



'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


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

_lowerCamelCase	:       Optional[Any]      	=	{
    "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/config.json",
    "distilbert-base-uncased-distilled-squad": (
        "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/config.json",
    "distilbert-base-cased-distilled-squad": (
        "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json",
    "distilbert-base-multilingual-cased": (
        "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json"
    ),
    "distilbert-base-uncased-finetuned-sst-2-english": (
        "https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json"
    ),
}

class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  """distilbert"""
    _SCREAMING_SNAKE_CASE	  =  {
        """hidden_size""": """dim""",
        """num_attention_heads""": """n_heads""",
        """num_hidden_layers""": """n_layers""",
    }






    def __init__(  self      :					Union[str, Any]  ,						UpperCamelCase__      :					Optional[int]=3_0_5_2_2  ,						UpperCamelCase__      :					List[Any]=5_1_2  ,						UpperCamelCase__      :					Dict=False  ,						UpperCamelCase__      :					int=6  ,						UpperCamelCase__      :					int=1_2  ,						UpperCamelCase__      :					str=7_6_8  ,						UpperCamelCase__      :					Optional[Any]=4 * 7_6_8  ,						UpperCamelCase__      :					List[str]=0.1  ,						UpperCamelCase__      :					List[str]=0.1  ,						UpperCamelCase__      :					List[str]="gelu"  ,						UpperCamelCase__      :					Tuple=0.0_2  ,						UpperCamelCase__      :					List[Any]=0.1  ,						UpperCamelCase__      :					Any=0.2  ,						UpperCamelCase__      :					Tuple=0  ,						**UpperCamelCase__      :					List[str]  ,						):


       """simple docstring"""







       UpperCamelCase					=  vocab_size
       UpperCamelCase					=  max_position_embeddings
       UpperCamelCase					=  sinusoidal_pos_embds
       UpperCamelCase					=  n_layers
       UpperCamelCase					=  n_heads
       UpperCamelCase					=  dim
       UpperCamelCase					=  hidden_dim
       UpperCamelCase					=  dropout
       UpperCamelCase					=  attention_dropout
       UpperCamelCase					=  activation
       UpperCamelCase					=  initializer_range
       UpperCamelCase					=  qa_dropout
       UpperCamelCase					=  seq_classif_dropout
       super().__init__(**UpperCamelCase__  ,						pad_token_id=UpperCamelCase__ )

class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""





    @property
    def  A       (  self      :					int ):


       """simple docstring"""







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






'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_lowerCamelCase	:       List[Any]      	=	{
    "configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
    "tokenization_m2m_100": ["M2M100Tokenizer"],
}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase	:       int      	=	[
       "M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST",
       "M2M100ForConditionalGeneration",
       "M2M100Model",
       "M2M100PreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
   from .tokenization_mam_aaa import MaMaaaTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mam_aaa import (
          M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
          MaMaaaForConditionalGeneration,
          MaMaaaModel,
          MaMaaaPreTrainedModel,
      )


else:
   import sys

   _lowerCamelCase	:       Optional[int]      	=	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

