[test] use workaround to enable rpc tests when cuda not available (#541)

fairscale/utils/testing.py

@@ -149,7 +149,12 @@ def dist_init(rank: int, world_size: int, filename: str, filename_rpc: str = "")
         tp_options = {"init_method": url_rpc}
         # Workaround for bug in torch v1.8.0. Should be fixed in v1.8.1
         if torch_version() == (1, 8, 0):
-            tp_options["_transports"] = ["uv"]  # type: ignore
+            if torch.cuda.is_available():
+                # Workaround for https://github.com/pytorch/pytorch/issues/53844
+                tp_options["_transports"] = ["ibv", "uv"]  # type: ignore
+            else:
+                # Workaround for https://github.com/pytorch/pytorch/issues/54266
+                tp_options["_channels"] = ["mpt_uv", "basic", "cuda_ipc", "cuda_gdr", "cuda_xth", "cuda_basic"]  # type: ignore
 
         rpc.init_rpc(
             f"Test{rank}",

tests/experimental/nn/ampnet_pipe_process/test_ampnet_pipe.py

@@ -17,21 +17,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pytest
 import torch
 from torch import nn
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader, Dataset
 
 from fairscale.experimental.nn.ampnet_pipe.pipe import AMPnetPipe
-from fairscale.utils.testing import get_worker_map, torch_spawn, torch_version
-
-# Current on CI, there appears to be a bug with torch 1.8
-# See:
-# https://app.circleci.com/pipelines/github/facebookresearch/fairscale/1892/workflows/8f658bf4-8052-4084-bb3e-4cc2c445c8aa/jobs/10080/parallel-runs/0/steps/0-112
-# So we skip this file in that case until it is fixed.
-if torch_version() >= (1, 8, 0):
-    pytestmark = pytest.mark.skip
+from fairscale.utils.testing import get_worker_map, torch_spawn
 
 
 class MySGD(Optimizer):

tests/experimental/nn/test_multiprocess_pipe.py

@@ -30,27 +30,20 @@ if torch.cuda.is_available():
 else:
     DEVICES = [CPU_DEVICES]
 
-# cuda test is because of https://github.com/pytorch/pytorch/issues/54266
-pytestmark = pytest.mark.skipif(
-    not torch.cuda.is_available() or torch_version() < (1, 8, 0), reason="requires torch version >= 1.8.0 and cuda"
-)
+pytestmark = pytest.mark.skipif(torch_version() < (1, 8, 0), reason="requires torch version >= 1.8.0")
 
 
 def rpc_worker(rank, world_size, init_file, func, *args):
-    # Workaround for https://github.com/pytorch/pytorch/issues/54266
-    if not torch.cuda.is_available():
-        options = rpc.ProcessGroupRpcBackendOptions(init_method="file://" + init_file)
-        rpc.init_rpc(
-            "worker" + str(rank),
-            rank=rank,
-            world_size=world_size,
-            backend=rpc.BackendType.PROCESS_GROUP,
-            rpc_backend_options=options,
-        )
-    else:
-        # Workaround for https://github.com/pytorch/pytorch/issues/53844
     if torch_version() == (1, 8, 0):
+        if torch.cuda.is_available():
+            # Workaround for https://github.com/pytorch/pytorch/issues/53844
             options = rpc.TensorPipeRpcBackendOptions(init_method="file://" + init_file, _transports=["ibv", "uv"])
+        else:
+            # Workaround for https://github.com/pytorch/pytorch/issues/54266
+            options = rpc.TensorPipeRpcBackendOptions(
+                init_method="file://" + init_file,
+                _channels=["mpt_uv", "basic", "cuda_ipc", "cuda_gdr", "cuda_xth", "cuda_basic"],
+            )
     else:
         options = rpc.TensorPipeRpcBackendOptions(init_method="file://" + init_file)
     rpc.init_rpc(

tests/nn/pipe_process/test_pipe.py

@@ -34,13 +34,6 @@ from fairscale.nn.model_parallel.initialize import (
 from fairscale.nn.pipe import AsyncPipe, LazyModule, MultiProcessPipe
 from fairscale.utils.testing import get_worker_map, torch_spawn, torch_version
 
-# Current on CI, there appears to be a bug with torch 1.8
-# See:
-# https://app.circleci.com/pipelines/github/facebookresearch/fairscale/1892/workflows/8f658bf4-8052-4084-bb3e-4cc2c445c8aa/jobs/10080/parallel-runs/0/steps/0-112
-# So we skip this file in that case until it is fixed.
-if torch_version() >= (1, 8, 0):
-    pytestmark = pytest.mark.skip
-
 
 @torch_spawn([2])
 @pytest.mark.parametrize("pipe_class", [MultiProcessPipe, AsyncPipe])