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Fixes #1258 #1268

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Merged
merged 2 commits into from
Sep 8, 2020
Merged

Fixes #1258 #1268

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5990e62
Fixes #1258
vfdev-5 Sep 8, 2020
823503d
Merge branch 'master' into issue-1258
vfdev-5 Sep 8, 2020
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2 changes: 1 addition & 1 deletion ignite/distributed/comp_models/native.py
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Original file line number Diff line number Diff line change
Expand Up @@ -279,7 +279,7 @@ def spawn(
if LooseVersion(torch.__version__) >= LooseVersion("1.5.0"):
spawn_kwargs["start_method"] = kwargs.get("start_method", "spawn")

mp.spawn(
mp.start_processes(
_NativeDistModel._dist_worker_task_fn,
nprocs=nproc_per_node,
args=(
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6 changes: 3 additions & 3 deletions ignite/distributed/utils.py
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Expand Up @@ -285,16 +285,16 @@ def train_fn(local_rank, a, b, c, d=12):

- | "nccl" or "gloo" : `nnodes` (default, 1), `node_rank` (default, 0), `master_addr`
| (default, "127.0.0.1"), `master_port` (default, 2222), `timeout` to `dist.init_process_group`_ function
| and kwargs for `mp.spawn`_ function.
| and kwargs for `mp.start_processes`_ function.

- | "xla-tpu" : `nnodes` (default, 1), `node_rank` (default, 0) and kwargs to `xmp.spawn`_ function.

- | "horovod": `hosts` (default, None) and other kwargs to `hvd_run`_ function. Arguments `nnodes=1`
| and `node_rank=0` are tolerated and ignored, otherwise an exception is raised.

.. _dist.init_process_group: https://pytorch.org/docs/stable/distributed.html#torch.distributed.init_process_group
.. _mp.spawn: https://pytorch.org/docs/stable/multiprocessing.html#torch.multiprocessing.spawn
.. _xmp.spawn: http://pytorch.org/xla/release/1.5/index.html#torch_xla.distributed.xla_multiprocessing.spawn
.. _mp.start_processes: https://pytorch.org/docs/stable/_modules/torch/multiprocessing/spawn.html#spawn
.. _xmp.spawn: http://pytorch.org/xla/release/1.6/index.html#torch_xla.distributed.xla_multiprocessing.spawn
.. _hvd_run: https://horovod.readthedocs.io/en/latest/api.html#module-horovod.run

"""
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4 changes: 3 additions & 1 deletion tests/ignite/distributed/comp_models/test_native.py
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Expand Up @@ -276,20 +276,22 @@ def _test_dist_spawn_fn(local_rank, backend, world_size, device):
assert _model.device() == torch.device(device)


def _test__native_dist_model_spawn(backend, num_workers_per_machine, device):
def _test__native_dist_model_spawn(backend, num_workers_per_machine, device, **spawn_kwargs):
_NativeDistModel.spawn(
_test_dist_spawn_fn,
args=(backend, num_workers_per_machine, device),
kwargs_dict={},
backend=backend,
nproc_per_node=num_workers_per_machine,
**spawn_kwargs,
)


@pytest.mark.distributed
@pytest.mark.skipif("WORLD_SIZE" in os.environ, reason="Skip if launched as multiproc")
def test__native_dist_model_spawn_gloo():
_test__native_dist_model_spawn("gloo", num_workers_per_machine=4, device="cpu")
_test__native_dist_model_spawn("gloo", num_workers_per_machine=4, device="cpu", start_method="fork")


@pytest.mark.distributed
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