

from __future__ import annotations

from random import random






class        A_		:
							def __init__(		self		:			Any   ,SCREAMING_SNAKE_CASE__		:			int | None = None):
								__lowerCamelCase				:				Union[str, Any]					       = value
								__lowerCamelCase				:				int					       = random()
								__lowerCamelCase				:				Node | None					       = None
								__lowerCamelCase				:				Node | None					       = None
							def __repr__(		self		:			List[Any]):
								from pprint import pformat

								if self.left is None and self.right is None:
									return F"'{self.value}: {self.prior:.5}'"
								else:
									return pformat(
									    {F"{self.value}: {self.prior:.5}": (self.left, self.right)}   ,indent=1)


							def __str__(		self		:			Union[str, Any]):
								__lowerCamelCase				:				Optional[int]					       = str(self.value) + ' '
								__lowerCamelCase				:				Optional[Any]					       = str(self.left or '')
								__lowerCamelCase				:				List[Any]					       = str(self.right or '')
								return value + left + right






def    SCREAMING_SNAKE_CASE__       (  lowerCamelCase__	, lowerCamelCase__			)  ->     tuple[Node | None, Node | None]:
	if root is None:  # None tree is split into 2 Nones
		return None, None
	elif root.value is None:
		return None, None
	else:
		if value < root.value:
			__lowerCamelCase       , __lowerCamelCase				:				Union[str, Any]					       = split(root.left	, lowerCamelCase__			)
			return left, root
		else:
			__lowerCamelCase       , __lowerCamelCase				:				List[str]					       = split(root.right	, lowerCamelCase__			)
			return root, right






def    SCREAMING_SNAKE_CASE__       (  lowerCamelCase__	, lowerCamelCase__			)  ->     Node | None:
	if (not left) or (not right):  # If one node is None, return the other
		return left or right
	elif left.prior < right.prior:
		__lowerCamelCase				:				Optional[Any]					       = merge(left.right	, lowerCamelCase__			)
		return left
	else:
		__lowerCamelCase				:				List[str]					       = merge(lowerCamelCase__	, right.left			)
		return right






def    SCREAMING_SNAKE_CASE__       (  lowerCamelCase__	, lowerCamelCase__			)  ->     Node | None:
	__lowerCamelCase				:				List[Any]					       = Node(lowerCamelCase__			)
	__lowerCamelCase       , __lowerCamelCase				:				Optional[int]					       = split(lowerCamelCase__	, lowerCamelCase__			)
	return merge(merge(lowerCamelCase__	, lowerCamelCase__			)	, lowerCamelCase__			)






def    SCREAMING_SNAKE_CASE__       (  lowerCamelCase__	, lowerCamelCase__			)  ->     Node | None:
	__lowerCamelCase       , __lowerCamelCase				:				List[str]					       = split(lowerCamelCase__	, value - 1			)
	__lowerCamelCase       , __lowerCamelCase				:				Any					       = split(lowerCamelCase__	, lowerCamelCase__			)
	return merge(lowerCamelCase__	, lowerCamelCase__			)






def    SCREAMING_SNAKE_CASE__       (  lowerCamelCase__			)  ->     None:
	if not root:  # None
		return
	else:
		inorder(root.left			)
		print(root.value	, end=','			)
		inorder(root.right			)






def    SCREAMING_SNAKE_CASE__       (  lowerCamelCase__	, lowerCamelCase__			)  ->     Node | None:
	for arg in args.split():
		if arg[0] == "+":
			__lowerCamelCase				:				str					       = insert(lowerCamelCase__	, int(arg[1:]			)			)

		elif arg[0] == "-":
			__lowerCamelCase				:				List[Any]					       = erase(lowerCamelCase__	, int(arg[1:]			)			)

		else:
			print('Unknown command'			)

	return root






def    SCREAMING_SNAKE_CASE__       (  )  ->     None:
	__lowerCamelCase				:				int					       = None
	print(
	    'enter numbers to create a tree, + value to add value into treap, '
	    '- value to erase all nodes with value. \'q\' to quit. '			)

	__lowerCamelCase				:				Optional[int]					       = input()
	while args != "q":
		__lowerCamelCase				:				Optional[int]					       = interact_treap(lowerCamelCase__	, lowerCamelCase__			)
		print(lowerCamelCase__			)
		__lowerCamelCase				:				int					       = input()

	print('good by!'			)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					main()







"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A						   =			logging.get_logger(__name__)

