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Mar 12, 2025
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Add GPU tests for local sgd / diloco #128

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48 changes: 43 additions & 5 deletions torchft/local_sgd_integ_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@
from torchft.local_sgd import DiLoCo, LocalSGD
from torchft.manager import Manager
from torchft.manager_integ_test import FailureInjector, MyModel, Runner
from torchft.process_group import ProcessGroupGloo, ProcessGroupNCCL
from torchft.process_group import ProcessGroupBabyNCCL, ProcessGroupGloo

logger: logging.Logger = logging.getLogger(__name__)

Expand All @@ -41,7 +41,10 @@ def state_dict() -> Dict[str, Dict[str, object]]:

print(f"worker {runner.replica_id=} {rank=} {runner.world_size=} starting")

pg = ProcessGroupGloo()
if device.type == "cuda":
pg = ProcessGroupBabyNCCL()
else:
pg = ProcessGroupGloo()
manager = Manager(
pg=pg,
min_replica_size=2,
Expand Down Expand Up @@ -110,7 +113,12 @@ def diloco_train_loop(
# pyre-ignore[53]
def load_state_dict(state_dict: Dict[str, Dict[str, object]]) -> None:
m.load_state_dict(state_dict["model"])
m.to(device)
diloco.original_parameters = state_dict["original_params"]
for name in diloco.original_parameters.keys():
diloco.original_parameters[name] = diloco.original_parameters[name].to(
device
)
inner_optimizer.load_state_dict(state_dict["inner_optim"])
outer_optimizer.load_state_dict(state_dict["outer_optim"])

Expand All @@ -124,7 +132,10 @@ def state_dict() -> Dict[str, Dict[str, object]]: # pyre-ignore[53]

print(f"worker {runner.replica_id=} {rank=} {runner.world_size=} starting")

pg = ProcessGroupGloo()
if device.type == "cuda":
pg = ProcessGroupBabyNCCL()
else:
pg = ProcessGroupGloo()
manager = Manager(
pg=pg,
min_replica_size=2,
Expand All @@ -138,6 +149,8 @@ def state_dict() -> Dict[str, Dict[str, object]]: # pyre-ignore[53]
world_size=runner.world_size,
lighthouse_addr=runner.lighthouse_address,
port=19530 + runner.replica_id,
connect_timeout=timedelta(seconds=10),
quorum_timeout=timedelta(seconds=10),
timeout=timedelta(seconds=10),
# pyre-fixme[6]: Incompatible parameter type
**runner.manager_args,
Expand All @@ -155,6 +168,12 @@ def state_dict() -> Dict[str, Dict[str, object]]: # pyre-ignore[53]
sync_every=2,
) as diloco:
while True:
manager_curr_step = manager.current_step()
if manager_curr_step not in all_state_dicts:
print(
f"{manager_curr_step=} {diloco._local_step=} {runner.replica_id=} {state_dict()=}"
)
all_state_dicts[manager_curr_step] = copy.deepcopy(state_dict())
batch_size = 1
inputs = m.get_rand_inputs(batch_size).to(device)
labels = m.get_rand_labels(batch_size).to(device)
Expand All @@ -164,7 +183,6 @@ def state_dict() -> Dict[str, Dict[str, object]]: # pyre-ignore[53]

inner_optimizer.zero_grad()
loss.backward()
all_state_dicts[str(manager.current_step())] = state_dict()
inner_optimizer.step()

# after 4 model updates then break
Expand All @@ -181,10 +199,15 @@ def state_dict() -> Dict[str, Dict[str, object]]: # pyre-ignore[53]
class LocalSGDIntegTest(TestCase):
@parameterized.expand(
[
(True,),
(False,),
]
)
def test_local_sgd_recovery(self, use_cuda: bool) -> None:
# Skip the test if use_cuda is True and there are not enough GPUs
if use_cuda and torch.cuda.device_count() < 2:
self.skipTest("Not enough GPUs for CUDA test")

lighthouse = LighthouseServer(
bind="[::]:0",
min_replicas=2,
Expand Down Expand Up @@ -236,10 +259,15 @@ def test_local_sgd_recovery(self, use_cuda: bool) -> None:

@parameterized.expand(
[
(True,),
(False,),
]
)
def test_diloco_healthy(self, use_cuda: bool) -> None:
# Skip the test if use_cuda is True and there are not enough GPUs
if use_cuda and torch.cuda.device_count() < 2:
self.skipTest("Not enough GPUs for CUDA test")

lighthouse = LighthouseServer(bind="[::]:0", min_replicas=2)
num_replicas = 2
futures = []
Expand Down Expand Up @@ -289,7 +317,17 @@ def test_diloco_healthy(self, use_cuda: bool) -> None:
check_device=False,
)

def test_diloco_recovery(self) -> None:
@parameterized.expand(
[
(True,),
(False,),
]
)
def test_diloco_recovery(self, use_cuda: bool) -> None:
# Skip the test if use_cuda is True and there are not enough GPUs
if use_cuda and torch.cuda.device_count() < 2:
self.skipTest("Not enough GPUs for CUDA test")

lighthouse = LighthouseServer(
bind="[::]:0",
min_replicas=2,
Expand Down