


from typing import TYPE_CHECKING

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


_A							     =       {
    """configuration_segformer""": ["""SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SegformerConfig""", """SegformerOnnxConfig"""]
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A							     =       ["""SegformerFeatureExtractor"""]
			_A							     =       ["""SegformerImageProcessor"""]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A							     =       [
			    """SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """SegformerDecodeHead""",
			    """SegformerForImageClassification""",
			    """SegformerForSemanticSegmentation""",
			    """SegformerLayer""",
			    """SegformerModel""",
			    """SegformerPreTrainedModel""",
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A							     =       [
			    """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

			_A							     =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


"""simple docstring"""

from typing import TYPE_CHECKING

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


a__			:						str							=			{
    """configuration_rwkv""": ["""RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RwkvConfig""", """RwkvOnnxConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a__			:						Optional[int]							=			[
							    """RWKV_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """RwkvForCausalLM""",
							    """RwkvModel""",
							    """RwkvPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_rwkv import (
														    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
														    RwkvForCausalLM,
														    RwkvModel,
														    RwkvPreTrainedModel,
														)
else:
							import sys

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


