IDE Setup (PyCharm)¶
Model developers may develop and debug models with their preferred IDE. In this guide, we show how to configure PyCharm in order to develop and debug experiments submitted from Python, i.e. this pattern for the Trial API.
Prerequisites¶
This guide assumes that you have created a virtualenv or Conda environment in which you have installed the dependencies required for local development. For example, to create a Python 3.7 virtualenv:
python3.7 -m venv /path/to/env/
source /path/to/env/bin/activate
You will then want to install the determined Python package, as well
the TensorFlow or PyTorch library versions that your code will run
against when submitting to the cluster. For example, if you are using
Determined’s default task container image
for a PyTorch model, you would install the following dependencies in
your virtualenv:
pip install determined==<Determined version>
pip install torch==<Determined's default image PyTorch version, e.g., 1.4.0>
pip install torchvision==<Determined's default image torchvision version, e.g., 0.5.0>
If you are using a custom Docker image for running task containers, you must also install the same dependencies in your local development environment.