



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


__snake_case    :		int  =logging.get_logger(__name__)

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



class 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



		snake_case_     ="""gpt_neox_japanese"""



		def __init__(self		,__lowerCamelCase=3_20_00		,__lowerCamelCase=25_60		,__lowerCamelCase=32		,__lowerCamelCase=32		,__lowerCamelCase=4		,__lowerCamelCase="gelu"		,__lowerCamelCase=1.00		,__lowerCamelCase=1_00_00		,__lowerCamelCase=20_48		,__lowerCamelCase=0.02		,__lowerCamelCase=1e-5		,__lowerCamelCase=True		,__lowerCamelCase=3_19_96		,__lowerCamelCase=3_19_99		,__lowerCamelCase=0.1		,__lowerCamelCase=0.0		,**__lowerCamelCase		,)					->      Optional[Any]:

						"""simple docstring"""






						super().__init__(bos_token_id=__lowerCamelCase		,eos_token_id=__lowerCamelCase		,**__lowerCamelCase			)
						lowerCAmelCase__					:    Dict												=					vocab_size
						lowerCAmelCase__					:    List[Any]												=					max_position_embeddings
						lowerCAmelCase__					:    List[Any]												=					hidden_size
						lowerCAmelCase__					:    List[str]												=					num_hidden_layers
						lowerCAmelCase__					:    List[Any]												=					num_attention_heads
						lowerCAmelCase__					:    Optional[int]												=					intermediate_multiple_size
						lowerCAmelCase__					:    int												=					hidden_act
						lowerCAmelCase__					:    int												=					rotary_pct
						lowerCAmelCase__					:    List[Any]												=					rotary_emb_base
						lowerCAmelCase__					:    Optional[int]												=					initializer_range
						lowerCAmelCase__					:    Dict												=					layer_norm_eps
						lowerCAmelCase__					:    Optional[Any]												=					use_cache
						lowerCAmelCase__					:    Dict												=					attention_dropout
						lowerCAmelCase__					:    List[str]												=					hidden_dropout






from typing import TYPE_CHECKING

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


__snake_case    :		Optional[int]  ={
    'configuration_vision_text_dual_encoder': ['VisionTextDualEncoderConfig'],
    'processing_vision_text_dual_encoder': ['VisionTextDualEncoderProcessor'],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__snake_case    :		int  =['VisionTextDualEncoderModel']


try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__snake_case    :		List[str]  =['FlaxVisionTextDualEncoderModel']

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__snake_case    :		Tuple  =['TFVisionTextDualEncoderModel']


if TYPE_CHECKING:
							from .configuration_vision_text_dual_encoder import VisionTextDualEncoderConfig
							from .processing_vision_text_dual_encoder import VisionTextDualEncoderProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_vision_text_dual_encoder import VisionTextDualEncoderModel

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_vision_text_dual_encoder import FlaxVisionTextDualEncoderModel

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_vision_text_dual_encoder import TFVisionTextDualEncoderModel


else:
							import sys

							__snake_case    :		str  =_LazyModule(__name__, globals()['__file__'], _import_structure)

