





'''simple docstring'''






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


A             =			logging.get_logger(__name__)

A             =			{'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}







class 			lowerCamelCase					(						__UpperCAmelCase  ):
					_SCREAMING_SNAKE_CASE							   =    "ctrl"
					_SCREAMING_SNAKE_CASE							   =    ["past_key_values"]
					_SCREAMING_SNAKE_CASE							   =    {
					    "max_position_embeddings": "n_positions",
					    "hidden_size": "n_embd",
					    "num_attention_heads": "n_head",
					    "num_hidden_layers": "n_layer",
					}


					def __init__(					self	:  Optional[Any]       ,     __snake_case	:  Dict=24_65_34       ,     __snake_case	:  Optional[Any]=2_56       ,     __snake_case	:  Dict=12_80       ,     __snake_case	:  str=81_92       ,     __snake_case	:  Any=48       ,     __snake_case	:  Union[str, Any]=16       ,     __snake_case	:  int=0.1       ,     __snake_case	:  List[Any]=0.1       ,     __snake_case	:  List[str]=1e-6       ,     __snake_case	:  Optional[Any]=0.02       ,     __snake_case	:  int=True       ,     **__snake_case	:  Tuple       ,     ):





											'''simple docstring'''





											_snake_case:   Optional[Any]  					=		vocab_size
											_snake_case:   str  					=		n_positions
											_snake_case:   Optional[int]  					=		n_embd
											_snake_case:   str  					=		n_layer
											_snake_case:   List[str]  					=		n_head
											_snake_case:   str  					=		dff
											_snake_case:   Dict  					=		resid_pdrop
											_snake_case:   Optional[Any]  					=		embd_pdrop
											_snake_case:   Optional[Any]  					=		layer_norm_epsilon
											_snake_case:   Optional[Any]  					=		initializer_range

											_snake_case:   Union[str, Any]  					=		use_cache

											super().__init__(**__snake_case       )












'''simple docstring'''






from __future__ import annotations

A   : Union[str, Any]             =			[-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
A   : Optional[int]             =			[-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]





def       lowercase_      (		lowercase__						)   ->list[float]:
						_snake_case:   Tuple  					=		[]
						_snake_case:   List[Any]  					=		len(lowercase__						)

						for i in range(lowercase__						):
												_snake_case:   float  					=		-1
												for j in range(i + 1				,  lowercase__						):
																		if arr[i] < arr[j]:
																								_snake_case:   List[str]  					=		arr[j]
																								break
												result.append(lowercase__						)
						return result





def       lowercase_      (		lowercase__						)   ->list[float]:
						_snake_case:   Tuple  					=		[]
						for i, outer in enumerate(lowercase__						):
												_snake_case:   float  					=		-1
												for inner in arr[i + 1 :]:
																		if outer < inner:
																								_snake_case:   List[Any]  					=		inner
																								break
												result.append(lowercase__						)
						return result





def       lowercase_      (		lowercase__						)   ->list[float]:
						_snake_case:   int  					=		len(lowercase__						)
						_snake_case:   list[float]  					=		[]
						_snake_case:   list[float]  					=		[-1] * arr_size

						for index in reversed(range(lowercase__						)						):
												if stack:
																		while stack[-1] <= arr[index]:
																								stack.pop()
																								if not stack:
																														break
												if stack:
																		_snake_case:   Dict  					=		stack[-1]
												stack.append(arr[index]						)
						return result


if __name__ == "__main__":
		from doctest import testmod
		from timeit import timeit

		testmod()
		print(next_greatest_element_slow(arr))
		print(next_greatest_element_fast(arr))
		print(next_greatest_element(arr))

		A   : Union[str, Any]             =			(
		    'from __main__ import arr, next_greatest_element_slow, '
		    'next_greatest_element_fast, next_greatest_element'
		)
		print(
		    'next_greatest_element_slow():',
		    timeit('next_greatest_element_slow(arr)', setup=setup),
		)
		print(
		    'next_greatest_element_fast():',
		    timeit('next_greatest_element_fast(arr)', setup=setup),
		)
		print(
		    '     next_greatest_element():',
		    timeit('next_greatest_element(arr)', setup=setup),
		)





