def test_build_elastic_role_flag_args(self):
role = ElasticRole("test_role", no_python=False).runs("user_script.py")
self.assertEqual(
[
"-m",
"torchelastic.distributed.launch",
"--rdzv_backend",
"etcd",
"--rdzv_id",
macros.app_id,
"user_script.py",
],
role.args,
)
def test_build_elastic_role_img_root_already_in_entrypoint(self):
role = ElasticRole("test_role", no_python=False).runs(
os.path.join(macros.img_root, "user_script.py"))
self.assertEqual(
[
"-m",
"torchelastic.distributed.launch",
"--rdzv_backend",
"etcd",
"--rdzv_id",
macros.app_id,
"--role",
"test_role",
os.path.join(macros.img_root, "user_script.py"),
],
role.args,
)
def test_build_elastic_role(self):
# runs: python -m torchelastic.distributed.launch
# --nnodes 2:4
# --max_restarts 3
# --no_python True
# --rdzv_backend etcd
# --rdzv_id ${app_id}
# /bin/echo hello world
container = Container(image="test_image")
container.ports(foo=8080)
elastic_trainer = (ElasticRole(
"elastic_trainer", nnodes="2:4", max_restarts=3,
no_python=True).runs("/bin/echo",
"hello",
"world",
ENV_VAR_1="FOOBAR").on(container).replicas(2))
self.assertEqual("elastic_trainer", elastic_trainer.name)
self.assertEqual("python", elastic_trainer.entrypoint)
self.assertEqual(
[
"-m",
"torchelastic.distributed.launch",
"--nnodes",
"2:4",
"--max_restarts",
"3",
"--no_python",
"--rdzv_backend",
"etcd",
"--rdzv_id",
macros.app_id,
"--role",
"elastic_trainer",
"/bin/echo",
"hello",
"world",
],
elastic_trainer.args,
)
self.assertEqual({"ENV_VAR_1": "FOOBAR"}, elastic_trainer.env)
self.assertEqual(container, elastic_trainer.container)
self.assertEqual(2, elastic_trainer.num_replicas)
def test_build_elastic_role_override_rdzv_params(self):
role = ElasticRole(
"test_role", nnodes="2:4", rdzv_backend="zeus", rdzv_id="foobar"
).runs("user_script.py", "--script_arg", "foo")
self.assertEqual(
[
"-m",
"torchelastic.distributed.launch",
"--nnodes",
"2:4",
"--rdzv_backend",
"zeus",
"--rdzv_id",
"foobar",
"user_script.py",
"--script_arg",
"foo",
],
role.args,
)
def test_json_serialization(self):
"""
Tests that an ElasticRole can be serialized into json (dict)
then recreated as a Role. An ElasticRole is really just a builder
utility to make it easy for users to create a Role with the entrypoint
being ``torchelastic.distributed.launch``
"""
resource = Resource(cpu=1, gpu=0, memMB=512)
container = Container(image="user_image",
resources={
"default": resource
}).ports(tensorboard=8080)
elastic_role = (ElasticRole("test_role",
nnodes="2:4",
rdzv_backend="etcd",
rdzv_id="foobar").runs(
"user_script.py", "--script_arg",
"foo").on(container).replicas(3))
# this is effectively JSON
elastic_json = dataclasses.asdict(elastic_role)
container_json = elastic_json.pop("container")
resources_json = container_json.pop("resources")
container_json["resources"] = {}
for sched, resource_json in resources_json.items():
container_json["resources"][sched] = Resource(**resource_json)
role = Role(
**elastic_json,
container=Container(**container_json),
)
self.assertEqual(container, role.container)
self.assertEqual(elastic_role.name, role.name)
self.assertEqual(elastic_role.entrypoint, role.entrypoint)
self.assertEqual(
elastic_role.args,
role.args,
)
self.assertEqual(dataclasses.asdict(elastic_role),
dataclasses.asdict(role))
