
from typing import TYPE_CHECKING

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


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

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

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

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A				=[
			    '''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

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




from abc import ABC, abstractmethod
from argparse import ArgumentParser




class     _SCREAMING_SNAKE_CASE     (      snake_case_						):



	@staticmethod
	@abstractmethod
	def     SCREAMING_SNAKE_CASE_(    lowercase )				->       int:
					raise NotImplementedError()



	@abstractmethod
	def     SCREAMING_SNAKE_CASE_(    self )				->       Union[str, Any]:
					raise NotImplementedError()


