CuPy-specific functions

CuPy-specific functions are placed under cupyx namespace.

cupyx.rsqrt	Returns the reciprocal square root.
cupyx.scatter_add(a, slices, value)	Adds given values to specified elements of an array.
cupyx.scatter_max(a, slices, value)	Stores a maximum value of elements specified by indices to an array.
cupyx.scatter_min(a, slices, value)	Stores a minimum value of elements specified by indices to an array.
cupyx.empty_pinned(shape[, dtype, order])	Returns a new, uninitialized NumPy array with the given shape and dtype.
cupyx.empty_like_pinned(a[, dtype, order, …])	Returns a new, uninitialized NumPy array with the same shape and dtype as those of the given array.
cupyx.zeros_pinned(shape[, dtype, order])	Returns a new, zero-initialized NumPy array with the given shape and dtype.
cupyx.zeros_like_pinned(a[, dtype, order, …])	Returns a new, zero-initialized NumPy array with the same shape and dtype as those of the given array.

DLPack utilities

This is a helper function for creating a cupy.ndarray from a DLPack tensor. For further detail see DLPack.

cupy.fromDlpack(dltensor)

Zero-copy conversion from a DLPack tensor to a ndarray.

Automatic Kernel Parameters Optimizations (cupyx.optimizing)

cupyx.optimizing.optimize(*[, key, path, …])

Context manager that optimizes kernel launch parameters.

cupyx.scipy.stats.entropy cupyx.rsqrt