
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

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


lowercase_       :						Union[str, Any]     					=	logging.get_logger(__name__)

lowercase_       :						List[Any]     					=	{
    '''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      (							__SCREAMING_SNAKE_CASE  ):
     A__      =			"""ibert"""
     def __init__(     self  ,     snake_case__=30522  ,     snake_case__=768  ,     snake_case__=12  ,     snake_case__=12  ,     snake_case__=3072  ,     snake_case__="gelu"  ,     snake_case__=0.1  ,     snake_case__=0.1  ,     snake_case__=512  ,     snake_case__=2  ,     snake_case__=0.02  ,     snake_case__=1E-12  ,     snake_case__=1  ,     snake_case__=0  ,     snake_case__=2  ,     snake_case__="absolute"  ,     snake_case__=False  ,     snake_case__="none"  ,     **snake_case__  ,     ):




       """simple docstring"""


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

       _SCREAMING_SNAKE_CASE   :				str							    = vocab_size
       _SCREAMING_SNAKE_CASE   :				Tuple							    = hidden_size
       _SCREAMING_SNAKE_CASE   :				int							    = num_hidden_layers
       _SCREAMING_SNAKE_CASE   :				Any							    = num_attention_heads
       _SCREAMING_SNAKE_CASE   :				Optional[int]							    = hidden_act
       _SCREAMING_SNAKE_CASE   :				Tuple							    = intermediate_size
       _SCREAMING_SNAKE_CASE   :				Dict							    = hidden_dropout_prob
       _SCREAMING_SNAKE_CASE   :				Tuple							    = attention_probs_dropout_prob
       _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = max_position_embeddings
       _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = type_vocab_size
       _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = initializer_range
       _SCREAMING_SNAKE_CASE   :				str							    = layer_norm_eps
       _SCREAMING_SNAKE_CASE   :				Optional[int]							    = position_embedding_type
       _SCREAMING_SNAKE_CASE   :				Optional[int]							    = quant_mode
       _SCREAMING_SNAKE_CASE   :				str							    = force_dequant
class 			UpperCamelCase      (							__SCREAMING_SNAKE_CASE  ):
     @property
     def 				__SCREAMING_SNAKE_CASE							(     self				):




       """simple docstring"""


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





"""simple docstring"""
import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


lowercase_       :						Union[str, Any]     					=	logging.get_logger(__name__)
class 			UpperCamelCase      (							__SCREAMING_SNAKE_CASE  ):
     def __init__(     self  ,     *snake_case__  ,     **snake_case__				):




       """simple docstring"""


       warnings.warn(
           "The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
           " Please use LayoutLMv2ImageProcessor instead."  ,     snake_case__  ,     )
       super().__init__(*snake_case__  ,     **snake_case__				)



