



from typing import TYPE_CHECKING

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


UpperCamelCase__ =						{
    '''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
    '''tokenization_roc_bert''': ['''RoCBertTokenizer'''],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			pass

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    '''ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''RoCBertForCausalLM''',
			    '''RoCBertForMaskedLM''',
			    '''RoCBertForMultipleChoice''',
			    '''RoCBertForPreTraining''',
			    '''RoCBertForQuestionAnswering''',
			    '''RoCBertForSequenceClassification''',
			    '''RoCBertForTokenClassification''',
			    '''RoCBertLayer''',
			    '''RoCBertModel''',
			    '''RoCBertPreTrainedModel''',
			    '''load_tf_weights_in_roc_bert''',
			]

if TYPE_CHECKING:
			from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
			from .tokenization_roc_bert import RoCBertTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						raise OptionalDependencyNotAvailable()

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_roc_bert import (
						    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    RoCBertForCausalLM,
						    RoCBertForMaskedLM,
						    RoCBertForMultipleChoice,
						    RoCBertForPreTraining,
						    RoCBertForQuestionAnswering,
						    RoCBertForSequenceClassification,
						    RoCBertForTokenClassification,
						    RoCBertLayer,
						    RoCBertModel,
						    RoCBertPreTrainedModel,
						    load_tf_weights_in_roc_bert,
						)


else:
			import sys

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










from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase			)
class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			lowercase__      :  str      =			field(default="""summarization"""    ,					metadata={"""include_in_asdict_even_if_is_default""": True}			)
			lowercase__      :  ClassVar[Features]      =			Features({"""text""": Value("""string"""			)}			)
			lowercase__      :  ClassVar[Features]      =			Features({"""summary""": Value("""string"""			)}			)
			lowercase__      :  str      =			"text"
			lowercase__      :  str      =			"summary"





			@property
			def 		snake_case__			(				self	:       List[Any]   )						->					Dict[str, str]:
									"""simple docstring"""







									return {self.text_column: "text", self.summary_column: "summary"}





