ruff-rules-for-pyupgrade (#436)

Author: cclauss

compiler_opt/benchmark/benchmark_chromium.py

@@ -52,8 +52,6 @@
 from compiler_opt.benchmark import gtest_executable_utils
 from compiler_opt.benchmark import benchmarking_utils
 
-from typing import List, Dict, Union
-
 FLAGS = flags.FLAGS
 
 test_prefix = './compiler_opt/benchmark/chromium_test_descriptions/'
@@ -110,7 +108,7 @@
 
 def build_chromium_tests(regalloc_advisor: str, chromium_build_path: str,
                          chromium_source_path: str, depot_tools_path: str,
-                         llvm_build_path: str, tests_to_build: List[str]):
+                         llvm_build_path: str, tests_to_build: list[str]):
   """Builds the chromium test suite
 
   This function will build the specified chromium tests using the specified
@@ -170,9 +168,9 @@ def build_chromium_tests(regalloc_advisor: str, chromium_build_path: str,
     ninja_compile_process.wait()
 
 
-def run_tests(tests_to_run: List[Dict[str, Union[str, List[str]]]],
+def run_tests(tests_to_run: list[dict[str, str | list[str]]],
               chromium_absolute_build_path: str, num_threads: int,
-              perf_counters: List[str]):
+              perf_counters: list[str]):
   """A utility to run a set of chromium tests
 
   This function takes in a list of test descriptions containing the

compiler_opt/benchmark/benchmark_report.py

@@ -18,31 +18,28 @@
 import statistics
 
 from typing import Any
-from typing import Dict
-from typing import Iterable
-from typing import List
-from typing import Tuple
+from collections.abc import Iterable
 
 from absl import logging
 
 # For each benchmark, and for each counter, capture the recorded values.
-PerBenchmarkResults = Dict[str, Dict[str, List[float]]]
+PerBenchmarkResults = dict[str, dict[str, list[float]]]
 
 # Benchmark data, as captured by the benchmark json output: a dictionary from
 # benchmark names to a list of run results. Each run result is a dictionary of
 # key-value pairs, e.g. counter name - value.
-BenchmarkRunResults = Dict[str, List[Dict[str, Any]]]
+BenchmarkRunResults = dict[str, list[dict[str, Any]]]
 
 # A comparison per benchmark, per counter, capturing the geomean and the stdev
 # of the base and experiment values.
-ABComparison = Dict[str, Dict[str, Tuple[float, float, float]]]
+ABComparison = dict[str, dict[str, tuple[float, float, float]]]
 
 
-def _geomean(data: List[float]):
+def _geomean(data: list[float]):
   return math.exp(sum(math.log(x) for x in data) / len(data))
 
 
-def _stdev(data: List[float]):
+def _stdev(data: list[float]):
   assert data
   return 0.0 if len(data) == 1 else statistics.stdev(data)
 
@@ -70,7 +67,7 @@ def counters(self):
   def raw_measurements(self):
     return self._raw_measurements
 
-  def counter_means(self, benchmark: str, counter: str) -> Tuple[float, float]:
+  def counter_means(self, benchmark: str, counter: str) -> tuple[float, float]:
     if counter not in self.counters():
       raise ValueError('unknown counter')
     if benchmark not in self.names():

compiler_opt/benchmark/benchmark_report_converter.py

@@ -32,7 +32,7 @@
 import csv
 import json
 
-from typing import Sequence
+from collections.abc import Sequence
 
 from absl import app
 from absl import flags

compiler_opt/benchmark/benchmarking_utils.py

@@ -20,11 +20,9 @@
 import tensorflow
 import json
 
-from typing import Optional, List
-
 
 def build_llvm(model_path: str, use_existing_build: bool, llvm_build_path: str,
-               llvm_source_path: Optional[str]):
+               llvm_source_path: str | None):
   """Builds LLVM/clang with the specified model and the correct settings
 
   This function invokes CMake with all the correct build flags specified
@@ -72,7 +70,7 @@ def build_llvm(model_path: str, use_existing_build: bool, llvm_build_path: str,
     cmake_compile_process.wait()
 
 
-def run_microbenchmark(executable: str, perf_counters: List[str]):
+def run_microbenchmark(executable: str, perf_counters: list[str]):
   """Runs all the tests in a specific google benchmark binary
 
   This function takes in an executable and performance counters according to the

compiler_opt/benchmark/gtest_executable_utils.py

@@ -18,11 +18,10 @@
 import re
 
 from joblib import Parallel, delayed
-from typing import Tuple, List, Optional, Dict
 from absl import logging
 
