Deep learning is transforming the way we approach complex problems in various fields, from image recognition to natural language processing. Among the tools available to researchers and developers, ...

Dr. James McCaffrey of Microsoft Research provides a full code sample and screenshots to explain how to create and use PyTorch Dataset and DataLoader objects, used to serve up training or test data in ...

Google aims to remove a significant obstacle that has limited the broader adoption of its chips by outside developers.

Machine learning is an increasingly important tool for developers, providing a way to build applications that can deliver a wide range of prediction-based tasks. In the past you might have had to ...

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Known for its flexibility, ease of use, and GPU acceleration, PyTorch is widely adopted in both ...

Facebook wants to make sure the open-source PyTorch machine-learning framework supports the needs of developers who want to use its AI models in production systems, not just research projects, it ...

PyTorch 1.0 shines for rapid prototyping with dynamic neural networks, auto-differentiation, deep Python integration, and strong support for GPUs Deep learning is an important part of the business of ...

During last year’s F8 developer conference, Facebook announced the 1.0 launch of PyTorch, the company’s open-source deep learning platform. At this year’s F8, the company launched version 1.1. The ...

In order to train a PyTorch neural network you must write code to read training data into memory, convert the data to PyTorch tensors, and serve the data up in batches. This task is not trivial and is ...