diff --git a/ignite/distributed/auto.py b/ignite/distributed/auto.py
index 6d617fdd..49ae70ca 100644
--- a/ignite/distributed/auto.py
+++ b/ignite/distributed/auto.py
@@ -24,7 +24,7 @@ def auto_dataloader(dataset, **kwargs):
 
     - batch size is scaled by world size: ``batch_size / world_size`` if larger or equal world size.
     - number of workers is scaled by number of local processes: ``num_workers / nprocs`` if larger or equal world size.
-    - if no sampler provided by user, `torch DistributedSampler` is setup.
+    - if no sampler provided by user, `torch DistributedSampler`_ is setup.
     - if a sampler is provided by user, it is wrapped by :class:`~ignite.distributed.auto.DistributedProxySampler`.
     - if the default device is 'cuda', `pin_memory` is automatically set to `True`.
 
@@ -122,7 +122,7 @@ def auto_dataloader(dataset, **kwargs):
     return dataloader
 
 
-def auto_model(model: nn.Module) -> nn.Module:
+def auto_model(model: nn.Module, sync_bn: bool = False) -> nn.Module:
     """Helper method to adapt provided model for non-distributed and distributed configurations (supporting
     all available backends from :meth:`~ignite.distributed.utils.available_backends()`).
 
@@ -152,12 +152,19 @@ def auto_model(model: nn.Module) -> nn.Module:
 
     Args:
         model (torch.nn.Module): model to adapt.
+        sync_bn (bool): if True, applies `torch convert_sync_batchnorm`_ to the model for native torch
+            distributed only. Default, False. Note, if using Nvidia/Apex, batchnorm conversion should be
+            applied before calling ``amp.initialize``.
 
     Returns:
         torch.nn.Module
 
-    .. _torch DistributedDataParallel: https://pytorch.org/docs/stable/nn.html#torch.nn.parallel.DistributedDataParallel
-    .. _torch DataParallel: https://pytorch.org/docs/stable/nn.html#torch.nn.DataParallel
+    .. _torch DistributedDataParallel: https://pytorch.org/docs/stable/generated/torch.nn.parallel.
+        DistributedDataParallel.html
+    .. _torch DataParallel: https://pytorch.org/docs/stable/generated/torch.nn.DataParallel.html
+    .. _torch convert_sync_batchnorm: https://pytorch.org/docs/stable/generated/torch.nn.SyncBatchNorm.html#
+        torch.nn.SyncBatchNorm.convert_sync_batchnorm
+
     """
     logger = setup_logger(__name__ + ".auto_model")
 
@@ -170,10 +177,18 @@ def auto_model(model: nn.Module) -> nn.Module:
     if idist.get_world_size() > 1:
         bnd = idist.backend()
         if idist.has_native_dist_support and bnd == idist_native.NCCL:
+            if sync_bn:
+                logger.info("Convert batch norm to sync batch norm")
+                model = nn.SyncBatchNorm.convert_sync_batchnorm(model)
+
             lrank = idist.get_local_rank()
             logger.info("Apply torch DistributedDataParallel on model, device id: {}".format(lrank))
             model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[lrank,])
         elif idist.has_native_dist_support and bnd == idist_native.GLOO:
+            if sync_bn:
+                logger.info("Convert batch norm to sync batch norm")
+                model = nn.SyncBatchNorm.convert_sync_batchnorm(model)
+
             logger.info("Apply torch DistributedDataParallel on model")
             model = torch.nn.parallel.DistributedDataParallel(model)
         elif idist.has_hvd_support and bnd == idist_hvd.HOROVOD:

Add option to replace bn by sync bn in auto_model
## 🚀 Feature

Idea is to add an option `sync_bn` (default, False) to apply [`convert_sync_batchnorm`](https://pytorch.org/docs/master/generated/torch.nn.SyncBatchNorm.html#torch.nn.SyncBatchNorm.convert_sync_batchnorm) on the input model if a DDP wrapper is used further.

