Files
pytorch/torch/_inductor/remote_cache.py
Maggie Moss 9944cac6e6 Add suppressions to torch/_inductor (#165062)
Adds suppressions to pyrefly will typecheck clean: https://github.com/pytorch/pytorch/issues/163283

Split this directory into two PRs to keep them from being too large.

Test plan:
dmypy restart && python3 scripts/lintrunner.py -a
pyrefly check

step 1: delete lines in the pyrefly.toml file from the project-excludes field
step 2: run pyrefly check
step 3: add suppressions, clean up unused suppressions
before: https://gist.github.com/maggiemoss/4b3bf2037014e116bc00706a16aef199

after:
INFO 0 errors (6,884 ignored)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/165062
Approved by: https://github.com/oulgen, https://github.com/mlazos
2025-10-09 20:34:20 +00:00

429 lines
13 KiB
Python

from __future__ import annotations
import atexit
import collections
import dataclasses
import functools
import json
import logging
import os
import sys
import typing
from abc import abstractmethod
from typing import Any, Callable, Generic, Optional, TypeVar, Union
from typing_extensions import override, TypeAlias
from torch._dynamo.utils import dynamo_timed
from torch._inductor import config
from torch.monitor import _WaitCounter
try:
import redis
except ImportError:
redis = None # type: ignore[assignment]
log = logging.getLogger(__name__)
if config.is_fbcode():
from rfe.scubadata.scubadata_py3 import ( # type: ignore[import-not-found]
Sample as Sample_,
)
Sample: TypeAlias = Sample_
else:
Sample: TypeAlias = type[object] # type: ignore[misc,no-redef]
_T = TypeVar("_T")
_U = TypeVar("_U")
remote_fx_cache_get_timed = functools.partial(
dynamo_timed,
"FbRemoteFxGraphCache.get",
phase_name="remote_fx_graph_cache_get",
log_pt2_compile_event=False,
dynamo_compile_column_us="remote_fx_graph_cache_get_time_us",
log_waitcounter=True,
)
remote_fx_cache_put_timed = functools.partial(
dynamo_timed,
"FbRemoteFxGraphCache.put",
phase_name="remote_fx_graph_cache_put",
log_pt2_compile_event=False,
dynamo_compile_column_us="remote_fx_graph_cache_put_time_us",
log_waitcounter=True,
)
class RemoteCacheBackend(Generic[_T]):
"""
A backend implementation for accessing a remote/distributed cache. Only
works with bytes in/out. For structured data use a RemoteCache.
"""
def __init__(self) -> None:
self._name = f"backend:{type(self).__name__}"
@abstractmethod
def _get(self, key: str) -> Optional[_T]:
pass
@abstractmethod
def _put(self, key: str, data: _T) -> None:
pass
def get(self, key: str) -> Optional[_T]:
try:
value = self._get(key)
cache_stats.get(self._name, value)
except Exception:
cache_stats.exception(self._name)
raise
return value
def put(self, key: str, data: _T) -> None:
try:
self._put(key, data)
cache_stats.put(self._name)
except Exception:
cache_stats.exception(self._name)
raise
# Serde that encodes from _T to _U and decodes from _U to _T.
class RemoteCacheSerde(Generic[_T, _U]):
@abstractmethod
def encode(self, data: _T) -> _U:
pass
@abstractmethod
def decode(self, data: _U) -> _T:
pass
JsonDataTy = Optional[
Union[int, float, str, bool, dict[str, "JsonDataTy"], list["JsonDataTy"]]
]
class RemoteCacheJsonSerde(RemoteCacheSerde[JsonDataTy, bytes]):
def encode(self, data: JsonDataTy) -> bytes:
return bytes(json.dumps(data), "ascii")
def decode(self, data: bytes) -> JsonDataTy:
return json.loads(data)
class RemoteCachePassthroughSerde(RemoteCacheSerde[_T, _T]):
def encode(self, data: _T) -> _T:
return data
def decode(self, data: _T) -> _T:
return data
