
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase__											=logging.get_logger(__name__)

lowercase__											={
    "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   a_ (      lowercase_					):
			lowerCamelCase__	:			Union[str, Any]       =    'xglm'
			lowerCamelCase__	:			List[Any]       =    ['past_key_values']

			lowerCamelCase__	:			str       =    {
			    'num_attention_heads': 'attention_heads',
			    'hidden_size': 'd_model',
			    'num_hidden_layers': 'num_layers',
			}




			def __init__(       self					,   UpperCAmelCase=25_60_08					,   UpperCAmelCase=20_48					,   UpperCAmelCase=10_24					,   UpperCAmelCase=40_96					,   UpperCAmelCase=24					,   UpperCAmelCase=16					,   UpperCAmelCase="gelu"					,   UpperCAmelCase=0.1					,   UpperCAmelCase=0.1					,   UpperCAmelCase=0.0					,   UpperCAmelCase=0.0					,   UpperCAmelCase=0.02					,   UpperCAmelCase=True					,   UpperCAmelCase=True					,   UpperCAmelCase=2					,   UpperCAmelCase=1					,   UpperCAmelCase=0					,   UpperCAmelCase=2					,   **UpperCAmelCase					,   ):
				a_      				=						vocab_size
				a_      				=						max_position_embeddings
				a_      				=						d_model
				a_      				=						ffn_dim
				a_      				=						num_layers
				a_      				=						attention_heads
				a_      				=						activation_function
				a_      				=						dropout
				a_      				=						attention_dropout
				a_      				=						activation_dropout
				a_      				=						layerdrop
				a_      				=						init_std
				a_      				=						scale_embedding  # scale factor will be sqrt(d_model) if True
				a_      				=						use_cache

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



'''simple docstring'''

SCREAMING_SNAKE_CASE							:				Union[str, Any]     	=			0  # The first color of the flag.
SCREAMING_SNAKE_CASE							:				List[str]     	=			1  # The second color of the flag.
SCREAMING_SNAKE_CASE							:				Optional[Any]     	=			2  # The third color of the flag.
SCREAMING_SNAKE_CASE							:				Tuple     	=			(red, white, blue)




def 							_UpperCamelCase				(   lowerCAmelCase__:					list   )      -> list:
							if not sequence:
														return []
							if len(lowerCAmelCase__   ) == 1:
														return list(lowerCAmelCase__   )
							SCREAMING_SNAKE_CASE_				=				0
							SCREAMING_SNAKE_CASE_				=				len(lowerCAmelCase__   ) - 1
							SCREAMING_SNAKE_CASE_				=				0
							while mid <= high:
														if sequence[mid] == colors[0]:
																					SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				=				sequence[mid], sequence[low]
																					low += 1
																					mid += 1
														elif sequence[mid] == colors[1]:
																					mid += 1
														elif sequence[mid] == colors[2]:
																					SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				=				sequence[high], sequence[mid]
																					high -= 1
														else:
																					SCREAMING_SNAKE_CASE_				=				F"""The elements inside the sequence must contains only {colors} values"""
																					raise ValueError(lowerCAmelCase__   )
							return sequence


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							SCREAMING_SNAKE_CASE							:				str     	=			input("Enter numbers separated by commas:\n").strip()
							SCREAMING_SNAKE_CASE							:				List[Any]     	=			[int(item.strip()) for item in user_input.split(",")]
							print(f"{dutch_national_flag_sort(unsorted)}")





