"""simple docstring"""






from __future__ import annotations

lowerCAmelCase__  :  Tuple						     =	[-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
lowerCAmelCase__  :  List[Any]						     =	[-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							[]
				UpperCAmelCase__             =							len(lowerCamelCase       )

				for i in range(lowerCamelCase       ):
								UpperCAmelCase__             =							-1
								for j in range(i + 1					,			lowerCamelCase       ):
												if arr[i] < arr[j]:
																UpperCAmelCase__             =							arr[j]
																break
								result.append(lowerCamelCase       )
				return result



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							[]
				for i, outer in enumerate(lowerCamelCase       ):
								UpperCAmelCase__             =							-1
								for inner in arr[i + 1 :]:
												if outer < inner:
																UpperCAmelCase__             =							inner
																break
								result.append(lowerCamelCase       )
				return result



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							len(lowerCamelCase       )
				UpperCAmelCase__             =							[]
				UpperCAmelCase__             =							[-1] * arr_size

				for index in reversed(range(lowerCamelCase       )       ):
								if stack:
												while stack[-1] <= arr[index]:
																stack.pop()
																if not stack:
																				break
								if stack:
												UpperCAmelCase__             =							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))

						lowerCAmelCase__  :  List[str]						     =	(
						    '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),
						)




"""simple docstring"""






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


lowerCAmelCase__  :  int						     =	logging.get_logger(__name__)

lowerCAmelCase__  :  str						     =	{
    'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/config.json',
    # See all XGLM models at https://huggingface.co/models?filter=xglm
}
class 				snake_case       ( __UpperCAmelCase				):




					"""simple docstring"""

					snake_case__				    = "xglm"
					snake_case__				    = ["past_key_values"]

					snake_case__				    = {
					    "num_attention_heads": "attention_heads",
					    "hidden_size": "d_model",
					    "num_hidden_layers": "num_layers",
					}







					def __init__(				self   :	Any    ,lowerCamelCase__   :	Any=256_008    ,lowerCamelCase__   :	Optional[Any]=2_048    ,lowerCamelCase__   :	List[str]=1_024    ,lowerCamelCase__   :	List[str]=4_096    ,lowerCamelCase__   :	Tuple=24    ,lowerCamelCase__   :	Optional[int]=16    ,lowerCamelCase__   :	int="gelu"    ,lowerCamelCase__   :	Dict=0.1    ,lowerCamelCase__   :	int=0.1    ,lowerCamelCase__   :	List[Any]=0.0    ,lowerCamelCase__   :	List[str]=0.0    ,lowerCamelCase__   :	Optional[Any]=0.0_2    ,lowerCamelCase__   :	List[str]=True    ,lowerCamelCase__   :	Optional[Any]=True    ,lowerCamelCase__   :	str=2    ,lowerCamelCase__   :	Dict=1    ,lowerCamelCase__   :	Optional[int]=0    ,lowerCamelCase__   :	Tuple=2    ,**lowerCamelCase__   :	List[Any]    ,):
									UpperCAmelCase__             =							vocab_size
									UpperCAmelCase__             =							max_position_embeddings
									UpperCAmelCase__             =							d_model
									UpperCAmelCase__             =							ffn_dim
									UpperCAmelCase__             =							num_layers
									UpperCAmelCase__             =							attention_heads
									UpperCAmelCase__             =							activation_function
									UpperCAmelCase__             =							dropout
									UpperCAmelCase__             =							attention_dropout
									UpperCAmelCase__             =							activation_dropout
									UpperCAmelCase__             =							layerdrop
									UpperCAmelCase__             =							init_std
									UpperCAmelCase__             =							scale_embedding  # scale factor will be sqrt(d_model) if True
									UpperCAmelCase__             =							use_cache

									super().__init__(
									    pad_token_id=lowerCamelCase__    ,bos_token_id=lowerCamelCase__    ,eos_token_id=lowerCamelCase__    ,decoder_start_token_id=lowerCamelCase__    ,**lowerCamelCase__    ,)



