




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


__A    :				int    						=	logging.get_logger(__name__)

__A    :				Dict    						=	{
    """uw-madison/nystromformer-512""": """https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json""",
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}




class       UpperCAmelCase_   ( __SCREAMING_SNAKE_CASE							):




							'''simple docstring'''



							a__    	=  '''nystromformer'''





							def __init__(       self							:						Union[str, Any]							,  a							:						str=30_000							,  a							:						Any=768							,  a							:						Any=12							,  a							:						List[str]=12							,  a							:						Optional[int]=3_072							,  a							:						Any="gelu_new"							,  a							:						List[str]=0.1							,  a							:						Union[str, Any]=0.1							,  a							:						List[str]=510							,  a							:						Union[str, Any]=2							,  a							:						Tuple=64							,  a							:						Tuple=64							,  a							:						List[str]=65							,  a							:						Optional[Any]=False							,  a							:						Dict=0.02							,  a							:						List[str]=1E-5							,  a							:						List[Any]=1							,  a							:						List[str]=0							,  a							:						str=2							,  **a							:						List[Any]							,  )      ->       Dict:
										SCREAMING_SNAKE_CASE     =       vocab_size
										SCREAMING_SNAKE_CASE     =       max_position_embeddings
										SCREAMING_SNAKE_CASE     =       hidden_size
										SCREAMING_SNAKE_CASE     =       num_hidden_layers
										SCREAMING_SNAKE_CASE     =       num_attention_heads
										SCREAMING_SNAKE_CASE     =       intermediate_size
										SCREAMING_SNAKE_CASE     =       hidden_act
										SCREAMING_SNAKE_CASE     =       hidden_dropout_prob
										SCREAMING_SNAKE_CASE     =       attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE     =       initializer_range
										SCREAMING_SNAKE_CASE     =       type_vocab_size
										SCREAMING_SNAKE_CASE     =       segment_means_seq_len
										SCREAMING_SNAKE_CASE     =       num_landmarks
										SCREAMING_SNAKE_CASE     =       conv_kernel_size
										SCREAMING_SNAKE_CASE     =       inv_coeff_init_option
										SCREAMING_SNAKE_CASE     =       layer_norm_eps
										super().__init__(pad_token_id=lowerCamelCase_							,  bos_token_id=lowerCamelCase_							,  eos_token_id=lowerCamelCase_							,  **lowerCamelCase_      )










"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available


__a      			= {}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      			= ["BarthezTokenizer"]

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      			= ["BarthezTokenizerFast"]


if TYPE_CHECKING:
						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_barthez import BarthezTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_barthez_fast import BarthezTokenizerFast

else:
						import sys

						__a      			= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)