155 lines
6.2 KiB
Python
155 lines
6.2 KiB
Python
"""Tests for process-scoped GPU memory accounting."""
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import os
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from unittest import mock
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import pytest
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class TestParseCudaVisibleDevices:
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def test_empty(self):
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from vllm_omni.worker.gpu_memory_utils import parse_cuda_visible_devices
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with mock.patch.dict(os.environ, {}, clear=True):
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os.environ.pop("CUDA_VISIBLE_DEVICES", None)
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assert parse_cuda_visible_devices() == []
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with mock.patch.dict(os.environ, {"CUDA_VISIBLE_DEVICES": ""}):
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assert parse_cuda_visible_devices() == []
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def test_integer_indices(self):
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from vllm_omni.worker.gpu_memory_utils import parse_cuda_visible_devices
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with mock.patch.dict(os.environ, {"CUDA_VISIBLE_DEVICES": "2,3,5"}):
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assert parse_cuda_visible_devices() == [2, 3, 5]
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with mock.patch.dict(os.environ, {"CUDA_VISIBLE_DEVICES": "0"}):
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assert parse_cuda_visible_devices() == [0]
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def test_uuids(self):
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from vllm_omni.worker.gpu_memory_utils import parse_cuda_visible_devices
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uuid1 = "GPU-12345678-1234-1234-1234-123456789abc"
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uuid2 = "GPU-87654321-4321-4321-4321-cba987654321"
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with mock.patch.dict(os.environ, {"CUDA_VISIBLE_DEVICES": f"{uuid1},{uuid2}"}):
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assert parse_cuda_visible_devices() == [uuid1, uuid2]
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def test_mig_ids(self):
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from vllm_omni.worker.gpu_memory_utils import parse_cuda_visible_devices
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mig1 = "MIG-GPU-12345678-1234-1234-1234-123456789abc/0/0"
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mig2 = "MIG-GPU-12345678-1234-1234-1234-123456789abc/1/0"
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with mock.patch.dict(os.environ, {"CUDA_VISIBLE_DEVICES": f"{mig1},{mig2}"}):
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assert parse_cuda_visible_devices() == [mig1, mig2]
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def test_spaces(self):
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from vllm_omni.worker.gpu_memory_utils import parse_cuda_visible_devices
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with mock.patch.dict(os.environ, {"CUDA_VISIBLE_DEVICES": " 2 , 3 , 5 "}):
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assert parse_cuda_visible_devices() == [2, 3, 5]
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class TestGetProcessGpuMemory:
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@pytest.mark.skipif(not os.path.exists("/dev/nvidia0"), reason="No GPU")
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def test_returns_memory_for_current_process(self):
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import torch
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from vllm_omni.worker.gpu_memory_utils import get_process_gpu_memory
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if not torch.cuda.is_available():
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pytest.skip("CUDA not available")
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device = torch.device("cuda:0")
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tensor = torch.zeros(1000, 1000, device=device)
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memory = get_process_gpu_memory(0)
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assert memory >= 0
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del tensor
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torch.cuda.empty_cache()
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def test_raises_on_invalid_device(self):
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from vllm_omni.worker.gpu_memory_utils import get_process_gpu_memory
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with (
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlInit"),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlShutdown"),
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mock.patch("vllm.third_party.pynvml.nvmlDeviceGetCount", return_value=1),
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):
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with pytest.raises(RuntimeError, match="Invalid GPU device"):
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get_process_gpu_memory(5)
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def test_returns_zero_when_process_not_found(self):
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from vllm_omni.worker.gpu_memory_utils import get_process_gpu_memory
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with (
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlInit"),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlShutdown"),
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mock.patch("vllm.third_party.pynvml.nvmlDeviceGetCount", return_value=8),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlDeviceGetHandleByIndex"),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlDeviceGetComputeRunningProcesses", return_value=[]),
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):
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memory = get_process_gpu_memory(0)
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assert memory == 0
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def test_uses_uuid_when_provided(self):
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from vllm_omni.worker.gpu_memory_utils import get_process_gpu_memory
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uuid = "GPU-12345678-1234-1234-1234-123456789abc"
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mock_handle = mock.MagicMock()
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with (
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mock.patch.dict(os.environ, {"CUDA_VISIBLE_DEVICES": uuid}),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlInit"),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlShutdown"),
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mock.patch("vllm.third_party.pynvml.nvmlDeviceGetHandleByUUID", return_value=mock_handle) as mock_by_uuid,
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlDeviceGetComputeRunningProcesses", return_value=[]),
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):
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memory = get_process_gpu_memory(0)
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assert memory == 0
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mock_by_uuid.assert_called_once_with(uuid)
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def test_raises_on_invalid_uuid(self):
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from vllm_omni.worker.gpu_memory_utils import get_process_gpu_memory
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uuid = "GPU-invalid-uuid"
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with (
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mock.patch.dict(os.environ, {"CUDA_VISIBLE_DEVICES": uuid}),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlInit"),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlShutdown"),
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mock.patch("vllm.third_party.pynvml.nvmlDeviceGetHandleByUUID", side_effect=Exception("Invalid UUID")),
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):
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with pytest.raises(RuntimeError, match="Failed to get NVML handle"):
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get_process_gpu_memory(0)
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def test_returns_none_on_nvml_init_failure(self):
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from vllm_omni.worker.gpu_memory_utils import get_process_gpu_memory
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with (
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlInit", side_effect=Exception("NVML unavailable")),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlShutdown"),
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):
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result = get_process_gpu_memory(0)
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assert result is None
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class TestIsProcessScopedMemoryAvailable:
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def test_returns_true_when_nvml_works(self):
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from vllm_omni.worker.gpu_memory_utils import is_process_scoped_memory_available
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with (
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlInit"),
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mock.patch("vllm_omni.worker.gpu_memory_utils.nvmlShutdown"),
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):
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assert is_process_scoped_memory_available() is True
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def test_returns_false_when_nvml_fails(self):
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from vllm_omni.worker.gpu_memory_utils import is_process_scoped_memory_available
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with mock.patch(
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"vllm_omni.worker.gpu_memory_utils.nvmlInit",
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side_effect=Exception("NVML unavailable"),
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):
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assert is_process_scoped_memory_available() is False
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