
"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase__        =		{
    "configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCamelCase__        =		[
							    "SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "Swinv2ForImageClassification",
							    "Swinv2ForMaskedImageModeling",
							    "Swinv2Model",
							    "Swinv2PreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_swinva import (
														    SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    SwinvaForImageClassification,
														    SwinvaForMaskedImageModeling,
														    SwinvaModel,
														    SwinvaPreTrainedModel,
														)


else:
							import sys

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



"""simple docstring"""







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

from ..features import ClassLabel, Features, Value
from .base import TaskTemplate




@dataclass(frozen=_lowerCamelCase)
class 			A__	(     _lowerCamelCase):
		# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
		A_						:	str           =     field(default='text-classification'	,					metadata={'include_in_asdict_even_if_is_default': True})
		A_						:	ClassVar[Features]           =     Features({'text': Value('string')})
		A_						:	ClassVar[Features]           =     Features({'labels': ClassLabel})
		A_						:	str           =     "text"
		A_						:	str           =     "labels"

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE			):
			if self.label_column not in features:
				raise ValueError(f"Column {self.label_column} is not present in features."			)
			if not isinstance(features[self.label_column]	,		_SCREAMING_SNAKE_CASE			):
				raise ValueError(f"Column {self.label_column} is not a ClassLabel."			)
			__lowerCAmelCase      :						Any						      =				copy.deepcopy(self			)
			__lowerCAmelCase      :						Dict						      =				self.label_schema.copy()
			__lowerCAmelCase      :						List[Any]						      =				features[self.label_column]
			__lowerCAmelCase      :						Dict						      =				label_schema
			return task_template







		@property
		def 							__lowerCamelCase							(				self			):
			return {
			    self.text_column: "text",
			    self.label_column: "labels",
			}