


from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


SCREAMING_SNAKE_CASE__					:     List[Any]       =     {
    'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
    'susnato/ernie-m-large_pytorch': 'https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json',
}


class 		_SCREAMING_SNAKE_CASE     (						A     ):
     __SCREAMING_SNAKE_CASE     					=    '''ernie_m'''
     __SCREAMING_SNAKE_CASE     					=    {"dropout": "classifier_dropout", "num_classes": "num_labels"}


     def __init__(  self							,					A_ = 25_00_02							,					A_ = 7_68							,					A_ = 12							,					A_ = 12							,					A_ = 30_72							,					A_ = "gelu"							,					A_ = 0.1							,					A_ = 0.1							,					A_ = 5_14							,					A_ = 0.0_2							,					A_ = 1							,					A_ = 1e-05							,					A_=None							,					A_=False							,					A_=0.0							,					**A_							,					):
       super().__init__(pad_token_id=A_							,					**A_    )
       _UpperCAmelCase		:							Tuple							=     vocab_size
       _UpperCAmelCase		:							List[str]							=     hidden_size
       _UpperCAmelCase		:							Optional[int]							=     num_hidden_layers
       _UpperCAmelCase		:							Tuple							=     num_attention_heads
       _UpperCAmelCase		:							Dict							=     intermediate_size
       _UpperCAmelCase		:							List[Any]							=     hidden_act
       _UpperCAmelCase		:							Any							=     hidden_dropout_prob
       _UpperCAmelCase		:							Any							=     attention_probs_dropout_prob
       _UpperCAmelCase		:							Tuple							=     max_position_embeddings
       _UpperCAmelCase		:							Dict							=     initializer_range
       _UpperCAmelCase		:							Optional[Any]							=     layer_norm_eps
       _UpperCAmelCase		:							str							=     classifier_dropout
       _UpperCAmelCase		:							Any							=     is_decoder
       _UpperCAmelCase		:							Union[str, Any]							=     act_dropout









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__					:     Optional[Any]       =     {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE__					:     List[str]       =     [
     'SEW_PRETRAINED_MODEL_ARCHIVE_LIST',
     'SEWForCTC',
     'SEWForSequenceClassification',
     'SEWModel',
     'SEWPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_sew import (
      SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
      SEWForCTC,
      SEWForSequenceClassification,
      SEWModel,
      SEWPreTrainedModel,
  )


else:
 import sys

 SCREAMING_SNAKE_CASE__					:     Tuple       =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





