126 lines
4.8 KiB
Python
126 lines
4.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import pytest
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import vllm
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from vllm.compilation.counter import compilation_counter
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from vllm.config import VllmConfig
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from vllm.utils import _is_torch_equal_or_newer
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def test_version():
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assert _is_torch_equal_or_newer('2.8.0.dev20250624+cu128', '2.8.0.dev')
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assert _is_torch_equal_or_newer('2.8.0a0+gitc82a174', '2.8.0.dev')
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assert _is_torch_equal_or_newer('2.8.0', '2.8.0.dev')
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assert _is_torch_equal_or_newer('2.8.1', '2.8.0.dev')
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assert not _is_torch_equal_or_newer('2.7.1', '2.8.0.dev')
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def test_use_cudagraphs_dynamic(monkeypatch):
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assert vllm.envs.VLLM_USE_V1
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vllm_config = VllmConfig()
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assert vllm_config.compilation_config.use_cudagraph
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monkeypatch.setenv('VLLM_USE_V1', '0')
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vllm_config = VllmConfig()
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assert not vllm_config.compilation_config.use_cudagraph
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# forked needed to workaround https://github.com/vllm-project/vllm/issues/21073
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@pytest.mark.forked
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# NB: We don't test VLLM_DISABLE_COMPILE_CACHE=0 because that depends
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# on the state of the cache directory on the current machine, which
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# may be influenced by other tests.
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@pytest.mark.parametrize("val", ["1"])
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def test_VLLM_DISABLE_COMPILE_CACHE(vllm_runner, monkeypatch, val):
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assert vllm.envs.VLLM_USE_V1
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# Disable multiprocessing so that the counter is in the same process
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monkeypatch.setenv('VLLM_ENABLE_V1_MULTIPROCESSING', '0')
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monkeypatch.setenv('VLLM_DISABLE_COMPILE_CACHE', val)
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compilation_config = {
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"use_cudagraph": False, # speed things up a bit
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}
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with (
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compilation_counter.expect(num_cache_entries_updated=0,
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num_compiled_artifacts_saved=0),
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# loading the model causes compilation (if enabled) to happen
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vllm_runner('facebook/opt-125m',
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compilation_config=compilation_config,
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gpu_memory_utilization=0.4) as _):
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pass
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# forked needed to workaround https://github.com/vllm-project/vllm/issues/21073
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@pytest.mark.forked
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@pytest.mark.parametrize("enabled", [True, False])
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def test_use_cudagraphs(vllm_runner, monkeypatch, enabled):
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assert vllm.envs.VLLM_USE_V1
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# Disable multiprocessing so that the counter is in the same process
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monkeypatch.setenv('VLLM_ENABLE_V1_MULTIPROCESSING', '0')
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compilation_config = {
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"cudagraph_capture_sizes": [100],
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"use_cudagraph": enabled,
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}
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with (
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compilation_counter.expect(
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num_graphs_seen=1,
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num_gpu_runner_capture_triggers=1 if enabled else 0,
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num_cudagraph_captured=13 if enabled else 0,
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),
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# loading the model causes compilation (if enabled) to happen
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vllm_runner('facebook/opt-125m',
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compilation_config=compilation_config,
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gpu_memory_utilization=0.4) as _):
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pass
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# forked needed to workaround https://github.com/vllm-project/vllm/issues/21073
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@pytest.mark.forked
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def test_dynamo_as_is(vllm_runner, monkeypatch):
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# Disable multiprocessing so that the counter is in the same process
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monkeypatch.setenv('VLLM_ENABLE_V1_MULTIPROCESSING', '0')
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with (
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compilation_counter.expect(dynamo_as_is_count=1),
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# loading the model causes compilation (if enabled) to happen
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vllm_runner('facebook/opt-125m',
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compilation_config={"level": 1},
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gpu_memory_utilization=0.4) as _):
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pass
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# forked needed to workaround https://github.com/vllm-project/vllm/issues/21073
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@pytest.mark.forked
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def test_no_compilation(vllm_runner, monkeypatch):
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# Disable multiprocessing so that the counter is in the same process
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monkeypatch.setenv('VLLM_ENABLE_V1_MULTIPROCESSING', '0')
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with (
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compilation_counter.expect(num_graphs_seen=0,
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dynamo_as_is_count=0),
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# loading the model causes compilation (if enabled) to happen
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vllm_runner('facebook/opt-125m',
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compilation_config={"level": 0},
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gpu_memory_utilization=0.4) as _):
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pass
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# forked needed to workaround https://github.com/vllm-project/vllm/issues/21073
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@pytest.mark.forked
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def test_enforce_eager(vllm_runner, monkeypatch):
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# Disable multiprocessing so that the counter is in the same process
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monkeypatch.setenv('VLLM_ENABLE_V1_MULTIPROCESSING', '0')
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with (
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compilation_counter.expect(num_graphs_seen=0,
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dynamo_as_is_count=0),
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# loading the model causes compilation (if enabled) to happen
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vllm_runner('facebook/opt-125m',
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enforce_eager=True,
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gpu_memory_utilization=0.4) as _):
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pass
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