Numpy operators: lcm, tril, identity and take (#16264).tvm numpy operator deg2rad & rad2deg (#16015).add numpy op hanning, hamming, blackman (#15815).add epsilon to sum(pvalue) upperbound (#16211).Numpy behavior normal distribution (#16109).add exception check for numpy reshape (#16180).numpy operator ravel, derive from reshape (#16016).Add fluent methods mean, std, var for ndarray (#16077).NumPy-compatible Mean, Std and Var (#16014).Support range as advanced index for ndarrays (#16047).NumPy-compatible infrastructure on Gluon (#16024).numpy-compatible cumsum upstream (#15924).Refines NDArray indexing and adds numpy ndarray indexing (#15942).np elemwise unary ops upstream (#15831).Numpy behavior random.uniform() (#15858).Numpy-compatible stack upstream (#15842).Numpy-compatible concatenate upstream (#15894).numpy-compatible split upstream (#15841).Numpy Tensordot and Dot Operator (#15820).Support NDArray indexing with None and Ellipsis (#13143).fix boolean_mask for 0-size output (#15731).Infra to use tvm write op kernels (#15550).
The efforts towards this goal would also help a secondary goal, which is to enable the existing NumPy ecosystem to utilize GPUs and accelerators to speed up large scale computation. The primary goal of the projects below is to provide the equivalent usability and expressiveness of NumPy in MXNet to facilitate Deep Learning model development, which not only helps existing deep learning practitioners but also provides people in the existing NumPy community with a shortcut for getting started in Deep Learning. In #14253, the MXNet community reached consensus on moving towards a NumPy-compatible programing experience and committed to a major endeavor on providing NumPy compatible operators. The popularity of NumPy comes from its flexibility and generality. With this library as the cornerstone, there are now the largest ecosystem and community for scientific computing. NumPy has long been established as the standard math library in Python, the most prevalent language for the deep learning community. New features NumPy compatible interface and using TVM to generate operators Therefore, MXNet 1.6 release is going to be the last MXNet release to support Python 2. MXNet community voted to no longer support Python 2 in future releases of MXNet.
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