Gahow Wang
445e491123
third_party/vllm/ now tracked in git for direct patch management.
Based on vLLM v0.18.1 release with one patch applied:
vllm/v1/core/sched/scheduler.py:
Replace fatal assert with graceful skip when KV transfer callback
arrives for an already-aborted request during PD disaggregated serving.
Future vLLM modifications should be made directly in third_party/vllm/
and committed normally. The patches/ directory is kept as documentation
of what changed from upstream.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
74 lines
2.3 KiB
Python
74 lines
2.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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# Expanded quantized model tests for CPU offloading
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# Base tests: tests/basic_correctness/test_cpu_offload.py
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import pytest
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from tests.quantization.utils import is_quant_method_supported
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from ..utils import compare_two_settings
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@pytest.mark.skipif(
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not is_quant_method_supported("fp8"),
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reason="fp8 is not supported on this GPU type.",
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)
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def test_cpu_offload_fp8():
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# Test loading a quantized checkpoint
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compare_two_settings(
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"neuralmagic/Qwen2-1.5B-Instruct-FP8",
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["--enforce_eager"],
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["--enforce_eager", "--cpu-offload-gb", "1"],
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max_wait_seconds=480,
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)
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@pytest.mark.skipif(
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not is_quant_method_supported("gptq_marlin"),
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reason="gptq_marlin is not supported on this GPU type.",
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)
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def test_cpu_offload_gptq(monkeypatch):
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# This quant method is sensitive to dummy weights, so we force real weights
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monkeypatch.setenv("VLLM_TEST_FORCE_LOAD_FORMAT", "auto")
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# Test GPTQ Marlin
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compare_two_settings(
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"Qwen/Qwen2-1.5B-Instruct-GPTQ-Int4",
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["--enforce_eager"],
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["--enforce_eager", "--cpu-offload-gb", "1"],
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max_wait_seconds=480,
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)
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@pytest.mark.skipif(
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not is_quant_method_supported("awq_marlin"),
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reason="awq_marlin is not supported on this GPU type.",
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)
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def test_cpu_offload_awq(monkeypatch):
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# This quant method is sensitive to dummy weights, so we force real weights
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monkeypatch.setenv("VLLM_TEST_FORCE_LOAD_FORMAT", "auto")
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# Test AWQ Marlin
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compare_two_settings(
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"Qwen/Qwen2-1.5B-Instruct-AWQ",
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["--enforce_eager"],
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["--enforce_eager", "--cpu-offload-gb", "1"],
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max_wait_seconds=480,
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)
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@pytest.mark.skipif(
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not is_quant_method_supported("gptq_marlin"),
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reason="gptq_marlin is not supported on this GPU type.",
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)
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def test_cpu_offload_compressed_tensors(monkeypatch):
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# This quant method is sensitive to dummy weights, so we force real weights
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monkeypatch.setenv("VLLM_TEST_FORCE_LOAD_FORMAT", "auto")
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# Test wNa16
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compare_two_settings(
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"nm-testing/Qwen1.5-MoE-A2.7B-Chat-quantized.w4a16",
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["--enforce_eager"],
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["--enforce_eager", "--cpu-offload-gb", "1"],
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max_wait_seconds=480,
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)
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