Input Parameters
================

``-m`` / ``--monitor-template``: defines the monitor template(s) to be processed. You can choose from the set of all implemented monitors (see :doc:`implemented-monitors`).

``-d`` / ``--dataset``: defines the ID-dataset that the NN was trained on. You can choose from the set of integrated datasets (see :doc:`benchmarks`) or implement your own (see :ref:`dataset-implementation`).

``-mu`` / ``--monitor-by-user``: If you choose to implement your own monitor, use this parameter instead of ``--monitor-template``. It refers to the file your monitor is implemented in (see :ref:`monitor-implementation`).

``-mu-name`` / ``--monitor-by-user-name``: If your monitor in your given file is not named ``Monitor``, you need to provide the class name here.

``-mc`` / ``--monitor-config``: (BETA) Configuration file to simplify the method of implementing a custom monitor and also for setting specified parameters (see :ref:`monitor-config`).

``-nn`` / ``--neural-network``: The NN given as either an ONNX or (preferrably because more stable) a Pytorch-model (torch.nn.Module saved with torch.save).

``-op`` / ``--optimize``: Boolean flag that determines whether Monitizer runs its optimization

``-oo`` / ``--optimization-objective``: The optimization configuration file. Monitizer provides a default ``optimization-configuration.ini``. Refer to :ref:`optimization-config` on the details of how the config should look like.

``-p` / ``--parameters``: You can give fixed parameters for the monitor template if you do not want to optimize. This must be given as a list in the format `` "{'PARAMETER_ONE' : VALUE, 'PARAMETER_TWO' : VALUE}"``, e.g. ``"{'temperature':99,'noise':0.9}"``.

``-e`` / ``--evaluate``: Boolean flag that determines whether Monitizer runs its evaluation.

``-ec`` / ``--evaluation-criteria``: Can be either ``short``,``test``,``full``, or ``auroc``. ``auroc`` is the only evalution that works on monitor templates without optimization. Any other evaluation must be performed on optimized monitors or on monitors with predefined values (see --parameters). ``short`` and ``test`` perform the evaluation on a subset of all OOD datasets. ``full`` uses all of them.

``-ed`` / ``--evaluation-dataset``: You can specify the OOD dataset that you want to evaluate on. Check out REFERENCE for possible dataset names you can use.

``-c`` / ``--confidence-intervals``: Boolean flag that determines whether Monitizer additionally outputs confidence intervals. 

.. _output-file:

``-o`` / ``--output``: You can define the location where Monitizer stores its output (see :doc:`output`).

``-l`` / ``--output-latex``: Whether the output results shall also immediately be printed as latex tabels (useful for paper writing :) ).

``-s`` / ``--seed``: Sets a seed to have reproducible results.

``--log``: You can specify where to store the log files. The logs are not stored if the location is not specified! CHECK