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pytorch/test/distributed/launcher/test_run.py
Aaron Orenstein 04a85b4c21 [compile-on-one-rank] Step 1: DeviceId (#166680) 
Add a "--virtual-local-rank" mode to torchrun. When used instead of passing the
local rank in LOCAL_RANK it uses a LOCAL_RANK of "0" and adjusts
CUDA_VISIBLE_DEVICES to reflect the desired GPU index.

Testing:
(tweaked run_train.sh to use `--log-dir`)
```
export NGPU=8
export CONFIG_FILE="./torchtitan/models/llama3/train_configs/debug_model.toml"
with-proxy ./run_train.sh --model.name compiler_toolkit.llama3 --compile.enable --parallelism.data_parallel_shard_degree=2 --parallelism.tensor_parallel_degree=4
```

And then comparing ranks:

Without --virtual-local-rank gives a lot of differences like:
```
 [rank#]:        mul_1: "f32[8, 512, 256]" = torch.ops.aten.mul.Tensor(mul, view_9);  mul = None
-[rank#]:        _to_copy_3: "bf16[8, 512, 256]" = torch.ops.aten._to_copy.default(mul_1, dtype = torch.bfloat16, layout = torch.strided, device = device(type='cuda', index=0));  mul_1 = None
+[rank#]:        _to_copy_3: "bf16[8, 512, 256]" = torch.ops.aten._to_copy.default(mul_1, dtype = torch.bfloat16, layout = torch.strided, device = device(type='cuda', index=1));  mul_1 = None
 [rank#]:        detach: "f32[8, 512, 1]" = torch.ops.aten.detach.default(rsqrt);  rsqrt = None
```

With --virtual-local-rank makes those differences go away.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/166680
Approved by: https://github.com/ezyang
2025-11-10 18:47:31 +00:00

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#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import io
import multiprocessing as mp
import os
import runpy
import shutil
import subprocess
import sys
import tempfile
import uuid
from contextlib import closing, redirect_stderr, redirect_stdout
from unittest import mock, skipIf
from unittest.mock import MagicMock, Mock, patch
import torch.distributed.run as launch
from torch.distributed.elastic.agent.server.api import RunResult, WorkerState
from torch.distributed.elastic.multiprocessing import DefaultLogsSpecs
from torch.distributed.elastic.multiprocessing.errors import ChildFailedError
from torch.distributed.elastic.utils import get_socket_with_port
from torch.distributed.elastic.utils.distributed import get_free_port
from torch.testing._internal.common_utils import (
run_tests,
skip_but_pass_in_sandcastle_if,
TEST_CUDA,
TEST_WITH_DEV_DBG_ASAN,
TestCase,
)
def launch_in_proc(args):
launch.main(args)
def path(script):
return os.path.join(os.path.dirname(__file__), script)
def get_child_pids(pid):
pgrep = subprocess.Popen(args=f"pgrep -P {pid}", shell=True, stdout=subprocess.PIPE)
pgrep.wait()
out = pgrep.stdout.read().decode("utf-8").rstrip().split("\n")
pids = []
for pid in out:
if pid:
pids.append(int(pid))
return pids
def pid_exists(pid):
try:
os.kill(pid, 0)
return True
except OSError:
return False
class MockException(Exception):
pass
class ElasticLaunchTest(TestCase):
def setUp(self):
self.test_dir = tempfile.mkdtemp()
# remove any lingering environment variables
for env in os.environ.keys(): # noqa: SIM118
if env.startswith("PET_"):
del os.environ[env]
# set a sentinel env var on the parent proc
# this should be present on the child and gets
# asserted in ``bin/test_script.py``
os.environ["TEST_SENTINEL_PARENT"] = "FOOBAR"
def tearDown(self):
shutil.rmtree(self.test_dir)
def test_launch_user_script_python(self):
self._test_launch_user_script_python()
def _test_launch_user_script_python(self):
run_id = str(uuid.uuid4().int)
nnodes = 1
nproc_per_node = 4
world_size = nnodes * nproc_per_node
args = [
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_per_node}",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--start-method=spawn",
path("bin/test_script.py"),
f"--touch-file-dir={self.test_dir}",
]
launch.main(args)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
def test_launch_user_script_python_caffe2_bc(self):
