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[Refactor] Remove dead env and config (#59781)

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Signed-off-by: yewentao256 <zhyanwentao@126.com>
This commit is contained in:
Wentao Ye
2026-10-02 18:07:20 +00:00
committed by GitHub
parent 4e4d75c459
commit f700178f90
16 changed files with 6 additions and 72 deletions
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.buildkite/performance-benchmarks/tests/latency-tests-arm64-cpu.json
-1
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@@ -3,7 +3,6 @@
"test_name": "latency_llama8B_tp1",
"environment_variables": {
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_KVCACHE_SPACE": 40
},
"parameters": {
.buildkite/performance-benchmarks/tests/latency-tests-cpu.json
-1
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@@ -3,7 +3,6 @@
"test_name": "latency_llama8B_tp2",
"environment_variables": {
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
"VLLM_CPU_KVCACHE_SPACE": 40
},
.buildkite/performance-benchmarks/tests/serving-tests-arm64-cpu.json
-1
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@@ -14,7 +14,6 @@
],
"server_environment_variables": {
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
"VLLM_CPU_KVCACHE_SPACE": 40
},
.buildkite/performance-benchmarks/tests/serving-tests-cpu-asr.json
-3
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@@ -4,9 +4,6 @@
"inf"
],
"max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
"server_environment_variables": {
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120
},
"server_parameters": {
"dtype": "bfloat16",
"model": "openai/whisper-large-v3-turbo"
.buildkite/performance-benchmarks/tests/serving-tests-cpu-embed.json
-1
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@@ -10,7 +10,6 @@
],
"server_environment_variables": {
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
"VLLM_CPU_KVCACHE_SPACE": 40
},
.buildkite/performance-benchmarks/tests/serving-tests-cpu-text.json
-1
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@@ -6,7 +6,6 @@
"max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
"server_environment_variables": {
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
"VLLM_CPU_KVCACHE_SPACE": 40
},
.buildkite/performance-benchmarks/tests/serving-tests-cpu.json
-1
View File
@@ -6,7 +6,6 @@
"max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
"server_environment_variables": {
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
"VLLM_CPU_KVCACHE_SPACE": 40
},
.buildkite/performance-benchmarks/tests/throughput-tests-arm64-cpu.json
-1
View File
@@ -3,7 +3,6 @@
"test_name": "throughput_llama8B_tp1",
"environment_variables": {
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_KVCACHE_SPACE": 40
},
"parameters": {
.buildkite/performance-benchmarks/tests/throughput-tests-cpu.json
-1
View File
@@ -3,7 +3,6 @@
"test_name": "throughput_llama8B_tp2",
"environment_variables": {
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
"VLLM_CPU_KVCACHE_SPACE": 40
},
tests/entrypoints/multimodal/openai/chat_completion/test_video.py
+1 -3
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@@ -40,13 +40,11 @@ def server():
"--trust-request-mm-kwargs",
]
# ROCm: Increase timeouts to handle potential network delays and slower
# video processing when downloading multiple videos from external sources
# ROCm: Allow more time to download videos from external sources.
env_overrides = {}
if current_platform.is_rocm():
env_overrides = {
"VLLM_VIDEO_FETCH_TIMEOUT": "120",
"VLLM_ENGINE_ITERATION_TIMEOUT_S": "300",
}
with RemoteOpenAIServer(MODEL_NAME, args, env_dict=env_overrides) as remote_server:
tests/entrypoints/multimodal/openai/chat_completion/test_vision.py
+1 -3
View File
@@ -88,13 +88,11 @@ def server():
*ROCM_EXTRA_ARGS,
]
# ROCm: Increase timeouts to handle potential network delays and slower
# video processing when downloading multiple videos from external sources
# ROCm: Allow more time to download videos from external sources.
env_overrides = {
**(
{
"VLLM_VIDEO_FETCH_TIMEOUT": "120",
"VLLM_ENGINE_ITERATION_TIMEOUT_S": "300",
}
if current_platform.is_rocm()
else {}
tests/entrypoints/speech_to_text/realtime/test_realtime_validation.py
+4 -18
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@@ -14,12 +14,6 @@ from tests.utils import ROCM_EXTRA_ARGS, RemoteOpenAIServer
