


'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase      :      str            =					{"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      List[Any]            =					["""GLPNFeatureExtractor"""]
	_lowercase      :      Optional[Any]            =					["""GLPNImageProcessor"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      Optional[int]            =					[
	    """GLPN_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """GLPNForDepthEstimation""",
	    """GLPNLayer""",
	    """GLPNModel""",
	    """GLPNPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_glpn import GLPNFeatureExtractor
		from .image_processing_glpn import GLPNImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_glpn import (
		    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GLPNForDepthEstimation,
		    GLPNLayer,
		    GLPNModel,
		    GLPNPreTrainedModel,
		)


else:
	import sys

	_lowercase      :      Any            =					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase      :      Union[str, Any]            =					{
    """configuration_poolformer""": [
        """POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """PoolFormerConfig""",
        """PoolFormerOnnxConfig""",
    ]
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      List[Any]            =					["""PoolFormerFeatureExtractor"""]
	_lowercase      :      Any            =					["""PoolFormerImageProcessor"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      Tuple            =					[
	    """POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """PoolFormerForImageClassification""",
	    """PoolFormerModel""",
	    """PoolFormerPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_poolformer import (
	    POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    PoolFormerConfig,
	    PoolFormerOnnxConfig,
	)

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_poolformer import PoolFormerFeatureExtractor
		from .image_processing_poolformer import PoolFormerImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_poolformer import (
		    POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    PoolFormerForImageClassification,
		    PoolFormerModel,
		    PoolFormerPreTrainedModel,
		)


else:
	import sys

	_lowercase      :      Dict            =					_LazyModule(__name__, globals()["""__file__"""], _import_structure)





