


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

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







@dataclass(frozen=UpperCAmelCase      )
class        lowerCamelCase__	(							UpperCAmelCase      ):






			"""simple docstring"""






			_UpperCamelCase		:					str    =		field(default='audio-classification'					,	metadata={'include_in_asdict_even_if_is_default': True}      )
			_UpperCamelCase		:					ClassVar[Features]    =		Features({'audio': Audio()}      )
			_UpperCamelCase		:					ClassVar[Features]    =		Features({'labels': ClassLabel}      )
			_UpperCamelCase		:					str    =		"audio"
			_UpperCamelCase		:					str    =		"labels"




			def 				snake_case__				(							self      ,						snake_case     ):

						'''simple docstring'''


						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]      ,						snake_case     ):
									raise ValueError(F'''Column {self.label_column} is not a ClassLabel.'''     )
						UpperCamelCase__					=       copy.deepcopy(self     )
						UpperCamelCase__					=       self.label_schema.copy()
						UpperCamelCase__					=       features[self.label_column]
						UpperCamelCase__					=       label_schema
						return task_template







			@property
			def 				snake_case__				(							self     ):

						'''simple docstring'''


						return {
						    self.audio_column: "audio",
						    self.label_column: "labels",
						}






from typing import TYPE_CHECKING

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


__UpperCamelCase    		=       {
    'configuration_resnet': ['RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ResNetConfig', 'ResNetOnnxConfig']
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__UpperCamelCase    		=       [
						    'RESNET_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'ResNetForImageClassification',
						    'ResNetModel',
						    'ResNetPreTrainedModel',
						    'ResNetBackbone',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__UpperCamelCase    		=       [
						    'TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TFResNetForImageClassification',
						    'TFResNetModel',
						    'TFResNetPreTrainedModel',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__UpperCamelCase    		=       [
						    'FlaxResNetForImageClassification',
						    'FlaxResNetModel',
						    'FlaxResNetPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_resnet import (
												    RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ResNetBackbone,
												    ResNetForImageClassification,
												    ResNetModel,
												    ResNetPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_resnet import (
												    TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFResNetForImageClassification,
												    TFResNetModel,
												    TFResNetPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
						import sys

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


