"""simple docstring"""


from typing import TYPE_CHECKING

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


a							={
    'configuration_markuplm': ['MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MarkupLMConfig'],
    'feature_extraction_markuplm': ['MarkupLMFeatureExtractor'],
    'processing_markuplm': ['MarkupLMProcessor'],
    'tokenization_markuplm': ['MarkupLMTokenizer'],
}

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

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a							=[
	    'MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'MarkupLMForQuestionAnswering',
	    'MarkupLMForSequenceClassification',
	    'MarkupLMForTokenClassification',
	    'MarkupLMModel',
	    'MarkupLMPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
	from .feature_extraction_markuplm import MarkupLMFeatureExtractor
	from .processing_markuplm import MarkupLMProcessor
	from .tokenization_markuplm import MarkupLMTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_markuplm_fast import MarkupLMTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_markuplm import (
		    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MarkupLMForQuestionAnswering,
		    MarkupLMForSequenceClassification,
		    MarkupLMForTokenClassification,
		    MarkupLMModel,
		    MarkupLMPreTrainedModel,
		)


else:
	import sys

	a							=_LazyModule(__name__, globals()['__file__'], _import_structure)



"""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}      )