 
-def run_test(test_executable: str, test_name: str, perf_counters: List[str]):
+def run_test(test_executable: str, test_name: str, perf_counters: list[str]):
   """Runs a specific test
 
   This function executes a specific test in a gtest executable using
@@ -55,7 +54,7 @@ def run_test(test_executable: str, test_name: str, perf_counters: List[str]):
     return decoded_stderr
 
 
-def parse_perf_stat_output(perf_stat_output: str, perf_counters: List[str]):
+def parse_perf_stat_output(perf_stat_output: str, perf_counters: list[str]):
   """Parses raw output from perf stat
 
   This function takes in the raw decoded output from perf stat
@@ -77,7 +76,7 @@ def parse_perf_stat_output(perf_stat_output: str, perf_counters: List[str]):
   return counters_dict
 
 
-def run_and_parse(test_description: Tuple[str, str, List[str]]):
+def run_and_parse(test_description: tuple[str, str, list[str]]):
   """Runs a test and processes the output of an individual test
 
   This function takes in a description of an individual test, runs the test
@@ -98,9 +97,9 @@ def run_and_parse(test_description: Tuple[str, str, List[str]]):
     return None
 
 
-def run_test_suite(test_suite_description: Dict[str, List[str]],
-                   test_executable: str, perf_counters: List[str],
-                   num_threads: Optional[int]):
+def run_test_suite(test_suite_description: dict[str, list[str]],
+                   test_executable: str, perf_counters: list[str],
+                   num_threads: int | None):
   """Runs an entire test suite
 
   This function takes in a test set description in the form of a path to a JSON

compiler_opt/distributed/buffered_scheduler.py

@@ -18,17 +18,18 @@
 import concurrent.futures
 import threading
 
-from typing import Any, Callable, Iterable, List, Optional, Tuple, TypeVar
+from typing import Any, TypeVar
+from collections.abc import Callable, Iterable
 
 from compiler_opt.distributed import worker
 
 T = TypeVar('T')
 W = TypeVar('W')
 
 
-def schedule(work: List[Callable[[T], worker.WorkerFuture]],
-             workers: List[T],
-             buffer=2) -> List[concurrent.futures.Future]:
+def schedule(work: list[Callable[[T], worker.WorkerFuture]],
+             workers: list[T],
+             buffer=2) -> list[concurrent.futures.Future]:
   """
   Assigns work to workers once previous work of the worker are
   completed.
@@ -86,8 +87,8 @@ def schedule_on_worker_pool(
     action: Callable[[W, T], Any],
     jobs: Iterable[T],
     worker_pool: worker.WorkerPool,
-    buffer_size: Optional[int] = None
-) -> Tuple[List[W], List[concurrent.futures.Future]]:
+    buffer_size: int | None = None
+) -> tuple[list[W], list[concurrent.futures.Future]]:
   """
   Schedule the given action on workers from the given worker pool.
   Args:
@@ -111,7 +112,7 @@ def work(w: worker.Worker):
     return work
 
   work = [work_factory(job) for job in jobs]
-  workers: List[W] = worker_pool.get_currently_active()
+  workers: list[W] = worker_pool.get_currently_active()
   return workers, schedule(work, workers,
                            (worker_pool.get_worker_concurrency()
                             if buffer_size is None else buffer_size))

compiler_opt/distributed/local/local_worker_manager.py

@@ -40,7 +40,8 @@
 
 from contextlib import AbstractContextManager
 from multiprocessing import connection
-from typing import Any, Callable, Dict, List, Optional
+from typing import Any
+from collections.abc import Callable
 
 
 @dataclasses.dataclass(frozen=True)
@@ -139,7 +140,7 @@ def __init__(self):
       # lock for the msgid -> reply future map. The map will be set to None
       # when we stop.
       self._lock = threading.Lock()
-      self._map: Dict[int, concurrent.futures.Future] = {}
+      self._map: dict[int, concurrent.futures.Future] = {}
 
       # thread draining the pipe
       self._pump = threading.Thread(target=self._msg_pump)
@@ -164,7 +165,7 @@ def observer():
 
     def _msg_pump(self):
       while True:
-        task_result: Optional[TaskResult] = self._pipe.recv()
+        task_result: TaskResult | None = self._pipe.recv()
         if task_result is None:  # Poison pill fed by observer
           break
         with self._lock:
@@ -229,7 +230,7 @@ def set_nice(self, val: int):
       """
       psutil.Process(self._process.pid).nice(val)
 
-    def set_affinity(self, val: List[int]):
+    def set_affinity(self, val: list[int]):
       """Sets the CPU affinity of the process, this modifies which cores the OS
       schedules it on.
       """
@@ -247,7 +248,7 @@ def __dir__(self):
 
 
 def create_local_worker_pool(worker_cls: 'type[worker.Worker]',
-                             count: Optional[int], *args,
+                             count: int | None, *args,
                              **kwargs) -> worker.FixedWorkerPool:
   """Create a local worker pool for worker_cls."""
   if not count:
@@ -271,7 +272,7 @@ def close_local_worker_pool(pool: worker.FixedWorkerPool):
 class LocalWorkerPoolManager(AbstractContextManager):
   """A pool of workers hosted on the local machines, each in its own process."""
 
