Write code that exploits a GPU when available and desirable, but that runs fine on your CPUs when not
The wonderful CuPy library allows you to easily run NumPy-compatible code on a NVIDIA GPU. However, sometimes
By defining three simple utility functions, you can make your code _GPU-optional. (_Find the utility functions’ definitions in this small GitHub project.)
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In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
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