nnodes = 1
nproc_per_node = 4
world_size = nnodes * nproc_per_node
sock = get_socket_with_port()
with closing(sock):
master_port = sock.getsockname()[1]
args = [
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_per_node}",
"--monitor-interval=1",
"--start-method=spawn",
"--master-addr=localhost",
f"--master-port={master_port}",
"--node-rank=0",
path("bin/test_script.py"),
f"--touch-file-dir={self.test_dir}",
]
launch.main(args)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_launch_user_script_bash(self):
run_id = str(uuid.uuid4().int)
nnodes = 1
nproc_per_node = 4
world_size = nnodes * nproc_per_node
args = [
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_per_node}",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--start-method=spawn",
"--no-python",
]
script_args = [path("bin/test_script.sh"), f"{self.test_dir}"]
with self.assertRaises(ValueError):
# --no-python cannot be used with --module
launch.main(args + ["--module"] + script_args)
launch.main(args + script_args)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_launch_user_script_default_nproc(self):
run_id = str(uuid.uuid4().int)
nnodes = 1
world_size = 1
args = [
f"--nnodes={nnodes}",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--start-method=spawn",
"--no-python",
]
script_args = [path("bin/test_script.sh"), f"{self.test_dir}"]
with self.assertRaises(ValueError):
# --no-python cannot be used with --module
launch.main(args + ["--module"] + script_args)
launch.main(args + script_args)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_launch_with_env_vars(self):
run_id = str(uuid.uuid4().int)
nnodes = 1
nproc_per_node = 4
world_size = nnodes * nproc_per_node
os.environ["PET_NNODES"] = str(nnodes)
os.environ["PET_NPROC_PER_NODE"] = str(nproc_per_node)
os.environ["PET_RDZV_ID"] = run_id
os.environ["PET_MONITOR_INTERVAL"] = "1"
os.environ["PET_START_METHOD"] = "spawn"
os.environ["PET_NO_PYTHON"] = "1"
script_args = [path("bin/test_script.sh"), f"{self.test_dir}"]
with self.assertRaises(ValueError):
# --no-python cannot be used with --module
os.environ["PET_MODULE"] = "1"
launch.main(script_args)
os.environ["PET_MODULE"] = "0"
launch.main(script_args)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
def _test_nproc_launch_configuration(self, nproc_type, expected_number):
run_id = str(uuid.uuid4().int)
nnodes = 1
args = [
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_type}",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--start-method=spawn",
"--no-python",
]
script_args = [path("bin/test_script.sh"), f"{self.test_dir}"]
launch.main(args + script_args)
world_size = nnodes * expected_number
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
@patch("torch.cuda.is_available", return_value=False)
def test_nproc_launch_auto_configurations(self, _mock1):
self._test_nproc_launch_configuration("auto", os.cpu_count())
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_nproc_launch_number_configurations(self):
self._test_nproc_launch_configuration("4", 4)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_nproc_launch_unknown_configurations(self):
with self.assertRaises(ValueError):
self._test_nproc_launch_configuration("unknown", 4)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
@patch("torch.cuda.is_available", return_value=True)
@patch("torch.cuda.device_count", return_value=3)
@patch("torch.accelerator.is_available", return_value=True)
@patch("torch.accelerator.device_count", return_value=3)
@patch("torch.accelerator.current_accelerator", return_value=MagicMock(type="gpu"))
def test_nproc_gpu_launch_configurations(
self, _mock1, _mock2, _mock3, _mock4, _mock5
):
self._test_nproc_launch_configuration("auto", 3)
self._test_nproc_launch_configuration("gpu", 3)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
@patch("torch.xpu.is_available", return_value=True)
@patch("torch.xpu.device_count", return_value=3)
@patch("torch.accelerator.is_available", return_value=True)