- Check performances on PascalVOC
- Update ref examples

diff --git a/tests/ignite/distributed/test_auto.py b/tests/ignite/distributed/test_auto.py
index 9635572f..2caf05c1 100644
--- a/tests/ignite/distributed/test_auto.py
+++ b/tests/ignite/distributed/test_auto.py
@@ -51,14 +51,14 @@ def _test_auto_dataloader(ws, nproc, batch_size, num_workers=1, sampler_name=Non
         assert dataloader.pin_memory == ("cuda" in idist.device().type)
 
 
-def _test_auto_model_optimizer(ws, device):
-    # Test auto_model
-    model = nn.Linear(10, 10)
-    model = auto_model(model)
+def _test_auto_model(model, ws, device, sync_bn=False):
+    model = auto_model(model, sync_bn=sync_bn)
     bnd = idist.backend()
     if ws > 1 and device in ("cuda", "cpu"):
         if idist.has_native_dist_support and bnd in ("nccl" or "gloo"):
             assert isinstance(model, nn.parallel.DistributedDataParallel)
+            if sync_bn:
+                assert any([isinstance(m, nn.SyncBatchNorm) for m in model.modules()])
         elif idist.has_hvd_support and bnd in ("horovod",):
             assert isinstance(model, nn.Module)
     elif device != "cpu" and torch.cuda.is_available() and torch.cuda.device_count() > 1:
@@ -70,7 +70,17 @@ def _test_auto_model_optimizer(ws, device):
         [p.device.type for p in model.parameters()], device
     )
 
+
+def _test_auto_model_optimizer(ws, device):
+    # Test auto_model
+    model = nn.Linear(10, 10)
+    _test_auto_model(model, ws, device)
+
+    model = nn.Sequential(nn.Linear(20, 100), nn.BatchNorm1d(100))
+    _test_auto_model(model, ws, device, sync_bn="cuda" in device)
+
     # Test auto_optim
+    bnd = idist.backend()
     optimizer = optim.SGD(model.parameters(), lr=0.01)
     optimizer = auto_optim(optimizer)
     if idist.has_xla_support and "xla" in device:

pip install -e .
parse_log_pytest
requirements.txt
pytest
apt-get update apt-get install -y gcc pip install torch torchvision -f https://download.pytorch.org/whl/cpu/torch_stable.html -U
3.7
requirements-dev.txt
pytest --no-header -rA --tb=line --color=no -p no:cacheprovider -W ignore::DeprecationWarning
absl-py==2.1.0
alembic==1.12.1
arrow==1.2.3
attrs==24.2.0
boto3==1.33.13
botocore==1.33.13
bravado==11.1.0
bravado-core==6.1.1
cached-property==1.5.2
cachetools==5.5.2
certifi @ file:///croot/certifi_1671487769961/work/certifi
charset-normalizer==3.4.1
click==7.1.2