-  def __init__(self, worker_class: 'type[worker.Worker]', count: Optional[int],
+  def __init__(self, worker_class: 'type[worker.Worker]', count: int | None,
                *args, **kwargs):
     self._pool = create_local_worker_pool(worker_class, count, *args, **kwargs)
 

compiler_opt/distributed/worker.py

@@ -14,7 +14,8 @@
 """Common abstraction for a worker contract."""
 
 import abc
-from typing import Any, List, Iterable, Optional, Protocol, TypeVar
+from typing import Any, Protocol, TypeVar
+from collections.abc import Iterable
 
 import gin
 
@@ -35,7 +36,7 @@ class WorkerPool(metaclass=abc.ABCMeta):
 
   # Issue #155 would strongly-type the return type.
   @abc.abstractmethod
-  def get_currently_active(self) -> List[Any]:
+  def get_currently_active(self) -> list[Any]:
     raise NotImplementedError()
 
   @abc.abstractmethod
@@ -47,7 +48,7 @@ class FixedWorkerPool(WorkerPool):
   """A WorkerPool built from a fixed list of workers."""
 
   # Issue #155 would strongly-type `workers`
-  def __init__(self, workers: List[Any], worker_concurrency: int = 2):
+  def __init__(self, workers: list[Any], worker_concurrency: int = 2):
     self._workers = workers
     self._worker_concurrency = worker_concurrency
 
@@ -80,7 +81,7 @@ def wait_for(futures: Iterable[WorkerFuture]):
       pass
 
 
-def get_exception(worker_future: WorkerFuture) -> Optional[Exception]:
+def get_exception(worker_future: WorkerFuture) -> Exception | None:
   assert worker_future.done()
   try:
     _ = worker_future.result()

compiler_opt/es/blackbox_evaluator.py

@@ -15,7 +15,6 @@
 
 import abc
 import concurrent.futures
-from typing import List, Optional
 
 from absl import logging
 import gin
@@ -36,16 +35,16 @@ def __init__(self, train_corpus: corpus.Corpus):
 
   @abc.abstractmethod
   def get_results(
-      self, pool: FixedWorkerPool, perturbations: List[policy_saver.Policy]
-  ) -> List[concurrent.futures.Future]:
+      self, pool: FixedWorkerPool, perturbations: list[policy_saver.Policy]
+  ) -> list[concurrent.futures.Future]:
     raise NotImplementedError()
 
   @abc.abstractmethod
   def set_baseline(self, pool: FixedWorkerPool) -> None:
     raise NotImplementedError()
 
   def get_rewards(
-      self, results: List[concurrent.futures.Future]) -> List[Optional[float]]:
+      self, results: list[concurrent.futures.Future]) -> list[float | None]:
     rewards = [None] * len(results)
 
     for i in range(len(results)):
@@ -74,8 +73,8 @@ def __init__(self, train_corpus: corpus.Corpus,
     super().__init__(train_corpus)
 
   def get_results(
-      self, pool: FixedWorkerPool, perturbations: List[policy_saver.Policy]
-  ) -> List[concurrent.futures.Future]:
+      self, pool: FixedWorkerPool, perturbations: list[policy_saver.Policy]
+  ) -> list[concurrent.futures.Future]:
     if not self._samples:
       for _ in range(self._total_num_perturbations):
         sample = self._train_corpus.sample(self._num_ir_repeats_within_worker)
@@ -118,11 +117,11 @@ def __init__(self, train_corpus: corpus.Corpus,
     self._bb_trace_path = bb_trace_path
     self._function_index_path = function_index_path
 
-    self._baseline: Optional[float] = None
+    self._baseline: float | None = None
 
   def get_results(
-      self, pool: FixedWorkerPool, perturbations: List[policy_saver.Policy]
-  ) -> List[concurrent.futures.Future]:
+      self, pool: FixedWorkerPool, perturbations: list[policy_saver.Policy]
+  ) -> list[concurrent.futures.Future]:
     job_args = [{
         'modules': self._train_corpus.module_specs,
         'function_index_path': self._function_index_path,