





"""simple docstring"""




from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE 		=						{
    """configuration_perceiver""": ["""PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PerceiverConfig""", """PerceiverOnnxConfig"""],
    """tokenization_perceiver""": ["""PerceiverTokenizer"""],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE 		=						["""PerceiverFeatureExtractor"""]
						_SCREAMING_SNAKE_CASE 		=						["""PerceiverImageProcessor"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE 		=						[
						    """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

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








from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE 		=						{
    """configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
    """feature_extraction_mctct""": ["""MCTCTFeatureExtractor"""],
    """processing_mctct""": ["""MCTCTProcessor"""],
}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE 		=						[
						    """MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """MCTCTForCTC""",
						    """MCTCTModel""",
						    """MCTCTPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig
						from .feature_extraction_mctct import MCTCTFeatureExtractor
						from .processing_mctct import MCTCTProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mctct import MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST, MCTCTForCTC, MCTCTModel, MCTCTPreTrainedModel

else:
						import sys

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

