[MISC] Consolidate cleanup() and refactor offline_inference_with_prefix.py (#9510)
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@@ -4,8 +4,7 @@ from typing import List
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import pytest
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from vllm import LLM, EmbeddingRequestOutput, PoolingParams
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from ...conftest import cleanup
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from vllm.distributed import cleanup_dist_env_and_memory
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MODEL_NAME = "intfloat/e5-mistral-7b-instruct"
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@@ -41,7 +40,7 @@ def llm():
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del llm
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cleanup()
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cleanup_dist_env_and_memory()
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def assert_outputs_equal(o1: List[EmbeddingRequestOutput],
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@@ -4,8 +4,7 @@ from typing import List
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import pytest
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from vllm import LLM, RequestOutput, SamplingParams
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from ...conftest import cleanup
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from vllm.distributed import cleanup_dist_env_and_memory
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MODEL_NAME = "facebook/opt-125m"
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@@ -39,7 +38,7 @@ def llm():
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del llm
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cleanup()
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cleanup_dist_env_and_memory()
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def assert_outputs_equal(o1: List[RequestOutput], o2: List[RequestOutput]):
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@@ -5,10 +5,9 @@ import pytest
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from huggingface_hub import snapshot_download
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from vllm import LLM
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from vllm.distributed import cleanup_dist_env_and_memory
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from vllm.lora.request import LoRARequest
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from ...conftest import cleanup
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MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
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PROMPTS = [
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@@ -39,7 +38,7 @@ def llm():
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del llm
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cleanup()
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cleanup_dist_env_and_memory()
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@pytest.fixture(scope="module")
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@@ -5,12 +5,11 @@ import weakref
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import jsonschema
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import pytest
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from vllm.distributed import cleanup_dist_env_and_memory
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from vllm.entrypoints.llm import LLM
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from vllm.outputs import RequestOutput
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from vllm.sampling_params import GuidedDecodingParams, SamplingParams
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from ...conftest import cleanup
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MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
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@@ -23,7 +22,7 @@ def llm():
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with llm.deprecate_legacy_api():
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yield weakref.proxy(llm)
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del llm
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cleanup()
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cleanup_dist_env_and_memory()
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@pytest.mark.skip_global_cleanup
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@@ -1,6 +1,7 @@
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import sys
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from vllm import LLM, SamplingParams
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from vllm.distributed import cleanup_dist_env_and_memory
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def test_lazy_outlines(sample_regex):
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@@ -14,6 +15,7 @@ def test_lazy_outlines(sample_regex):
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]
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sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
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# Create an LLM without guided decoding as a baseline.
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llm = LLM(model="facebook/opt-125m",
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enforce_eager=True,
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gpu_memory_utilization=0.3)
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@@ -26,8 +28,11 @@ def test_lazy_outlines(sample_regex):
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# make sure outlines is not imported
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assert 'outlines' not in sys.modules
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# The second LLM needs to request a higher gpu_memory_utilization because
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# the first LLM has already allocated a full 30% of the gpu memory.
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# Destroy the LLM object and free up the GPU memory.
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del llm
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cleanup_dist_env_and_memory()
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# Create an LLM with guided decoding enabled.
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llm = LLM(model="facebook/opt-125m",
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enforce_eager=True,
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guided_decoding_backend="lm-format-enforcer",
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@@ -6,8 +6,7 @@ import weakref
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import pytest
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from vllm import LLM
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from ...conftest import cleanup
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from vllm.distributed import cleanup_dist_env_and_memory
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MODEL_NAME = "facebook/opt-125m"
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@@ -27,7 +26,7 @@ def llm():
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del llm
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cleanup()
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cleanup_dist_env_and_memory()
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@pytest.mark.skip_global_cleanup
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