cupyx.GeneralizedUFunc

class cupyx.GeneralizedUFunc(func, signature, **kwargs)[source]

Creates a Generalized Universal Function by wrapping a user provided function with the signature.

signature determines if the function consumes or produces core dimensions. The remaining dimensions in given input arrays (*args) are considered loop dimensions and are required to broadcast naturally against each other.

Parameters
  • func (callable) – Function to call like func(*args, **kwargs) on input arrays (*args) that returns an array or tuple of arrays. If multiple arguments with non-matching dimensions are supplied, this function is expected to vectorize (broadcast) over axes of positional arguments in the style of NumPy universal functions.

  • signature (string) – Specifies what core dimensions are consumed and produced by func. According to the specification of numpy.gufunc signature.

  • supports_batched (bool, optional) – If the wrapped function supports to pass the complete input array with the loop and the core dimensions. Defaults to False. Dimensions will be iterated in the GUFunc processing code.

  • supports_out (bool, optional) – If the wrapped function supports out as one of its kwargs. Defaults to False.

  • signatures (list of tuple of str) – Contains strings in the form of ‘ii->i’ with i being the char of a dtype. Each element of the list is a tuple with the string and a alternative function to func to be executed when the inputs of the function can be casted as described by this function.

  • name (str, optional) – Name for the GUFunc object. If not specified, func’s name is used.

Methods

__call__(*args, **kwargs)[source]

Apply a generalized ufunc.

Parameters
  • args – Input arguments. Each of them can be a cupy.ndarray object or a scalar. The output arguments can be omitted or be specified by the out argument.

  • axes (List of tuples of int, optional) – A list of tuples with indices of axes a generalized ufunc should operate on. For instance, for a signature of '(i,j),(j,k)->(i,k)' appropriate for matrix multiplication, the base elements are two-dimensional matrices and these are taken to be stored in the two last axes of each argument. The corresponding axes keyword would be [(-2, -1), (-2, -1), (-2, -1)]. For simplicity, for generalized ufuncs that operate on 1-dimensional arrays (vectors), a single integer is accepted instead of a single-element tuple, and for generalized ufuncs for which all outputs are scalars, the output tuples can be omitted.

  • axis (int, optional) – A single axis over which a generalized ufunc should operate. This is a short-cut for ufuncs that operate over a single, shared core dimension, equivalent to passing in axes with entries of (axis,) for each single-core-dimension argument and () for all others. For instance, for a signature '(i),(i)->()', it is equivalent to passing in axes=[(axis,), (axis,), ()].

  • keepdims (bool, optional) – If this is set to True, axes which are reduced over will be left in the result as a dimension with size one, so that the result will broadcast correctly against the inputs. This option can only be used for generalized ufuncs that operate on inputs that all have the same number of core dimensions and with outputs that have no core dimensions , i.e., with signatures like '(i),(i)->()' or '(m,m)->()'. If used, the location of the dimensions in the output can be controlled with axes and axis.

  • casting (str, optional) – Provides a policy for what kind of casting is permitted. Defaults to 'same_kind'

  • dtype (dtype, optional) – Overrides the dtype of the calculation and output arrays. Similar to signature.

  • signature (str or tuple of dtype, optional) – Either a data-type, a tuple of data-types, or a special signature string indicating the input and output types of a ufunc. This argument allows you to provide a specific signature for the function to be used if registered in the signatures kwarg of the __init__ method. If the loop specified does not exist for the ufunc, then a TypeError is raised. Normally, a suitable loop is found automatically by comparing the input types with what is available and searching for a loop with data-types to which all inputs can be cast safely. This keyword argument lets you bypass that search and choose a particular loop.

  • order (str, optional) – Specifies the memory layout of the output array. Defaults to 'K'.``’C’`` means the output should be C-contiguous, 'F' means F-contiguous, 'A' means F-contiguous if the inputs are F-contiguous and not also not C-contiguous, C-contiguous otherwise, and 'K' means to match the element ordering of the inputs as closely as possible.

  • out (cupy.ndarray) – Output array. It outputs to new arrays default.

Returns

Output array or a tuple of output arrays.

__eq__(value, /)

Return self==value.

__ne__(value, /)

Return self!=value.

__lt__(value, /)

Return self<value.

__le__(value, /)

Return self<=value.

__gt__(value, /)

Return self>value.

__ge__(value, /)

Return self>=value.