/ machine learning

Useful Questions and Answers for PyTorch (Facebook's Deep Learning Framework)

Introduction

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.

  1. How do you get the model summary in PyTorch?
  2. How do you initialize weights in PyTorch?
  3. What are the gradient arguments?
  4. How does the view() method work?
  5. 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.

Answer:

link: https://stackoverflow.com/a/42616812/3896984


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:

link: https://stackoverflow.com/a/49433937/3896984


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.

link: https://stackoverflow.com/a/47026836/3896984


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 np.reshape().

link: https://stackoverflow.com/a/42482819/3896984


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.

link: https://stackoverflow.com/a/48152675/3896984

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Useful Questions and Answers for PyTorch (Facebook's Deep Learning Framework)
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