


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase       		=    {
    """configuration_xlm_roberta_xl""": [
        """XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XLMRobertaXLConfig""",
        """XLMRobertaXLOnnxConfig""",
    ],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase       		=    [
				    """XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """XLMRobertaXLForCausalLM""",
				    """XLMRobertaXLForMaskedLM""",
				    """XLMRobertaXLForMultipleChoice""",
				    """XLMRobertaXLForQuestionAnswering""",
				    """XLMRobertaXLForSequenceClassification""",
				    """XLMRobertaXLForTokenClassification""",
				    """XLMRobertaXLModel""",
				    """XLMRobertaXLPreTrainedModel""",
				]

if TYPE_CHECKING:
				from .configuration_xlm_roberta_xl import (
				    XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    XLMRobertaXLConfig,
				    XLMRobertaXLOnnxConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_xlm_roberta_xl import (
								    XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
								    XLMRobertaXLForCausalLM,
								    XLMRobertaXLForMaskedLM,
								    XLMRobertaXLForMultipleChoice,
								    XLMRobertaXLForQuestionAnswering,
								    XLMRobertaXLForSequenceClassification,
								    XLMRobertaXLForTokenClassification,
								    XLMRobertaXLModel,
								    XLMRobertaXLPreTrainedModel,
								)

else:
				import sys

				lowerCAmelCase       		=    _LazyModule(__name__, globals()["""__file__"""], _import_structure)





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


lowerCAmelCase       		=    logging.get_logger(__name__)

lowerCAmelCase       		=    {
    """abeja/gpt-neox-japanese-2.7b""": """https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json""",
}




class 							lowerCamelCase   (  _UpperCamelCase ):
	_lowerCAmelCase     :		Tuple										=						'''gpt_neox_japanese'''


	def __init__(    self				,     lowercase__=3_2_0_0_0				,     lowercase__=2_5_6_0				,     lowercase__=3_2				,     lowercase__=3_2				,     lowercase__=4				,     lowercase__="gelu"				,     lowercase__=1.0_0				,     lowercase__=1_0_0_0_0				,     lowercase__=2_0_4_8				,     lowercase__=0.0_2				,     lowercase__=1e-5				,     lowercase__=True				,     lowercase__=3_1_9_9_6				,     lowercase__=3_1_9_9_9				,     lowercase__=0.1				,     lowercase__=0.0				,     **lowercase__				,     ):
							super().__init__(bos_token_id=lowercase__				,     eos_token_id=lowercase__				,     **lowercase__)
							__UpperCAmelCase			:							Optional[Any]	    =	vocab_size
							__UpperCAmelCase			:							Dict	    =	max_position_embeddings
							__UpperCAmelCase			:							int	    =	hidden_size
							__UpperCAmelCase			:							List[Any]	    =	num_hidden_layers
							__UpperCAmelCase			:							Union[str, Any]	    =	num_attention_heads
							__UpperCAmelCase			:							Optional[int]	    =	intermediate_multiple_size
							__UpperCAmelCase			:							Any	    =	hidden_act
							__UpperCAmelCase			:							str	    =	rotary_pct
							__UpperCAmelCase			:							Any	    =	rotary_emb_base
							__UpperCAmelCase			:							Dict	    =	initializer_range
							__UpperCAmelCase			:							Tuple	    =	layer_norm_eps
							__UpperCAmelCase			:							Optional[int]	    =	use_cache
							__UpperCAmelCase			:							str	    =	attention_dropout
							__UpperCAmelCase			:							Any	    =	hidden_dropout

