



'''simple docstring'''





from typing import TYPE_CHECKING

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


_UpperCamelCase											=						{'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=						['SpeechEncoderDecoderModel']

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=						['FlaxSpeechEncoderDecoderModel']

if TYPE_CHECKING:
   from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel

else:
   import sys

   _UpperCamelCase											=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

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


_UpperCamelCase											=						logging.get_logger(__name__)

_UpperCamelCase											=						{
    'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/config.json',
    'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/config.json',
    'xlm-roberta-large-finetuned-conll02-dutch': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll02-spanish': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll03-english': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll03-german': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json'
    ),
}






class 					lowerCamelCase_    (				SCREAMING_SNAKE_CASE_     ):
  """simple docstring"""




  a_												="""xlm-roberta"""




  def __init__( self      :	Any			,	_a      :	Optional[Any]=3_0522			,	_a      :	Optional[Any]=768			,	_a      :	int=12			,	_a      :	Tuple=12			,	_a      :	str=3072			,	_a      :	List[Any]="gelu"			,	_a      :	int=0.1			,	_a      :	Optional[int]=0.1			,	_a      :	Optional[int]=512			,	_a      :	List[Any]=2			,	_a      :	Optional[Any]=0.02			,	_a      :	str=1e-12			,	_a      :	str=1			,	_a      :	str=0			,	_a      :	Optional[Any]=2			,	_a      :	Optional[int]="absolute"			,	_a      :	int=True			,	_a      :	Tuple=None			,	**_a      :	Any			,	)					->					Dict:
    super().__init__(pad_token_id=_a			,	bos_token_id=_a			,	eos_token_id=_a			,	**_a   )

    __lowerCamelCase       :       int           = vocab_size
    __lowerCamelCase       :       Union[str, Any]           = hidden_size
    __lowerCamelCase       :       int           = num_hidden_layers
    __lowerCamelCase       :       Optional[int]           = num_attention_heads
    __lowerCamelCase       :       List[str]           = hidden_act
    __lowerCamelCase       :       Any           = intermediate_size
    __lowerCamelCase       :       int           = hidden_dropout_prob
    __lowerCamelCase       :       List[Any]           = attention_probs_dropout_prob
    __lowerCamelCase       :       Optional[int]           = max_position_embeddings
    __lowerCamelCase       :       Tuple           = type_vocab_size
    __lowerCamelCase       :       Optional[int]           = initializer_range
    __lowerCamelCase       :       Optional[int]           = layer_norm_eps
    __lowerCamelCase       :       str           = position_embedding_type
    __lowerCamelCase       :       List[Any]           = use_cache
    __lowerCamelCase       :       int           = classifier_dropout






class 					lowerCamelCase_    (				SCREAMING_SNAKE_CASE_     ):
  """simple docstring"""




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






