Profiling your PyTorch Module
------------
**Author:** `Suraj Subramanian `
PyTorch includes a profiler API that is useful to identify the time and
memory costs of various PyTorch operations in your code. Profiler can be
easily integrated in your code, and the results can be printed as a table
or returned in a JSON trace file.
.. note::
Profiler supports multithreaded models. Profiler runs in the
same thread as the operation but it will also profile child operators
that might run in another thread. Concurrently-running profilers will be
scoped to their own thread to prevent mixing of results.
.. note::
PyTorch 1.8 introduces the new API that will replace the older profiler API
in the future releases. Check the new API at `this page <https://pytorch.org/docs/master/profiler.html>`__.
Head on over to `this
recipe <https://pytorch.org/tutorials/recipes/recipes/profiler_recipe.html>`__
for a quicker walkthrough of Profiler API usage.
Tasks: Profiling, Deep Learning Fundamentals
Task Categories: Deep Learning Fundamentals
Published: 10/07/23