



import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


_lowercase						  =		logging.get_logger(__name__)



class     _UpperCAmelCase			(       A__     ):




     def __init__(				self ,						*a__ ,						**a__):
         warnings.warn(
             '''The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
             ''' use DonutImageProcessor instead.''' ,						a__ ,						)
         super().__init__(*a__ ,						**a__)





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


_lowercase						  =		{
    "albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/config.json",
    "albert-large-v1": "https://huggingface.co/albert-large-v1/resolve/main/config.json",
    "albert-xlarge-v1": "https://huggingface.co/albert-xlarge-v1/resolve/main/config.json",
    "albert-xxlarge-v1": "https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json",
    "albert-base-v2": "https://huggingface.co/albert-base-v2/resolve/main/config.json",
    "albert-large-v2": "https://huggingface.co/albert-large-v2/resolve/main/config.json",
    "albert-xlarge-v2": "https://huggingface.co/albert-xlarge-v2/resolve/main/config.json",
    "albert-xxlarge-v2": "https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json",
}



class     _UpperCAmelCase			(       A__     ):
     UpperCamelCase__		    =				'''albert'''




     def __init__(				self ,						a__=3_0_0_0_0 ,						a__=1_2_8 ,						a__=4_0_9_6 ,						a__=1_2 ,						a__=1 ,						a__=6_4 ,						a__=1_6_3_8_4 ,						a__=1 ,						a__="gelu_new" ,						a__=0 ,						a__=0 ,						a__=5_1_2 ,						a__=2 ,						a__=0.0_2 ,						a__=1e-12 ,						a__=0.1 ,						a__="absolute" ,						a__=0 ,						a__=2 ,						a__=3 ,						**a__ ,						):
         super().__init__(pad_token_id=a__ ,						bos_token_id=a__ ,						eos_token_id=a__ ,						**a__)

         A__		 =					vocab_size
         A__		 =					embedding_size
         A__		 =					hidden_size
         A__		 =					num_hidden_layers
         A__		 =					num_hidden_groups
         A__		 =					num_attention_heads
         A__		 =					inner_group_num
         A__		 =					hidden_act
         A__		 =					intermediate_size
         A__		 =					hidden_dropout_prob
         A__		 =					attention_probs_dropout_prob
         A__		 =					max_position_embeddings
         A__		 =					type_vocab_size
         A__		 =					initializer_range
         A__		 =					layer_norm_eps
         A__		 =					classifier_dropout_prob
         A__		 =					position_embedding_type







class     _UpperCAmelCase			(       A__     ):




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