# This class is the top of a RemoteCache. A RemoteCache is fundamentally made of
# three parts:
#
# 1. The controller (this class).
# 2. A serializer/deserializer (instance of RemoteCacheSerde).
# 3. A backend (instance of RemoteCacheBackend).
#
# To write (`put`), the RemoteCache takes data, uses the RemoteCacheSerde to
# convert it for the backend and passes it to the backend.
#
# Conversely when reading (`get`), the RemoteCache takes data from the backend,
# uses the RemoteCacheSerde to convert it and returns it.
#
# The RemoteCacheBackend is generic on _U - which is the type of data the
# backend can directly cache (usually `bytes`).
#
# The RemoteCacheSerde is responsible for converting between _T (the type of
# data the RemoteCache accepts in `put` and returns in `get`) and _U.
#
# When instantiating a RemoteCache you should override, not directly create a
# RemoteCache. The reason is that when logging cache use (`TORCH_LOGS=cache`) we
# use the concrete type of the RemoteCache as the reported cache. See
# RemoteFxGraphCache below as an example.
class RemoteCache(Generic[_T]):
backend_override_cls: Optional[Callable[[], RemoteCacheBackend[Any]]] = None
def __init__(
self, backend: RemoteCacheBackend[_U], serde: RemoteCacheSerde[_T, _U]
) -> None:
# Support for testing to mock out the backend on a class-by-class basis.
if (override_cls := self.__class__.backend_override_cls) is not None:
self.backend = override_cls()
else:
self.backend = backend
# pyrefly: ignore # invalid-type-var
self.serde = serde
# See if the cache contains `key`. Returns `None` if the value is not
# present in the cache.
def get(self, key: str) -> Optional[_T]:
with _WaitCounter("pytorch.remote_cache.get").guard():
sample = self._create_sample()
try:
result = self._get(key, sample)
cache_stats.get(type(self).__name__, result)
except Exception as e:
cache_stats.exception(type(self).__name__)
if sample:
sample.fail_reason = str(e)
raise
finally:
self._log_sample(sample)
return result
# Add `value` to the cache with the key `key`. Note that `None` is not a
# valid value even if _T supports it (because you can't tell the difference
# between `None` and a missing cache entry).
def put(self, key: str, value: _T) -> None:
with _WaitCounter("pytorch.remote_cache.put").guard():
assert value is not None
sample = self._create_sample()
try:
self._put(key, value, sample)
cache_stats.put(type(self).__name__)
except Exception as e:
cache_stats.exception(type(self).__name__)
if sample:
sample.fail_reason = str(e)
raise
finally:
self._log_sample(sample)
# Used to convert data from the cache into structured data.
def _decode(self, data: _U, sample: Optional[Sample]) -> _T: # type: ignore[override]
return self.serde.decode(data) # type: ignore[arg-type]
# Used to convert structured data into data for the cache.
def _encode(self, value: _T, sample: Optional[Sample]) -> object: # returns _U
return self.serde.encode(value)
# Get structured data from the cache.
# Separate from `get` so that it can be overridden.
def _get(self, key: str, sample: Optional[Sample]) -> Optional[_T]:
if data := self._backend_get(key):
return self._decode(data, sample)
return None
# Get unstructured data from the cache.
# Separate from `get` so that it can be overridden.
# Returns _U - but we aren't actually generic on _U
def _backend_get(self, key: str) -> object:
return self.backend.get(key)
# Put structured data into the cache.
# Separate from `put` so that it can be overridden.
def _put(self, key: str, value: _T, sample: Optional[Sample]) -> None:
data = self._encode(value, sample)
self._backend_put(key, data)
# Put unstructured data into the cache.
# Separate from `put` so that it can be overridden.
# Takes data: _U - but we aren't actually generic on _U
def _backend_put(self, key: str, data: object) -> None:
self.backend.put(key, data)
# Create a logging Sample - used with internal loggers to monitor cache
# effectiveness.
def _create_sample(self) -> Optional[Sample]:
return None
# Write the logging Sample to the logger.
def _log_sample(self, sample: Optional[Sample]) -> None:
pass
class RedisRemoteCacheBackend(RemoteCacheBackend[bytes]):
"""
A Redis implementation of a remote/distributed cache.
"""
# pyrefly: ignore # missing-attribute
_redis: Optional[redis.Redis] = None
def __init__(self, cache_id: str) -> None:
super().__init__()
if not redis:
raise RuntimeError("redis not available but required for remote cache")
if "TORCHINDUCTOR_REDIS_URL" in os.environ:
