

from collections import OrderedDict
from typing import Mapping

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


lowercase_     =       logging.get_logger(__name__)

lowercase_     =       {
    'google/mobilebert-uncased': 'https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json'
}





class 			__lowerCAmelCase					( SCREAMING_SNAKE_CASE							):
  _a						      =  MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
  _a						      =  """mobilebert"""




  def __init__(    self							,       lowerCAmelCase=30_522							,       lowerCAmelCase=512							,       lowerCAmelCase=24							,       lowerCAmelCase=4							,       lowerCAmelCase=512							,       lowerCAmelCase="relu"							,       lowerCAmelCase=0.0							,       lowerCAmelCase=0.1							,       lowerCAmelCase=512							,       lowerCAmelCase=2							,       lowerCAmelCase=0.02							,       lowerCAmelCase=1e-12							,       lowerCAmelCase=0							,       lowerCAmelCase=128							,       lowerCAmelCase=True							,       lowerCAmelCase=True							,       lowerCAmelCase=128							,       lowerCAmelCase=False							,       lowerCAmelCase=True							,       lowerCAmelCase=4							,       lowerCAmelCase="no_norm"							,       lowerCAmelCase=True							,       lowerCAmelCase=None							,       **lowerCAmelCase							,       )  ->			List[Any]:
        '''simple docstring'''






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

        _lowercase     	=vocab_size
        _lowercase     	=hidden_size
        _lowercase     	=num_hidden_layers
        _lowercase     	=num_attention_heads
        _lowercase     	=hidden_act
        _lowercase     	=intermediate_size
        _lowercase     	=hidden_dropout_prob
        _lowercase     	=attention_probs_dropout_prob
        _lowercase     	=max_position_embeddings
        _lowercase     	=type_vocab_size
        _lowercase     	=initializer_range
        _lowercase     	=layer_norm_eps
        _lowercase     	=embedding_size
        _lowercase     	=trigram_input
        _lowercase     	=use_bottleneck
        _lowercase     	=intra_bottleneck_size
        _lowercase     	=use_bottleneck_attention
        _lowercase     	=key_query_shared_bottleneck
        _lowercase     	=num_feedforward_networks
        _lowercase     	=normalization_type
        _lowercase     	=classifier_activation

        if self.use_bottleneck:
              _lowercase     	=intra_bottleneck_size
        else:
              _lowercase     	=hidden_size

        _lowercase     	=classifier_dropout





class 			__lowerCAmelCase					( SCREAMING_SNAKE_CASE							):




  @property
  def   A__					(    self )  ->			Mapping[str, Mapping[int, str]]:
        '''simple docstring'''






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



import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


lowercase_     =       logging.get_logger(__name__)





class 			__lowerCAmelCase					( SCREAMING_SNAKE_CASE							):




  def __init__(    self							,       *lowerCAmelCase							,       **lowerCAmelCase )  ->			None:
        '''simple docstring'''






        warnings.warn(
            'The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
            ' use ViTImageProcessor instead.'							,       lowerCAmelCase							,       )
        super().__init__(*lowerCAmelCase							,       **lowerCAmelCase )


