


from __future__ import annotations






class     UpperCamelCase:


					def __init__(						self	:		int     ,    SCREAMING_SNAKE_CASE	:		str=None						)			->	str:




											'''simple docstring'''

											__snake_case				=		data
											__snake_case				=		None






					def __repr__(						self	:		List[str]						)			->	Optional[int]:




											'''simple docstring'''

											__snake_case				=		[]
											__snake_case				=		self
											while temp:
																	string_rep.append(f'''{temp.data}'''						)
																	__snake_case				=		temp.next
											return "->".join(SCREAMING_SNAKE_CASE						)





def 	_lowerCAmelCase       (    _lowerCAmelCase )						->	Union[str, Any]:


						'''simple docstring'''






						if not elements_list:
												raise Exception("The Elements List is empty" )

						__snake_case				=		__snake_case				=		Node(elements_list[0] )
						for i in range(1      ,	len(_lowerCAmelCase ) ):
												__snake_case				=		Node(elements_list[i] )
												__snake_case				=		current.next
						return head





def 	_lowerCAmelCase       (    _lowerCAmelCase )						->	None:


						'''simple docstring'''






						if head_node is not None and isinstance(_lowerCAmelCase      ,	_lowerCAmelCase ):
												print_reverse(head_node.next )
												print(head_node.data )





def 	_lowerCAmelCase       (    )						->	Dict:


						'''simple docstring'''






						from doctest import testmod

						testmod()

						__snake_case				=		make_linked_list([14, 52, 14, 12, 43] )
						print("Linked List:" )
						print(_lowerCAmelCase )
						print("Elements in Reverse:" )
						print_reverse(_lowerCAmelCase )


if __name__ == "__main__":
	main()









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


A							:					str     						=     logging.get_logger(__name__)

A							:					str     						=     {
    'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
    'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/config.json'
    # See all FNet models at https://huggingface.co/models?filter=fnet
}






class     UpperCamelCase(  _a   ):
					snake_case_		:				List[Any]										=	"""fnet"""


					def __init__(						self	:		Dict     ,    SCREAMING_SNAKE_CASE	:		Dict=3_2_0_0_0     ,    SCREAMING_SNAKE_CASE	:		Optional[int]=7_6_8     ,    SCREAMING_SNAKE_CASE	:		Optional[Any]=1_2     ,    SCREAMING_SNAKE_CASE	:		Any=3_0_7_2     ,    SCREAMING_SNAKE_CASE	:		Tuple="gelu_new"     ,    SCREAMING_SNAKE_CASE	:		Any=0.1     ,    SCREAMING_SNAKE_CASE	:		Dict=5_1_2     ,    SCREAMING_SNAKE_CASE	:		str=4     ,    SCREAMING_SNAKE_CASE	:		Tuple=0.02     ,    SCREAMING_SNAKE_CASE	:		Optional[Any]=1e-1_2     ,    SCREAMING_SNAKE_CASE	:		Dict=False     ,    SCREAMING_SNAKE_CASE	:		int=5_1_2     ,    SCREAMING_SNAKE_CASE	:		str=3     ,    SCREAMING_SNAKE_CASE	:		str=1     ,    SCREAMING_SNAKE_CASE	:		Optional[int]=2     ,    **SCREAMING_SNAKE_CASE	:		List[Any]     ,    )			->	List[Any]:




											'''simple docstring'''

											super().__init__(pad_token_id=SCREAMING_SNAKE_CASE     ,    bos_token_id=SCREAMING_SNAKE_CASE     ,    eos_token_id=SCREAMING_SNAKE_CASE     ,    **SCREAMING_SNAKE_CASE						)

											__snake_case				=		vocab_size
											__snake_case				=		max_position_embeddings
											__snake_case				=		hidden_size
											__snake_case				=		num_hidden_layers
											__snake_case				=		intermediate_size
											__snake_case				=		hidden_act
											__snake_case				=		hidden_dropout_prob
											__snake_case				=		initializer_range
											__snake_case				=		type_vocab_size
											__snake_case				=		layer_norm_eps
											__snake_case				=		use_tpu_fourier_optimizations
											__snake_case				=		tpu_short_seq_length





