





'''simple docstring'''


import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


if TYPE_CHECKING:
 from ... import PreTrainedTokenizerBase, TensorType

lowerCAmelCase					:     str												=logging.get_logger(__name__)
class       a_   (				_lowerCAmelCase							):
     __A      =			"vision-encoder-decoder"
     __A      =			True





     def __init__( self		:					List[str]	,      **lowercase		:					List[Any]						):





        """simple docstring"""




        super().__init__(**lowercase						)
        if "encoder" not in kwargs or "decoder" not in kwargs:
           raise ValueError(
               F'A configuraton of type {self.model_type} cannot be instantiated because '
               F'not both `encoder` and `decoder` sub-configurations are passed, but only {kwargs}'						)

        lowercase_			:Dict    			= kwargs.pop("encoder"						)
        lowercase_			:Any    			= encoder_config.pop("model_type"						)
        lowercase_			:int    			= kwargs.pop("decoder"						)
        lowercase_			:Optional[int]    			= decoder_config.pop("model_type"						)

        lowercase_			:Optional[Any]    			= AutoConfig.for_model(lowercase	,      **lowercase						)
        lowercase_			:int    			= AutoConfig.for_model(lowercase	,      **lowercase						)
        lowercase_			:Optional[Any]    			= True





     @classmethod
     def 							lowercase__      ( cls		:					Any	,      lowercase		:					PretrainedConfig	,      lowercase		:					PretrainedConfig	,      **lowercase		:					List[Any]						):





        """simple docstring"""




        logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"						)
        lowercase_			:List[str]    			= True
        lowercase_			:Optional[Any]    			= True

        return cls(encoder=encoder_config.to_dict()	,      decoder=decoder_config.to_dict()	,      **lowercase						)







     def 							lowercase__      ( self		:					int						):





        """simple docstring"""




        lowercase_			:List[Any]    			= copy.deepcopy(self.__dict__						)
        lowercase_			:Any    			= self.encoder.to_dict()
        lowercase_			:Any    			= self.decoder.to_dict()
        lowercase_			:List[Any]    			= self.__class__.model_type
        return output







class       a_   (				_lowerCAmelCase							):
     __A      =			version.parse("1.11"							)





     @property
     def 							lowercase__      ( self		:					int						):





        """simple docstring"""




        return OrderedDict(
            [
                ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
            ]						)





     @property
     def 							lowercase__      ( self		:					Dict						):





        """simple docstring"""




        return 1e-4







     @property
     def 							lowercase__      ( self		:					List[str]						):





        """simple docstring"""




        return OrderedDict({"last_hidden_state": {0: "batch", 1: "encoder_sequence"}}						)







class       a_   (				_lowerCAmelCase							):





     @property
     def 							lowercase__      ( self		:					Dict						):





        """simple docstring"""




        lowercase_			:str    			= OrderedDict()
        lowercase_			:int    			= {0: "batch", 1: "past_decoder_sequence + sequence"}
        lowercase_			:List[str]    			= {0: "batch", 1: "past_decoder_sequence + sequence"}
        lowercase_			:Any    			= {0: "batch", 1: "encoder_sequence"}

        return common_inputs







     def 							lowercase__      ( self		:					str	,      lowercase		:					"PreTrainedTokenizerBase"	,      lowercase		:					int = -1	,      lowercase		:					int = -1	,      lowercase		:					bool = False	,      lowercase		:					Optional["TensorType"] = None	,      ):





        """simple docstring"""




        import torch

        lowercase_			:Tuple    			= OrderedDict()

        lowercase_			:List[Any]    			= super().generate_dummy_inputs(
            lowercase	,      batch_size=lowercase	,      seq_length=lowercase	,      is_pair=lowercase	,      framework=lowercase						)

        lowercase_			,							lowercase_			:Dict    			= dummy_input["input_ids"].shape
        lowercase_			:Optional[Any]    			= (batch, encoder_sequence, self._config.encoder_hidden_size)
        lowercase_			:Optional[int]    			= dummy_input.pop("input_ids"						)
        lowercase_			:Optional[int]    			= dummy_input.pop("attention_mask"						)
        lowercase_			:List[str]    			= torch.zeros(lowercase						)

        return common_inputs







class       a_   (				_lowerCAmelCase							):





     @property
     def 							lowercase__      ( self		:					Union[str, Any]						):





        """simple docstring"""




        pass





     def 							lowercase__      ( self		:					Optional[Any]	,      lowercase		:					PretrainedConfig						):





        """simple docstring"""




        return VisionEncoderDecoderEncoderOnnxConfig(lowercase						)







     def 							lowercase__      ( self		:					Optional[int]	,      lowercase		:					PretrainedConfig	,      lowercase		:					PretrainedConfig	,      lowercase		:					str = "default"						):





        """simple docstring"""




        lowercase_			:Union[str, Any]    			= encoder_config.hidden_size
        return VisionEncoderDecoderDecoderOnnxConfig(lowercase	,      lowercase						)









'''simple docstring'''


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


lowerCAmelCase					:     Optional[Any]												=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       a_   (				_lowerCAmelCase							):
     __A      =			"vit_mae"





     def __init__( self		:					Any	,      lowercase		:					int=768	,      lowercase		:					Tuple=12	,      lowercase		:					str=12	,      lowercase		:					Optional[Any]=3_072	,      lowercase		:					List[Any]="gelu"	,      lowercase		:					Tuple=0.0	,      lowercase		:					Union[str, Any]=0.0	,      lowercase		:					str=0.02	,      lowercase		:					Optional[int]=1e-1_2	,      lowercase		:					List[Any]=224	,      lowercase		:					str=16	,      lowercase		:					List[str]=3	,      lowercase		:					Optional[Any]=True	,      lowercase		:					int=16	,      lowercase		:					Optional[Any]=512	,      lowercase		:					Optional[Any]=8	,      lowercase		:					Optional[Any]=2_048	,      lowercase		:					List[str]=0.75	,      lowercase		:					str=False	,      **lowercase		:					Union[str, Any]	,      ):





        """simple docstring"""




        super().__init__(**lowercase						)

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


