Files
2026-07-13 13:17:40 +08:00

112 lines
4.6 KiB
Python

import uuid
from typing import Any, Optional
from ray.experimental.channel.common import ChannelInterface
class CachedChannel(ChannelInterface):
"""
CachedChannel wraps an inner channel and caches the data read from it until
`num_reads` reads have completed. If inner channel is None, the data
is written to serialization context and retrieved from there. This is useful
when passing data within the same actor and a shared memory channel can be
avoided.
Args:
num_reads: The number of reads from this channel that must happen before
writing again. Readers must be methods of the same actor.
inner_channel: The inner channel to cache data from. If None, the data is
read from the serialization context.
_channel_id: The unique ID for the channel. If None, a new ID is generated.
"""
def __init__(
self,
num_reads: int,
inner_channel: Optional[ChannelInterface] = None,
_channel_id: Optional[str] = None,
):
assert num_reads > 0, "num_reads must be greater than 0."
self._num_reads = num_reads
self._inner_channel = inner_channel
# Generate a unique ID for the channel. The writer and reader will use
# this ID to store and retrieve data from the _SerializationContext.
self._channel_id = _channel_id
if self._channel_id is None:
self._channel_id = str(uuid.uuid4())
def ensure_registered_as_writer(self) -> None:
if self._inner_channel is not None:
self._inner_channel.ensure_registered_as_writer()
def ensure_registered_as_reader(self) -> None:
if self._inner_channel is not None:
self._inner_channel.ensure_registered_as_reader()
def __reduce__(self):
return CachedChannel, (
self._num_reads,
self._inner_channel,
self._channel_id,
)
def __str__(self) -> str:
return (
f"CachedChannel(channel_id={self._channel_id}, "
f"num_reads={self._num_reads}), "
f"inner_channel={self._inner_channel})"
)
def write(self, value: Any, timeout: Optional[float] = None):
self.ensure_registered_as_writer()
# TODO: better organize the imports
from ray.experimental.channel import ChannelContext
if self._inner_channel is not None:
self._inner_channel.write(value, timeout)
return
# Otherwise no need to check timeout as the operation is non-blocking.
# Because both the reader and writer are in the same worker process,
# we can directly store the data in the context instead of storing
# it in the channel object. This removes the serialization overhead of `value`.
ctx = ChannelContext.get_current().serialization_context
ctx.set_data(self._channel_id, value, self._num_reads)
def read(self, timeout: Optional[float] = None) -> Any:
self.ensure_registered_as_reader()
# TODO: better organize the imports
from ray.experimental.channel import ChannelContext
ctx = ChannelContext.get_current().serialization_context
if ctx.has_data(self._channel_id):
# No need to check timeout as the operation is non-blocking.
return ctx.get_data(self._channel_id)
assert (
self._inner_channel is not None
), "Cannot read from the serialization context while inner channel is None."
value = self._inner_channel.read(timeout)
ctx.set_data(self._channel_id, value, self._num_reads)
# NOTE: Currently we make a contract with Compiled Graph users that the
# channel results should not be mutated by the actor methods.
# When the user needs to modify the channel results, they should
# make a copy of the channel results and modify the copy.
# This is the same contract as used in IntraProcessChannel.
# This contract is NOT enforced right now in either case.
# TODO(rui): introduce a flag to control the behavior:
# for example, by default we make a deep copy of the channel
# result, but the user can turn off the deep copy for performance
# improvements.
# https://github.com/ray-project/ray/issues/47409
return ctx.get_data(self._channel_id)
def close(self) -> None:
from ray.experimental.channel import ChannelContext
if self._inner_channel is not None:
self._inner_channel.close()
ctx = ChannelContext.get_current().serialization_context
ctx.reset_data(self._channel_id)