Event

class tensorplay.cuda.streams.Event(device=None, *, enable_timing=False, blocking=False, interprocess=False)[source]

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

Parameters:

• device (tensorplay.device, optional) – the desired device for the Event. If not given, the current the relevant documentation 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 tensorplay.Event object.

Return type:

Event

Example:

>>> event = tensorplay.Event()
>>> e_cuda = tensorplay.Event(device='cuda')

elapsed_time(end_event) → float[source]

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

Parameters:

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

Returns:

Time between starting and ending event in milliseconds.

Return type:

float

Example:

>>> s_cuda = tensorplay.Stream(device='cuda')
>>> e1_cuda = s_cuda.record_event()
>>> e2_cuda = s_cuda.record_event()
>>> ms = e1_cuda.elapsed_time(e2_cuda)

classmethod from_ipc_handle(device, handle)[source]

Reconstruct an event from an IPC handle on the given device.

ipc_handle()[source]

Return an IPC handle of this event.

query() → bool[source]

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 = tensorplay.Stream(device='cuda')
>>> e_cuda = s_cuda.record_event()
>>> e_cuda.query()
True

record(stream=None) → None[source]

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

Example:

>>> e_cuda = tensorplay.Event(device='cuda')
>>> e_cuda.record()

synchronize() → None[source]

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

Example:

>>> s_cuda = tensorplay.Stream(device='cuda')
>>> e_cuda = s_cuda.record_event()
>>> e_cuda.synchronize()

wait(stream=None) → None[source]

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

Parameters:

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

Example:

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