






"""simple docstring"""



from typing import TYPE_CHECKING

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


__A		:       List[str]  				=		{
    '''configuration_perceiver''': ['''PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PerceiverConfig''', '''PerceiverOnnxConfig'''],
    '''tokenization_perceiver''': ['''PerceiverTokenizer'''],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:       Optional[int]  				=		['''PerceiverFeatureExtractor''']
						__A		:       List[Any]  				=		['''PerceiverImageProcessor''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:       Dict  				=		[
						    '''PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''PerceiverForImageClassificationConvProcessing''',
						    '''PerceiverForImageClassificationFourier''',
						    '''PerceiverForImageClassificationLearned''',
						    '''PerceiverForMaskedLM''',
						    '''PerceiverForMultimodalAutoencoding''',
						    '''PerceiverForOpticalFlow''',
						    '''PerceiverForSequenceClassification''',
						    '''PerceiverLayer''',
						    '''PerceiverModel''',
						    '''PerceiverPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_perceiver import PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP, PerceiverConfig, PerceiverOnnxConfig
						from .tokenization_perceiver import PerceiverTokenizer

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_perceiver import PerceiverFeatureExtractor
												from .image_processing_perceiver import PerceiverImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_perceiver import (
												    PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    PerceiverForImageClassificationConvProcessing,
												    PerceiverForImageClassificationFourier,
												    PerceiverForImageClassificationLearned,
												    PerceiverForMaskedLM,
												    PerceiverForMultimodalAutoencoding,
												    PerceiverForOpticalFlow,
												    PerceiverForSequenceClassification,
												    PerceiverLayer,
												    PerceiverModel,
												    PerceiverPreTrainedModel,
												)

else:
						import sys

						__A		:       Optional[int]  				=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)











"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__A		:       Union[str, Any]  				=		{}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:       Dict  				=		['''NllbTokenizer''']

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:       Dict  				=		['''NllbTokenizerFast''']


if TYPE_CHECKING:
						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_nllb import NllbTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_nllb_fast import NllbTokenizerFast

else:
						import sys

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



