Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71658
This adds the beginnings of a TensorboardEventHandler which will log stats to Tensorboard.
Test Plan: buck test //caffe2/test:monitor
Reviewed By: edward-io
Differential Revision: D33719954
fbshipit-source-id: e9847c1319255ce0d9cf2d85d8b54b7a3c681bd2
(cherry picked from commit 5c8520a6baea51db02e4e29d0210b3ced60fa18d)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69567
This exposes torch.monitor events and stats via pybind11 to the underlying C++ implementation.
* The registration interface is a tad different since it takes a lambda function in Python where as in C++ it's a full class.
* This has a small amount of changes to the counter interfaces since there's no way to create an initializer list at runtime so they now also take a vector.
* Only double based stats are provided in Python since it's intended more for high level stats where float imprecision shouldn't be an issue. This can be changed down the line if need arises.
```
events = []
def handler(event):
events.append(event)
handle = register_event_handler(handler)
log_event(Event(type="torch.monitor.TestEvent", timestamp=datetime.now(), metadata={"foo": 1.0}))
```
D32969391 is now included in this diff.
This cleans up the naming for events. type is now name, message is gone, and metadata is renamed data.
Test Plan: buck test //caffe2/test:monitor //caffe2/test/cpp/monitor:monitor
Reviewed By: kiukchung
Differential Revision: D32924141
fbshipit-source-id: 563304c2e3261a4754e40cca39fc64c5a04b43e8
