






from collections import OrderedDict
from typing import Mapping

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


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

UpperCamelCase__  :					int  						=    {
    """squeezebert/squeezebert-uncased""": (
        """https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json"""
    ),
    """squeezebert/squeezebert-mnli""": """https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json""",
    """squeezebert/squeezebert-mnli-headless""": (
        """https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json"""
    ),
}







class  lowerCamelCase_   (		a_   ):
							SCREAMING_SNAKE_CASE_     =	SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
							SCREAMING_SNAKE_CASE_     =	'squeezebert'
							def __init__(  self						:    str							,__lowerCamelCase						:    Optional[int]=3_05_22							,__lowerCamelCase						:    Any=7_68							,__lowerCamelCase						:    List[Any]=12							,__lowerCamelCase						:    Any=12							,__lowerCamelCase						:    Tuple=30_72							,__lowerCamelCase						:    Optional[Any]="gelu"							,__lowerCamelCase						:    Any=0.1							,__lowerCamelCase						:    List[str]=0.1							,__lowerCamelCase						:    int=5_12							,__lowerCamelCase						:    List[Any]=2							,__lowerCamelCase						:    Optional[int]=0.02							,__lowerCamelCase						:    List[Any]=1e-12							,__lowerCamelCase						:    Union[str, Any]=0							,__lowerCamelCase						:    Dict=7_68							,__lowerCamelCase						:    Optional[int]=4							,__lowerCamelCase						:    Optional[int]=4							,__lowerCamelCase						:    str=4							,__lowerCamelCase						:    int=1							,__lowerCamelCase						:    Tuple=4							,__lowerCamelCase						:    List[Any]=4							,**__lowerCamelCase						:    Any							,):





								'''simple docstring'''



								super().__init__(pad_token_id=lowercase__							,**lowercase__    )

								a				=	vocab_size
								a				=	hidden_size
								a				=	num_hidden_layers
								a				=	num_attention_heads
								a				=	hidden_act
								a				=	intermediate_size
								a				=	hidden_dropout_prob
								a				=	attention_probs_dropout_prob
								a				=	max_position_embeddings
								a				=	type_vocab_size
								a				=	initializer_range
								a				=	layer_norm_eps
								a				=	embedding_size
								a				=	q_groups
								a				=	k_groups
								a				=	v_groups
								a				=	post_attention_groups
								a				=	intermediate_groups
								a				=	output_groups







class  lowerCamelCase_   (		a_   ):
							@property
							def        SCREAMING_SNAKE_CASE_       (  self						:    Any    ):





								'''simple docstring'''



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






from typing import TYPE_CHECKING

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


lowerCAmelCase__							= {
    'configuration_deberta_v2': ['DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DebertaV2Config', 'DebertaV2OnnxConfig'],
    'tokenization_deberta_v2': ['DebertaV2Tokenizer'],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= ['DebertaV2TokenizerFast']

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= [
        'TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
        'TFDebertaV2ForMaskedLM',
        'TFDebertaV2ForQuestionAnswering',
        'TFDebertaV2ForSequenceClassification',
        'TFDebertaV2ForTokenClassification',
        'TFDebertaV2Model',
        'TFDebertaV2PreTrainedModel',
    ]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= [
        'DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
        'DebertaV2ForMaskedLM',
        'DebertaV2ForMultipleChoice',
        'DebertaV2ForQuestionAnswering',
        'DebertaV2ForSequenceClassification',
        'DebertaV2ForTokenClassification',
        'DebertaV2Model',
        'DebertaV2PreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_deberta_va import (
        DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
        DebertaVaConfig,
        DebertaVaOnnxConfig,
    )
    from .tokenization_deberta_va import DebertaVaTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_deberta_va import (
            TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFDebertaVaForMaskedLM,
            TFDebertaVaForQuestionAnswering,
            TFDebertaVaForSequenceClassification,
            TFDebertaVaForTokenClassification,
            TFDebertaVaModel,
            TFDebertaVaPreTrainedModel,
        )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_deberta_va import (
            DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
            DebertaVaForMaskedLM,
            DebertaVaForMultipleChoice,
            DebertaVaForQuestionAnswering,
            DebertaVaForSequenceClassification,
            DebertaVaForTokenClassification,
            DebertaVaModel,
            DebertaVaPreTrainedModel,
        )

else:
    import sys

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