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- # Copyright 2022 The HuggingFace Team. All rights reserved.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- from typing import TYPE_CHECKING
- from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
- _import_structure = {
- "configuration_upernet": ["UperNetConfig"],
- }
- try:
- if not is_torch_available():
- raise OptionalDependencyNotAvailable()
- except OptionalDependencyNotAvailable:
- pass
- else:
- _import_structure["modeling_upernet"] = [
- "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
- sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
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