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Event

class torch.Event(device=None, *, enable_timing=False, blocking=False, interprocess=False)

Query and record Stream status to identify or control dependencies across Stream and measure timing.

Parameters
  • device (torch.device, optional) – the desired device for the Event. If not given, the current accelerator type will be used.
  • enable_timing (bool, optional) – indicates if the event should measure time (default: False)
  • blocking (bool, optional) – if True, wait() will be blocking (default: False)
  • interprocess (bool) – if True, the event can be shared between processes (default: False)

Warning

Both blocking and interprocess are not supported right now and are noops.

Returns

An torch.Event object.

Return type

Event

Example:

>>> event = torch.Event()
>>> e_cuda = torch.Event(device='cuda')
elapsed_time(end_event) → float

Returns the elapsed time in milliseconds between when this event and the end_event are each recorded via torch.Stream.record_event().

Parameters

end_event (torch.Event) – The ending event has been recorded.

Returns

Time between starting and ending event in milliseconds.

Return type

float

Example:

>>> s_cuda = torch.Stream(device='cuda')
>>> e1_cuda = s_cuda.record_event()
>>> e2_cuda = s_cuda.record_event()
>>> ms = e1_cuda.elapsed_time(e2_cuda)
query() → bool

Check if the stream where this event was recorded already moved past the point where the event was recorded. Always returns True if the Event was not recorded.

Returns

A boolean indicating if all work currently captured by event has completed.

Return type

bool

Example:

>>> s_cuda = torch.Stream(device='cuda')
>>> e_cuda = s_cuda.record_event()
>>> e_cuda.query()
True
record(stream=None) → None

Record the event in a given stream. The stream’s device must match the event’s device. This function is equivalent to stream.record_event(self).

Parameters

stream (torch.Stream, optional) – A stream to be recorded. If not given, the current stream will be used.

Example:

>>> e_cuda = torch.Event(device='cuda')
>>> e_cuda.record()
synchronize() → None

Wait for the event to complete. This prevents the CPU thread from proceeding until the event completes.

Example:

>>> s_cuda = torch.Stream(device='cuda')
>>> e_cuda = s_cuda.record_event()
>>> e_cuda.synchronize()
wait(stream=None) → None

Make all future work submitted to the given stream wait for this event.

Parameters

stream (torch.Stream, optional) – A stream to synchronize. If not given, the current stream will be used.

Example:

>>> s1_cuda = torch.Stream(device='cuda')
>>> s2_cuda = torch.Stream(device='cuda')
>>> e_cuda = s1_cuda.record()
>>> e_cuda.wait(s2)

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https://docs.pytorch.org/docs/2.9/generated/torch.Event.html