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README.md

Graphcore

PopART MNIST Training Demo

This example trains a network on the MNIST dataset using PopART.

File structure

  • popart_mnist.py The main PopART program that uses a linear network.
  • popart_mnist_conv.py The main PopART program that uses a convolutional network.
  • get_data.sh Script to fetch the images and labels.
  • README.md This file.
  • requirements.txt Specifies the required modules.
  • test_popart_mnist.py Tests for popart_mnist.py.
  • test_popart_mnist_conv.py Tests for popart_mnist_conv.py.

How to use this demo

  1. Prepare the environment.

    Install the Poplar SDK following the instructions in the Getting Started guide for your IPU System. Make sure to source the enable.sh scripts for Poplar and PopART.

    The PopART Python API only supports Python 3. It is recommended to use a virtualenv.

    Install the required modules:

    pip3 install -r requirements.txt

  2. Download the data.

    ./get_data.sh

    This will create and populate a data directory.

  3. Run the program.

    python3 popart_mnist.py

    or

    python3 popart_mnist_conv.py

  4. (Optional) To run the tests

    python3 -m pytest

Options

The programs have a few command line options.

Note: popart_mnist_conv.py does not support the --replication-factor or --pipeline options.

-h Show usage information.

--batch-size Sets the batch size. This must be a multiple of the replication factor.

--batches-per-step Number on mini-batches to perform on the device before returning to the host.

--epochs Number of epoch to train for.

--num-ipus Number of IPUs to use.

--pipeline Pipeline the model over IPUs. Only valid for this model if the number of IPUs is double the replication factor.

--replication-factor Number of times to replicate the graph to perform data parallel training. This must be a factor of the number of IPUs. Defaults to 1.

--simulation Run with the IPU_MODEL device instead of hardware.

--log-graph-trace Turn on IR logging to display the graph's ops.

Examples:

 python popart_mnist.py --num-ipus 2 --pipeline

 python popart_mnist.py --num-ipus 4 --replication-factor 2 --pipeline