Added distributed tests with Horovod and XLA for early_stopping

tests/ignite/handlers/test_early_stopping.py

@@ -249,7 +249,10 @@ def evaluation(engine):
 
 def _test_distrib_with_engine_early_stopping(device):
 
-    import torch.distributed as dist
+    if device is None:
+        device = idist.device()
+    if isinstance(device, str):
+        device = torch.device(device)
 
     torch.manual_seed(12)
 
@@ -264,8 +267,8 @@ def __init__(self, count=0):
     def score_function(engine):
         i = trainer.state.epoch - 1
         v = scores[i]
-        dist.all_reduce(v)
-        v /= dist.get_world_size()
+        idist.all_reduce(v)
+        v /= idist.get_world_size()
         return v.item()
 
     trainer = Engine(do_nothing_update_fn)
@@ -285,12 +288,18 @@ def evaluation(engine):
 
 def _test_distrib_integration_engine_early_stopping(device):
 
-    import torch.distributed as dist
-
     from ignite.metrics import Accuracy
 
-    rank = dist.get_rank()
-    ws = dist.get_world_size()
+    if device is None:
+        device = idist.device()
+    if isinstance(device, str):
+        device = torch.device(device)
+    metric_device = device
+    if device.type == "xla":
+        metric_device = "cpu"
+
+    rank = idist.get_rank()
+    ws = idist.get_world_size()
     torch.manual_seed(12)
 
     n_epochs = 10
@@ -314,7 +323,7 @@ def update(engine, _):
         return y_preds[e][i, rank], y_true[e][i, rank]
 
     evaluator = Engine(update)
-    acc = Accuracy(device=device)
+    acc = Accuracy(device=metric_device)
     acc.attach(evaluator, "acc")
 
     def score_function(engine):
@@ -352,6 +361,18 @@ def test_distrib_gloo_cpu_or_gpu(distributed_context_single_node_gloo):
     _test_distrib_integration_engine_early_stopping(device)
 
 
+@pytest.mark.distributed
+@pytest.mark.skipif(not idist.has_hvd_support, reason="Skip if no Horovod dist support")
+@pytest.mark.skipif("WORLD_SIZE" in os.environ, reason="Skip if launched as multiproc")
+def test_distrib_hvd(gloo_hvd_executor):
+
+    device = torch.device("cpu" if not torch.cuda.is_available() else "cuda")
+    nproc = 4 if not torch.cuda.is_available() else torch.cuda.device_count()
+
+    gloo_hvd_executor(_test_distrib_with_engine_early_stopping, (device,), np=nproc, do_init=True)
+    gloo_hvd_executor(_test_distrib_integration_engine_early_stopping, (device,), np=nproc, do_init=True)
+
+
 @pytest.mark.multinode_distributed
 @pytest.mark.skipif(not idist.has_native_dist_support, reason="Skip if no native dist support")
 @pytest.mark.skipif("MULTINODE_DISTRIB" not in os.environ, reason="Skip if not multi-node distributed")
@@ -370,3 +391,26 @@ def test_multinode_distrib_nccl_gpu(distributed_context_multi_node_nccl):
     device = idist.device()
     _test_distrib_with_engine_early_stopping(device)
     _test_distrib_integration_engine_early_stopping(device)
+
+
+@pytest.mark.tpu
+@pytest.mark.skipif("NUM_TPU_WORKERS" in os.environ, reason="Skip if NUM_TPU_WORKERS is in env vars")
+@pytest.mark.skipif(not idist.has_xla_support, reason="Skip if no PyTorch XLA package")
+def test_distrib_single_device_xla():
+    device = idist.device()
+    _test_distrib_with_engine_early_stopping(device)
+    _test_distrib_integration_engine_early_stopping(device)
+
+
+def _test_distrib_xla_nprocs(index):
+    device = idist.device()
+    _test_distrib_with_engine_early_stopping(device)
+    _test_distrib_integration_engine_early_stopping(device)
+
+
+@pytest.mark.tpu
+@pytest.mark.skipif("NUM_TPU_WORKERS" not in os.environ, reason="Skip if no NUM_TPU_WORKERS in env vars")
+@pytest.mark.skipif(not idist.has_xla_support, reason="Skip if no PyTorch XLA package")
+def test_distrib_xla_nprocs(xmp_executor):
+    n = int(os.environ["NUM_TPU_WORKERS"])
+    xmp_executor(_test_distrib_xla_nprocs, args=(), nprocs=n)