






'''simple docstring'''




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


__lowerCamelCase :       Tuple 				=       logging.get_logger(__name__)

__lowerCamelCase :       Any 				=       {
    '''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
    # See all Cvt models at https://huggingface.co/models?filter=cvt
}







class  A_						(A_				):
							"""simple docstring"""




							a__ 		=						"cvt"

							def __init__(		self      :Union[str, Any]							,				lowerCAmelCase__      :Union[str, Any]=3							,				lowerCAmelCase__      :Any=[7, 3, 3]							,				lowerCAmelCase__      :int=[4, 2, 2]							,				lowerCAmelCase__      :List[Any]=[2, 1, 1]							,				lowerCAmelCase__      :int=[64, 192, 384]							,				lowerCAmelCase__      :Optional[Any]=[1, 3, 6]							,				lowerCAmelCase__      :Union[str, Any]=[1, 2, 10]							,				lowerCAmelCase__      :Any=[4.0, 4.0, 4.0]							,				lowerCAmelCase__      :Union[str, Any]=[0.0, 0.0, 0.0]							,				lowerCAmelCase__      :Optional[int]=[0.0, 0.0, 0.0]							,				lowerCAmelCase__      :Any=[0.0, 0.0, 0.1]							,				lowerCAmelCase__      :Any=[True, True, True]							,				lowerCAmelCase__      :int=[False, False, True]							,				lowerCAmelCase__      :Optional[int]=["dw_bn", "dw_bn", "dw_bn"]							,				lowerCAmelCase__      :Optional[Any]=[3, 3, 3]							,				lowerCAmelCase__      :Tuple=[1, 1, 1]							,				lowerCAmelCase__      :Optional[int]=[2, 2, 2]							,				lowerCAmelCase__      :Dict=[1, 1, 1]							,				lowerCAmelCase__      :List[Any]=[1, 1, 1]							,				lowerCAmelCase__      :List[str]=0.0_2							,				lowerCAmelCase__      :str=1E-1_2							,				**lowerCAmelCase__      :Dict							,				)					->	Optional[Any]:


										'''simple docstring'''




										super().__init__(**snake_case__					)
										snake_case_					:       Tuple =							num_channels
										snake_case_					:       Optional[int] =							patch_sizes
										snake_case_					:       List[str] =							patch_stride
										snake_case_					:       Optional[int] =							patch_padding
										snake_case_					:       List[str] =							embed_dim
										snake_case_					:       int =							num_heads
										snake_case_					:       str =							depth
										snake_case_					:       Optional[Any] =							mlp_ratio
										snake_case_					:       Tuple =							attention_drop_rate
										snake_case_					:       Union[str, Any] =							drop_rate
										snake_case_					:       Tuple =							drop_path_rate
										snake_case_					:       int =							qkv_bias
										snake_case_					:       Tuple =							cls_token
										snake_case_					:       List[str] =							qkv_projection_method
										snake_case_					:       Optional[int] =							kernel_qkv
										snake_case_					:       Optional[Any] =							padding_kv
										snake_case_					:       int =							stride_kv
										snake_case_					:       Union[str, Any] =							padding_q
										snake_case_					:       List[str] =							stride_q
										snake_case_					:       Optional[Any] =							initializer_range
										snake_case_					:       Dict =							layer_norm_eps






from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase				=			logging.get_logger(__name__)

__lowerCamelCase				=			{
    """kssteven/ibert-roberta-base""": """https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json""",
    """kssteven/ibert-roberta-large""": """https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json""",
    """kssteven/ibert-roberta-large-mnli""": (
        """https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json"""
    ),
}






class     UpperCAmelCase						(		A_					):
   A__   :						Optional[int]			=	"ibert"



   def __init__(self						:   List[Any]       ,		snake_case__						:   int=3_05_22       ,		snake_case__						:   int=7_68       ,		snake_case__						:   Any=12       ,		snake_case__						:   str=12       ,		snake_case__						:   Optional[int]=30_72       ,		snake_case__						:   Union[str, Any]="gelu"       ,		snake_case__						:   Any=0.1       ,		snake_case__						:   List[Any]=0.1       ,		snake_case__						:   str=5_12       ,		snake_case__						:   Optional[int]=2       ,		snake_case__						:   Any=0.02       ,		snake_case__						:   List[Any]=1e-12       ,		snake_case__						:   Optional[Any]=1       ,		snake_case__						:   List[Any]=0       ,		snake_case__						:   str=2       ,		snake_case__						:   Tuple="absolute"       ,		snake_case__						:   List[str]=False       ,		snake_case__						:   Tuple="none"       ,		**snake_case__						:   Tuple       ,		)						->      Union[str, Any]:


          '''simple docstring'''


          super().__init__(pad_token_id=snake_case__       ,		bos_token_id=snake_case__       ,		eos_token_id=snake_case__       ,		**snake_case__					)

          snake_case			:  str     							= vocab_size
          snake_case			:  Tuple     							= hidden_size
          snake_case			:  Optional[Any]     							= num_hidden_layers
          snake_case			:  Optional[int]     							= num_attention_heads
          snake_case			:  List[Any]     							= hidden_act
          snake_case			:  Optional[Any]     							= intermediate_size
          snake_case			:  Dict     							= hidden_dropout_prob
          snake_case			:  List[str]     							= attention_probs_dropout_prob
          snake_case			:  List[str]     							= max_position_embeddings
          snake_case			:  Union[str, Any]     							= type_vocab_size
          snake_case			:  Optional[int]     							= initializer_range
          snake_case			:  Optional[int]     							= layer_norm_eps
          snake_case			:  int     							= position_embedding_type
          snake_case			:  Union[str, Any]     							= quant_mode
          snake_case			:  Dict     							= force_dequant






class     UpperCAmelCase						(		A_					):



   @property
   def 							_SCREAMING_SNAKE_CASE  (self						:   Tuple					)						->      Mapping[str, Mapping[int, str]]:


          '''simple docstring'''


          if self.task == "multiple-choice":
                 snake_case			:  Optional[Any]     							= {0: "batch", 1: "choice", 2: "sequence"}
          else:
                 snake_case			:  List[Any]     							= {0: "batch", 1: "sequence"}
          return OrderedDict(
              [
                  ("input_ids", dynamic_axis),
                  ("attention_mask", dynamic_axis),
              ]					)





