'''simple docstring'''




from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE :  int  =						{
    """configuration_bart""": ["""BART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BartConfig""", """BartOnnxConfig"""],
    """tokenization_bart""": ["""BartTokenizer"""],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __SCREAMING_SNAKE_CASE :  Optional[Any]  =						["""BartTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __SCREAMING_SNAKE_CASE :  Union[str, Any]  =						[
      """BART_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """BartForCausalLM""",
      """BartForConditionalGeneration""",
      """BartForQuestionAnswering""",
      """BartForSequenceClassification""",
      """BartModel""",
      """BartPretrainedModel""",
      """PretrainedBartModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __SCREAMING_SNAKE_CASE :  Optional[Any]  =						[
      """TFBartForConditionalGeneration""",
      """TFBartForSequenceClassification""",
      """TFBartModel""",
      """TFBartPretrainedModel""",
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __SCREAMING_SNAKE_CASE :  Tuple  =						[
      """FlaxBartDecoderPreTrainedModel""",
      """FlaxBartForCausalLM""",
      """FlaxBartForConditionalGeneration""",
      """FlaxBartForQuestionAnswering""",
      """FlaxBartForSequenceClassification""",
      """FlaxBartModel""",
      """FlaxBartPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
  from .tokenization_bart import BartTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_bart_fast import BartTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bart import (
        BART_PRETRAINED_MODEL_ARCHIVE_LIST,
        BartForCausalLM,
        BartForConditionalGeneration,
        BartForQuestionAnswering,
        BartForSequenceClassification,
        BartModel,
        BartPretrainedModel,
        PretrainedBartModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_bart import (
        TFBartForConditionalGeneration,
        TFBartForSequenceClassification,
        TFBartModel,
        TFBartPretrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_bart import (
        FlaxBartDecoderPreTrainedModel,
        FlaxBartForCausalLM,
        FlaxBartForConditionalGeneration,
        FlaxBartForQuestionAnswering,
        FlaxBartForSequenceClassification,
        FlaxBartModel,
        FlaxBartPreTrainedModel,
    )

else:
  import sys

  __SCREAMING_SNAKE_CASE :  Union[str, Any]  =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


'''simple docstring'''




import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar

from ..features import Features


__SCREAMING_SNAKE_CASE :  Any  =						TypeVar("""T""", bound="""TaskTemplate""")

@dataclass(frozen=snake_case__					)
class 			lowerCamelCase_			(abc.ABC					):
      '''simple docstring'''

      __UpperCamelCase:						str
      __UpperCamelCase:						ClassVar[Features]
      __UpperCamelCase:						ClassVar[Features]




      def   _A			( self		:       T		,      A		:       Features ):
             return copy.deepcopy(self )




      @property
      def   _A			( self		:       List[str] ):
             return Features(**self.input_schema		,      **self.label_schema )




      @property
      @abc.abstractmethod
      def   _A			( self		:       Optional[int] ):
             raise NotImplementedError





      @classmethod
      def   _A			( cls		:       Type[T]		,      A		:       dict ):
             _UpperCAmelCase  :						Optional[Any]							   =					{f.name for f in dataclasses.fields(cls )}
             return cls(**{k: v for k, v in template_dict.items() if k in field_names} )

