

"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE				:     List[Any]       				=       {
    """configuration_gptsan_japanese""": ["""GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTSanJapaneseConfig"""],
    """tokenization_gptsan_japanese""": ["""GPTSanJapaneseTokenizer"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE				:     Any       				=       [
				    """GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """GPTSanJapaneseForConditionalGeneration""",
				    """GPTSanJapaneseModel""",
				    """GPTSanJapanesePreTrainedModel""",
				]
				_SCREAMING_SNAKE_CASE				:     List[str]       				=       [
				    """GPTSanJapaneseTokenizer""",
				]


if TYPE_CHECKING:
				from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
				from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_gptsan_japanese import (
								    GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
								    GPTSanJapaneseForConditionalGeneration,
								    GPTSanJapaneseModel,
								    GPTSanJapanesePreTrainedModel,
								)
								from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer


else:
				import sys

				_SCREAMING_SNAKE_CASE				:     Tuple       				=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








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


lowercase_		=							logging.get_logger(__name__)

lowercase_		=							{
    '''uw-madison/yoso-4096''': '''https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json''',
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}





class 		A__				(   __SCREAMING_SNAKE_CASE ):
	lowerCamelCase__		: Tuple				    ="yoso"






	def __init__(	self				,     lowerCamelCase=50265				,     lowerCamelCase=768				,     lowerCamelCase=12				,     lowerCamelCase=12				,     lowerCamelCase=3072				,     lowerCamelCase="gelu"				,     lowerCamelCase=0.1				,     lowerCamelCase=0.1				,     lowerCamelCase=4096				,     lowerCamelCase=1				,     lowerCamelCase=0.0_2				,     lowerCamelCase=1e-12				,     lowerCamelCase="absolute"				,     lowerCamelCase=True				,     lowerCamelCase=9				,     lowerCamelCase=64				,     lowerCamelCase=None				,     lowerCamelCase=True				,     lowerCamelCase=True				,     lowerCamelCase=1				,     lowerCamelCase=0				,     lowerCamelCase=2				,     **lowerCamelCase				,     )      ->   Tuple:




						"""simple docstring"""






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

						__magic_name__					:							Union[str, Any]		   =							vocab_size
						__magic_name__					:							Union[str, Any]		   =							max_position_embeddings
						__magic_name__					:							Tuple		   =							hidden_size
						__magic_name__					:							Optional[Any]		   =							num_hidden_layers
						__magic_name__					:							Any		   =							num_attention_heads
						__magic_name__					:							List[str]		   =							intermediate_size
						__magic_name__					:							List[str]		   =							hidden_act
						__magic_name__					:							Tuple		   =							hidden_dropout_prob
						__magic_name__					:							str		   =							attention_probs_dropout_prob
						__magic_name__					:							str		   =							initializer_range
						__magic_name__					:							List[str]		   =							type_vocab_size
						__magic_name__					:							Dict		   =							layer_norm_eps
						__magic_name__					:							Any		   =							position_embedding_type
						__magic_name__					:							Optional[Any]		   =							use_expectation
						__magic_name__					:							Optional[Any]		   =							hash_code_len
						__magic_name__					:							Dict		   =							num_hash
						__magic_name__					:							str		   =							conv_window
						__magic_name__					:							Optional[Any]		   =							use_fast_hash
						__magic_name__					:							Union[str, Any]		   =							lsh_backward



