
from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase							=       logging.get_logger(__name__)

__lowerCamelCase							=       {
    """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json""",
    """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json""",
    """junnyu/roformer_chinese_char_small""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json"""
    ),
    """junnyu/roformer_chinese_char_base""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_discriminator""": (
        """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_generator""": (
        """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json"""
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}






class   UpperCAmelCase		(						A_ ):
   A__					:		Tuple						     =     "roformer"



   def __init__(self		:					int    ,						snake_case__		:					Optional[Any]=5_00_00    ,						snake_case__		:					Optional[int]=None    ,						snake_case__		:					Any=7_68    ,						snake_case__		:					Optional[int]=12    ,						snake_case__		:					Optional[int]=12    ,						snake_case__		:					Union[str, Any]=30_72    ,						snake_case__		:					Optional[int]="gelu"    ,						snake_case__		:					int=0.1    ,						snake_case__		:					Dict=0.1    ,						snake_case__		:					Tuple=15_36    ,						snake_case__		:					List[str]=2    ,						snake_case__		:					str=0.02    ,						snake_case__		:					Dict=1e-12    ,						snake_case__		:					Any=0    ,						snake_case__		:					str=False    ,						snake_case__		:					Dict=True    ,						**snake_case__		:					Optional[Any]    ,						)		->	Dict:


          '''simple docstring'''


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

          snake_case       :   List[Any]							=      vocab_size
          snake_case       :   Any							=      hidden_size if embedding_size is None else embedding_size
          snake_case       :   Tuple							=      hidden_size
          snake_case       :   str							=      num_hidden_layers
          snake_case       :   int							=      num_attention_heads
          snake_case       :   Optional[int]							=      hidden_act
          snake_case       :   Optional[int]							=      intermediate_size
          snake_case       :   int							=      hidden_dropout_prob
          snake_case       :   List[str]							=      attention_probs_dropout_prob
          snake_case       :   str							=      max_position_embeddings
          snake_case       :   Union[str, Any]							=      type_vocab_size
          snake_case       :   List[Any]							=      initializer_range
          snake_case       :   Optional[int]							=      layer_norm_eps
          snake_case       :   Optional[Any]							=      rotary_value
          snake_case       :   Union[str, Any]							=      use_cache






class   UpperCAmelCase		(						A_ ):



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


          '''simple docstring'''


          if self.task == "multiple-choice":
                 snake_case       :   Any							=      {0: "batch", 1: "choice", 2: "sequence"}
          else:
                 snake_case       :   Tuple							=      {0: "batch", 1: "sequence"}
          snake_case       :   str							=      {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_dpt import DPTImageProcessor


snake_case_			  = logging.get_logger(__name__)


class       SCREAMING_SNAKE_CASE__					(__snake_case     ):





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

