






import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
from ..clip.configuration_clip import CLIPVisionConfig


a    =       logging.get_logger(__name__)
class        __snake_case(					__UpperCamelCase      ):
 lowercase :       int		      =		'''vision-text-dual-encoder'''
 lowercase :       Union[str, Any]		      =		True



 def __init__(	self   :   Tuple ,		UpperCAmelCase__   :   int=512 ,		UpperCAmelCase__   :   Tuple=2.6_592 ,		**UpperCAmelCase__   :   Dict	):

    """simple docstring"""






    super().__init__(**UpperCAmelCase__	)

    if "vision_config" not in kwargs:
       raise ValueError("""`vision_config` can not be `None`."""	)

    if "text_config" not in kwargs:
       raise ValueError("""`text_config` can not be `None`."""	)

    lowercase__						:	Tuple         = kwargs.pop("""vision_config"""	)
    lowercase__						:	List[str]         = kwargs.pop("""text_config"""	)

    lowercase__						:	Optional[int]         = vision_config.pop("""model_type"""	)
    lowercase__						:	Any         = text_config.pop("""model_type"""	)

    if vision_model_type == "clip":
       lowercase__						:	Optional[int]         = AutoConfig.for_model(UpperCAmelCase__ ,		**UpperCAmelCase__	).vision_config
    elif vision_model_type == "clip_vision_model":
       lowercase__						:	List[Any]         = CLIPVisionConfig(**UpperCAmelCase__	)
    else:
       lowercase__						:	List[Any]         = AutoConfig.for_model(UpperCAmelCase__ ,		**UpperCAmelCase__	)

    lowercase__						:	str         = AutoConfig.for_model(UpperCAmelCase__ ,		**UpperCAmelCase__	)

    lowercase__						:	Dict         = projection_dim
    lowercase__						:	Optional[int]         = logit_scale_init_value



 @classmethod
 def 						UpperCAmelCase    (	cls   :   Tuple ,		UpperCAmelCase__   :   PretrainedConfig ,		UpperCAmelCase__   :   PretrainedConfig ,		**UpperCAmelCase__   :   int	):

    """simple docstring"""






    return cls(vision_config=vision_config.to_dict() ,		text_config=text_config.to_dict() ,		**UpperCAmelCase__	)







 def 						UpperCAmelCase    (	self   :   Optional[Any]	):

    """simple docstring"""






    lowercase__						:	List[Any]         = copy.deepcopy(self.__dict__	)
    lowercase__						:	Optional[Any]         = self.vision_config.to_dict()
    lowercase__						:	Optional[Any]         = self.text_config.to_dict()
    lowercase__						:	Dict         = self.__class__.model_type
    return output










from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a    =       logging.get_logger(__name__)

a    =       {
    'nghuyong/ernie-1.0-base-zh': 'https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json',
    'nghuyong/ernie-2.0-base-en': 'https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json',
    'nghuyong/ernie-2.0-large-en': 'https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json',
    'nghuyong/ernie-3.0-base-zh': 'https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-medium-zh': 'https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-mini-zh': 'https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-micro-zh': 'https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json',
    'nghuyong/ernie-3.0-nano-zh': 'https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json',
    'nghuyong/ernie-gram-zh': 'https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json',
    'nghuyong/ernie-health-zh': 'https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json',
}
class        __snake_case(					__UpperCamelCase      ):
 lowercase :       Dict		      =		'''ernie'''



 def __init__(	self   :   Tuple ,		UpperCAmelCase__   :   int=30_522 ,		UpperCAmelCase__   :   List[str]=768 ,		UpperCAmelCase__   :   Tuple=12 ,		UpperCAmelCase__   :   Optional[int]=12 ,		UpperCAmelCase__   :   Any=3_072 ,		UpperCAmelCase__   :   Tuple="gelu" ,		UpperCAmelCase__   :   Union[str, Any]=0.1 ,		UpperCAmelCase__   :   str=0.1 ,		UpperCAmelCase__   :   List[str]=512 ,		UpperCAmelCase__   :   str=2 ,		UpperCAmelCase__   :   Optional[int]=3 ,		UpperCAmelCase__   :   Dict=False ,		UpperCAmelCase__   :   Any=0.02 ,		UpperCAmelCase__   :   Any=1e-12 ,		UpperCAmelCase__   :   str=0 ,		UpperCAmelCase__   :   Any="absolute" ,		UpperCAmelCase__   :   List[str]=True ,		UpperCAmelCase__   :   Tuple=None ,		**UpperCAmelCase__   :   Dict ,		):

    """simple docstring"""






    super().__init__(pad_token_id=UpperCAmelCase__ ,		**UpperCAmelCase__	)

    lowercase__						:	List[str]         = vocab_size
    lowercase__						:	Optional[int]         = hidden_size
    lowercase__						:	Union[str, Any]         = num_hidden_layers
    lowercase__						:	Any         = num_attention_heads
    lowercase__						:	Optional[int]         = hidden_act
    lowercase__						:	str         = intermediate_size
    lowercase__						:	Tuple         = hidden_dropout_prob
    lowercase__						:	Tuple         = attention_probs_dropout_prob
    lowercase__						:	str         = max_position_embeddings
    lowercase__						:	List[Any]         = type_vocab_size
    lowercase__						:	Any         = task_type_vocab_size
    lowercase__						:	Optional[Any]         = use_task_id
    lowercase__						:	Optional[Any]         = initializer_range
    lowercase__						:	Union[str, Any]         = layer_norm_eps
    lowercase__						:	Dict         = position_embedding_type
    lowercase__						:	Union[str, Any]         = use_cache
    lowercase__						:	int         = classifier_dropout
class        __snake_case(					__UpperCamelCase      ):



 @property
 def 						UpperCAmelCase    (	self   :   List[Any]	):

    """simple docstring"""






    if self.task == "multiple-choice":
       lowercase__						:	Dict         = {0: """batch""", 1: """choice""", 2: """sequence"""}
    else:
       lowercase__						:	Dict         = {0: """batch""", 1: """sequence"""}
    return OrderedDict(
        [
            ("""input_ids""", dynamic_axis),
            ("""attention_mask""", dynamic_axis),
            ("""token_type_ids""", dynamic_axis),
            ("""task_type_ids""", dynamic_axis),
        ]	)


