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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; 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:

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

For an introduction to using the Trial API, refer to the PyTorch MNIST and tf.keras MNIST tutorials.

Computer Vision

Framework

Dataset

Filename

PyTorch

CIFAR-10

cifar10_pytorch.tgz

PyTorch

MNIST

mnist_pytorch.tgz

PyTorch

Imagenet

imagenet_pytorch.tgz

PyTorch

Penn-Fudan Dataset

fasterrcnn_coco_pytorch.tgz

PyTorch

COCO

mmdetection_pytorch.tgz

PyTorch

COCO

detr_coco_pytorch.tgz

PyTorch

COCO

deformabledetr_coco_pytorch.tgz

PyTorch

COCO

efficientdet_pytorch.tgz

PyTorch (Lightning Adapter)

MNIST

mnist_pl.tgz

TensorFlow (Estimator API)

MNIST

mnist_estimator.tgz

TensorFlow (tf.layers via Estimator API)

MNIST

mnist_tf_layers.tgz

TensorFlow (tf.keras)

Fashion MNIST

fashion_mnist_tf_keras.tgz

TensorFlow (tf.keras)

CIFAR-10

cifar10_tf_keras.tgz

TensorFlow (tf.keras)

Iris Dataset

iris_tf_keras.tgz

TensorFlow (tf.keras)

Oxford-IIIT Pet Dataset

unets_tf_keras.tgz

Natural Language Processing (NLP)

Framework

Dataset

Filename

PyTorch

SQuAD

bert_squad_pytorch.tgz

PyTorch

SQuAD 2.0

albert_squad_pytorch.tgz

PyTorch

GLUE

bert_glue_pytorch.tgz

PyTorch

WikiText-2

word_language_model.tgz

PyTorch (Model Hub Transformers)

WikiText-2

language-modeling.tgz

PyTorch (Model Hub Transformers)

SWAG

multiple-choice.tgz

PyTorch (Model Hub Transformers)

SQuAD v1 and v2

question-answering.tgz

PyTorch (Model Hub Transformers)

GLUE and XNLI

text-classification.tgz

PyTorch (Model Hub Transformers)

CoNLL-2003

token-classification.tgz

HP Search Benchmarking

Framework

Dataset

Filename

PyTorch

CIFAR-10

darts_cifar10_pytorch.tgz

PyTorch

Penn Treebank Dataset

darts_penntreebank_pytorch.tgz

Neural Architecture Search (NAS)

Framework

Dataset

Filename

PyTorch

DARTS

gaea_pytorch.tgz

Meta Learning

Framework

Dataset

Filename

PyTorch

Omniglot

protonet_omniglot_pytorch.tgz

Generative Adversarial Networks (GANs)

Framework

Dataset

Filename

PyTorch

MNIST

gan_mnist_pytorch.tgz

TensorFlow (tf.keras)

MNIST

dcgan_tf_keras.tgz

Decision Trees

Framework

Dataset

Filename

TensorFlow (Estimator API)

Titanic

gbt_titanic_estimator.tgz

Features: Data Layer

Framework

Dataset

Filename

TensorFlow (Estimator API)

MNIST

data_layer_mnist_estimator.tgz

TensorFlow (tf.keras)

MNIST

data_layer_mnist_tf_keras.tgz

Features: Custom Reducers

Framework

Dataset

Filename

PyTorch

MNIST

custom_reducers_mnist_pytorch.tgz

Features: HP Search Constraints

Framework

Dataset

Filename

PyTorch

MNIST

hp_constraints_mnist_pytorch.tgz