@patch("torch.accelerator.device_count", return_value=3)
@patch("torch.accelerator.current_accelerator", return_value=MagicMock(type="xpu"))
def test_nproc_xpu_launch_configurations(
self, _mock1, _mock2, _mock3, _mock4, _mock5
):
self._test_nproc_launch_configuration("auto", 3)
self._test_nproc_launch_configuration("xpu", 3)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_launch_elastic(self):
run_id = str(uuid.uuid4().int)
min_nodes = 1
max_nodes = 2
nproc_per_node = 4
# we are only launching 1 node (even though max = 2)
world_size = nproc_per_node
args = [
f"--nnodes={min_nodes}:{max_nodes}",
f"--nproc-per-node={nproc_per_node}",
"--rdzv-backend=c10d",
f"--rdzv-endpoint=localhost:{get_free_port()}",
"--rdzv-conf='join_timeout=5,last_call_timeout=1,timeout=5'",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--start-method=spawn",
path("bin/test_script.py"),
f"--touch-file-dir={self.test_dir}",
]
launch.main(args)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
@mock.patch("torch.distributed.elastic.events.record")
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_launch_elastic_worker_raise_exception(self, record_mock):
"""
Asserts that when the worker program fails and lancher raieses exception
to indicate that worker process failed
"""
run_id = str(uuid.uuid4().int)
min_nodes = 1
max_nodes = 2
nproc_per_node = 4
args = [
f"--nnodes={min_nodes}:{max_nodes}",
f"--nproc-per-node={nproc_per_node}",
"--rdzv-backend=c10d",
f"--rdzv-endpoint=localhost:{get_free_port()}",
"--rdzv-conf='join_timeout=5,last_call_timeout=1,timeout=5'",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--max-restarts=0",
"--start-method=spawn",
path("bin/test_script.py"),
"--fail",
]
with self.assertRaises(ChildFailedError):
launch.main(args)
record_mock.assert_called_once()
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
@mock.patch(
"torch.distributed.elastic.agent.server.local_elastic_agent.LocalElasticAgent.run"
)
@mock.patch("torch.distributed.elastic.events.record")
def test_launch_elastic_agent_raise_exception(self, record_mock, mock_agent_run):
"""
Asserts that when the agent raises an exception
the launcher re-raises the original exception
"""
run_id = str(uuid.uuid4().int)
min_nodes = 1
max_nodes = 2
nproc_per_node = 4
args = [
f"--nnodes={min_nodes}:{max_nodes}",
f"--nproc-per-node={nproc_per_node}",
"--rdzv-backend=c10d",
f"--rdzv-endpoint=localhost:{get_free_port()}",
"--rdzv_conf=timeout=5",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--max-restarts=0",
"--start-method=spawn",
path("bin/test_script.py"),
f"--touch-file-dir={self.test_dir}",
]
mock_agent_run.side_effect = MockException
with self.assertRaises(MockException):
launch.main(args)
record_mock.assert_called_once()
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_launch_standalone(self):
nnodes = 1
nproc_per_node = 4
world_size = nnodes * nproc_per_node
args = [
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_per_node}",
"--standalone",
"--monitor-interval=1",
"--start-method=spawn",
path("bin/test_script.py"),
f"--touch-file-dir={self.test_dir}",
]
launch.main(args)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_launch_run_path(self):
nnodes = 1
nproc_per_node = 4
world_size = nnodes * nproc_per_node
args = [
"--run-path",
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_per_node}",
"--monitor-interval=1",
"--start-method=spawn",
path("bin/test_script.py"),
f"--touch-file-dir={self.test_dir}",
]
launch.main(args)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_launch_elastic_multiple_agents(self):
run_id = str(uuid.uuid4().int)
min_nodes = 1
max_nodes = 2
nproc_per_node = 4
nnodes = 2
world_size = nnodes * nproc_per_node
args = [
f"--nnodes={min_nodes}:{max_nodes}",
f"--nproc-per-node={nproc_per_node}",
"--rdzv-backend=c10d",
f"--rdzv-endpoint=localhost:{get_free_port()}",
"--rdzv_conf=timeout=5",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--start-method=spawn",
path("bin/test_script.py"),
