66 lines
1.8 KiB
Python
66 lines
1.8 KiB
Python
from logging import getLogger
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from torch.multiprocessing import Queue, Value
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from typing import Any, Callable, Tuple
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from ..params import DeviceParams
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logger = getLogger(__name__)
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ProgressCallback = Callable[[int, int, Any], None]
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class WorkerContext:
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cancel: "Value[bool]" = None
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key: str = None
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pending: "Queue[Tuple[Callable, Any, Any]]" = None
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progress: "Value[int]" = None
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def __init__(
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self,
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key: str,
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cancel: "Value[bool]",
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device: DeviceParams,
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pending: "Queue[Any]",
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progress: "Value[int]",
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logs: "Queue[str]",
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finished: "Value[bool]",
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):
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self.key = key
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self.cancel = cancel
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self.device = device
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self.pending = pending
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self.progress = progress
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self.logs = logs
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self.finished = finished
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def is_cancelled(self) -> bool:
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return self.cancel.value
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def get_device(self) -> DeviceParams:
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"""
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Get the device assigned to this job.
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"""
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return self.device
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def get_progress(self) -> int:
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return self.progress.value
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def get_progress_callback(self) -> ProgressCallback:
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def on_progress(step: int, timestep: int, latents: Any):
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on_progress.step = step
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if self.is_cancelled():
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raise RuntimeError("job has been cancelled")
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else:
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logger.debug("setting progress for job %s to %s", self.key, step)
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self.set_progress(step)
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return on_progress
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def set_cancel(self, cancel: bool = True) -> None:
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with self.cancel.get_lock():
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self.cancel.value = cancel
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def set_progress(self, progress: int) -> None:
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with self.progress.get_lock():
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self.progress.value = progress
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