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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

reviewer1455297 - PeerSpot reviewer
Freelance AI Engineer at a tech services company with self employed
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.
reviewer1508772 - PeerSpot reviewer
Associate Data Analyst at a financial services firm with 10,001+ employees
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.
Swayan Jeet Mishra - PeerSpot reviewer
Lead Machine Learning Engineer at Schlumberger
Oct 31, 2022
The framework of the solution is valuable.
Learn what your peers think about PyTorch. Get advice and tips from experienced pros sharing their opinions. Updated: January 2026.
881,082 professionals have used our research since 2012.
Arucy Lionel - PeerSpot reviewer
Co-Founder at Afriziki
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.
reviewer2384079 - PeerSpot reviewer
Data Scientist. at a computer software company with 501-1,000 employees
Mar 27, 2024
It's been pretty scalable in terms of using multiple GPUs.
Jithin James - PeerSpot reviewer
Financial Analyst 4 (Supply Chain & Financial Analytics) at Juniper Networks
Mar 28, 2024
The tool is very user-friendly.
Praveen Kumar Tiwari - PeerSpot reviewer
Team Lead at Tech Mahindra Limited
May 28, 2024
It’s reliable, secure and user-friendly. It allows you to develop any AIML project efficiently. PySearch is the best option for developing any project in the AIML domain. The product is easy to install.
Murali Mallikarjuna Perumalla - PeerSpot reviewer
Data Scientist at a tech services company with 201-500 employees
May 29, 2024
The product's initial setup phase is easy.
reviewer2514822 - PeerSpot reviewer
Associate Machine Learning Engineer at a tech services company with 501-1,000 employees
Jul 15, 2024
For me, the product's initial setup phase is easy...For beginners, it is fairly easy to learn.
reviewer2538639 - PeerSpot reviewer
Software Engineer Intern at a tech services company with 11-50 employees
Aug 27, 2024
We use PyTorch libraries, which are working well. It's very easy.
 

PyTorch Cons review quotes

reviewer1455297 - PeerSpot reviewer
Freelance AI Engineer at a tech services company with self employed
Nov 17, 2020
There is not enough documentation about some methods and parameters. It is sometimes difficult to find information.
reviewer1508772 - PeerSpot reviewer
Associate Data Analyst at a financial services firm with 10,001+ employees
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.
Swayan Jeet Mishra - PeerSpot reviewer
Lead Machine Learning Engineer at Schlumberger
Oct 31, 2022
The training of the models could be faster.
Learn what your peers think about PyTorch. Get advice and tips from experienced pros sharing their opinions. Updated: January 2026.
881,082 professionals have used our research since 2012.
Arucy Lionel - PeerSpot reviewer
Co-Founder at Afriziki
Nov 27, 2023
On the production side of things, having more frameworks would be helpful.
reviewer2384079 - PeerSpot reviewer
Data Scientist. at a computer software company with 501-1,000 employees
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.
Jithin James - PeerSpot reviewer
Financial Analyst 4 (Supply Chain & Financial Analytics) at Juniper Networks
Mar 28, 2024
I've had issues with stability when I use a lot of data and try out different combinations of modeling techniques.
Praveen Kumar Tiwari - PeerSpot reviewer
Team Lead at Tech Mahindra Limited
May 28, 2024
I would like to see better learning documents.
Murali Mallikarjuna Perumalla - PeerSpot reviewer
Data Scientist at a tech services company with 201-500 employees
May 29, 2024
The product has certain shortcomings in the automation of machine learning.
reviewer2514822 - PeerSpot reviewer
Associate Machine Learning Engineer at a tech services company with 501-1,000 employees
Jul 15, 2024
The product has breakdowns when we change the versions a lot.
reviewer2538639 - PeerSpot reviewer
Software Engineer Intern at a tech services company with 11-50 employees
Aug 27, 2024
We faced an issue with PyTorch due to version incompatibility. PyTorch has no latest version after v12.3.