



'''simple docstring'''




from typing import TYPE_CHECKING

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


a     :    Optional[Any]      						=					{"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a     :    Union[str, Any]      						=					["""GLPNFeatureExtractor"""]
							a     :    Tuple      						=					["""GLPNImageProcessor"""]

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

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






'''simple docstring'''




from typing import TYPE_CHECKING

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


a     :    Any      						=					{
    """configuration_nezha""": ["""NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NezhaConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a     :    Any      						=					[
							    """NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """NezhaForNextSentencePrediction""",
							    """NezhaForMaskedLM""",
							    """NezhaForPreTraining""",
							    """NezhaForMultipleChoice""",
							    """NezhaForQuestionAnswering""",
							    """NezhaForSequenceClassification""",
							    """NezhaForTokenClassification""",
							    """NezhaModel""",
							    """NezhaPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_nezha import (
														    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    NezhaForMaskedLM,
														    NezhaForMultipleChoice,
														    NezhaForNextSentencePrediction,
														    NezhaForPreTraining,
														    NezhaForQuestionAnswering,
														    NezhaForSequenceClassification,
														    NezhaForTokenClassification,
														    NezhaModel,
														    NezhaPreTrainedModel,
														)


else:
							import sys

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

