





'''simple docstring'''




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


__UpperCAmelCase            =       logging.get_logger(__name__)




class      UpperCamelCase__					(					lowercase_			):




					"""simple docstring"""
					SCREAMING_SNAKE_CASE__				=	'''timm_backbone'''


					def __init__(						self				:			Tuple      ,						lowerCamelCase_				:			List[str]=None      ,						lowerCamelCase_				:			Dict=3      ,						lowerCamelCase_				:			List[Any]=True      ,						lowerCamelCase_				:			List[str]=True      ,						lowerCamelCase_				:			Optional[int]=None      ,						**lowerCamelCase_				:			Optional[int]      ,						):

							'''simple docstring'''



							super().__init__(**lowerCamelCase_						)
							SCREAMING_SNAKE_CASE :				Optional[int]		=			backbone
							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			num_channels
							SCREAMING_SNAKE_CASE :				Dict		=			features_only
							SCREAMING_SNAKE_CASE :				List[Any]		=			use_pretrained_backbone
							SCREAMING_SNAKE_CASE :				List[str]		=			True
							SCREAMING_SNAKE_CASE :				str		=			out_indices if out_indices is not None else (-1,)










'''simple docstring'''




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


__UpperCAmelCase            =       logging.get_logger(__name__)

__UpperCAmelCase            =       {
    """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__					(					lowercase_			):




					"""simple docstring"""
					SCREAMING_SNAKE_CASE__				=	'''fnet'''


					def __init__(						self				:			Any      ,						lowerCamelCase_				:			List[str]=3_20_00      ,						lowerCamelCase_				:			List[Any]=7_68      ,						lowerCamelCase_				:			Union[str, Any]=12      ,						lowerCamelCase_				:			Optional[Any]=30_72      ,						lowerCamelCase_				:			Optional[Any]="gelu_new"      ,						lowerCamelCase_				:			Any=0.1      ,						lowerCamelCase_				:			Union[str, Any]=5_12      ,						lowerCamelCase_				:			Optional[int]=4      ,						lowerCamelCase_				:			Optional[int]=0.02      ,						lowerCamelCase_				:			str=1e-12      ,						lowerCamelCase_				:			Any=False      ,						lowerCamelCase_				:			str=5_12      ,						lowerCamelCase_				:			str=3      ,						lowerCamelCase_				:			int=1      ,						lowerCamelCase_				:			Optional[Any]=2      ,						**lowerCamelCase_				:			Optional[int]      ,						):

							'''simple docstring'''



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

							SCREAMING_SNAKE_CASE :				Dict		=			vocab_size
							SCREAMING_SNAKE_CASE :				Dict		=			max_position_embeddings
							SCREAMING_SNAKE_CASE :				str		=			hidden_size
							SCREAMING_SNAKE_CASE :				Optional[Any]		=			num_hidden_layers
							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			intermediate_size
							SCREAMING_SNAKE_CASE :				int		=			hidden_act
							SCREAMING_SNAKE_CASE :				Dict		=			hidden_dropout_prob
							SCREAMING_SNAKE_CASE :				Tuple		=			initializer_range
							SCREAMING_SNAKE_CASE :				List[Any]		=			type_vocab_size
							SCREAMING_SNAKE_CASE :				Any		=			layer_norm_eps
							SCREAMING_SNAKE_CASE :				int		=			use_tpu_fourier_optimizations
							SCREAMING_SNAKE_CASE :				List[Any]		=			tpu_short_seq_length



