x ^= y >> 13
												y ^= x << 17
												x ^= y >> 5
												return x

						# Choosing Dynamical Systems (Increment)
						_SCREAMING_SNAKE_CASE					=			machine_time % m

						# Evolution (Time Length)
						for _ in range(0						,      lowercase__	):
												# Variables (Position + Parameters)
												_SCREAMING_SNAKE_CASE					=			params_space[key]
												_SCREAMING_SNAKE_CASE					=			buffer_space[key]

												# Modification (Transition Function) - Flow
												_SCREAMING_SNAKE_CASE					=			round(float(r * value * (1 - value)	)						,      10	)
												_SCREAMING_SNAKE_CASE					=			(machine_time * 0.01 + r * 1.01) % 1 + 3

						# Choosing Chaotic Data
						_SCREAMING_SNAKE_CASE					=			int(buffer_space[(key + 2) % m] * (10**10)	)
						_SCREAMING_SNAKE_CASE					=			int(buffer_space[(key - 2) % m] * (10**10)	)

						# Machine Time
						machine_time += 1

						return xorshift(lowercase__						,      lowercase__	) % 0xFF_FF_FF_FF



def       _a		(						):
						global buffer_space, params_space, machine_time, K, m, t

						_SCREAMING_SNAKE_CASE					=			K
						_SCREAMING_SNAKE_CASE					=			[0] * m
						_SCREAMING_SNAKE_CASE					=			0


if __name__ == "__main__":
						# Initialization
						reset()

						# Pushing Data (Input)
						import random

						_snake_case					: Any     			=					random.sample(range(0XF_F_F_F_F_F_F_F), 100)
						for chunk in message:
												push(chunk)

						# for controlling
						_snake_case					: Dict     			=					""""""

						# Pulling Data (Output)
						while inp in ("e", "E"):
												print(F"{format(pull(), '#04x')}")
												print(buffer_space)
												print(params_space)
												_snake_case					: Tuple     			=					input("""(e)exit? """).strip()

"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import is_detectrona_available, logging


__UpperCAmelCase 					=    logging.get_logger(__name__)

__UpperCAmelCase 					=    {
    'layoutlmv2-base-uncased': 'https://huggingface.co/microsoft/layoutlmv2-base-uncased/resolve/main/config.json',
    'layoutlmv2-large-uncased': 'https://huggingface.co/microsoft/layoutlmv2-large-uncased/resolve/main/config.json',
    # See all LayoutLMv2 models at https://huggingface.co/models?filter=layoutlmv2
}

# soft dependency
if is_detectrona_available():
				import detectrona




class      _SCREAMING_SNAKE_CASE   (     A__				):
			UpperCAmelCase_    :Optional[int]												=		"layoutlmv2"






			def __init__(   self			,  __A=3_0522			,  __A=768			,  __A=12			,  __A=12			,  __A=3072			,  __A="gelu"			,  __A=0.1			,  __A=0.1			,  __A=512			,  __A=2			,  __A=0.0_2			,  __A=1E-12			,  __A=0			,  __A=1024			,  __A=128			,  __A=32			,  __A=True			,  __A=256			,  __A=64			,  __A=True			,  __A=[7, 7, 256]			,  __A=128			,  __A=128			,  __A=True			,  __A=True			,  __A=False			,  __A=None			,  **__A			,  )     ->	List[str]:
						super().__init__(
						    vocab_size=__A			,  hidden_size=__A			,  num_hidden_layers=__A			,  num_attention_heads=__A			,  intermediate_size=__A			,  hidden_act=__A			,  hidden_dropout_prob=__A			,  attention_probs_dropout_prob=__A			,  max_position_embeddings=__A			,  type_vocab_size=__A			,  initializer_range=__A			,  layer_norm_eps=__A			,  pad_token_id=__A			,  **__A			,  )
						lowerCAmelCase_       :Optional[Any]     	=    max_ad_position_embeddings
						lowerCAmelCase_       :Dict     	=    max_rel_pos
						lowerCAmelCase_       :str     	=    rel_pos_bins
						lowerCAmelCase_       :List[str]     	=    fast_qkv
						lowerCAmelCase_       :Union[str, Any]     	=    max_rel_ad_pos
						lowerCAmelCase_       :List[str]     	=    rel_ad_pos_bins
						lowerCAmelCase_       :Any     	=    convert_sync_batchnorm
						lowerCAmelCase_       :Dict     	=    image_feature_pool_shape
						lowerCAmelCase_       :str     	=    coordinate_size
						lowerCAmelCase_       :Tuple     	=    shape_size
						lowerCAmelCase_       :Tuple     	=    has_relative_attention_bias
						lowerCAmelCase_       :Union[str, Any]     	=    has_spatial_attention_bias
						lowerCAmelCase_       :int     	=    has_visual_segment_embedding
						lowerCAmelCase_       :Any     	=    (
						    detectrona_config_args if detectrona_config_args is not None else self.get_default_detectrona_config()
						)






			@classmethod
			def 					__lowerCAmelCase					(   self			)     ->	Optional[Any]:
						return {
						    "MODEL.MASK_ON": True,
						    "MODEL.PIXEL_STD": [5_7.3_7_5, 5_7.1_2_0, 5_8.3_9_5],
						    "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
						    "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
						    "MODEL.ANCHOR_GENERATOR.SIZES": [[32], [64], [128], [256], [512]],
						    "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
						    "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 2000,
						    "MODEL.RPN.PRE_NMS_TOPK_TEST": 1000,
						    "MODEL.RPN.POST_NMS_TOPK_TRAIN": 1000,
						    "MODEL.POST_NMS_TOPK_TEST": 1000,
						    "MODEL.ROI_HEADS.NAME": "StandardROIHeads",
						    "MODEL.ROI_HEADS.NUM_CLASSES": 5,
						    "MODEL.ROI_HEADS.IN_FEATURES": ["p2", "p3", "p4", "p5"],
						    "MODEL.ROI_BOX_HEAD.NAME": "FastRCNNConvFCHead",
						    "MODEL.ROI_BOX_HEAD.NUM_FC": 2,
						    "MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION": 14,
						    "MODEL.ROI_MASK_HEAD.NAME": "MaskRCNNConvUpsampleHead",
						    "MODEL.ROI_MASK_HEAD.NUM_CONV": 4,
						    "MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION": 7,
						    "MODEL.RESNETS.DEPTH": 101,
						    "MODEL.RESNETS.SIZES": [[32], [64], [128], [256], [512]],
						    "MODEL.RESNETS.ASPECT_RATIOS": [[0.5, 1.0, 2.0]],
						    "MODEL.RESNETS.OUT_FEATURES": ["res2", "res3", "res4", "res5"],
						    "MODEL.RESNETS.NUM_GROUPS": 32,
						    "MODEL.RESNETS.WIDTH_PER_GROUP": 8,
						    "MODEL.RESNETS.STRIDE_IN_1X1": False,
						}






			def 					__lowerCAmelCase					(   self			)     ->	List[Any]:
						lowerCAmelCase_       :Any     	=    detectrona.config.get_cfg()
						for k, v in self.detectrona_config_args.items():
									lowerCAmelCase_       :int     	=    k.split("""."""			)
									lowerCAmelCase_       :List[Any]     	=    detectrona_config
									for attribute in attributes[:-1]:
												lowerCAmelCase_       :List[Any]     	=    getattr(__A			,  __A			)
									setattr(__A			,  attributes[-1]			,  __A			)

						return detectrona_config






