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

.. py:module:: neural_compressor.benchmark

.. autoapi-nested-parse::

   Benchmark is used for evaluating the model performance.



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


Functions
~~~~~~~~~

.. autoapisummary::

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



.. 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:function:: fit(model, config=None, b_dataloader=None, b_func=None)

   Benchmark the model performance with the configure.

   :param model: The model to be benchmarked.
   :type model: object
   :param config: The configuration for benchmark containing accuracy goal,
                  tuning objective and preferred calibration & quantization
                  tuning space etc.
   :type config: BenchmarkConfig
   :param b_dataloader: The dataloader for frameworks.
   :param b_func: Customized benchmark function. If user passes the dataloader,
                  then b_func is not needed.

   Example::

       # Run benchmark according to config
       from neural_compressor.benchmark import fit

       conf = BenchmarkConfig(iteration=100, cores_per_instance=4, num_of_instance=7)
       fit(model='./int8.pb', config=conf, b_dataloader=eval_dataloader)