# 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_flax_available, is_tf_available, is_torch_available, ) _import_structure = {"configuration_regnet": ["REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "RegNetConfig"]} try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_regnet"] = [ "REGNET_PRETRAINED_MODEL_ARCHIVE_LIST", "RegNetForImageClassification", "RegNetModel", "RegNetPreTrainedModel", ] try: if not is_tf_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_tf_regnet"] = [ "TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST", "TFRegNetForImageClassification", "TFRegNetModel", "TFRegNetPreTrainedModel", ] try: if not is_flax_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_flax_regnet"] = [ "FlaxRegNetForImageClassification", "FlaxRegNetModel", "FlaxRegNetPreTrainedModel", ] if TYPE_CHECKING: from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_regnet import ( REGNET_PRETRAINED_MODEL_ARCHIVE_LIST, RegNetForImageClassification, RegNetModel, RegNetPreTrainedModel, ) try: if not is_tf_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_tf_regnet import ( TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST, TFRegNetForImageClassification, TFRegNetModel, TFRegNetPreTrainedModel, ) try: if not is_flax_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_flax_regnet import ( FlaxRegNetForImageClassification, FlaxRegNetModel, FlaxRegNetPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)