# What does this PR do?

[Sorry for the spams, GitHub had some issues]

Same as #24075, but that PR got freezed after I force pushed (after rebase), and my changes to address the comments were not able to appear)

(amy have already approved #24075)

----

Byebye!

EOL of python 3.7 is `2023/06/27`.

https://endoflife.date/python
⚠️ Time to say goodbye to py37. # What does this PR do?

[Sorry for the spams, GitHub had some issues]

Same as #24075, but that PR got freezed after I force pushed (after rebase), and my changes to address the comments were not able to appear)

(amy have already approved #24075)

----

Byebye!

EOL of python 3.7 is `2023/06/27`.

https://endoflife.date/python
# 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_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfig", "ResNetOnnxConfig"]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_resnet"] = [
        "RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ResNetForImageClassification",
        "ResNetModel",
        "ResNetPreTrainedModel",
        "ResNetBackbone",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_tf_resnet"] = [
        "TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFResNetForImageClassification",
        "TFResNetModel",
        "TFResNetPreTrainedModel",
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_flax_resnet"] = [
        "FlaxResNetForImageClassification",
        "FlaxResNetModel",
        "FlaxResNetPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_resnet import (
            RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            ResNetBackbone,
            ResNetForImageClassification,
            ResNetModel,
            ResNetPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_resnet import (
            TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFResNetForImageClassification,
            TFResNetModel,
            TFResNetPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)

# 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_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfig", "ResNetOnnxConfig"]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_resnet"] = [
        "RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ResNetForImageClassification",
        "ResNetModel",
        "ResNetPreTrainedModel",
        "ResNetBackbone",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_tf_resnet"] = [
        "TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFResNetForImageClassification",
        "TFResNetModel",
        "TFResNetPreTrainedModel",
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_flax_resnet"] = [
        "FlaxResNetForImageClassification",
        "FlaxResNetModel",
        "FlaxResNetPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_resnet import (
            RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            ResNetBackbone,
            ResNetForImageClassification,
            ResNetModel,
            ResNetPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_resnet import (
            TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFResNetForImageClassification,
            TFResNetModel,
            TFResNetPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)
