



from collections import OrderedDict
from typing import Mapping

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


a_      :      int    =     {
    '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			(       _lowercase				):

 """simple docstring"""



 _lowercase   :    Dict      						=					'''albert'''

 def __init__(	self		,				SCREAMING_SNAKE_CASE=3_0_0_0_0		,				SCREAMING_SNAKE_CASE=1_2_8		,				SCREAMING_SNAKE_CASE=4_0_9_6		,				SCREAMING_SNAKE_CASE=1_2		,				SCREAMING_SNAKE_CASE=1		,				SCREAMING_SNAKE_CASE=6_4		,				SCREAMING_SNAKE_CASE=1_6_3_8_4		,				SCREAMING_SNAKE_CASE=1		,				SCREAMING_SNAKE_CASE="gelu_new"		,				SCREAMING_SNAKE_CASE=0		,				SCREAMING_SNAKE_CASE=0		,				SCREAMING_SNAKE_CASE=5_1_2		,				SCREAMING_SNAKE_CASE=2		,				SCREAMING_SNAKE_CASE=0.02		,				SCREAMING_SNAKE_CASE=1e-1_2		,				SCREAMING_SNAKE_CASE=0.1		,				SCREAMING_SNAKE_CASE="absolute"		,				SCREAMING_SNAKE_CASE=0		,				SCREAMING_SNAKE_CASE=2		,				SCREAMING_SNAKE_CASE=3		,				**SCREAMING_SNAKE_CASE		,				) ->			List[Any]:
  super().__init__(pad_token_id=SCREAMING_SNAKE_CASE		,				bos_token_id=SCREAMING_SNAKE_CASE		,				eos_token_id=SCREAMING_SNAKE_CASE		,				**SCREAMING_SNAKE_CASE      )

  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			(       _lowercase				):

 """simple docstring"""



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










a_      :      str    =     6_55_21






def     __a					(		__UpperCAmelCase       ):
 a__												= 1
 a__												= 0
 for plain_chr in plain_text:
  a__												= (a + ord(__UpperCAmelCase       )) % MOD_ADLER
  a__												= (b + a) % MOD_ADLER
 return (b << 16) | a





