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[mypy] Enable type checking for more directories (#29674)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
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Cyrus Leung 2025-11-29 00:39:27 +08:00 committed by GitHub
parent 9eec282cb5
commit 9e6bcda3ac
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12 changed files with 35 additions and 31 deletions
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12
tools/pre_commit/mypy.py
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@ -27,19 +27,24 @@ FILES = [
"vllm/*.py",
"vllm/assets",
"vllm/distributed",
"vllm/engine",
"vllm/entrypoints",
"vllm/executor",
"vllm/inputs",
"vllm/logging_utils",
"vllm/multimodal",
"vllm/platforms",
"vllm/plugins",
"vllm/transformers_utils",
"vllm/triton_utils",
"vllm/usage",
"vllm/utils",
"vllm/worker",
"vllm/v1/core",
"vllm/v1/engine",
"vllm/v1/metrics",
"vllm/v1/pool",
"vllm/v1/sample",
"vllm/v1/worker",
]
@ -50,24 +55,19 @@ SEPARATE_GROUPS = [
# v0 related
"vllm/attention",
"vllm/compilation",
"vllm/engine",
"vllm/inputs",
"vllm/lora",
"vllm/model_executor",
"vllm/plugins",
"vllm/worker",
# v1 related
"vllm/v1/attention",
"vllm/v1/executor",
"vllm/v1/kv_offload",
"vllm/v1/metrics",
"vllm/v1/sample",
"vllm/v1/spec_decode",
"vllm/v1/structured_output",
]
# TODO(woosuk): Include the code from Megatron and HuggingFace.
EXCLUDE = [
"vllm/engine/arg_utils.py",
"vllm/model_executor/parallel_utils",
"vllm/model_executor/models",
"vllm/model_executor/layers/fla/ops",

2
vllm/distributed/kv_transfer/kv_connector/v1/base.py
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@ -565,7 +565,7 @@ class KVConnectorBase_V1(ABC):
vllm_config: "VllmConfig",
metric_types: dict[type["PromMetric"], type["PromMetricT"]],
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
) -> Optional["KVConnectorPromMetrics"]:
"""
Create a KVConnectorPromMetrics subclass which should register

2
vllm/distributed/kv_transfer/kv_connector/v1/lmcache_mp_connector.py
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@ -806,7 +806,7 @@ class LMCacheMPConnector(KVConnectorBase_V1):
vllm_config: "VllmConfig",
metric_types: dict[type["PromMetric"], type["PromMetricT"]],
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
) -> Optional["KVConnectorPromMetrics"]:
"""
Create a KVConnectorPromMetrics subclass which should register

12
vllm/distributed/kv_transfer/kv_connector/v1/metrics.py
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@ -52,13 +52,13 @@ class KVConnectorStats:
class KVConnectorLogging:
def __init__(self, kv_tranfer_config: KVTransferConfig):
def __init__(self, kv_transfer_config: KVTransferConfig | None):
# This should be called on frontend process.
assert not has_kv_transfer_group()
# Instantiate the connector's stats class.
if kv_tranfer_config and kv_tranfer_config.kv_connector:
if kv_transfer_config and kv_transfer_config.kv_connector:
self.connector_cls = KVConnectorFactory.get_connector_class(
kv_tranfer_config
kv_transfer_config
)
self.reset()
@ -120,7 +120,7 @@ class KVConnectorPromMetrics:
vllm_config: VllmConfig,
metric_types: dict[type[PromMetric], type[PromMetricT]],
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
):
self._kv_transfer_config = vllm_config.kv_transfer_config
self._gauge_cls = metric_types[Gauge]
@ -129,7 +129,7 @@ class KVConnectorPromMetrics:
self._labelnames = labelnames
self._per_engine_labelvalues = per_engine_labelvalues
def make_per_engine(self, metric: PromMetric) -> PromMetric:
def make_per_engine(self, metric: PromMetric) -> dict[int, PromMetric]:
"""
Create a per-engine child of a prometheus_client.Metric with
the appropriate labels set. The parent metric must be created
@ -165,7 +165,7 @@ class KVConnectorPrometheus:
self,
vllm_config: VllmConfig,
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
):
self.prom_metrics: KVConnectorPromMetrics | None = None
kv_transfer_config = vllm_config.kv_transfer_config

4
vllm/distributed/kv_transfer/kv_connector/v1/multi_connector.py
View File

@ -85,7 +85,7 @@ class MultiKVConnectorPromMetrics(KVConnectorPromMetrics):
vllm_config: "VllmConfig",
metric_types: dict[type[PromMetric], type[PromMetricT]],
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
prom_metrics: dict[str, KVConnectorPromMetrics],
):
super().__init__(vllm_config, metric_types, labelnames, per_engine_labelvalues)
@ -434,7 +434,7 @@ class MultiConnector(KVConnectorBase_V1):
vllm_config: "VllmConfig",
metric_types: dict[type["PromMetric"], type["PromMetricT"]],
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
) -> KVConnectorPromMetrics:
prom_metrics: dict[str, KVConnectorPromMetrics] = {}
for connector_cls, temp_config in cls._get_connector_classes_and_configs(

