


"""simple docstring"""







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


__a      			= logging.get_logger(__name__)

__a      			= {
    "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 				lowerCamelCase							(      __SCREAMING_SNAKE_CASE			):


							"""simple docstring"""
							SCREAMING_SNAKE_CASE              =   """nystromformer"""






							def __init__(    self			:  Union[str, Any]		,			lowerCamelCase_			:  str=30000		,			lowerCamelCase_			:  Any=768		,			lowerCamelCase_			:  Any=12		,			lowerCamelCase_			:  List[str]=12		,			lowerCamelCase_			:  Optional[int]=3072		,			lowerCamelCase_			:  Any="gelu_new"		,			lowerCamelCase_			:  List[str]=0.1		,			lowerCamelCase_			:  Union[str, Any]=0.1		,			lowerCamelCase_			:  List[str]=510		,			lowerCamelCase_			:  Union[str, Any]=2		,			lowerCamelCase_			:  Tuple=64		,			lowerCamelCase_			:  Tuple=64		,			lowerCamelCase_			:  List[str]=65		,			lowerCamelCase_			:  Optional[Any]=False		,			lowerCamelCase_			:  Dict=0.02		,			lowerCamelCase_			:  List[str]=1E-5		,			lowerCamelCase_			:  List[Any]=1		,			lowerCamelCase_			:  List[str]=0		,			lowerCamelCase_			:  str=2		,			**lowerCamelCase_			:  List[Any]		,			):
													UpperCAmelCase__												=     vocab_size
													UpperCAmelCase__												=     max_position_embeddings
													UpperCAmelCase__												=     hidden_size
													UpperCAmelCase__												=     num_hidden_layers
													UpperCAmelCase__												=     num_attention_heads
													UpperCAmelCase__												=     intermediate_size
													UpperCAmelCase__												=     hidden_act
													UpperCAmelCase__												=     hidden_dropout_prob
													UpperCAmelCase__												=     attention_probs_dropout_prob
													UpperCAmelCase__												=     initializer_range
													UpperCAmelCase__												=     type_vocab_size
													UpperCAmelCase__												=     segment_means_seq_len
													UpperCAmelCase__												=     num_landmarks
													UpperCAmelCase__												=     conv_kernel_size
													UpperCAmelCase__												=     inv_coeff_init_option
													UpperCAmelCase__												=     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_torch_available


__a      			= {"configuration_bert_generation": ["BertGenerationConfig"]}

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

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      			= [
						    "BertGenerationDecoder",
						    "BertGenerationEncoder",
						    "BertGenerationPreTrainedModel",
						    "load_tf_weights_in_bert_generation",
						]


if TYPE_CHECKING:
						from .configuration_bert_generation import BertGenerationConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_bert_generation import BertGenerationTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_bert_generation import (
												    BertGenerationDecoder,
												    BertGenerationEncoder,
												    BertGenerationPreTrainedModel,
												    load_tf_weights_in_bert_generation,
												)

else:
						import sys

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