This is the release note of v5.0.0b3. See here for the complete list of solved issues and merged PRs.

Highlights

• cupyx.scipy namespace has been introduced to provide SciPy-compatible APIs for CuPy ndarrays. cupy.sparse module has been renamed to cupyx.scipy.sparse; cupy.sparse is kept for backward compatibility.

• New user-defined kernel class called cupy.RawKernel has been added. By using raw kernels, you can define kernels from raw CUDA source. See the documentation for details.

New Features

• Introduce SciPy namespace (#1079)
• Logarithmic gamma and related functions (#1232)
• Binomial distribution (#1356)
• Implement cupyx.scipy.linalg.solve_triangular (#1383)
• Implement RawKernel (#1398)
• Beta distribution (#1413)
• Dirichlet distribution (#1415)

Enhancements

• Use fmin and fmax for HIP environment (#1116)
• Improve reduce_dims for speed up (#1324)
• Remove overhead in creation/basic.py (#1342)
• Improve performance of host to device memory copy (#1367)
• Fix cupy.cov for degrees of freedom <= 0 (#1370, thanks @tsurumeso!)
• Add compilation methods in Fusion class (#1382)
• Make the method cupy.random.RandomState.interval private (#1430)
• Use get_cublas_handle to reduce creation of Device object (#1440)
• Remove overhead in generator and distribution (#1442)
• Remove stream option from RawKernel and add missing docs of arguments in ReductionKernel (#1444)
• Allow cupy.get_array_module to take fusion parameters (#1446)
• Use internal.clp2 in reduction (#1448)

Bug Fixes

• Fix issue of cuDNN convolution math_type setting (#1428)
• Fix Module and LinkState not freed (#1439)
• Fix fromDlpack memory management (#1445, thanks @t-vi!)
• Fix error in PooledMemory in Python 3.7 (#1457)

Documentation

• Fix documentation of the option arg of ElementwiseKernel (#1437)
• Convert cupy.sparse to cupyx.scipy.sparse in docstrings (#1450)

Installation

• Change required Cython version to 0.28 or later (#1407)

Tests

• Fix requirements of numpy in test_einsum.py (#1400)
• Refactor TestOrder (#1405)