The intended audience for this article is anyone interested in PyTorch, Facebook's deep learning framework. The questions and answers are sourced from StackOverflow - a famous Q&A site for software engineering.
We quickly go over 5 helpful answers on stack overflow about PyTorch (Facebook's deep learning framework) and why they're important answers.
- How do you get the model summary in PyTorch?
- How do you initialize weights in PyTorch?
- What are the gradient arguments?
- How does the
- How to check if PyTorch is using the GPU?
Helpful PyTorch Q&A on Stack Overflow
Question: How do you get the model summary in PyTorch?
The first question we curate here is important because it raises a simple yet not quite obvious feature of PyTorch. The resulting answer shows the simplicity of PyTorch and how easy it is to get detailed information on a model.
Question: How do you initialize weights in PyTorch?
The method of initializing weights is different in every single deep learning framework. Here this is a common question on fine tuning a model (or retraining another model) that is answered below:
Question: What are the gradient arguments?
This is actually a really great question and answer that get into the nitty gritty of the programming around PyTorch and the computational execution framework. Sometimes that's abstracted around the simplicity of the framework. I recommend clicking on the link and checking out this full answer with more detailed examples that couldn't fit into a screenshot.
Question: How does the
view() method work?
Through a lot of examples on the PyTorch website there are many calls to this
view() function. It tripped me upped the first time as a long time numpy user. Only to find out that
view() is pretty much the equivalent of
Question: How to check if PyTorch is using the GPU?
We've all been in the situation where we try running a model and it should be really fast on the expensive GPU you just bought, but it's actually running really slow. This answer solves that issue by re-assuring that PyTorch is taking advantage of the GPU.
Milton is the product of a AI company named Apteo, which is made up of curious data scientists, engineers, and financial analysts based in the Flatiron neighborhood in New York City. We have a passion for technology and investing, and we strongly believe that investing is one of the most reliable and effective ways to build long-term wealth. We build AI tools to help informed investors make better decisions.
Apteo, Inc. is not an investment advisor and makes no representation or recommendation regarding investment in any fund or investment vehicle.
Subscribe to Milton's Blog
Get the latest posts delivered right to your inbox