HowToLaunchFromPython.rst

**How to Launch an experiment from Python**
===========================================

Overview
--------
Since ``nni v2.0``, we provide a new way to launch experiments. Before that, you need to configure the experiment in the yaml configuration file and then use the experiment ``nnictl`` command to launch the experiment. Now, you can also configure and run experiments directly in python file. If you are familiar with python programming, this will undoubtedly bring you more convenience.

How to Use
----------
After successfully installing ``nni``, you can start the experiment with a python script in the following 3 steps.

..

    Step 1 - Initialize a tuner you want to use


.. code-block:: python

    from nni.algorithms.hpo.hyperopt_tuner import HyperoptTuner
    tuner = HyperoptTuner('tpe')

Very simple, you have successfully initialized a ``HyperoptTuner`` instance called ``tuner``.

See all real `builtin tuners <../builtin_tuner.rst>`__ supported in NNI.

..

    Step 2 - Initialize an experiment instance and configure it

.. code-block:: python

    experiment = Experiment(tuner=tuner, training_service='local')

Now, you have a ``Experiment`` instance with ``tuner`` you have initialized in the previous step, and this experiment will launch trials on your local machine due to ``training_service='local'``.

See all `training services <../training_services.rst>`__ supported in NNI.

.. code-block:: python

    experiment.config.experiment_name = 'test'
    experiment.config.trial_concurrency = 2
    experiment.config.max_trial_number = 5
    experiment.config.search_space = search_space
    experiment.config.trial_command = 'python3 mnist.py'
    experiment.config.trial_code_directory = Path(__file__).parent
    experiment.config.training_service.use_active_gpu = True

Use the form like ``experiment.config.foo = 'bar'`` to configure your experiment.

See `parameter configuration <../reference/experiment_config.rst>`__ required by different training services.

..

    Step 3 - Just run

.. code-block:: python

    experiment.run(port=8081)

Now, you have successfully launched an NNI experiment. And you can type ``localhost:8081`` in your browser to observe your experiment in real time.

Example
-------
Below is an example for this new launching approach. You can also find this code in :githublink:`mnist-tfv2/launch.py <examples/trials/mnist-tfv2/launch.py>` .

.. code-block:: python

    from pathlib import Path
    from nni.experiment import Experiment
    from nni.algorithms.hpo.hyperopt_tuner import HyperoptTuner

    tuner = HyperoptTuner('tpe')

    search_space = {
        "dropout_rate": { "_type": "uniform", "_value": [0.5, 0.9] },
        "conv_size": { "_type": "choice", "_value": [2, 3, 5, 7] },
        "hidden_size": { "_type": "choice", "_value": [124, 512, 1024] },
        "batch_size": { "_type": "choice", "_value": [16, 32] },
        "learning_rate": { "_type": "choice", "_value": [0.0001, 0.001, 0.01, 0.1] }
    }

    experiment = Experiment(tuner, 'local')
    experiment.config.experiment_name = 'test'
    experiment.config.trial_concurrency = 2
    experiment.config.max_trial_number = 5
    experiment.config.search_space = search_space
    experiment.config.trial_command = 'python3 mnist.py'
    experiment.config.trial_code_directory = Path(__file__).parent
    experiment.config.training_service.use_active_gpu = True

    experiment.run(8081)

API
---

..  autoclass:: nni.experiment.Experiment
    :members: