





from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase__   : List[Any]					  = logging.get_logger(__name__)

UpperCamelCase__   : Optional[Any]					  = {
    """facebook/data2vec-text-base""": """https://huggingface.co/data2vec/resolve/main/config.json""",
}







class   _UpperCamelCase  (       A_  ):







					'''simple docstring'''

					lowerCamelCase     :     str			    =       'data2vec-text'





					def __init__(						self    :  Tuple ,					__lowercase    :  str=3_05_22 ,					__lowercase    :  Optional[Any]=7_68 ,					__lowercase    :  Any=12 ,					__lowercase    :  List[Any]=12 ,					__lowercase    :  Optional[Any]=30_72 ,					__lowercase    :  List[Any]="gelu" ,					__lowercase    :  List[str]=0.1 ,					__lowercase    :  Optional[Any]=0.1 ,					__lowercase    :  Optional[Any]=5_12 ,					__lowercase    :  Optional[Any]=2 ,					__lowercase    :  Any=0.02 ,					__lowercase    :  Union[str, Any]=1e-12 ,					__lowercase    :  int=1 ,					__lowercase    :  Optional[Any]=0 ,					__lowercase    :  Any=2 ,					__lowercase    :  List[str]="absolute" ,					__lowercase    :  List[str]=True ,					__lowercase    :  Tuple=None ,					**__lowercase    :  Optional[Any] ,					):






						'''simple docstring'''







						super().__init__(pad_token_id=__lowercase ,					bos_token_id=__lowercase ,					eos_token_id=__lowercase ,					**__lowercase		)

						UpperCAmelCase_								=     vocab_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_								=     position_embedding_type
						UpperCAmelCase_								=     use_cache
						UpperCAmelCase_								=     classifier_dropout







class   _UpperCamelCase  (       A_  ):







					'''simple docstring'''

					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''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),
						    ]		)









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__   : List[Any]					  = {"""configuration_sew""": ["""SEW_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWConfig"""]}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__   : List[str]					  = [
				    """SEW_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """SEWForCTC""",
				    """SEWForSequenceClassification""",
				    """SEWModel""",
				    """SEWPreTrainedModel""",
				]

if TYPE_CHECKING:
				from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_sew import (
								    SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SEWForCTC,
								    SEWForSequenceClassification,
								    SEWModel,
								    SEWPreTrainedModel,
								)


else:
				import sys

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


