mindspore.hal.Event

class mindspore.hal.Event(enable_timing=False, blocking=False)

Wrapper around a device event, this api will be deprecated and removed in future versions, please use the api mindspore.runtime.Event() instead.

Device events are synchronization markers that can be used to monitor the device’s progress, to accurately measure timing, and to synchronize device streams.

The underlying device events are lazily initialized when the event is first recorded.

Parameters

• enable_timing (bool, optional) – indicates if the event should measure time. Default False.

• blocking (bool, optional) – if True, wait will be blocking. Default False.

Examples

>>> import mindspore
>>> start = mindspore.hal.Event(enable_timing=True)
>>> end = mindspore.hal.Event(enable_timing=True)
>>> s1 = mindspore.hal.Stream()
>>> s2 = mindspore.hal.Stream()
>>> a = mindspore.tensor(mindspore.ops.ones([2, 2]), mindspore.float32)
>>> b = mindspore.tensor(mindspore.ops.ones([2, 2]), mindspore.float32)
>>> c = mindspore.tensor(mindspore.ops.ones([2, 2]), mindspore.float32)
>>> with mindspore.hal.StreamCtx(s1):
...     d = mindspore.ops.matmul(a, b)
...     start.record()
>>> c += 2
>>> end.record()
>>> with mindspore.hal.StreamCtx(s2):
...     start.synchronize()
...     end.synchronize()
...     e = c + d
>>> mindspore.hal.synchronize()
>>> print(e)
[[5. 5.]
 [5. 5.]]
>>> elapsed_time = start.elapsed_time(end)

elapsed_time(end_event)

Return the time elapsed in milliseconds after the event was recorded and before the end_event was recorded.

Parameters

end_event (Event) – end event.

Returns

float, the time elapsed in milliseconds.

query()

Check if all work currently captured by event has completed.

Returns

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

Examples

>>> import mindspore
>>> a = mindspore.tensor(mindspore.ops.ones([1024, 2048]), mindspore.float32)
>>> b = mindspore.tensor(mindspore.ops.ones([2048, 4096]), mindspore.float32)
>>> s1 = mindspore.hal.Stream()
>>> with mindspore.hal.StreamCtx(s1):
...     c = mindspore.ops.matmul(a, b)
...     ev = s1.record_event()
>>> s1.synchronize()
>>> assert ev.query()

record(stream=None)

Record the event in a given stream.

Uses mindspore.hal.current_stream() if no stream is specified. The stream's device must match the event's device.

Parameters

stream (Stream, optional) – a stream to record. If this argument is None, current stream will be used. Default None.

synchronize()

Wait for the event to complete.

Waits until the completion of all work currently captured in this event. This prevents the CPU thread from proceeding until the event completes.

wait(stream=None)

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

Use mindspore.hal.current_stream() if no stream is specified.

Parameters

stream (Stream, optional) – a stream to record. If this argument is None, current stream will be used. Default None.

Examples

>>> import mindspore
>>> event = mindspore.hal.Event()
>>> s1 = mindspore.hal.Stream()
>>> s2 = mindspore.hal.Stream()
>>> a = mindspore.tensor(mindspore.ops.ones([2, 2]), mindspore.float32)
>>> b = mindspore.tensor(mindspore.ops.ones([2, 2]), mindspore.float32)
>>> with mindspore.hal.StreamCtx(s1):
...     c = mindspore.ops.matmul(a, b)
...     event.record()
>>> event.wait()
>>> d = c + 2
>>> mindspore.hal.synchronize()
>>> print(d)
[[4. 4.]
 [4. 4.]]