__A						   =			{
    "google/switch-base-8": "https://huggingface.co/google/switch-base-8/blob/main/config.json",
}





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      Union[str, Any]         =  """switch_transformers"""
				SCREAMING_SNAKE_CASE_   :      Tuple         =  ["""past_key_values"""]
				SCREAMING_SNAKE_CASE_   :      Any         =  {"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}

				def __init__(	self							:				List[str]     ,  UpperCamelCase__							:				List[str]=3_2_1_2_8     ,  UpperCamelCase__							:				str=7_6_8     ,  UpperCamelCase__							:				Union[str, Any]=6_4     ,  UpperCamelCase__							:				Optional[int]=2_0_4_8     ,  UpperCamelCase__							:				Dict=6_4     ,  UpperCamelCase__							:				List[str]=1_2     ,  UpperCamelCase__							:				Dict=3     ,  UpperCamelCase__							:				Any=1_2     ,  UpperCamelCase__							:				Dict=3     ,  UpperCamelCase__							:				Dict=1_2     ,  UpperCamelCase__							:				List[str]=8     ,  UpperCamelCase__							:				Optional[Any]=False     ,  UpperCamelCase__							:				Optional[int]=0.01     ,  UpperCamelCase__							:				Optional[int]="float32"     ,  UpperCamelCase__							:				Any=False     ,  UpperCamelCase__							:				Dict=3_2     ,  UpperCamelCase__							:				Union[str, Any]=1_2_8     ,  UpperCamelCase__							:				Union[str, Any]=0.1     ,  UpperCamelCase__							:				Optional[int]=1e-6     ,  UpperCamelCase__							:				Optional[Any]=0.001     ,  UpperCamelCase__							:				Dict=0.001     ,  UpperCamelCase__							:				int=1.0     ,  UpperCamelCase__							:				str="relu"     ,  UpperCamelCase__							:				int=True     ,  UpperCamelCase__							:				Any=False     ,  UpperCamelCase__							:				str=True     ,  UpperCamelCase__							:				Tuple=0     ,  UpperCamelCase__							:				str=1     ,  **UpperCamelCase__							:				Tuple     ,  )->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       int          =			vocab_size
						__lowerCAmelCase:       str          =			d_model
						__lowerCAmelCase:       str          =			d_kv
						__lowerCAmelCase:       str          =			d_ff

						__lowerCAmelCase:       List[str]          =			num_sparse_encoder_layers

						__lowerCAmelCase:       List[Any]          =			num_layers
						__lowerCAmelCase:       Optional[Any]          =			(
						    num_decoder_layers if num_decoder_layers is not None else self.num_layers
						)  # default = symmetry
						__lowerCAmelCase:       Tuple          =			num_sparse_decoder_layers

						# This tells us, each how many encoder layer we'll have to set a sparse layer.
						if self.num_sparse_encoder_layers > 0:
								__lowerCAmelCase:       int          =			self.num_layers // self.num_sparse_encoder_layers
						else:
								__lowerCAmelCase:       Union[str, Any]          =			self.num_layers  # HACK: this will create 0 sparse layers

						# This tells us, each how many encoder layer we'll have to set a sparse layer.
						if self.num_sparse_decoder_layers > 0:
								__lowerCAmelCase:       Dict          =			self.num_decoder_layers // self.num_sparse_decoder_layers
						else:
								__lowerCAmelCase:       Any          =			self.num_decoder_layers  # HACK: this will create 0 sparse layers

						__lowerCAmelCase:       Dict          =			num_heads
						__lowerCAmelCase:       Dict          =			num_experts
						__lowerCAmelCase:       Any          =			expert_capacity
						__lowerCAmelCase:       List[Any]          =			router_bias
						__lowerCAmelCase:       int          =			router_jitter_noise
						if router_dtype not in ["float32", "float16", "bfloat16"]:
								raise ValueError(f"`router_dtype` must be one of 'float32', 'float16' or 'bfloat16', got {router_dtype}")
						__lowerCAmelCase:       Dict          =			router_dtype

						__lowerCAmelCase:       Optional[Any]          =			router_ignore_padding_tokens
						__lowerCAmelCase:       Union[str, Any]          =			relative_attention_num_buckets
						__lowerCAmelCase:       str          =			relative_attention_max_distance

						__lowerCAmelCase:       Optional[int]          =			dropout_rate
						__lowerCAmelCase:       Optional[Any]          =			layer_norm_epsilon
						__lowerCAmelCase:       int          =			initializer_factor
						__lowerCAmelCase:       Tuple          =			feed_forward_proj
						__lowerCAmelCase:       int          =			use_cache
						__lowerCAmelCase:       int          =			add_router_probs

						__lowerCAmelCase:       Optional[Any]          =			router_z_loss_coef
						__lowerCAmelCase:       Dict          =			router_aux_loss_coef

						__lowerCAmelCase:       Union[str, Any]          =			self.feed_forward_proj.split("-")
						__lowerCAmelCase:       Tuple          =			act_info[-1]
						__lowerCAmelCase:       str          =			act_info[0] == "gated"

						if len(UpperCamelCase__) > 1 and act_info[0] != "gated" or len(UpperCamelCase__) > 2:
								raise ValueError(
								    f"`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."
								    "Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. "
								    "'gated-gelu' or 'relu'")

						# for backwards compatibility
						if feed_forward_proj == "gated-gelu":
								__lowerCAmelCase:       List[str]          =			"gelu_new"

						super().__init__(
						    pad_token_id=UpperCamelCase__     ,  eos_token_id=UpperCamelCase__     ,  is_encoder_decoder=UpperCamelCase__     ,  **UpperCamelCase__     ,  )


