Along with the PyTorch-Ignite 0.4.5 release, we are excited to announce the new release of the web application for generating PyTorch-Ignite's training pipelines. This blog post is an overview of the key features and updates of the Code Generator v0.2.0 project release.
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Few things hinder productivity more than interruption. A notification, random realization, or unrelated error can derail one's train of thought when deep in a complex analysis – a frustrating experience.
In the software development context, forgetting to import a statement in an
interactive Jupyter session is such an experience. This can be especially
frustrating when using typical abbreviations, like
plt, where the
meaning is obvious to the human reader, but not to the computer. The
time-to-first-plot, and ability to quickly cleanup one's notebook afterward
are critical to an enjoyable and efficient workflow.
Writing agnostic distributed code that supports different platforms, hardware configurations (GPUs, TPUs) and communication frameworks is tedious. In this blog, we will discuss how PyTorch-Ignite solves this problem with minimal code change.