examples.txt

.. _examples:

####################################################
 Examples
####################################################

Determined includes several example machine learning models that have
been ported to Determined's APIs. These examples can be found in the
``examples/`` subdirectory of the `Determined GitHub repo
<https://github.com/determined-ai/determined/tree/master/examples>`__;
download links to each example can also be found below.

Each example consists of a model definition, along with one or more experiment
configuration files. To run one of these examples, download the appropriate
``.tgz`` file, extract it, ``cd`` into the directory, and use ``det experiment
create`` to create a new experiment, passing in the appropriate configuration
file. For example, here is how to train the ``mnist_pytorch`` example with a
fixed set of hyperparameters:

.. code::

    tar xzvf mnist_pytorch.tgz
    cd mnist_pytorch
    det experiment create const.yaml .

For an introduction to using the Trial API, refer to the :ref:`PyTorch MNIST <pytorch-mnist-tutorial>` and
:ref:`tf.keras MNIST <tf-mnist-tutorial>` tutorials.

Computer Vision
===============

.. list-table::
  :header-rows: 1

  * - Framework
    - Dataset
    - Filename

  * - PyTorch
    - CIFAR-10
    - :download:`cifar10_pytorch.tgz </examples/cifar10_pytorch.tgz>`

  * - PyTorch
    - MNIST
    - :download:`mnist_pytorch.tgz </examples/mnist_pytorch.tgz>`

  * - PyTorch
    - MNIST
    - :download:`mnist_multi_output_pytorch.tgz </examples/mnist_multi_output_pytorch.tgz>`

  * - PyTorch
    - Penn-Fudan Dataset
    - :download:`fasterrcnn_coco_pytorch.tgz </examples/fasterrcnn_coco_pytorch.tgz>`

  * - TensorFlow (Estimator API)
    - MNIST
    - :download:`mnist_estimator.tgz </examples/mnist_estimator.tgz>`

  * - TensorFlow (tf.layers via Estimator API)
    - MNIST
    - :download:`mnist_tf_layers.tgz </examples/mnist_tf_layers.tgz>`

  * - TensorFlow (tf.keras)
    - Fashion MNIST
    - :download:`fashion_mnist_tf_keras.tgz </examples/fashion_mnist_tf_keras.tgz>`

  * - TensorFlow (tf.keras)
    - CIFAR-10
    - :download:`cifar10_tf_keras.tgz </examples/cifar10_tf_keras.tgz>`

  * - TensorFlow (tf.keras)
    - Iris Dataset
    - :download:`iris_tf_keras.tgz </examples/iris_tf_keras.tgz>`

  * - TensorFlow (tf.keras)
    - Oxford-IIIT Pet Dataset
    - :download:`unets_tf_keras.tgz </examples/unets_tf_keras.tgz>`

Natural Language Processing (NLP)
=================================

.. list-table::
  :header-rows: 1

  * - Framework
    - Dataset
    - Filename

  * - PyTorch
    - SQuAD
    - :download:`bert_squad_pytorch.tgz </examples/bert_squad_pytorch.tgz>`

  * - PyTorch
    - GLUE
    - :download:`bert_glue_pytorch.tgz </examples/bert_glue_pytorch.tgz>`

HP Search Benchmarking
======================

.. list-table::
  :header-rows: 1

  * - Framework
    - Dataset
    - Filename

  * - PyTorch
    - CIFAR-10
    - :download:`darts_cifar10_pytorch.tgz </examples/darts_cifar10_pytorch.tgz>`

  * - PyTorch
    - Penn Treebank Dataset
    - :download:`darts_penntreebank_pytorch.tgz </examples/darts_penntreebank_pytorch.tgz>`

Neural Architecture Search (NAS)
================================

.. list-table::
  :header-rows: 1

  * - Framework
    - Dataset
    - Filename

  * - PyTorch
    - DARTS
    - :download:`gaea_pytorch.tgz </examples/gaea_pytorch.tgz>`

Meta Learning
=============

.. list-table::
  :header-rows: 1

  * - Framework
    - Dataset
    - Filename

  * - PyTorch
    - Omniglot
    - :download:`protonet_omniglot_pytorch.tgz </examples/protonet_omniglot_pytorch.tgz>`

Generative Adversarial Networks (GANs)
======================================

.. list-table::
  :header-rows: 1

  * - Framework
    - Dataset
    - Filename

  * - PyTorch
    - MNIST
    - :download:`gan_mnist_pytorch.tgz </examples/gan_mnist_pytorch.tgz>`

Decision Trees
==============

.. list-table::
  :header-rows: 1

  * - Framework
    - Dataset
    - Filename

  * - TensorFlow (Estimator API)
    - Titanic
    - :download:`gbt_titanic_estimator.tgz </examples/gbt_titanic_estimator.tgz>`

Data Layer
==========

.. list-table::
  :header-rows: 1

  * - Framework
    - Dataset
    - Filename

  * - TensorFlow (Estimator API)
    - MNIST
    - :download:`data_layer_mnist_estimator.tgz </examples/data_layer_mnist_estimator.tgz>`

  * - TensorFlow (tf.keras)
    - MNIST
    - :download:`data_layer_mnist_tf_keras.tgz </examples/data_layer_mnist_tf_keras.tgz>`