





from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificationProcessor
from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowercase       :str       =  {
    "configuration_upernet": ["UperNetConfig"],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowercase       :Union[str, Any]       =  [
				    "UperNetForSemanticSegmentation",
				    "UperNetPreTrainedModel",
				]


if TYPE_CHECKING:
				from .configuration_upernet import UperNetConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
				import sys

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