# Event

Source: https://www.tensorplay.cn/docs/generated/tensorplay.cuda.streams.Event.html

```python
class tensorplay.cuda.streams.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 ([tensorplay.device](/docs/generated/tensorplay.Device.html#tensorplay.Device), optional) – the desired device for the Event. If not given, the current the relevant documentation type will be used.

- enable_timing ([bool](https://docs.python.org/3/builtins/functions.html#bool), optional) – indicates if the event should measure time (default: False)

- blocking ([bool](https://docs.python.org/3/builtins/functions.html#bool), optional) – if True, [wait()](#tensorplay.cuda.streams.Event.wait) will be blocking (default: False)

- interprocess ([bool](https://docs.python.org/3/builtins/functions.html#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](#tensorplay.cuda.streams.Event)

Example:

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

```python
elapsed_time(end_event) → float
```

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](https://docs.python.org/3/builtins/functions.html#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)
```

```python
classmethod from_ipc_handle(device, handle)
```

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

```python
ipc_handle()
```

Return an IPC handle of this event.

```python
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](https://docs.python.org/3/builtins/functions.html#bool)

Example:

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

```python
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 (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()
```

```python
synchronize() → None
```

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()
```

```python
wait(stream=None) → None
```

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)
```