:py:mod:`neural_compressor.experimental.benchmark`
==================================================

.. py:module:: neural_compressor.experimental.benchmark

.. autoapi-nested-parse::

   Benchmarking: measure the model performance with the objective settings.



Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   neural_compressor.experimental.benchmark.Benchmark



Functions
~~~~~~~~~

.. autoapisummary::

   neural_compressor.experimental.benchmark.set_env_var
   neural_compressor.experimental.benchmark.set_all_env_var
   neural_compressor.experimental.benchmark.get_architecture
   neural_compressor.experimental.benchmark.get_threads_per_core
   neural_compressor.experimental.benchmark.get_threads
   neural_compressor.experimental.benchmark.get_physical_ids
   neural_compressor.experimental.benchmark.get_core_ids
   neural_compressor.experimental.benchmark.get_bounded_threads



.. py:function:: set_env_var(env_var, value, overwrite_existing=False)

   Set the specified environment variable.

   Only set new env in two cases:
   1. env not exists
   2. env already exists but overwrite_existing params set True


.. py:function:: set_all_env_var(conf, overwrite_existing=False)

   Set all the environment variables with the configuration dict.

   Neural Compressor only uses physical cores


.. py:function:: get_architecture()

   Get the architecture name of the system.


.. py:function:: get_threads_per_core()

   Get the threads per core.


.. py:function:: get_threads()

   Get the list of threads.


.. py:function:: get_physical_ids()

   Get the list of sockets.


.. py:function:: get_core_ids()

   Get the ids list of the cores.


.. py:function:: get_bounded_threads(core_ids, threads, sockets)

   Return the threads id list that we will bind instances to.


.. py:class:: Benchmark(conf_fname_or_obj=None)




   Benchmark class is used to evaluate the model performance with the objective settings.

   Users can use the data that they configured in YAML
   NOTICE: neural_compressor Benchmark will use the original command to run sub-process, which
   depends on the user's code and has the possibility to run unnecessary code