# 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_tf_available, is_torch_available, is_vision_available, ) _import_structure = { "configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"] } try: if not is_vision_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["feature_extraction_convnext"] = ["ConvNextFeatureExtractor"] _import_structure["image_processing_convnext"] = ["ConvNextImageProcessor"] try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_convnext"] = [ "CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST", "ConvNextForImageClassification", "ConvNextModel", "ConvNextPreTrainedModel", "ConvNextBackbone", ] try: if not is_tf_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_tf_convnext"] = [ "TFConvNextForImageClassification", "TFConvNextModel", "TFConvNextPreTrainedModel", ] if TYPE_CHECKING: from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig try: if not is_vision_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .feature_extraction_convnext import ConvNextFeatureExtractor from .image_processing_convnext import ConvNextImageProcessor try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_convnext import ( CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST, ConvNextBackbone, ConvNextForImageClassification, ConvNextModel, ConvNextPreTrainedModel, ) try: if not is_tf_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)