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# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import signal
from unittest.mock import MagicMock, PropertyMock, patch
import pytest
import torch
from lightning.pytorch import Trainer
from nemo.lightning.pytorch.callbacks.preemption import PreemptionCallback
class TestPreemptionCallback:
@pytest.fixture
def callback(self):
return PreemptionCallback()
@pytest.fixture
def mock_trainer(self):
trainer = MagicMock(spec=Trainer)
trainer.should_stop = False
return trainer
def test_init(self, callback):
assert callback.sig == signal.SIGTERM
assert not callback._interrupted
assert callback._handler_context is None
def test_custom_signal(self):
custom_callback = PreemptionCallback(sig=signal.SIGUSR1)
assert custom_callback.sig == signal.SIGUSR1
@pytest.mark.parametrize("initially_supported,becomes_supported", [(False, True), (False, False), (True, True)])
def test_on_train_batch_start_distributed_init(
self, callback, mock_trainer, initially_supported, becomes_supported
):
with (
patch.object(PreemptionCallback, '_check_preemption_support') as mock_check,
patch.object(callback, '_preemption_handler') as mock_handler,
):
mock_check.side_effect = [initially_supported, becomes_supported]
callback.on_train_start(mock_trainer, None)
callback.on_train_batch_start(mock_trainer, None, None, 0)
expected_call_count = 1 if initially_supported else (1 if becomes_supported else 0)
assert mock_handler.call_count == expected_call_count
if initially_supported:
mock_handler.assert_called_once_with()
elif becomes_supported:
mock_handler.assert_called_once_with()
else:
mock_handler.assert_not_called()
@pytest.mark.parametrize(
"is_supported,interrupted,expected",
[
(True, True, True),
(True, False, False),
(False, True, False),
(False, False, False),
],
)
def test_interrupted_property(self, callback, is_supported, interrupted, expected):
with (
patch.object(PreemptionCallback, '_check_preemption_support', return_value=is_supported),
patch('torch.distributed.broadcast'),
patch('torch.tensor', return_value=torch.tensor(interrupted)),
patch('torch.cuda.is_available', return_value=True),
patch('torch.cuda.current_device', return_value=0),
):
callback._interrupted = interrupted
assert callback.interrupted == expected
def test_on_train_start(self, callback, mock_trainer):
with (
patch.object(PreemptionCallback, 'preemption_supported', new_callable=PropertyMock) as mock_supported,
patch.object(callback, '_preemption_handler') as mock_handler,
):
# Test when preemption is supported
mock_supported.return_value = True
callback.on_train_start(mock_trainer, None)
mock_handler.assert_called_once()
mock_handler.reset_mock()
# Test when preemption is not supported
mock_supported.return_value = False
callback.on_train_start(mock_trainer, None)
mock_handler.assert_not_called()
def test_on_train_end(self, callback, mock_trainer):
mock_context = MagicMock()
callback._handler_context = mock_context
callback.on_train_end(mock_trainer, None)
mock_context.__exit__.assert_called_once_with(None, None, None)
@pytest.mark.parametrize("interrupted", [True, False])
def test_on_train_batch_end(self, callback, mock_trainer, interrupted):
with patch.object(PreemptionCallback, 'interrupted', new_callable=lambda: property(lambda self: interrupted)):
if interrupted:
with pytest.raises(SystemExit):
callback.on_train_batch_end(mock_trainer, None, None, None, 0)
else:
callback.on_train_batch_end(mock_trainer, None, None, None, 0)
assert mock_trainer.should_stop == interrupted
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