
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

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


if TYPE_CHECKING:
						from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


lowercase__		    =	logging.get_logger(__name__)

lowercase__		    =	{
    "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/config.json",
    "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/config.json",
    "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json",
    "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json",
    "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json",
    "microsoft/deberta-xlarge-mnli": "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json",
}






class      snake_case__    (	__SCREAMING_SNAKE_CASE ):







		"""simple docstring"""

		lowerCamelCase							=		"""deberta"""



		def __init__(	self							:       Optional[Any]   ,     UpperCamelCase__							:       Dict=5_0265   ,     UpperCamelCase__							:       Optional[Any]=768   ,     UpperCamelCase__							:       int=12   ,     UpperCamelCase__							:       List[str]=12   ,     UpperCamelCase__							:       Dict=3072   ,     UpperCamelCase__							:       Any="gelu"   ,     UpperCamelCase__							:       Optional[int]=0.1   ,     UpperCamelCase__							:       Union[str, Any]=0.1   ,     UpperCamelCase__							:       Union[str, Any]=512   ,     UpperCamelCase__							:       str=0   ,     UpperCamelCase__							:       Tuple=0.02   ,     UpperCamelCase__							:       str=1e-7   ,     UpperCamelCase__							:       Optional[int]=False   ,     UpperCamelCase__							:       Tuple=-1   ,     UpperCamelCase__							:       List[Any]=0   ,     UpperCamelCase__							:       Dict=True   ,     UpperCamelCase__							:       List[Any]=None   ,     UpperCamelCase__							:       str=0   ,     UpperCamelCase__							:       str="gelu"   ,     **UpperCamelCase__							:       Dict   ,     )		->       int:






				"""simple docstring"""







				super().__init__(**UpperCamelCase__	)

				snake_case   :    Optional[int]			       =		hidden_size
				snake_case   :    Dict			       =		num_hidden_layers
				snake_case   :    Dict			       =		num_attention_heads
				snake_case   :    Dict			       =		intermediate_size
				snake_case   :    Tuple			       =		hidden_act
				snake_case   :    List[str]			       =		hidden_dropout_prob
				snake_case   :    Any			       =		attention_probs_dropout_prob
				snake_case   :    str			       =		max_position_embeddings
				snake_case   :    str			       =		type_vocab_size
				snake_case   :    Optional[Any]			       =		initializer_range
				snake_case   :    Optional[Any]			       =		relative_attention
				snake_case   :    Dict			       =		max_relative_positions
				snake_case   :    Optional[int]			       =		pad_token_id
				snake_case   :    int			       =		position_biased_input

				# Backwards compatibility
				if type(UpperCamelCase__	) == str:
						snake_case   :    Optional[int]			       =		[x.strip() for x in pos_att_type.lower().split('''|'''	)]

				snake_case   :    Optional[Any]			       =		pos_att_type
				snake_case   :    Tuple			       =		vocab_size
				snake_case   :    Union[str, Any]			       =		layer_norm_eps

				snake_case   :    Union[str, Any]			       =		kwargs.get('''pooler_hidden_size'''   ,     UpperCamelCase__	)
				snake_case   :    str			       =		pooler_dropout
				snake_case   :    Optional[int]			       =		pooler_hidden_act







class      snake_case__    (	__SCREAMING_SNAKE_CASE ):







		"""simple docstring"""

		@property
		def 	lowerCAmelCase							(	self							:       List[Any]	)		->       Mapping[str, Mapping[int, str]]:






				"""simple docstring"""







				if self.task == "multiple-choice":
						snake_case   :    List[Any]			       =		{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
				else:
						snake_case   :    Any			       =		{0: '''batch''', 1: '''sequence'''}
				if self._config.type_vocab_size > 0:
						return OrderedDict(
						    [('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis), ('''token_type_ids''', dynamic_axis)]	)
				else:
						return OrderedDict([('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis)]	)



		@property
		def 	lowerCAmelCase							(	self							:       List[Any]	)		->       int:






				"""simple docstring"""







				return 12



		def 	lowerCAmelCase							(	self							:       Tuple   ,     UpperCamelCase__							:       Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]   ,     UpperCamelCase__							:       int = -1   ,     UpperCamelCase__							:       int = -1   ,     UpperCamelCase__							:       int = -1   ,     UpperCamelCase__							:       bool = False   ,     UpperCamelCase__							:       Optional["TensorType"] = None   ,     UpperCamelCase__							:       int = 3   ,     UpperCamelCase__							:       int = 40   ,     UpperCamelCase__							:       int = 40   ,     UpperCamelCase__							:       "PreTrainedTokenizerBase" = None   ,     )		->       Mapping[str, Any]:






				"""simple docstring"""







				snake_case   :    int			       =		super().generate_dummy_inputs(preprocessor=UpperCamelCase__   ,     framework=UpperCamelCase__	)
				if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
						del dummy_inputs["token_type_ids"]
				return dummy_inputs









"""simple docstring"""





from typing import TYPE_CHECKING

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


_lowerCamelCase       =	{
    '''configuration_mobilenet_v1''': [
        '''MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileNetV1Config''',
        '''MobileNetV1OnnxConfig''',
    ],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase       =	['''MobileNetV1FeatureExtractor''']
    _lowerCamelCase       =	['''MobileNetV1ImageProcessor''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase       =	[
        '''MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''MobileNetV1ForImageClassification''',
        '''MobileNetV1Model''',
        '''MobileNetV1PreTrainedModel''',
        '''load_tf_weights_in_mobilenet_v1''',
    ]


if TYPE_CHECKING:
    from .configuration_mobilenet_va import (
        MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
        MobileNetVaConfig,
        MobileNetVaOnnxConfig,
    )

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
        from .image_processing_mobilenet_va import MobileNetVaImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mobilenet_va import (
            MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
            MobileNetVaForImageClassification,
            MobileNetVaModel,
            MobileNetVaPreTrainedModel,
            load_tf_weights_in_mobilenet_va,
        )


else:
    import sys

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

