Prerequisite | ETRecord - ExecuTorch Record =========================================== Overview -------- ``ETRecord`` is intended to be the debug artifact that is generated by users ahead of time (when they export their model to run on ExecuTorch). To draw a rough equivalent to conventional software development, ``ETRecord`` can be considered as the binary built with debug symbols that is used for debugging in GNU Debugger (gdb). It is expected that the user will supply this to the ExecuTorch SDK tooling in order for them to debug and visualize their model. ``ETRecord`` contains numerous components such as: * Edge dialect graph with debug handles * Delegate debug handle maps The ``ETRecord`` object itself is intended to be opaque to users and they should not access any components inside it directly. It should be provided to the `Inspector API `__ to link back performance and debug data sourced from the runtime back to the Python source code. Generating an ``ETRecord`` -------------------------- The user should use the following API to generate an ``ETRecord`` file. They will be expected to provide the Edge Dialect program (returned by the call to ``to_edge()``), the ExecuTorch program (returned by the call to ``to_executorch()``), and optional models that they are interested in working with via our tooling. .. warning:: Users should do a deepcopy of the output of ``to_edge()`` and pass in the deepcopy to the ``generate_etrecord`` API. This is needed because the subsequent call, ``to_executorch()``, does an in-place mutation and will lose debug data in the process. .. currentmodule:: executorch.sdk.etrecord._etrecord .. autofunction:: generate_etrecord Using an ``ETRecord`` --------------------- Pass the ``ETRecord`` as an optional argument into the `Inspector API `__ to access this data and do post-run analysis.