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