



from typing import TYPE_CHECKING

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


lowerCAmelCase					:				List[str]   	={
    'configuration_segformer': ['SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SegformerConfig', 'SegformerOnnxConfig']
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase					:				Any   	=['SegformerFeatureExtractor']
		lowerCAmelCase					:				Union[str, Any]   	=['SegformerImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase					:				Optional[Any]   	=[
		    'SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'SegformerDecodeHead',
		    'SegformerForImageClassification',
		    'SegformerForSemanticSegmentation',
		    'SegformerLayer',
		    'SegformerModel',
		    'SegformerPreTrainedModel',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase					:				Optional[int]   	=[
		    'TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TFSegformerDecodeHead',
		    'TFSegformerForImageClassification',
		    'TFSegformerForSemanticSegmentation',
		    'TFSegformerModel',
		    'TFSegformerPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_segformer import SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SegformerConfig, SegformerOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_segformer import SegformerFeatureExtractor
				from .image_processing_segformer import SegformerImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_segformer import (
				    SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SegformerDecodeHead,
				    SegformerForImageClassification,
				    SegformerForSemanticSegmentation,
				    SegformerLayer,
				    SegformerModel,
				    SegformerPreTrainedModel,
				)
		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_segformer import (
				    TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFSegformerDecodeHead,
				    TFSegformerForImageClassification,
				    TFSegformerForSemanticSegmentation,
				    TFSegformerModel,
				    TFSegformerPreTrainedModel,
				)

else:
		import sys

		lowerCAmelCase					:				Tuple   	=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






from typing import TYPE_CHECKING

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


lowerCAmelCase					:				Optional[int]   	={
    'configuration_speech_to_text_2': ['SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Speech2Text2Config'],
    'processing_speech_to_text_2': ['Speech2Text2Processor'],
    'tokenization_speech_to_text_2': ['Speech2Text2Tokenizer'],
}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase					:				int   	=[
		    'SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'Speech2Text2ForCausalLM',
		    'Speech2Text2PreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
		from .processing_speech_to_text_a import SpeechaTextaProcessor
		from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_speech_to_text_a import (
				    SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SpeechaTextaForCausalLM,
				    SpeechaTextaPreTrainedModel,
				)

else:
		import sys

		lowerCAmelCase					:				Union[str, Any]   	=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

