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PyTorch pros and cons

Vendor: PyTorch
4.3 out of 5

Pros & Cons summary

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Prominent pros & cons

PROS

PyTorch follows a pythonic way, making it user-friendly and easy to use.
The framework is valuable and suitable for AIML project development.
PyTorch is gaining credibility in research, with increased availability of example papers.
It has good scalability when using multiple GPUs.
PyTorch's scalability and developer-friendly nature support continuous new project creation.

CONS

Documentation for some methods and parameters is lacking, making it hard to find necessary information.
Faster training of models and support for more frameworks in production are needed.
Beginners may find concepts in backward propagation complex despite clarity in defining loss functions and gradients.
Stability issues arise when handling large datasets and testing various modeling techniques.
Version incompatibility and lack of updates beyond version 12.3 are problematic.
 

PyTorch Pros review quotes

reviewer2384079 - PeerSpot reviewer
Mar 27, 2024
It's been pretty scalable in terms of using multiple GPUs.
Murali Mallikarjuna Perumalla - PeerSpot reviewer
May 29, 2024
The product's initial setup phase is easy.
reviewer2514822 - PeerSpot reviewer
Jul 15, 2024
For me, the product's initial setup phase is easy...For beginners, it is fairly easy to learn.
Learn what your peers think about PyTorch. Get advice and tips from experienced pros sharing their opinions. Updated: March 2025.
842,296 professionals have used our research since 2012.
reviewer1508772 - PeerSpot reviewer
Apr 16, 2021
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.
Arucy Lionel - PeerSpot reviewer
Nov 27, 2023
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.
Jithin James - PeerSpot reviewer
Mar 28, 2024
The tool is very user-friendly.
Rohan Sharma - PeerSpot reviewer
Feb 12, 2025
PyTorch is developer-friendly, allowing developers to continuously create new projects.
Karthikeyan Katkam - PeerSpot reviewer
Nov 18, 2024
I like PyTorch's scalability.
TS
Nov 29, 2024
PyTorch allows me to build my projects from scratch.
reviewer1455297 - PeerSpot reviewer
Nov 17, 2020
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.
 

PyTorch Cons review quotes

reviewer2384079 - PeerSpot reviewer
Mar 27, 2024
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.
Murali Mallikarjuna Perumalla - PeerSpot reviewer
May 29, 2024
The product has certain shortcomings in the automation of machine learning.
reviewer2514822 - PeerSpot reviewer
Jul 15, 2024
The product has breakdowns when we change the versions a lot.
Learn what your peers think about PyTorch. Get advice and tips from experienced pros sharing their opinions. Updated: March 2025.
842,296 professionals have used our research since 2012.
reviewer1508772 - PeerSpot reviewer
Apr 16, 2021
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.
Arucy Lionel - PeerSpot reviewer
Nov 27, 2023
On the production side of things, having more frameworks would be helpful.
Jithin James - PeerSpot reviewer
Mar 28, 2024
I've had issues with stability when I use a lot of data and try out different combinations of modeling techniques.
Rohan Sharma - PeerSpot reviewer
Feb 12, 2025
PyTorch needs improvement in working on ARM-based chips. They have unified memory for GPU and RAM, however, current GPUs used for processing are slow.
Karthikeyan Katkam - PeerSpot reviewer
Nov 18, 2024
The analyzing and latency of compiling could be improved to provide enhanced results.
TS
Nov 29, 2024
I do not have any complaints.
reviewer1455297 - PeerSpot reviewer
Nov 17, 2020
There is not enough documentation about some methods and parameters. It is sometimes difficult to find information.