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Update deprecated type hinting in vllm/compilation (#18072)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-05-13 16:32:48 +01:00
committed by GitHub
parent fc407a1425
commit 19324d660c
13 changed files with 70 additions and 69 deletions
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38
vllm/compilation/compiler_interface.py
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@@ -4,7 +4,7 @@ import copy
import hashlib
import os
from contextlib import ExitStack
from typing import Any, Callable, Dict, List, Optional, Tuple
from typing import Any, Callable, Optional
from unittest.mock import patch
import torch
@@ -48,11 +48,11 @@ class CompilerInterface:
def compile(
self,
graph: fx.GraphModule,
example_inputs: List[Any],
compiler_config: Dict[str, Any],
example_inputs: list[Any],
compiler_config: dict[str, Any],
runtime_shape: Optional[int] = None,
key: Optional[str] = None,
) -> Tuple[Optional[Callable], Optional[Any]]:
) -> tuple[Optional[Callable], Optional[Any]]:
"""
Compile the graph with the given example inputs and compiler config,
with a runtime shape. If the `runtime_shape` is None, it means
@@ -82,7 +82,7 @@ class CompilerInterface:
def load(self,
handle: Any,
graph: fx.GraphModule,
example_inputs: List[Any],
example_inputs: list[Any],
graph_index: int,
runtime_shape: Optional[int] = None) -> Callable:
"""
@@ -120,7 +120,7 @@ class AlwaysHitShapeEnv:
"""
def __init__(self) -> None:
self.guards: List[Any] = []
self.guards: list[Any] = []
def evaluate_guards_expression(self, *args, **kwargs):
return True
@@ -132,8 +132,8 @@ class AlwaysHitShapeEnv:
return ""
def get_inductor_factors() -> List[Any]:
factors: List[Any] = []
def get_inductor_factors() -> list[Any]:
factors: list[Any] = []
# summarize system state
from torch._inductor.codecache import CacheBase
system_factors = CacheBase.get_system()
@@ -169,11 +169,11 @@ class InductorStandaloneAdaptor(CompilerInterface):
def compile(
self,
graph: fx.GraphModule,
example_inputs: List[Any],
compiler_config: Dict[str, Any],
example_inputs: list[Any],
compiler_config: dict[str, Any],
runtime_shape: Optional[int] = None,
key: Optional[str] = None,
) -> Tuple[Optional[Callable], Optional[Any]]:
) -> tuple[Optional[Callable], Optional[Any]]:
current_config = {}
if compiler_config is not None:
current_config.update(compiler_config)
@@ -201,7 +201,7 @@ class InductorStandaloneAdaptor(CompilerInterface):
def load(self,
handle: Any,
graph: fx.GraphModule,
example_inputs: List[Any],
example_inputs: list[Any],
graph_index: int,
runtime_shape: Optional[int] = None) -> Callable:
assert isinstance(handle, tuple)
@@ -256,11 +256,11 @@ class InductorAdaptor(CompilerInterface):
def compile(
self,
graph: fx.GraphModule,
example_inputs: List[Any],
compiler_config: Dict[str, Any],
example_inputs: list[Any],
compiler_config: dict[str, Any],
runtime_shape: Optional[int] = None,
key: Optional[str] = None,
) -> Tuple[Optional[Callable], Optional[Any]]:
) -> tuple[Optional[Callable], Optional[Any]]:
from torch._inductor.compile_fx import compile_fx
current_config = {}
if compiler_config is not None:
@@ -420,7 +420,7 @@ class InductorAdaptor(CompilerInterface):
def load(self,
handle: Any,
graph: fx.GraphModule,
example_inputs: List[Any],
example_inputs: list[Any],
graph_index: int,
runtime_shape: Optional[int] = None) -> Callable:
assert isinstance(handle, tuple)
@@ -522,11 +522,11 @@ class EagerAdaptor(CompilerInterface):
def compile(
self,
graph: fx.GraphModule,
example_inputs: List[Any],
compiler_config: Dict[str, Any],
example_inputs: list[Any],
compiler_config: dict[str, Any],
runtime_shape: Optional[int] = None,
key: Optional[str] = None,
) -> Tuple[Optional[Callable], Optional[Any]]:
) -> tuple[Optional[Callable], Optional[Any]]:
# we don't need to compile the graph, just return the graph itself.
# It does not support caching, return None for the handle.
return graph, None