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


_lowerCamelCase					:   List[str]							=		logging.get_logger(__name__)

_lowerCamelCase					:   Tuple							=		{
    '''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 						lowercase    (     _UpperCamelCase     ):
							lowercase__						:       List[str]								=							"vit_mae"




							def __init__(						self   :					List[Any]	,							_UpperCamelCase   :					Optional[int]=768	,							_UpperCamelCase   :					List[Any]=12	,							_UpperCamelCase   :					Optional[Any]=12	,							_UpperCamelCase   :					Optional[int]=3_072	,							_UpperCamelCase   :					int="gelu"	,							_UpperCamelCase   :					str=0.0	,							_UpperCamelCase   :					Union[str, Any]=0.0	,							_UpperCamelCase   :					Tuple=0.0_2	,							_UpperCamelCase   :					Optional[int]=1e-12	,							_UpperCamelCase   :					Any=224	,							_UpperCamelCase   :					Dict=16	,							_UpperCamelCase   :					int=3	,							_UpperCamelCase   :					str=True	,							_UpperCamelCase   :					Dict=16	,							_UpperCamelCase   :					Optional[int]=512	,							_UpperCamelCase   :					List[Any]=8	,							_UpperCamelCase   :					Optional[int]=2_048	,							_UpperCamelCase   :					Tuple=0.7_5	,							_UpperCamelCase   :					Optional[Any]=False	,							**_UpperCamelCase   :					int	,							)					->				str:



												'''simple docstring'''

												super().__init__(**__a      )

												SCREAMING_SNAKE_CASE    			=       hidden_size
												SCREAMING_SNAKE_CASE    			=       num_hidden_layers
												SCREAMING_SNAKE_CASE    			=       num_attention_heads
												SCREAMING_SNAKE_CASE    			=       intermediate_size
												SCREAMING_SNAKE_CASE    			=       hidden_act
												SCREAMING_SNAKE_CASE    			=       hidden_dropout_prob
												SCREAMING_SNAKE_CASE    			=       attention_probs_dropout_prob
												SCREAMING_SNAKE_CASE    			=       initializer_range
												SCREAMING_SNAKE_CASE    			=       layer_norm_eps
												SCREAMING_SNAKE_CASE    			=       image_size
												SCREAMING_SNAKE_CASE    			=       patch_size
												SCREAMING_SNAKE_CASE    			=       num_channels
												SCREAMING_SNAKE_CASE    			=       qkv_bias
												SCREAMING_SNAKE_CASE    			=       decoder_num_attention_heads
												SCREAMING_SNAKE_CASE    			=       decoder_hidden_size
												SCREAMING_SNAKE_CASE    			=       decoder_num_hidden_layers
												SCREAMING_SNAKE_CASE    			=       decoder_intermediate_size
												SCREAMING_SNAKE_CASE    			=       mask_ratio
												SCREAMING_SNAKE_CASE    			=       norm_pix_loss





from typing import TYPE_CHECKING

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


_lowerCamelCase					:   Optional[int]							=		{
    '''configuration_blenderbot''': [
        '''BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlenderbotConfig''',
        '''BlenderbotOnnxConfig''',
    ],
    '''tokenization_blenderbot''': ['''BlenderbotTokenizer'''],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCamelCase					:   List[Any]							=		['''BlenderbotTokenizerFast''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCamelCase					:   Tuple							=		[
							    '''BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''BlenderbotForCausalLM''',
							    '''BlenderbotForConditionalGeneration''',
							    '''BlenderbotModel''',
							    '''BlenderbotPreTrainedModel''',
							]


try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCamelCase					:   List[str]							=		[
							    '''TFBlenderbotForConditionalGeneration''',
							    '''TFBlenderbotModel''',
							    '''TFBlenderbotPreTrainedModel''',
							]


try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCamelCase					:   Optional[int]							=		[
							    '''FlaxBlenderbotForConditionalGeneration''',
							    '''FlaxBlenderbotModel''',
							    '''FlaxBlenderbotPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_blenderbot import (
							    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    BlenderbotConfig,
							    BlenderbotOnnxConfig,
							)
							from .tokenization_blenderbot import BlenderbotTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_blenderbot import (
														    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BlenderbotForCausalLM,
														    BlenderbotForConditionalGeneration,
														    BlenderbotModel,
														    BlenderbotPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_blenderbot import (
														    TFBlenderbotForConditionalGeneration,
														    TFBlenderbotModel,
														    TFBlenderbotPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_blenderbot import (
														    FlaxBlenderbotForConditionalGeneration,
														    FlaxBlenderbotModel,
														    FlaxBlenderbotPreTrainedModel,
														)

else:
							import sys

							_lowerCamelCase					:   Dict							=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




