


"""simple docstring"""

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


lowercase__					:						Dict												=			logging.get_logger(__name__)

lowercase__					:						Any												=			{
    '''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}




class  _UpperCAmelCase (    lowerCAmelCase__):
 _lowerCAmelCase     :    Optional[int]	      =	"""vit_mae"""

 def __init__(  self	: Tuple						,  lowercase_	: Optional[Any]=768						,  lowercase_	: List[Any]=12						,  lowercase_	: Optional[Any]=12						,  lowercase_	: Union[str, Any]=3072						,  lowercase_	: Optional[int]="gelu"						,  lowercase_	: str=0.0						,  lowercase_	: Tuple=0.0						,  lowercase_	: List[str]=0.02						,  lowercase_	: Dict=1E-12						,  lowercase_	: List[Any]=224						,  lowercase_	: Dict=16						,  lowercase_	: Tuple=3						,  lowercase_	: List[str]=True						,  lowercase_	: Any=16						,  lowercase_	: Union[str, Any]=512						,  lowercase_	: int=8						,  lowercase_	: Optional[int]=2048						,  lowercase_	: Optional[Any]=0.75						,  lowercase_	: Optional[Any]=False						,  **lowercase_	: List[Any]						,  ):
     super().__init__(**lowercase_       )

     snake_case_				:  Dict       =			hidden_size
     snake_case_				:  Optional[Any]       =			num_hidden_layers
     snake_case_				:  Union[str, Any]       =			num_attention_heads
     snake_case_				:  Union[str, Any]       =			intermediate_size
     snake_case_				:  str       =			hidden_act
     snake_case_				:  Tuple       =			hidden_dropout_prob
     snake_case_				:  List[str]       =			attention_probs_dropout_prob
     snake_case_				:  Tuple       =			initializer_range
     snake_case_				:  str       =			layer_norm_eps
     snake_case_				:  Union[str, Any]       =			image_size
     snake_case_				:  Dict       =			patch_size
     snake_case_				:  List[Any]       =			num_channels
     snake_case_				:  int       =			qkv_bias
     snake_case_				:  str       =			decoder_num_attention_heads
     snake_case_				:  Tuple       =			decoder_hidden_size
     snake_case_				:  List[str]       =			decoder_num_hidden_layers
     snake_case_				:  Dict       =			decoder_intermediate_size
     snake_case_				:  List[str]       =			mask_ratio
     snake_case_				:  str       =			norm_pix_loss










"""simple docstring"""

from typing import TYPE_CHECKING

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


lowercase__					:						List[Any]												=			{'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						List[Any]												=			['''XGLMTokenizer''']

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						List[str]												=			['''XGLMTokenizerFast''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						Tuple												=			[
         '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''XGLMForCausalLM''',
         '''XGLMModel''',
         '''XGLMPreTrainedModel''',
     ]


try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						int												=			[
         '''FlaxXGLMForCausalLM''',
         '''FlaxXGLMModel''',
         '''FlaxXGLMPreTrainedModel''',
     ]


try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						Tuple												=			[
         '''TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFXGLMForCausalLM''',
         '''TFXGLMModel''',
         '''TFXGLMPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_xglm import XGLMTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_xglm_fast import XGLMTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_xglm import (
              TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFXGLMForCausalLM,
              TFXGLMModel,
              TFXGLMPreTrainedModel,
          )


else:
     import sys

     lowercase__					:						List[Any]												=			_LazyModule(__name__, globals()['''__file__'''], _import_structure)





