File size: 8,296 Bytes
b386992 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 | # 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.
from unittest.mock import MagicMock, patch
import pytest
import torch
from nemo.lightning.pytorch.callbacks.nsys import NsysCallback
class TestNsysCallback:
@pytest.fixture(autouse=True)
def setup_mocks(self):
self.cuda_mock = patch('torch.cuda')
self.cudart_mock = patch('torch.cuda.cudart')
self.emit_nvtx_mock = patch('torch.autograd.profiler.emit_nvtx')
self.get_rank_mock = patch('nemo.lightning.pytorch.callbacks.nsys.get_rank')
self.cuda_mock.start()
self.cudart_mock.start()
self.emit_nvtx_mock.start()
self.get_rank_mock.start()
# Mock CUDA availability
torch.cuda.is_available = MagicMock(return_value=True)
torch.cuda.current_device = MagicMock(return_value=0)
# Set up fixed cudart mock for all tests
self.fixed_cudart = MagicMock()
torch.cuda.cudart = MagicMock(return_value=self.fixed_cudart)
yield
self.cuda_mock.stop()
self.cudart_mock.stop()
self.emit_nvtx_mock.stop()
self.get_rank_mock.stop()
@pytest.fixture
def mock_trainer(self):
trainer = MagicMock()
trainer.strategy.root_device.type = 'cuda'
return trainer
@pytest.fixture
def mock_pl_module(self):
return MagicMock()
def test_init_valid_params(self):
"""Test initialization with valid parameters."""
callback = NsysCallback(start_step=10, end_step=20, ranks=[0, 1], gen_shape=True)
assert callback._nsys_profile_start_step == 10
assert callback._nsys_profile_end_step == 20
assert callback._nsys_profile_ranks == [0, 1]
assert callback._nsys_profile_gen_shape == True
def test_init_invalid_params(self):
"""Test initialization with invalid parameters."""
with pytest.raises(AssertionError):
NsysCallback(start_step='10', end_step=20)
with pytest.raises(AssertionError):
NsysCallback(start_step=10, end_step='20')
with pytest.raises(AssertionError):
NsysCallback(start_step=20, end_step=10)
@patch('nemo.lightning.pytorch.callbacks.nsys.get_rank')
@patch('torch.autograd.profiler.emit_nvtx')
def test_on_train_batch_start_profiling(self, mock_emit_nvtx, mock_get_rank, mock_trainer, mock_pl_module):
# Set mocked cudart via the fixture patch
mock_get_rank.return_value = 0
callback = NsysCallback(start_step=10, end_step=20, ranks=[0], gen_shape=True)
mock_trainer.strategy.current_epoch_step = 10
callback.on_train_batch_start(mock_trainer, mock_pl_module, None, 10)
self.fixed_cudart.cudaProfilerStart.assert_called_once()
mock_emit_nvtx.assert_called_once_with(record_shapes=True)
@patch('nemo.lightning.pytorch.callbacks.nsys.get_rank')
def test_on_train_batch_start_no_profiling(self, mock_get_rank, mock_trainer, mock_pl_module):
mock_get_rank.return_value = 0
callback = NsysCallback(start_step=10, end_step=20, ranks=[0])
mock_trainer.strategy.current_epoch_step = 9
callback.on_train_batch_start(mock_trainer, mock_pl_module, None, 9)
self.fixed_cudart.cudaProfilerStart.assert_not_called()
@patch('nemo.lightning.pytorch.callbacks.nsys.get_rank')
@patch('torch.autograd.profiler.emit_nvtx')
def test_on_train_batch_end_profiling(self, mock_emit_nvtx, mock_get_rank, mock_trainer, mock_pl_module):
mock_get_rank.return_value = 0
callback = NsysCallback(start_step=10, end_step=20, ranks=[0])
mock_trainer.strategy.current_epoch_step = 20
assert callback._has_nsys_enabled == False
callback._has_nsys_enabled = True
callback.on_train_batch_end(mock_trainer, mock_pl_module, None, None, 20)
self.fixed_cudart.cudaProfilerStop.assert_called_once()
@patch('nemo.lightning.pytorch.callbacks.nsys.get_rank')
@patch('torch.autograd.profiler.emit_nvtx')
def test_on_train_batch_end_no_profiling(self, mock_emit_nvtx, mock_get_rank, mock_trainer, mock_pl_module):
mock_get_rank.return_value = 0
callback = NsysCallback(start_step=10, end_step=20, ranks=[0])
callback.on_train_batch_end(mock_trainer, mock_pl_module, None, None, 19)
self.fixed_cudart.cudaProfilerStop.assert_not_called()
def test_non_cuda_device(self, mock_trainer, mock_pl_module):
"""Test behavior when the device is not CUDA."""
