The post will walk you through the difference between the two most popular Deep Learning Frameworks i.e., PyTorch and TensorFlow.
The Slide show will also make the entire discussion more interesting. So Let’s get started.
PyTorch
- Pytorch is an open-source library based on Torch library developed by the Facebook AI Research Lab (FAIR)
- It was released in 2016
- Pytorch is for implementation in Computer vision and NLP tasks.
- Visualization is done with the help of libraries like Matplotlib, seaborn.
- Pytorch does not have a feature for deployment so far but will release Torchserve, a PyTorch model serving library.
- PyTorch creates dynamic graphs. the graphs can be manipulated during runtime.
- PyTorch community support is less compared to TensorFlow.
- In terms of Usage, PyTorch is preferred for research work and deep learning research.
- Simplicity, PyTorch is simple to understand, is more Pythonic and intuitive, it is easy to work with.
TensorFlow
- TensorFlow is also a free and open-source library developed by Google Brain Team
- TensorFlow was released in 2015
- TensorFlow is used to perform Machine Learning tasks like Deep Learning, Neural Networks, and Natural Language Processing (NLP).
- Visualization in TensorFlow is done with the help of Tensorboard, in web browsers.
- TensorFlow offers great flexibility to deploy models.
- TensorFlow creates static graphs. Graphs can be modified after compilation.
- Community support is wider as compared to Pytorch.
- In terms of Usage, TensorFlow is widely used in Production.
- Complexity, TensorFlow is much more complex to understand as compared to Pytorch.
TensorFlow is based on Theano Library, a math library. TensorFlow is widely been used for deployment purposes as it was designed as a production-ready library.
Which one to Choose? PyTorch or TensorFlow?
The concluding thoughts are both TensorFlow and PyTorch are great Machine Learning libraries. Updated regularly, and better functionalities are been added. These Deep Learning Frameworks have made working with Neural Networks quite easy. Beginners as well as researchers use it. Hence, experience with both PyTorch and TensorFlow can help one to decide which one is better.
TensorFlow offers more flexibility and also is a bit complex to understand for beginners while PyTorch is more simple and easier to start with. Work with both libraries to get a better idea about which one is better.
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