cloudpickle==2.2.1
codecov==2.1.13
coverage==7.2.7
cycler==0.11.0
databricks-cli==0.18.0
dill==0.3.7
docker==6.1.3
docker-pycreds==0.4.0
entrypoints==0.4
exceptiongroup==1.2.2
execnet==2.0.2
Flask==1.1.4
fonttools==4.38.0
fqdn==1.5.1
funcsigs==1.0.2
furl==2.1.4
future==1.0.0
gitdb==4.0.12
GitPython==3.1.44
google-auth==2.38.0
google-auth-oauthlib==0.4.6
greenlet==3.1.1
grpcio==1.62.3
gunicorn==20.1.0
gym==0.26.2
gym-notices==0.0.8
hestia==0.6.0
humanfriendly==10.0
idna==3.10
imageio==2.31.2
importlib-metadata==5.2.0
importlib-resources==5.12.0
iniconfig==2.0.0
isoduration==20.11.0
itsdangerous==1.1.0
Jinja2==2.10.3
jmespath==1.0.1
joblib==1.3.2
jsonpatch==1.33
jsonpointer==3.0.0
jsonref==1.1.0
jsonschema==4.17.3
kiwisolver==1.4.5
Mako==1.2.4
Markdown==3.4.4
MarkupSafe==2.1.5
marshmallow==3.0.0rc5
matplotlib==3.5.3
mlflow==1.30.1
monotonic==1.6
msgpack==1.0.5
neptune-client==1.11.1
networkx==2.6.3
numpy==1.21.6
oauthlib==3.2.2
orderedmultidict==1.0.1
packaging==21.3
pandas==1.3.5
pathlib2==2.3.7.post1
Pillow==9.5.0
pkgutil_resolve_name==1.3.10
platformdirs==4.0.0
pluggy==1.2.0
polyaxon-client==0.6.1
polyaxon-schemas==0.6.1
polystores==0.2.5
prometheus-client==0.17.1
prometheus_flask_exporter==0.23.2
protobuf==3.20.3
psutil==7.0.0
pyasn1==0.5.1
pyasn1-modules==0.3.0
PyJWT==2.8.0
pynvml==11.5.3
pyparsing==3.1.4
pyrsistent==0.19.3
pytest==7.4.4
pytest-cov==4.1.0
pytest-xdist==3.5.0
python-dateutil==2.9.0.post0
-e git+https://github.com/pytorch/ignite.git@789958afe49c5b7a9c8e6d51d5522db541e4000e#egg=pytorch_ignite
pytz==2022.7.1
PyWavelets==1.3.0
PyYAML==6.0.1
querystring-parser==1.2.4
requests==2.31.0
requests-file==2.1.0
requests-oauthlib==2.0.0
requests-toolbelt==1.0.0
rfc3339-validator==0.1.4
rfc3986-validator==0.1.1
rhea==0.5.5
rsa==4.9
s3transfer==0.8.2
scikit-image==0.19.3
scikit-learn==1.0.2
scipy==1.7.3
sentry-sdk==2.24.1
setproctitle==1.3.3
simplejson==3.20.1
six==1.17.0
smmap==5.0.2
SQLAlchemy==1.4.54
sqlparse==0.4.4
swagger-spec-validator==3.0.3
tabulate==0.9.0
tensorboard==2.11.2
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorboardX==2.6.2.2
threadpoolctl==3.1.0
tifffile==2021.11.2
tomli==2.0.1
torch==1.13.1+cpu
torchvision==0.14.1+cpu
tornado==6.2
tqdm==4.67.1
trains==0.16.4
typing_extensions==4.7.1
uri-template==1.3.0
urllib3==1.26.20
visdom==0.2.4
wandb==0.18.7
webcolors==1.13
websocket-client==1.6.1
Werkzeug==1.0.1
zipp==3.15.0