mock_trainer.strategy.root_device.type = 'cpu'
callback = NsysCallback(start_step=10, end_step=20, ranks=[0])
callback.on_train_batch_start(mock_trainer, mock_pl_module, None, 10)
callback.on_train_batch_end(mock_trainer, mock_pl_module, None, None, 20)
# No exceptions should be raised, and no profiling calls should be made
@patch('nemo.lightning.pytorch.callbacks.nsys.get_rank')
def test_rank_not_in_profile_ranks(self, mock_get_rank, mock_trainer, mock_pl_module):
"""Test behavior when the current rank is not in the profile ranks."""
mock_get_rank.return_value = 1
callback = NsysCallback(start_step=10, end_step=20, ranks=[0])
callback.on_train_batch_start(mock_trainer, mock_pl_module, None, 10)
callback.on_train_batch_end(mock_trainer, mock_pl_module, None, None, 20)
# No profiling calls should be made
@pytest.mark.parametrize(
"start_step,end_step,batch_idx,expected_call",
[
(10, 20, 9, False),
(10, 20, 10, True),
(10, 20, 15, False),
(10, 20, 20, False),
(10, 20, 21, False),
],
)
@patch('nemo.lightning.pytorch.callbacks.nsys.get_rank')
@patch('torch.autograd.profiler.emit_nvtx')
def test_profiling_range(
self,
mock_emit_nvtx,
mock_get_rank,
start_step,
end_step,
batch_idx,
expected_call,
mock_trainer,
mock_pl_module,
):
mock_get_rank.return_value = 0
callback = NsysCallback(start_step=start_step, end_step=end_step, ranks=[0])
mock_trainer.strategy.current_epoch_step = batch_idx
callback.on_train_batch_start(mock_trainer, mock_pl_module, None, batch_idx)
if expected_call:
self.fixed_cudart.cudaProfilerStart.assert_called_once()
mock_emit_nvtx.assert_called_once()
else:
self.fixed_cudart.cudaProfilerStart.assert_not_called()
mock_emit_nvtx.assert_not_called()
@patch('nemo.lightning.pytorch.callbacks.nsys.get_rank')
def test_single_profile_range(self, mock_get_rank, mock_trainer, mock_pl_module):
mock_get_rank.return_value = 0
callback = NsysCallback(start_step=10, end_step=40, ranks=[0])
# Ensure the device type is 'cuda'
mock_trainer.strategy.root_device.type = 'cuda'
# Start of range
mock_trainer.strategy.current_epoch_step = 10
callback.on_train_batch_start(mock_trainer, mock_pl_module, None, 10)
assert self.fixed_cudart.cudaProfilerStart.call_count == 1, "cudaProfilerStart was not called"
# Middle of range
mock_trainer.strategy.current_epoch_step = 25
callback.on_train_batch_start(mock_trainer, mock_pl_module, None, 25)
assert self.fixed_cudart.cudaProfilerStart.call_count == 1, "cudaProfilerStart was called again"
# End of range
mock_trainer.strategy.current_epoch_step = 40
callback.on_train_batch_end(mock_trainer, mock_pl_module, None, None, 40)
assert self.fixed_cudart.cudaProfilerStop.call_count == 1, "cudaProfilerStop was not called"
|