# 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, is_vision_available _import_structure = { "configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"], "configuration_maskformer_swin": ["MaskFormerSwinConfig"], } try: if not is_vision_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["feature_extraction_maskformer"] = ["MaskFormerFeatureExtractor"] _import_structure["image_processing_maskformer"] = ["MaskFormerImageProcessor"] try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_maskformer"] = [ "MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", "MaskFormerForInstanceSegmentation", "MaskFormerModel", "MaskFormerPreTrainedModel", ] _import_structure["modeling_maskformer_swin"] = [ "MaskFormerSwinBackbone", "MaskFormerSwinModel", "MaskFormerSwinPreTrainedModel", ] if TYPE_CHECKING: from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig from .configuration_maskformer_swin import MaskFormerSwinConfig try: if not is_vision_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .feature_extraction_maskformer import MaskFormerFeatureExtractor from .image_processing_maskformer import MaskFormerImageProcessor try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_maskformer import ( MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, MaskFormerForInstanceSegmentation, MaskFormerModel, MaskFormerPreTrainedModel, ) from .modeling_maskformer_swin import ( MaskFormerSwinBackbone, MaskFormerSwinModel, MaskFormerSwinPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)