added version check and skipped mps tests

ignite/distributed/comp_models/base.py

@@ -3,6 +3,9 @@
 from typing import Any, Callable, cast, List, Optional, Union
 
 import torch
+from packaging.version import Version
+
+_torch_version_le_112 = Version(torch.__version__) > Version("1.12.0")
 
 
 class ComputationModel(metaclass=ABCMeta):
@@ -326,7 +329,7 @@ def get_node_rank(self) -> int:
     def device(self) -> torch.device:
         if torch.cuda.is_available():
             return torch.device("cuda")
-        if torch.backends.mps.is_available():
+        if _torch_version_le_112 and torch.backends.mps.is_available():
             return torch.device("mps")
         return torch.device("cpu")
 

tests/ignite/distributed/comp_models/test_base.py

@@ -1,9 +1,12 @@
 import pytest
 import torch
 
-from ignite.distributed.comp_models.base import _SerialModel, ComputationModel
+from ignite.distributed.comp_models.base import _torch_version_le_112, _SerialModel, ComputationModel
 
 
+@pytest.mark.skipif(
+    _torch_version_le_112 and torch.backends.mps.is_available(), reason="Temporary skip if MPS is available"
+)
 def test_serial_model():
     _SerialModel.create_from_backend()
     model = _SerialModel.create_from_context()

tests/ignite/distributed/test_auto.py

@@ -12,6 +12,7 @@
 
 import ignite.distributed as idist
 from ignite.distributed.auto import auto_dataloader, auto_model, auto_optim, DistributedProxySampler
+from ignite.distributed.comp_models.base import _torch_version_le_112
 
 
 class DummyDS(Dataset):
@@ -179,6 +180,9 @@ def _test_auto_model_optimizer(ws, device):
         assert optimizer.backward_passes_per_step == backward_passes_per_step
 
 
+@pytest.mark.skipif(
+    _torch_version_le_112 and torch.backends.mps.is_available(), reason="Temporary skip if MPS is available"
+)
 def test_auto_methods_no_dist():
     _test_auto_dataloader(1, 1, batch_size=1)
     _test_auto_dataloader(1, 1, batch_size=10, num_workers=2)

tests/ignite/distributed/test_launcher.py

@@ -8,6 +8,7 @@
 from packaging.version import Version
 
 import ignite.distributed as idist
+from ignite.distributed.comp_models.base import _torch_version_le_112
 from ignite.distributed.utils import has_hvd_support, has_native_dist_support, has_xla_support
 
 
@@ -257,6 +258,9 @@ def test_idist_parallel_n_procs_native(init_method, backend, get_fixed_dirname,
 
 
 @pytest.mark.skipif("WORLD_SIZE" in os.environ, reason="Skip if launched as multiproc")
+@pytest.mark.skipif(
+    _torch_version_le_112 and torch.backends.mps.is_available(), reason="Temporary skip if MPS is available"
+)
 def test_idist_parallel_no_dist():
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
     with idist.Parallel(backend=None) as parallel:

tests/ignite/distributed/utils/test_serial.py

@@ -1,6 +1,7 @@
 import torch
 
 import ignite.distributed as idist
+from ignite.distributed.comp_models.base import _torch_version_le_112
 from tests.ignite.distributed.utils import (
     _sanity_check,
     _test_distrib__get_max_length,
@@ -13,6 +14,9 @@
 )
 
 
+@pytest.mark.skipif(
+    _torch_version_le_112 and torch.backends.mps.is_available(), reason="Temporary skip if MPS is available"
+)
 def test_no_distrib(capsys):
     assert idist.backend() is None
     if torch.cuda.is_available():

tests/ignite/engine/test_create_supervised.py

@@ -12,6 +12,7 @@
 from torch.optim import SGD
 
 import ignite.distributed as idist
+from ignite.distributed.comp_models.base import _torch_version_le_112
 from ignite.engine import (
     _check_arg,
     create_supervised_evaluator,
@@ -307,7 +308,9 @@ def _test_create_supervised_evaluator(
     else:
         if Version(torch.__version__) >= Version("1.7.0"):
             # This is broken in 1.6.0 but will be probably fixed with 1.7.0
-            with pytest.raises(RuntimeError, match=r"Expected all tensors to be on the same device"):
+            err_msg_1 = "Expected all tensors to be on the same device"
+            err_msg_2 = "Placeholder storage has not been allocated on MPS device" 
+            with pytest.raises(RuntimeError, match=f"({err_msg_1}|{err_msg_2})"):
                 evaluator.run(data)
 
 
@@ -659,14 +662,14 @@ def test_create_supervised_evaluator_on_cuda_with_model_on_cpu():
     _test_mocked_supervised_evaluator(evaluator_device="cuda")
 
 
-@pytest.mark.skipif(not torch.backends.mps.is_available(), reason="Skip if no MPS Backend")
+@pytest.mark.skipif(not (_torch_version_le_112 and torch.backends.mps.is_available()), reason="Skip if no MPS")
 def test_create_supervised_evaluator_on_mps():
     model_device = evaluator_device = "mps"
     _test_create_supervised_evaluator(model_device=model_device, evaluator_device=evaluator_device)
     _test_mocked_supervised_evaluator(model_device=model_device, evaluator_device=evaluator_device)
 
 
-@pytest.mark.skipif(not torch.backends.mps.is_available(), reason="Skip if no MPS Backend")
+@pytest.mark.skipif(not (_torch_version_le_112 and torch.backends.mps.is_available()), reason="Skip if no MPS")
 def test_create_supervised_evaluator_on_mps_with_model_on_cpu():
     _test_create_supervised_evaluator(evaluator_device="mps")
     _test_mocked_supervised_evaluator(evaluator_device="mps")