




"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

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


_A													=      logging.get_logger(__name__)

_A													=      {
    '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 _lowerCamelCase    (					UpperCamelCase__						):
   _lowerCamelCase    :Any     				=     "roformer"






   def __init__(		self       :		Union[str, Any]   ,     UpperCamelCase       :		int=5_00_00   ,     UpperCamelCase       :		Optional[Any]=None   ,     UpperCamelCase       :		Union[str, Any]=7_68   ,     UpperCamelCase       :		Optional[Any]=12   ,     UpperCamelCase       :		List[Any]=12   ,     UpperCamelCase       :		int=30_72   ,     UpperCamelCase       :		Tuple="gelu"   ,     UpperCamelCase       :		Optional[int]=0.1   ,     UpperCamelCase       :		List[str]=0.1   ,     UpperCamelCase       :		Dict=15_36   ,     UpperCamelCase       :		int=2   ,     UpperCamelCase       :		Dict=0.02   ,     UpperCamelCase       :		str=1E-1_2   ,     UpperCamelCase       :		List[str]=0   ,     UpperCamelCase       :		str=False   ,     UpperCamelCase       :		Any=True   ,     **UpperCamelCase       :		Optional[Any]   ,     )			->						Tuple:

         """simple docstring"""
         super().__init__(pad_token_id=__lowerCamelCase   ,     **__lowerCamelCase   )

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






class _lowerCamelCase    (					UpperCamelCase__						):






   @property
   def 	_lowerCAmelCase   (		self       :		Any   )			->						List[str]:

         """simple docstring"""
         if self.task == "multiple-choice":
               lowerCAmelCase__      :			Optional[int]   =	{0: """batch""", 1: """choice""", 2: """sequence"""}
         else:
               lowerCAmelCase__      :			int   =	{0: """batch""", 1: """sequence"""}
         lowerCAmelCase__      :			int   =	{0: """batch""", 1: """sequence"""}
         return OrderedDict(
             [
                 ("""input_ids""", dynamic_axis),
                 ("""attention_mask""", dynamic_axis),
                 ("""token_type_ids""", dynamic_axis),
             ]   )











"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


_A													=      logging.get_logger(__name__)


class _lowerCamelCase    (					a_						):






   def __init__(		self       :		Union[str, Any]   ,     *UpperCamelCase       :		int   ,     **UpperCamelCase       :		List[Any]   )			->						None:

         """simple docstring"""
         warnings.warn(
             """The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
             """ use CLIPImageProcessor instead."""   ,     UpperCamelCase   ,     )
         super().__init__(*UpperCamelCase   ,     **UpperCamelCase   )