self._redis = redis.Redis.from_url(os.environ["TORCHINDUCTOR_REDIS_URL"])
else:
self._redis = redis.Redis(
host=os.environ.get("TORCHINDUCTOR_REDIS_HOST", "localhost"),
port=int(os.environ.get("TORCHINDUCTOR_REDIS_PORT", 6379)),
)
@override
def _get(self, key: str) -> Optional[bytes]:
if not self._redis:
# Either redis wasn't found or we already had some trouble...
return None
try:
# pyrefly: ignore # missing-attribute
value = self._redis.get(key)
# pyrefly: ignore # missing-attribute
except redis.exceptions.ConnectionError:
# Redis is lazy and doesn't actually attempt to connect until the
# first use. Mark is as unavailable now.
self._redis = None
return None
# In theory redis.get() can return an Awaitable as well...
assert value is None or isinstance(value, bytes)
return value
@override
def _put(self, key: str, data: bytes) -> None:
if not self._redis:
# Either redis wasn't found or we already had some trouble...
return
try:
# pyrefly: ignore # missing-attribute
self._redis.set(key, data)
# pyrefly: ignore # missing-attribute
except redis.exceptions.ConnectionError:
# Redis is lazy and doesn't actually attempt to connect until the
# first use. Mark is as unavailable now.
self._redis = None
class RedisRemoteCache(RemoteCache[JsonDataTy]):
def __init__(self, cache_id: str) -> None:
# Special test handling: If we're just going to override the backend
# anyway don't require redis
if self.__class__.backend_override_cls:
# This is totally bogus but it works for now...
backend = typing.cast(RemoteCacheBackend[bytes], None)
else:
backend = RedisRemoteCacheBackend(cache_id)
serde = RemoteCacheJsonSerde()
super().__init__(backend, serde)
version = 1 # consistency between various types of keys
self._key_fmt = f"pt2:{cache_id}::{{key}}:c{version}"
def _get_key(self, key: str) -> str:
return self._key_fmt.format(key=key)
@override
def _get(self, key: str, sample: Optional[Sample]) -> Optional[JsonDataTy]:
key = self._get_key(key)
return super()._get(key, sample)
@override
def _put(self, key: str, value: JsonDataTy, sample: Optional[Sample]) -> None:
key = self._get_key(key)
super()._put(key, value, sample)
class RemoteAutotuneCache(RedisRemoteCache):
pass
class RemoteBundledAutotuneCache(RedisRemoteCache):
pass
class RemoteFxGraphCache(RedisRemoteCache):
pass
class RemoteAOTAutogradCache(RedisRemoteCache):
pass
class RemoteDynamoPGOCache(RedisRemoteCache):
pass
def create_cache(
key: str,
is_fbcode: bool,
fb_cache_cls: str,
oss_cache_cls: str,
) -> Optional[RemoteCache[JsonDataTy]]:
try:
if is_fbcode:
import torch._inductor.fb.remote_cache
cache_cls = getattr(torch._inductor.fb.remote_cache, fb_cache_cls)
return cache_cls(key)
else:
this_module = sys.modules[__name__]
cache_cls = getattr(this_module, oss_cache_cls)
return cache_cls(key)
except Exception:
log.warning("Unable to create a remote cache", exc_info=True)
return None
# Some simple stat capture
@dataclasses.dataclass
class _CacheStat:
miss: int = 0
hit: int = 0
put: int = 0
exception: int = 0
def __str__(self) -> str:
return f"{{hit: {self.hit}, miss: {self.miss}, put: {self.put}, exception: {self.exception}}}"
class _CacheStats:
_stats: dict[str, _CacheStat]
def __init__(self) -> None:
self._stats = collections.defaultdict(_CacheStat)
def miss(self, name: str, count: int = 1) -> None:
self._stats[name].miss += count
def hit(self, name: str, count: int = 1) -> None:
self._stats[name].hit += count
def get(self, name: str, value: Optional[object]) -> None:
if value is None:
self.miss(name)
else:
self.hit(name)
def put(self, name: str, count: int = 1) -> None:
self._stats[name].put += count
def exception(self, name: str, count: int = 1) -> None:
self._stats[name].exception += count
cache_stats = _CacheStats()
@atexit.register
def dump_cache_stats() -> None:
if not log.isEnabledFor(logging.INFO):
return
import io
out = io.StringIO()
if not cache_stats._stats:
print(" None", file=out)
else:
print(file=out)
for k, v in sorted(cache_stats._stats.items()):
print(f" {k}: {v}", file=out)
log.info("Cache Metrics:%s", out.getvalue())