PyTorch - Deep Learning AMI
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Activating PyTorch

When a stable Conda package of a framework is released, it's tested and pre-installed on the DLAMI. If you want to run the latest, untested nightly build, you can Install PyTorch's Nightly Build (experimental) manually.

To activate the currently installed framework, follow these instructions on your Deep Learning AMI with Conda.

For PyTorch on Python 3 with CUDA and MKL-DNN, run this command:

$ source activate pytorch_p310

Start the iPython terminal.

(pytorch_p310)$ ipython

Run a quick PyTorch program.

import torch x = torch.rand(5, 3) print(x) print(x.size()) y = torch.rand(5, 3) print(torch.add(x, y))

You should see the initial random array printed, then its size, and then the addition of another random array.

Install PyTorch's Nightly Build (experimental)

How to install PyTorch from a nightly build

You can install the latest PyTorch build into either or both of the PyTorch Conda environments on your Deep Learning AMI with Conda.

    • (Option for Python 3) - Activate the Python 3 PyTorch environment:

      $ source activate pytorch_p310
  1. The remaining steps assume you are using the pytorch_p310 environment. Remove the currently installed PyTorch:

    (pytorch_p310)$ pip uninstall torch
    • (Option for GPU instances) - Install the latest nightly build of PyTorch with CUDA.0:

      (pytorch_p310)$ pip install torch_nightly -f
    • (Option for CPU instances) - Install the latest nightly build of PyTorch for instances with no GPUs:

      (pytorch_p310)$ pip install torch_nightly -f
  2. To verify you have successfully installed latest nightly build, start the IPython terminal and check the version of PyTorch.

    (pytorch_p310)$ ipython
    import torch print (torch.__version__)

    The output should print something similar to 1.0.0.dev20180922

  3. To verify that the PyTorch nightly build works well with the MNIST example, you can run a test script from PyTorch's examples repository:

    (pytorch_p310)$ cd ~ (pytorch_p310)$ git clone pytorch_examples (pytorch_p310)$ cd pytorch_examples/mnist (pytorch_p310)$ python || exit 1

More Tutorials

For further tutorials and examples refer to the framework's official docs, PyTorch documentation, and the PyTorch website.