name: ignite
channels:
  - defaults
  - https://repo.anaconda.com/pkgs/main
  - https://repo.anaconda.com/pkgs/r
  - conda-forge
dependencies:
  - _libgcc_mutex=0.1=main
  - _openmp_mutex=5.1=1_gnu
  - ca-certificates=2025.2.25=h06a4308_0
  - certifi=2022.12.7=py37h06a4308_0
  - ld_impl_linux-64=2.40=h12ee557_0
  - libffi=3.4.4=h6a678d5_1
  - libgcc-ng=11.2.0=h1234567_1
  - libgomp=11.2.0=h1234567_1
  - libstdcxx-ng=11.2.0=h1234567_1
  - ncurses=6.4=h6a678d5_0
  - openssl=1.1.1w=h7f8727e_0
  - pip=22.3.1=py37h06a4308_0
  - python=3.7.16=h7a1cb2a_0
  - readline=8.2=h5eee18b_0
  - setuptools=65.6.3=py37h06a4308_0
  - sqlite=3.45.3=h5eee18b_0
  - tk=8.6.14=h39e8969_0
  - wheel=0.38.4=py37h06a4308_0
  - xz=5.6.4=h5eee18b_1
  - zlib=1.2.13=h5eee18b_1
  - pip:
      - absl-py==2.1.0
      - alembic==1.12.1
      - arrow==1.2.3
      - attrs==24.2.0
      - boto3==1.33.13
      - botocore==1.33.13
      - bravado==11.1.0
      - bravado-core==6.1.1
      - cached-property==1.5.2
      - cachetools==5.5.2
      - charset-normalizer==3.4.1
      - click==7.1.2
      - cloudpickle==2.2.1
      - codecov==2.1.13
      - coverage==7.2.7
      - cycler==0.11.0
      - databricks-cli==0.18.0
      - dill==0.3.7
      - docker==6.1.3
      - docker-pycreds==0.4.0
      - entrypoints==0.4
      - exceptiongroup==1.2.2
      - execnet==2.0.2
      - flask==1.1.4
      - fonttools==4.38.0
      - fqdn==1.5.1
      - funcsigs==1.0.2
      - furl==2.1.4
      - future==1.0.0
      - gitdb==4.0.12
      - gitpython==3.1.44
      - google-auth==2.38.0
      - google-auth-oauthlib==0.4.6
      - greenlet==3.1.1
      - grpcio==1.62.3
      - gunicorn==20.1.0
      - gym==0.26.2
      - gym-notices==0.0.8
      - hestia==0.6.0
      - humanfriendly==10.0
      - idna==3.10
      - imageio==2.31.2
      - importlib-metadata==5.2.0
      - importlib-resources==5.12.0
      - iniconfig==2.0.0
      - isoduration==20.11.0
      - itsdangerous==1.1.0
      - jinja2==2.10.3
      - jmespath==1.0.1
      - joblib==1.3.2
      - jsonpatch==1.33
      - jsonpointer==3.0.0
      - jsonref==1.1.0
      - jsonschema==4.17.3
      - kiwisolver==1.4.5
      - mako==1.2.4
      - markdown==3.4.4
      - markupsafe==2.1.5
      - marshmallow==3.0.0rc5
      - matplotlib==3.5.3
      - mlflow==1.30.1
      - monotonic==1.6
      - msgpack==1.0.5
      - neptune-client==1.11.1
      - networkx==2.6.3
      - numpy==1.21.6
      - oauthlib==3.2.2
      - orderedmultidict==1.0.1
      - packaging==21.3
      - pandas==1.3.5
      - pathlib2==2.3.7.post1
      - pillow==9.5.0
      - pkgutil-resolve-name==1.3.10
      - platformdirs==4.0.0
      - pluggy==1.2.0
      - polyaxon-client==0.6.1
      - polyaxon-schemas==0.6.1
      - polystores==0.2.5
      - prometheus-client==0.17.1
      - prometheus-flask-exporter==0.23.2
      - protobuf==3.20.3
      - psutil==7.0.0
      - pyasn1==0.5.1
      - pyasn1-modules==0.3.0
      - pyjwt==2.8.0
      - pynvml==11.5.3
      - pyparsing==3.1.4
      - pyrsistent==0.19.3
      - pytest==7.4.4
      - pytest-cov==4.1.0
      - pytest-xdist==3.5.0
      - python-dateutil==2.9.0.post0
      - pytorch-ignite==0.5.0
      - pytz==2022.7.1
      - pywavelets==1.3.0
      - pyyaml==6.0.1
      - querystring-parser==1.2.4
      - requests==2.31.0
      - requests-file==2.1.0
      - requests-oauthlib==2.0.0
      - requests-toolbelt==1.0.0
      - rfc3339-validator==0.1.4
      - rfc3986-validator==0.1.1
      - rhea==0.5.5
      - rsa==4.9
      - s3transfer==0.8.2
      - scikit-image==0.19.3
      - scikit-learn==1.0.2
      - scipy==1.7.3
      - sentry-sdk==2.24.1
      - setproctitle==1.3.3
      - simplejson==3.20.1
      - six==1.17.0
      - smmap==5.0.2
      - sqlalchemy==1.4.54
      - sqlparse==0.4.4
      - swagger-spec-validator==3.0.3
      - tabulate==0.9.0
      - tensorboard==2.11.2
      - tensorboard-data-server==0.6.1
      - tensorboard-plugin-wit==1.8.1
      - tensorboardx==2.6.2.2
      - threadpoolctl==3.1.0
      - tifffile==2021.11.2
      - tomli==2.0.1
      - torch==1.13.1+cpu
      - torchvision==0.14.1+cpu
      - tornado==6.2
      - tqdm==4.67.1
      - trains==0.16.4
      - typing-extensions==4.7.1
      - uri-template==1.3.0
      - urllib3==1.26.20
      - visdom==0.2.4
      - wandb==0.18.7
      - webcolors==1.13
      - websocket-client==1.6.1
      - werkzeug==1.0.1
      - zipp==3.15.0
prefix: /opt/conda/envs/ignite

tests/ignite/distributed/test_auto.py::test_auto_methods_no_dist tests/ignite/distributed/test_auto.py::test_auto_methods_gloo
tests/ignite/distributed/test_auto.py::test_dist_proxy_sampler
ignite/distributed/auto.py
ignite/distributed/auto.py