


"""simple docstring"""


from typing import TYPE_CHECKING

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


A     :   List[Any]			    =			{
    "configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"]
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   Optional[Any]			    =			["ConvNextFeatureExtractor"]
	A     :   Optional[int]			    =			["ConvNextImageProcessor"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   List[Any]			    =			[
	    "CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "ConvNextForImageClassification",
	    "ConvNextModel",
	    "ConvNextPreTrainedModel",
	    "ConvNextBackbone",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   List[Any]			    =			[
	    "TFConvNextForImageClassification",
	    "TFConvNextModel",
	    "TFConvNextPreTrainedModel",
	]

if TYPE_CHECKING:
	from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_convnext import ConvNextFeatureExtractor
		from .image_processing_convnext import ConvNextImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_convnext import (
		    CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ConvNextBackbone,
		    ConvNextForImageClassification,
		    ConvNextModel,
		    ConvNextPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
	import sys

	A     :   Optional[Any]			    =			_LazyModule(__name__, globals()["__file__"], _import_structure)











from typing import TYPE_CHECKING

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


UpperCAmelCase						:   Any			  =     {
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase						:   int			  =     ['''MvpTokenizerFast''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase						:   str			  =     [
				    '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''MvpForCausalLM''',
				    '''MvpForConditionalGeneration''',
				    '''MvpForQuestionAnswering''',
				    '''MvpForSequenceClassification''',
				    '''MvpModel''',
				    '''MvpPreTrainedModel''',
				]

if TYPE_CHECKING:
				from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
				from .tokenization_mvp import MvpTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_mvp_fast import MvpTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mvp import (
								    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MvpForCausalLM,
								    MvpForConditionalGeneration,
								    MvpForQuestionAnswering,
								    MvpForSequenceClassification,
								    MvpModel,
								    MvpPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase						:   List[str]			  =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




