


'''simple docstring'''


from typing import TYPE_CHECKING

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


lowerCamelCase__    	=     {
    'configuration_deberta': ['DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DebertaConfig', 'DebertaOnnxConfig'],
    'tokenization_deberta': ['DebertaTokenizer'],
}

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

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

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__    	=     [
						    '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

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







'''simple docstring'''


from typing import Optional
from urllib.parse import quote

import huggingface_hub as hfh
from packaging import version






def  __lowerCAmelCase (__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase = None   ):
		if version.parse(hfh.__version__   ).release < version.parse("0.11.0"   ).release:
				# old versions of hfh don't url-encode the file path
				_UpperCAmelCase		:       str								=      quote(__lowerCAmelCase   )
		return hfh.hf_hub_url(__lowerCAmelCase      , __lowerCAmelCase      , repo_type="dataset"      , revision=__lowerCAmelCase   )



