PyTorch

How do the new M1 chips perform with the new PyTorch update?Photo by Content Pixie on UnsplashThe release of M1 Macs in November 2020 marked a significant step up in the processing power of Apple machines . Unfortunately, these new features were not integrated into PyTorch until now.Today’s deep learning models owe a great deal of their exponential performance gains to ever increasing model sizes. Those larger models require more computations to train and run.Video version of this article 🙌🏼These models are simply too big…

Perform rapid loss-function prototypes to take full advantage of XGBoost’s flexibilityPhoto by Matt Artz on UnsplashMotivationRunning XGBoost with custom loss functions can greatly increase classification/regression performance in certain applications. Being able to quickly test many different loss functions is key in time-critical research environments. Thus, manual differentiation is not always feasible (and sometimes even prone to human errors, or numerical instability).Automatic differentiation allows us to…

It is a reasonable thing to expect n-dimensional tensor to have a possibility to be reshaped. Reshape means to change the spatial size of a container that holds underlying data. One can create any n-dimensional tensor that wraps a numerical array as long as the product of dimensions stays equal to the number of the array’s elements.  import torch # underlying data data = # has 8 elements # two ways to store identical data tens_A = torch.tensor(data).reshape(shape=(2,4)) # 2-dimensional tensor of…

                                Figure 1 GNN Demo Using PyTorck Lightning and PyTorch Geometric Using PyTorch Lightning with Graph Neural Networks In the world of deep learning, Python rules. But while the Python programming language on its own is swift to develop in a so-called “high-productivity” language, execution speed pales in comparison to compiled and lower-level languages like C++ or FORTRAN. One of the fundamental drivers of the neural network renaissance of the 2010s to today, aka the advent of deep learning,…

Natural language processing (NLP) is continuing to grow in popularity, and necessity, as artificial intelligence and deep learning programs grow and thrive in the coming years. Natural language processing with PyTorch is the best bet to implement these programs. In this guide, we will address some of the obvious questions that may arise when starting to dive into natural language processing, but we will also engage with deeper questions and give you the right steps to get started working on your own NLP programs. Can…