
from collections import OrderedDict
from typing import Mapping

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


lowercase__		:List[str]			  =   logging.get_logger(__name__)

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







class     lowercase		( __UpperCamelCase		):
       lowercase_	:	List[str]	 ='''data2vec-text'''




       def __init__(    self       ,A__=3_0_5_2_2       ,A__=7_6_8       ,A__=1_2       ,A__=1_2       ,A__=3_0_7_2       ,A__="gelu"       ,A__=0.1       ,A__=0.1       ,A__=5_1_2       ,A__=2       ,A__=0.02       ,A__=1E-12       ,A__=1       ,A__=0       ,A__=2       ,A__="absolute"       ,A__=True       ,A__=None       ,**A__       ,):
            super().__init__(pad_token_id=A__       ,bos_token_id=A__       ,eos_token_id=A__       ,**A__)

            lowercase						     =						vocab_size
            lowercase						     =						hidden_size
            lowercase						     =						num_hidden_layers
            lowercase						     =						num_attention_heads
            lowercase						     =						hidden_act
            lowercase						     =						intermediate_size
            lowercase						     =						hidden_dropout_prob
            lowercase						     =						attention_probs_dropout_prob
            lowercase						     =						max_position_embeddings
            lowercase						     =						type_vocab_size
            lowercase						     =						initializer_range
            lowercase						     =						layer_norm_eps
            lowercase						     =						position_embedding_type
            lowercase						     =						use_cache
            lowercase						     =						classifier_dropout







class     lowercase		( __UpperCamelCase		):




       @property
       def 			A__				(    self):
            if self.task == "multiple-choice":
                 lowercase						     =						{0: 'batch', 1: 'choice', 2: 'sequence'}
            else:
                 lowercase						     =						{0: 'batch', 1: 'sequence'}
            return OrderedDict(
                [
                    ('''input_ids''', dynamic_axis),
                    ('''attention_mask''', dynamic_axis),
                ])






from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


lowercase__		:Union[str, Any]			  =   {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"]}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:List[Any]			  =   ["DPTFeatureExtractor"]
							lowercase__		:List[Any]			  =   ["DPTImageProcessor"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Optional[int]			  =   [
							    "DPT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "DPTForDepthEstimation",
							    "DPTForSemanticSegmentation",
							    "DPTModel",
							    "DPTPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_dpt import DPTFeatureExtractor
														from .image_processing_dpt import DPTImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_dpt import (
														    DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DPTForDepthEstimation,
														    DPTForSemanticSegmentation,
														    DPTModel,
														    DPTPreTrainedModel,
														)


else:
							import sys

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