from vllm.assets.audio import AudioAsset
from vllm.multimodal.media.audio import load_audio
# Increase engine iteration timeout for ROCm where first-use JIT compilation
# can exceed the default 60s, causing a silent deadlock in feed_tokens.
REALTIME_ENV_OVERRIDES = {
"VLLM_ENGINE_ITERATION_TIMEOUT_S": "600",
}
MISTRAL_FORMAT_ARGS = [
"--tokenizer_mode",
"mistral",
@@ -77,9 +71,7 @@ async def test_multi_chunk_streaming(model_name, mary_had_lamb_audio_chunks):
if model_name.startswith("mistralai"):
server_args += MISTRAL_FORMAT_ARGS
with RemoteOpenAIServer(
model_name, server_args, env_dict=REALTIME_ENV_OVERRIDES
) as remote_server:
with RemoteOpenAIServer(model_name, server_args) as remote_server:
ws_url = _get_websocket_url(remote_server)
async with websockets.connect(ws_url) as ws:
# Receive session.created
@@ -183,9 +175,7 @@ async def test_empty_commit_does_not_crash_engine(
if model_name.startswith("mistralai"):
server_args += MISTRAL_FORMAT_ARGS
with RemoteOpenAIServer(
model_name, server_args, env_dict=REALTIME_ENV_OVERRIDES
) as remote_server:
with RemoteOpenAIServer(model_name, server_args) as remote_server:
ws_url = _get_websocket_url(remote_server)
# --- First connection: empty commit (no audio appended) ----------
@@ -272,9 +262,7 @@ async def test_session_update_invalid_model_returns_error(model_name):
if model_name.startswith("mistralai"):
server_args += MISTRAL_FORMAT_ARGS
with RemoteOpenAIServer(
model_name, server_args, env_dict=REALTIME_ENV_OVERRIDES
) as remote_server:
with RemoteOpenAIServer(model_name, server_args) as remote_server:
ws_url = _get_websocket_url(remote_server)
async with websockets.connect(ws_url) as ws:
event = await receive_event(ws, timeout=30.0)
@@ -301,9 +289,7 @@ async def test_commit_without_session_update_returns_error(model_name):
if model_name.startswith("mistralai"):
server_args += MISTRAL_FORMAT_ARGS
with RemoteOpenAIServer(
model_name, server_args, env_dict=REALTIME_ENV_OVERRIDES
) as remote_server:
with RemoteOpenAIServer(model_name, server_args) as remote_server:
ws_url = _get_websocket_url(remote_server)
async with websockets.connect(ws_url) as ws:
event = await receive_event(ws, timeout=30.0)
vllm/config/ec_transfer.py
-9
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@@ -42,15 +42,6 @@ class ECTransferConfig:
"""Whether this vLLM instance produces, consumes EC cache, or both. Choices
are 'ec_producer', 'ec_consumer', 'ec_both'."""
ec_rank: int | None = None
"""The rank of this vLLM instance in the EC cache transfer. Typical value:
0 for encoder, 1 for pd instance.
Currently only 1P1D is supported."""
ec_parallel_size: int = 1
"""The number of parallel instances for EC cache transfer. For
PyNcclConnector, this should be 2."""
ec_ip: str = "127.0.0.1"
"""The EC connector ip, used to build distributed connection."""
vllm/config/kv_transfer.py
-15
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@@ -68,25 +68,10 @@ class KVTransferConfig:
"""The device used by kv connector to buffer the KV cache. Choices are
'cuda', 'cpu' and 'xpu'."""
kv_buffer_size: float = 1e9
"""The buffer size for TorchDistributedConnector. Measured in number of
bytes. Recommended value: 1e9 (about 1GB)."""
kv_role: KVRole | None = None
"""Whether this vLLM instance produces, consumes KV cache, or both. Choices
are 'kv_producer', 'kv_consumer', and 'kv_both'."""
kv_rank: int | None = None
"""The rank of this vLLM instance in the KV cache transfer. Typical value:
0 for prefill instance, 1 for decode instance.
