





'''simple docstring'''







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

from ..features import Features


lowercase			:      Dict			=					TypeVar("""T""", bound="""TaskTemplate""")







@dataclass(frozen=UpperCamelCase__  )
class 				_a   (abc.ABC  ):





     '''simple docstring'''



     lowerCAmelCase_     :    str
     lowerCAmelCase_     :    ClassVar[Features]
     lowerCAmelCase_     :    ClassVar[Features]







     def  snake_case_			(							self       ,__a       )			->							T:
          return copy.deepcopy(self       )







     @property
     def  snake_case_			(							self       )			->							Features:
          return Features(**self.input_schema       ,**self.label_schema       )







     @property
     @abc.abstractmethod
     def  snake_case_			(							self       )			->							Dict[str, str]:
          raise NotImplementedError







     @classmethod
     def  snake_case_			(							cls       ,__a       )			->							T:
          snake_case :			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}       )









'''simple docstring'''







from typing import TYPE_CHECKING

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


lowercase			:      Tuple			=					{"""configuration_bert_generation""": ["""BertGenerationConfig"""]}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase			:      Tuple			=					["""BertGenerationTokenizer"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase			:      List[Any]			=					[
          """BertGenerationDecoder""",
          """BertGenerationEncoder""",
          """BertGenerationPreTrainedModel""",
          """load_tf_weights_in_bert_generation""",
      ]


if TYPE_CHECKING:
      from .configuration_bert_generation import BertGenerationConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_bert_generation import BertGenerationTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_bert_generation import (
                BertGenerationDecoder,
                BertGenerationEncoder,
                BertGenerationPreTrainedModel,
                load_tf_weights_in_bert_generation,
            )

else:
      import sys

      lowercase			:      Optional[Any]			=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