f"--touch-file-dir={self.test_dir}",
]
procs = []
for _ in range(nnodes - 1):
p = mp.Process(target=launch.main, args=[args])
procs.append(p)
p.start()
launch.main(args)
for i in range(nnodes - 1):
p = procs[i]
p.join()
self.assertEqual(0, p.exitcode)
# make sure all the workers ran
# each worker touches a file with its global rank as the name
self.assertSetEqual(
{str(i) for i in range(world_size)}, set(os.listdir(self.test_dir))
)
def test_min_max_nodes_parse(self):
min_nodes, max_nodes = launch.parse_min_max_nnodes("1")
self.assertEqual(min_nodes, max_nodes)
self.assertEqual(1, min_nodes)
min_nodes, max_nodes = launch.parse_min_max_nnodes("2:20")
self.assertEqual(2, min_nodes)
self.assertEqual(20, max_nodes)
with self.assertRaises(RuntimeError):
launch.parse_min_max_nnodes("2:20:30")
@patch("torch.distributed.launcher.api.LocalElasticAgent")
def test_launch_shutdown(self, agent_mock_cls):
nnodes = 1
nproc_per_node = 4
args = [
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_per_node}",
"--monitor-interval=1",
"--start-method=spawn",
path("bin/test_script.py"),
f"--touch-file-dir={self.test_dir}",
]
agent_mock = Mock()
agent_mock.run.return_value = RunResult(WorkerState.SUCCEEDED)
agent_mock_cls.return_value = agent_mock
rdzv_handler_mock = Mock()
with patch(
"torch.distributed.elastic.rendezvous.registry.get_rendezvous_handler"
) as param_mock:
param_mock.return_value = rdzv_handler_mock
launch.main(args)
rdzv_handler_mock.shutdown.assert_called_once()
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_is_torchelastic_launched(self):
# launch test script with torchelastic and validate that
# torch.distributed.is_torchelastic_launched() returns True
out_file = f"{os.path.join(self.test_dir, 'out')}"
launch.main(
[
"--run-path",
"--nnodes=1",
"--nproc-per-node=1",
"--monitor-interval=1",
path("bin/test_script_is_torchelastic_launched.py"),
f"--out-file={out_file}",
]
)
with open(out_file) as fp:
is_torchelastic_launched = fp.readline()
self.assertEqual("True", is_torchelastic_launched)
@patch("torch.distributed.run.metadata")
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_is_torchelastic_launched_with_logs_spec_defined(self, metadata_mock):
# mock the entrypoint API to avoid version issues.
entrypoints = MagicMock()
metadata_mock.entry_points.return_value = entrypoints
group = MagicMock()
entrypoints.select.return_value = group
ep = MagicMock()
ep.load.return_value = DefaultLogsSpecs
group.select.return_value = ep
group.__getitem__.return_value = ep
out_file = f"{os.path.join(self.test_dir, 'out')}"
if os.path.exists(out_file):
os.remove(out_file)
launch.main(
[
"--run-path",
"--nnodes=1",
"--nproc-per-node=1",
"--monitor-interval=1",
"--logs_specs=default",
path("bin/test_script_is_torchelastic_launched.py"),
f"--out-file={out_file}",
]
)
with open(out_file) as fp:
is_torchelastic_launched = fp.readline()
self.assertEqual("True", is_torchelastic_launched)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_logs_logs_spec_entrypoint_must_be_defined(self):
with self.assertRaises(ValueError):
launch.main(
[
"--run-path",
"--nnodes=1",
"--nproc-per-node=1",
"--monitor-interval=1",
"--logs_specs=DOESNOT_EXIST",
path("bin/test_script_is_torchelastic_launched.py"),
]
)
def test_is_not_torchelastic_launched(self):
# launch test script without torchelastic and validate that
# torch.distributed.is_torchelastic_launched() returns False
out_file = f"{os.path.join(self.test_dir, 'out')}"
# need to run the script with runpy in the same interpreter
# as the test because otherwise (depending on the environment)
# it will not find torch as a dependency
with patch.object(
sys,
"argv",
[
path("bin/test_script_is_torchelastic_launched.py"),
f"--out-file={out_file}",
],
):
runpy.run_path(sys.argv[0], run_name="__main__")
with open(out_file) as fp:
is_torchelastic_launched = fp.readline()
self.assertEqual("False", is_torchelastic_launched)
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_init_method_tcp_with_torchelastic(self):
