




"""simple docstring"""






from typing import TYPE_CHECKING

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


lowercase__  		=		{
    """configuration_deberta""": ["""DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DebertaConfig""", """DebertaOnnxConfig"""],
    """tokenization_deberta""": ["""DebertaTokenizer"""],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__  		=		["""DebertaTokenizerFast"""]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__  		=		[
			    """DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """DebertaForMaskedLM""",
			    """DebertaForQuestionAnswering""",
			    """DebertaForSequenceClassification""",
			    """DebertaForTokenClassification""",
			    """DebertaModel""",
			    """DebertaPreTrainedModel""",
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__  		=		[
			    """TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """TFDebertaForMaskedLM""",
			    """TFDebertaForQuestionAnswering""",
			    """TFDebertaForSequenceClassification""",
			    """TFDebertaForTokenClassification""",
			    """TFDebertaModel""",
			    """TFDebertaPreTrainedModel""",
			]


if TYPE_CHECKING:
			from .configuration_deberta import DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaConfig, DebertaOnnxConfig
			from .tokenization_deberta import DebertaTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_deberta_fast import DebertaTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_deberta import (
						    DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
						    DebertaForMaskedLM,
						    DebertaForQuestionAnswering,
						    DebertaForSequenceClassification,
						    DebertaForTokenClassification,
						    DebertaModel,
						    DebertaPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_deberta import (
						    TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFDebertaForMaskedLM,
						    TFDebertaForQuestionAnswering,
						    TFDebertaForSequenceClassification,
						    TFDebertaForTokenClassification,
						    TFDebertaModel,
						    TFDebertaPreTrainedModel,
						)


else:
			import sys

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





"""simple docstring"""






def   _snake_case    (       lowercase__	):
				return "".join(chr(ord(lowercase__	) - 32	) if 'a' <= char <= 'z' else char for char in word	)


if __name__ == "__main__":
			from doctest import testmod

			testmod()