support mounting neuron devices for local_docker scheduler

torchx/schedulers/devices.py

@@ -6,26 +6,33 @@
 # LICENSE file in the root directory of this source tree.
 
 # pyre-strict
+from functools import partial
 import warnings
 from typing import Callable, Dict, List, Mapping
 
 from torchx.specs.api import DeviceMount
+from torchx.specs.named_resources_aws import EFA_DEVICE, NEURON_DEVICE
 
 
-def efa_to_devicemounts(num_devices: int) -> List[DeviceMount]:
+def to_devicemounts(num_devices: int, device_type: str) -> List[DeviceMount]:
     device_mounts = []
     for device_index in range(0, num_devices):
         device_mounts.append(
             DeviceMount(
-                src_path="/dev/infiniband/uverbs" + str(device_index),
-                dst_path="/dev/infiniband/uverbs" + str(device_index),
+                src_path=device_type + str(device_index),
+                dst_path=device_type + str(device_index),
             )
         )
     return device_mounts
 
 
+neuron_to_devicemounts = partial(to_devicemounts, device_type="/dev/neuron")
+efa_to_devicemounts = partial(to_devicemounts, device_type="/dev/infiniband/uverbs")
+
+
 DEVICES: Mapping[str, Callable[[int], List[DeviceMount]]] = {
-    "vpc.amazonaws.com/efa": efa_to_devicemounts,
+    EFA_DEVICE: efa_to_devicemounts,
+    NEURON_DEVICE: neuron_to_devicemounts,
 }
 
 

torchx/schedulers/test/aws_batch_scheduler_test.py

@@ -361,7 +361,10 @@ def test_resource_devices(self) -> None:
             image="",
             mounts=[],
             resource=specs.Resource(
-                cpu=1, memMB=1000, gpu=0, devices={"vpc.amazonaws.com/efa": 2}
+                cpu=1,
+                memMB=1000,
+                gpu=0,
+                devices={"vpc.amazonaws.com/efa": 2, "aws.amazon.com/neurondevice": 1},
             ),
         )
         props = _role_to_node_properties(role, 0)
@@ -379,6 +382,11 @@ def test_resource_devices(self) -> None:
                     "containerPath": "/dev/infiniband/uverbs1",
                     "permissions": ["READ", "WRITE", "MKNOD"],
                 },
+                {
+                    "hostPath": "/dev/neuron0",
+                    "containerPath": "/dev/neuron0",
+                    "permissions": ["READ", "WRITE", "MKNOD"],
+                },
             ],
         )
 

torchx/schedulers/test/devices_test.py

@@ -16,7 +16,7 @@
 
 class DevicesTest(unittest.TestCase):
     def test_get_efa(self) -> None:
-        devices = {"vpc.amazonaws.com/efa": 2}
+        devices = {"vpc.amazonaws.com/efa": 2, "aws.amazon.com/neurondevice": 1}
         self.assertEqual(
             get_device_mounts(devices),
             [
@@ -28,6 +28,7 @@ def test_get_efa(self) -> None:
                     src_path="/dev/infiniband/uverbs1",
                     dst_path="/dev/infiniband/uverbs1",
                 ),
+                DeviceMount(src_path="/dev/neuron0", dst_path="/dev/neuron0"),
             ],
         )
 

torchx/schedulers/test/docker_scheduler_test.py

@@ -161,12 +161,19 @@ def test_device_mounts(self) -> None:
     def test_resource_devices(self) -> None:
         app = _test_app()
         app.roles[0].mounts = []
-        app.roles[0].resource.devices = {"vpc.amazonaws.com/efa": 1}
+        app.roles[0].resource.devices = {
+            "vpc.amazonaws.com/efa": 1,
+            "aws.amazon.com/neurondevice": 2,
+        }
 
         info = self.scheduler.submit_dryrun(app, cfg={})
         self.assertEqual(
             info.request.containers[0].kwargs["devices"],
-            ["/dev/infiniband/uverbs0:/dev/infiniband/uverbs0:rwm"],
+            [
+                "/dev/infiniband/uverbs0:/dev/infiniband/uverbs0:rwm",
+                "/dev/neuron0:/dev/neuron0:rwm",
+                "/dev/neuron1:/dev/neuron1:rwm",
+            ],
         )
 
     @patch("os.environ", {"FOO_1": "f1", "BAR_1": "b1", "FOOBAR_1": "fb1"})

torchx/specs/named_resources_aws.py

@@ -37,6 +37,7 @@
 from torchx.specs.api import Resource
 
 EFA_DEVICE = "vpc.amazonaws.com/efa"
+NEURON_DEVICE = "aws.amazon.com/neurondevice"
 
 # ecs and ec2 have memtax and currently AWS Batch uses hard memory limits
 # so we have to account for mem tax when registering these resources for AWS
@@ -255,7 +256,11 @@ def aws_g5_48xlarge() -> Resource:
 
 def aws_trn1_2xlarge() -> Resource:
     return Resource(
-        cpu=8, gpu=0, memMB=32 * GiB, capabilities={K8S_ITYPE: "trn1.2xlarge"}
+        cpu=8,
+        gpu=0,
+        memMB=32 * GiB,
+        capabilities={K8S_ITYPE: "trn1.2xlarge"},
+        devices={NEURON_DEVICE: 1},
     )
 
 
@@ -265,7 +270,7 @@ def aws_trn1_32xlarge() -> Resource:
         gpu=0,
         memMB=512 * GiB,
         capabilities={K8S_ITYPE: "trn1.32xlarge"},
-        devices={EFA_DEVICE: 8},
+        devices={EFA_DEVICE: 8, NEURON_DEVICE: 16},
     )
 
 

torchx/specs/test/named_resources_aws_test.py

@@ -35,6 +35,7 @@
     aws_trn1_2xlarge,
     aws_trn1_32xlarge,
     EFA_DEVICE,
+    NEURON_DEVICE,
     GiB,
     K8S_ITYPE,
     NAMED_RESOURCES,
@@ -170,11 +171,13 @@ def test_aws_trn1(self) -> None:
         self.assertEqual(8, trn1_2.cpu)
         self.assertEqual(0, trn1_2.gpu)
         self.assertEqual(32 * GiB, trn1_2.memMB)
+        self.assertEqual({NEURON_DEVICE: 1}, trn1_2.devices)
 
         trn1_32 = aws_trn1_32xlarge()
         self.assertEqual(trn1_32.cpu, trn1_2.cpu * 16)
         self.assertEqual(trn1_32.gpu, trn1_2.gpu)
         self.assertEqual(trn1_32.memMB, trn1_2.memMB * 16)
+        self.assertEqual({EFA_DEVICE: 8, NEURON_DEVICE: 16}, trn1_32.devices)
 
     def test_aws_m5_2xlarge(self) -> None:
         resource = aws_m5_2xlarge()