Chapter 14: Rapid Prototyping with PyTorch
In the preceding chapters, we have seen multiple facets of PyTorch as a Python library. We have seen its use for training vision and text models. We have learned about its extensive application programming interfaces (APIs) for loading and processing datasets. We have explored the model inference support provided by PyTorch. We have also noticed the interoperability of PyTorch across programming languages (such as C++) as well as with other deep learning libraries (such as TensorFlow).
To accommodate all of these features, PyTorch provides a rich and extensive family of APIs, which makes it one of the best deep learning libraries of all time. However, the vast expanse of those features also makes PyTorch ...
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