8
vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
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@ -288,7 +288,7 @@ class NixlConnector(KVConnectorBase_V1):
vllm_config: VllmConfig,
metric_types: dict[type[PromMetric], type[PromMetricT]],
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
) -> KVConnectorPromMetrics:
return NixlPromMetrics(
vllm_config, metric_types, labelnames, per_engine_labelvalues
@ -2345,9 +2345,9 @@ class NixlKVConnectorStats(KVConnectorStats):
return {
"Num successful transfers": n,
"Avg xfer time (ms)": round(xfer_time.mean() * 1e3, 3),
"P90 xfer time (ms)": round(np.percentile(xfer_time, 90) * 1e3, 3),
"P90 xfer time (ms)": round(np.percentile(xfer_time, 90).item() * 1e3, 3),
"Avg post time (ms)": round(post_time.mean() * 1e3, 3),
"P90 post time (ms)": round(np.percentile(post_time, 90) * 1e3, 3),
"P90 post time (ms)": round(np.percentile(post_time, 90).item() * 1e3, 3),
"Avg MB per transfer": round(avg_mb, 3),
"Throughput (MB/s)": round(throughput_mb_s, 3),
"Avg number of descriptors": round(descs.mean(), 1),
@ -2364,7 +2364,7 @@ class NixlPromMetrics(KVConnectorPromMetrics):
vllm_config: VllmConfig,
metric_types: dict[type[PromMetric], type[PromMetricT]],
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
):
super().__init__(vllm_config, metric_types, labelnames, per_engine_labelvalues)

4
vllm/engine/arg_utils.py
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@ -1954,7 +1954,9 @@ class EngineArgs:
self.enable_prefix_caching = False
def _set_default_max_num_seqs_and_batched_tokens_args(
self, usage_context: UsageContext, model_config: ModelConfig
self,
usage_context: UsageContext | None,
model_config: ModelConfig,
):
world_size = self.pipeline_parallel_size * self.tensor_parallel_size
(

4
vllm/transformers_utils/config.py
View File

@ -614,12 +614,12 @@ def _maybe_remap_hf_config_attrs(config: PretrainedConfig) -> PretrainedConfig:
def maybe_override_with_speculators(
model: str,
tokenizer: str,
tokenizer: str | None,
trust_remote_code: bool,
revision: str | None = None,
vllm_speculative_config: dict[str, Any] | None = None,
**kwargs,
) -> tuple[str, str, dict[str, Any] | None]:
) -> tuple[str, str | None, dict[str, Any] | None]:
"""
Resolve model configuration when speculators are detected.

3
vllm/triton_utils/__init__.py
View File

@ -1,5 +1,6 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from typing import TYPE_CHECKING
from vllm.triton_utils.importing import (
HAS_TRITON,
@ -7,7 +8,7 @@ from vllm.triton_utils.importing import (
TritonPlaceholder,
)
if HAS_TRITON:
if TYPE_CHECKING or HAS_TRITON:
import triton
import triton.language as tl
import triton.language.extra.libdevice as tldevice

8
vllm/v1/metrics/loggers.py
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@ -104,8 +104,8 @@ class LoggingStatLogger(StatLoggerBase):
self.mm_caching_metrics = CachingMetrics()
self.spec_decoding_logging = SpecDecodingLogging()
kv_tranfer_config = self.vllm_config.kv_transfer_config
self.kv_connector_logging = KVConnectorLogging(kv_tranfer_config)
kv_transfer_config = self.vllm_config.kv_transfer_config
self.kv_connector_logging = KVConnectorLogging(kv_transfer_config)
self.last_prompt_throughput: float = 0.0
self.last_generation_throughput: float = 0.0
self.engine_is_idle = False
@ -380,7 +380,7 @@ class PrometheusStatLogger(AggregateStatLoggerBase):
model_name = vllm_config.model_config.served_model_name
max_model_len = vllm_config.model_config.max_model_len
per_engine_labelvalues: dict[int, list[str]] = {
per_engine_labelvalues: dict[int, list[object]] = {
idx: [model_name, str(idx)] for idx in engine_indexes
}
@ -1052,7 +1052,7 @@ PromMetric: TypeAlias = Gauge | Counter | Histogram
def make_per_engine(
metric: PromMetric, engine_idxs: list[int], model_name: str
metric: PromMetric, engine_idxs: list[int], model_name: object
) -> dict[int, PromMetric]:
return {idx: metric.labels(model_name, str(idx)) for idx in engine_idxs}

2
vllm/v1/sample/logits_processor/__init__.py
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@ -313,7 +313,7 @@ class AdapterLogitsProcessor(LogitsProcessor):
if (len(inspect.signature(req_lp).parameters) == 3)
else [output_ids]
)
return partial(req_lp, *args)
return partial(req_lp, *args) # type: ignore[misc]
return None
def update_state(self, batch_update: BatchUpdate | None):

5
vllm/v1/spec_decode/metrics.py
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@ -144,7 +144,7 @@ class SpecDecodingProm:
self,
speculative_config: SpeculativeConfig | None,
labelnames: list[str],
per_engine_labelvalues: dict[int, list[str]],
per_engine_labelvalues: dict[int, list[object]],
):
self.spec_decoding_enabled = speculative_config is not None
if not self.spec_decoding_enabled:
@ -215,7 +215,8 @@ class SpecDecodingProm:
def make_per_engine(
counter: prometheus_client.Counter, per_engine_labelvalues: dict[int, list[str]]
counter: prometheus_client.Counter,
per_engine_labelvalues: dict[int, list[object]],
):
"""Create a counter for each label value."""
return {