





"""simple docstring"""




from typing import TYPE_CHECKING

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


UpperCamelCase_           ={
    """configuration_xlm_prophetnet""": ["""XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMProphetNetConfig"""],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase_           =["""XLMProphetNetTokenizer"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase_           =[
						    """XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """XLMProphetNetDecoder""",
						    """XLMProphetNetEncoder""",
						    """XLMProphetNetForCausalLM""",
						    """XLMProphetNetForConditionalGeneration""",
						    """XLMProphetNetModel""",
						    """XLMProphetNetPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_xlm_prophetnet import (
												    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    XLMProphetNetDecoder,
												    XLMProphetNetEncoder,
												    XLMProphetNetForCausalLM,
												    XLMProphetNetForConditionalGeneration,
												    XLMProphetNetModel,
												    XLMProphetNetPreTrainedModel,
												)

else:
						import sys

						UpperCamelCase_           =_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


a							=TypeVar('T', bound='TaskTemplate')






@dataclass(frozen=__lowerCAmelCase	)
class    __UpperCAmelCase						(	abc.ABC	):
				# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
				A__      :   str
				A__      :   ClassVar[Features]
				A__      :   ClassVar[Features]

				def 		_a	(      self	, _lowerCamelCase      ):
										return copy.deepcopy(self      )

				@property
				def 		_a	(      self      ):
										return Features(**self.input_schema	, **self.label_schema      )

				@property
				@abc.abstractmethod
				def 		_a	(      self      ):
										raise NotImplementedError






				@classmethod
				def 		_a	(      cls	, _lowerCamelCase      ):
										lowerCamelCase__					={f.name for f in dataclasses.fields(cls      )}
										return cls(**{k: v for k, v in template_dict.items() if k in field_names}      )