Currently only 1P1D is supported."""
kv_parallel_size: int = 1
"""The number of parallel instances for KV cache transfer."""
kv_ip: str = "127.0.0.1"
"""The KV connector ip, used to build distributed connection."""
kv_port: int = 14579
"""The KV connector port, used to build distributed connection."""
vllm/config/parallel.py
-4
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@@ -277,9 +277,6 @@ class ParallelConfig:
worker_cls: str = "auto"
"""The full name of the worker class to use. If "auto", the worker class
will be determined based on the platform."""
sd_worker_cls: str = "auto"
"""The full name of the worker class to use for speculative decoding.
If "auto", the worker class will be determined based on the platform."""
worker_extension_cls: str = ""
"""The full name of the worker extension class to use. The worker extension
class is dynamically inherited by the worker class. This is used to inject
@@ -894,7 +891,6 @@ class ParallelConfig:
"placement_group",
"distributed_executor_backend",
"worker_cls",
"sd_worker_cls",
"worker_extension_cls",
"_api_process_count",
"_api_process_rank",
vllm/envs.py
-9
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@@ -23,7 +23,6 @@ if TYPE_CHECKING:
VLLM_ROCM_SLEEP_MEM_CHUNK_SIZE: int = 256
LOCAL_RANK: int = 0
CUDA_VISIBLE_DEVICES: str | None = None
VLLM_ENGINE_ITERATION_TIMEOUT_S: int = 60
VLLM_ENGINE_READY_TIMEOUT_S: int = 600
VLLM_CHAT_TEMPLATE_RENDER_TIMEOUT: float = 30.0
VLLM_API_KEY: str | None = None
@@ -166,9 +165,6 @@ if TYPE_CHECKING:
VLLM_DISABLE_COMPILE_CACHE: bool = False
VLLM_REPLICATE_EMBED: bool = False
VLLM_USE_LAYERNAME: bool = True
Q_SCALE_CONSTANT: int = 200
K_SCALE_CONSTANT: int = 200
V_SCALE_CONSTANT: int = 100
VLLM_USE_RUST_FRONTEND: bool = False
VLLM_USE_RUST_BENCH: bool = False
VLLM_RUST_FRONTEND_PATH: str | None = "auto"
@@ -804,10 +800,6 @@ environment_variables: dict[str, Callable[[], Any]] = {
"LOCAL_RANK": lambda: int(os.environ.get("LOCAL_RANK", "0")),
# used to control the visible devices in the distributed setting
"CUDA_VISIBLE_DEVICES": lambda: os.environ.get("CUDA_VISIBLE_DEVICES", None),
# timeout for each iteration in the engine
"VLLM_ENGINE_ITERATION_TIMEOUT_S": lambda: int(
os.environ.get("VLLM_ENGINE_ITERATION_TIMEOUT_S", "60")
),
# Timeout in seconds for waiting for engine cores to become ready
# during startup. Default is 600 seconds (10 minutes).
"VLLM_ENGINE_READY_TIMEOUT_S": lambda: int(
@@ -2368,7 +2360,6 @@ def compile_factors() -> dict[str, object]:
"VLLM_TUNED_CONFIG_FOLDER",
"VLLM_FLASHINFER_AUTOTUNE_CACHE_DIR",
"VLLM_FLASHINFER_AUTOTUNE_SKIP_OPS",
"VLLM_ENGINE_ITERATION_TIMEOUT_S",
"VLLM_HTTP_TIMEOUT_KEEP_ALIVE",
"VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS",
"VLLM_WORKER_SHUTDOWN_TIMEOUT_SECONDS",