'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

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


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

lowercase__  :      Union[str, Any]        =					{
    "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							(	lowerCamelCase					):




  '''simple docstring'''



  lowerCAmelCase__										=	'''roformer'''






  def __init__(      self			:       List[str]  ,							UpperCAmelCase__			:       Dict=5_0000  ,							UpperCAmelCase__			:       Optional[Any]=None  ,							UpperCAmelCase__			:       List[Any]=768  ,							UpperCAmelCase__			:       Optional[int]=12  ,							UpperCAmelCase__			:       Dict=12  ,							UpperCAmelCase__			:       Optional[int]=3072  ,							UpperCAmelCase__			:       Any="gelu"  ,							UpperCAmelCase__			:       Tuple=0.1  ,							UpperCAmelCase__			:       int=0.1  ,							UpperCAmelCase__			:       Union[str, Any]=1536  ,							UpperCAmelCase__			:       Optional[int]=2  ,							UpperCAmelCase__			:       Any=0.02  ,							UpperCAmelCase__			:       Optional[Any]=1e-12  ,							UpperCAmelCase__			:       Union[str, Any]=0  ,							UpperCAmelCase__			:       Any=False  ,							UpperCAmelCase__			:       Optional[Any]=True  ,							**UpperCAmelCase__			:       Any  ,							)				->Tuple:
        super().__init__(pad_token_id=UpperCAmelCase__  ,							**UpperCAmelCase__  )

        UpperCAmelCase_            =  vocab_size
        UpperCAmelCase_            =  hidden_size if embedding_size is None else embedding_size
        UpperCAmelCase_            =  hidden_size
        UpperCAmelCase_            =  num_hidden_layers
        UpperCAmelCase_            =  num_attention_heads
        UpperCAmelCase_            =  hidden_act
        UpperCAmelCase_            =  intermediate_size
        UpperCAmelCase_            =  hidden_dropout_prob
        UpperCAmelCase_            =  attention_probs_dropout_prob
        UpperCAmelCase_            =  max_position_embeddings
        UpperCAmelCase_            =  type_vocab_size
        UpperCAmelCase_            =  initializer_range
        UpperCAmelCase_            =  layer_norm_eps
        UpperCAmelCase_            =  rotary_value
        UpperCAmelCase_            =  use_cache







class lowerCamelCase							(	lowerCamelCase					):




  '''simple docstring'''



  @property
  def  lowerCAmelCase__ (      self			:       str  )				->Mapping[str, Mapping[int, str]]:
        if self.task == "multiple-choice":
              UpperCAmelCase_            =  {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
        else:
              UpperCAmelCase_            =  {0: '''batch''', 1: '''sequence'''}
        UpperCAmelCase_            =  {0: '''batch''', 1: '''sequence'''}
        return OrderedDict(
            [
                ('''input_ids''', dynamic_axis),
                ('''attention_mask''', dynamic_axis),
                ('''token_type_ids''', dynamic_axis),
            ]  )






'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowercase__  :      Optional[Any]        =					{
    "configuration_encodec": [
        "ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EncodecConfig",
    ],
    "feature_extraction_encodec": ["EncodecFeatureExtractor"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__  :      List[str]        =					[
          "ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST",
          "EncodecModel",
          "EncodecPreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_encodec import (
          ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
          EncodecConfig,
      )
      from .feature_extraction_encodec import EncodecFeatureExtractor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_encodec import (
                ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
                EncodecModel,
                EncodecPreTrainedModel,
            )

else:
      import sys

      lowercase__  :      str        =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





