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

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

tools/pre_commit/mypy.py

@@ -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",

vllm/distributed/kv_transfer/kv_connector/v1/base.py

@@ -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

vllm/distributed/kv_transfer/kv_connector/v1/lmcache_mp_connector.py

@@ -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

vllm/distributed/kv_transfer/kv_connector/v1/metrics.py

@@ -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

vllm/distributed/kv_transfer/kv_connector/v1/multi_connector.py

@@ -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(

vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py

@@ -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)
 

vllm/engine/arg_utils.py

@@ -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
         (

vllm/transformers_utils/config.py

@@ -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.
 

vllm/triton_utils/__init__.py

 # 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

vllm/v1/metrics/loggers.py

@@ -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}
 

vllm/v1/sample/logits_processor/__init__.py

@@ -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):

vllm/v1/spec_decode/metrics.py

@@ -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 {