We performed a comparison between Caffe and PyTorch based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Google, TensorFlow and others in AI Development Platforms."Caffe has helped our company become up-to-date in the market and has helped us speed up the development process of our projects."
"I like that PyTorch actually follows the pythonic way, and I feel that it's quite easy. It's easy to find compared to others who require us to type a long paragraph of code."
"yTorch is gaining credibility in the research space, it's becoming easier to find examples of papers that use PyTorch. This is an advantage for someone who uses PyTorch primarily."
"The tool is very user-friendly."
"The framework of the solution is valuable."
"It's been pretty scalable in terms of using multiple GPUs."
"Its interface is the most valuable. The ability to have an interface to train machine learning models and construct them with the high-level interface, without excess busting and reconstructing the same technical elements, is very useful."
"The concept of Caffe is a little bit complex because it was developed and based in C++. They need to make it easier for a new developer, data scientist, or a new machine or deep learning engineer to understand it."
"I've had issues with stability when I use a lot of data and try out different combinations of modeling techniques."
"There is not enough documentation about some methods and parameters. It is sometimes difficult to find information."
"I would like a model to be available. I think Google recently released a new version of EfficientNet. It's a really good classifier, and a PyTorch implementation would be nice."
"PyTorch could make certain things more obvious. Even though it does make things like defining loss functions and calculating gradients in backward propagation clear, these concepts may confuse beginners. We find that it's kind of problematic. Despite having methods called on loss functions during backward passes, the oral documentation for beginners is quite complex."
"On the production side of things, having more frameworks would be helpful."
"The training of the models could be faster."
Earn 20 points
Caffe is ranked 15th in AI Development Platforms while PyTorch is ranked 11th in AI Development Platforms with 6 reviews. Caffe is rated 7.0, while PyTorch is rated 8.6. The top reviewer of Caffe writes "Speeds up the development process but needs to evolve more to stay relevant". On the other hand, the top reviewer of PyTorch writes "Offers good backward compatible and simple to use". Caffe is most compared with , whereas PyTorch is most compared with OpenVINO, MXNet, Microsoft Azure Machine Learning Studio, Google Cloud AI Platform and Google Vertex AI.
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