port = get_free_port()
launch.main(
[
"--run-path",
"--nnodes=1",
"--nproc-per-node=4",
"--master-addr=localhost",
f"--master-port={port}",
"--monitor-interval=1",
path("bin/test_script_init_method.py"),
f"--init-method=tcp://localhost:{port}",
]
)
# nothing to validate, just make sure it runs
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
def test_init_method_env_with_torchelastic(self):
port = get_free_port()
launch.main(
[
"--run-path",
"--nnodes=1",
"--nproc-per-node=4",
"--master-addr=localhost",
f"--master-port={port}",
"--monitor-interval=1",
path("bin/test_script_init_method.py"),
"--init-method=env://",
]
)
# nothing to validate, just make sure it runs
def test_capture_logs_using_default_logs_specs(self):
run_id = str(uuid.uuid4().int)
nnodes = 1
nproc_per_node = 4
args = [
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_per_node}",
f"--rdzv-id={run_id}",
"--redirect=3",
"--tee=3",
"--monitor-interval=1",
"--start-method=spawn",
"--no-python",
]
script_args = [path("bin/test_script.sh"), f"{self.test_dir}"]
captured_out = io.StringIO()
captured_err = io.StringIO()
with redirect_stdout(captured_out), redirect_stderr(captured_err):
with patch.dict(
os.environ, {"TORCHELASTIC_LOG_LINE_PREFIX_TEMPLATE": "[rank${rank}]: "}
):
launch.main(args + script_args)
for i in range(nproc_per_node):
self.assertTrue(f"[rank{i}]: creating " in captured_out.getvalue())
@skip_but_pass_in_sandcastle_if(
TEST_WITH_DEV_DBG_ASAN, "test incompatible with dev/dbg asan"
)
@skipIf(not TEST_CUDA, "requires CUDA")
def test_virtual_local_rank(self):
"""
Test that virtual-local-rank ensures consistent device IDs across ranks.
Without it, ranks may compile to different devices, leading to different code.
"""
run_id = str(uuid.uuid4().int)
nnodes = 1
nproc_per_node = 2
# Helper function to run and capture output
def run_test(use_virtual_local_rank):
args = [
f"--nnodes={nnodes}",
f"--nproc-per-node={nproc_per_node}",
f"--rdzv-id={run_id}",
"--monitor-interval=1",
"--start-method=spawn",
"--redirect=3",
"--tee=3",
]
if use_virtual_local_rank:
args.append("--virtual-local-rank")
args.append(path("script_deviceid.py"))
captured_out = io.StringIO()
captured_err = io.StringIO()
with redirect_stdout(captured_out), redirect_stderr(captured_err):
launch.main(args)
return captured_out.getvalue()
def split_ranks(output):
default0 = []
default1 = []
for line in output.splitlines():
if "cuda:" not in line:
continue
if line.startswith("[default0]:"):
default0.append(line[11:])
elif line.startswith("[default1]:"):
default1.append(line[11:])
return default0, default1
# First, run WITHOUT virtual-local-rank - outputs should differ
output = run_test(use_virtual_local_rank=False)
rank0, rank1 = split_ranks(output)
# Verify we actually captured compiled code from both ranks
self.assertGreater(
len(rank0), 0, "Expected to capture compiled code from rank 0"
)
self.assertGreater(
len(rank1), 0, "Expected to capture compiled code from rank 1"
)
# Without virtual-local-rank, the ranks should have DIFFERENT compiled code
# because they see different device IDs (cuda:0 vs cuda:1)
self.assertNotEqual(
rank0,
rank1,
"Expected different compiled code without --virtual-local-rank",
)
# Now run WITH virtual-local-rank - outputs should be identical
output = run_test(use_virtual_local_rank=True)
rank0, rank1 = split_ranks(output)
# Verify we actually captured compiled code from both ranks
self.assertGreater(
len(rank0),
0,
"Expected to capture compiled code from rank 0 with --virtual-local-rank",
)
self.assertGreater(
len(rank1),
0,
"Expected to capture compiled code from rank 1 with --virtual-local-rank",
)
# With virtual-local-rank, both ranks should have IDENTICAL compiled code
# because they both see cuda:0 during compilation
self.assertEqual(
rank0, rank1, "Expected identical compiled code with --virtual-local-rank"
)
if __name__ == "__main__":
run_tests()
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