About obtaining ET before execution

[191220042]

hello,I wonder if I can get an ET or some other information that can be used to generate chakra before the actual execution of the program, as I saw “We extended PyTorch to support trace collection with the Execution Graph Observer [1], which does not require intrusive modifications to ML models. Simply enabling the Execution Graph Observer before running a model yields traces that closely reflect real-world execution.” when I read the paper ，
but in the example,

the code use ExecutionTraceObserver instead of Execution Graph Observer，I think I only got the profile information after actually running the code here, whether to abandon the use of the Execution Graph Observer

[191220042]

The converter only supports these schemas,and the schema comes from pytorch_et.json, why does the pytorch profile appear like "1.0.2-chakra.0.0.4", "1.0.3-chakra.0.0.4", "1.1.0-chakra.0.0.4" Version