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Numpy is one of the most popular Python data libraries, and TensorFlow offers integration and compatibility with its data structures. [66] Numpy NDarrays, the library's native datatype, are automatically converted to TensorFlow Tensors in TF operations; the same is also true vice versa. [66]
CPython is distributed with a large standard library written in a mixture of C and native Python, and is available for many platforms, including Windows (starting with Python 3.9, the Python installer deliberately fails to install on Windows 7 and 8; [141] [142] Windows XP was supported until Python 3.5) and most modern Unix-like systems ...
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.
CUDA is designed to work with programming languages such as C, C++, Fortran, Python and Julia. This accessibility makes it easier for specialists in parallel programming to use GPU resources, in contrast to prior APIs like Direct3D and OpenGL , which require advanced skills in graphics programming. [ 7 ]
py2exe is a Python extension which converts Python scripts (.py) into Microsoft Windows executables (.exe). These executables can run on a system without Python installed. [3] It is the most common tool for doing so.
Windows Subsystem for Linux (WSL) is a feature of Microsoft Windows that allows the use of a GNU/Linux environment from within Windows, foregoing the overhead of a virtual machine and being an alternative to dual booting.
To avoid installing the large SciPy package just to get an array object, this new package was separated and called NumPy. Support for Python 3 was added in 2011 with NumPy version 1.5.0. [15] In 2011, PyPy started development on an implementation of the NumPy API for PyPy. [16] As of 2023, it is not yet fully compatible with NumPy. [17]
RK3399 was the flagship SoC of Rockchip, Dual A72 and Quad A53 and Mali-T860MP4 GPU, providing high computing and multi-media performance, rich interfaces and peripherals. And software supports multiple APIs: OpenGL ES 3.2, Vulkan 1.0, OpenCL 1.1/1.2, OpenVX1.0, AI interfaces support TensorFlow Lite/AndroidNN API. [1]