mnist.md

MNIST on Graphcore

Go to directory with mnist example

cd ~/graphcore/examples/tutorials/simple_applications/pytorch/mnist

Activate PopTorch Environment and install requirements

source ~/venvs/graphcore/poptorch33_env/bin/activate
python -m pip install -r requirements.txt

Submit Job

/opt/slurm/bin/srun --ipus=1 python mnist_poptorch.py

Sample Output

  srun: job 10671 queued and waiting for resources
  srun: job 10671 has been allocated resources
  TrainingModelWithLoss(
  (model): Network(
      (layer1): Block(
      (conv): Conv2d(1, 32, kernel_size=(3, 3), stride=(1, 1))
      (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
      (relu): ReLU()
      )
      (layer2): Block(
      (conv): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1))
      (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
      (relu): ReLU()
      )
      (layer3): Linear(in_features=1600, out_features=128, bias=True)
      (layer3_act): ReLU()
      (layer3_dropout): Dropout(p=0.5, inplace=False)
      (layer4): Linear(in_features=128, out_features=10, bias=True)
      (softmax): Softmax(dim=1)
  )
  (loss): CrossEntropyLoss()
  )
  Epochs:   0%|          | 0/10 [00:00<?,[23:27:06.753] [poptorch:cpp] [warning] [DISPATCHER] Type coerced from Long to Int for tensor id 10
  Graph compilation: 100%|██████████| 100/100 [00:00<00:00]
  Epochs: 100%|██████████| 10/10 [01:17<00:00,  7.71s/it]
  Graph compilation: 100%|██████████| 100/100 [00:00<00:00]                          
  Accuracy on test set: 96.85%██████| 100/100 [00:00<00:00]