cupy.einsum#

cupy.einsum(subscripts, *operands, dtype=None, optimize=False)[source]#

Evaluates the Einstein summation convention on the operands. Using the Einstein summation convention, many common multi-dimensional array operations can be represented in a simple fashion. This function provides a way to compute such summations.

Note

  • Memory contiguity of the returned array is not always compatible with that of numpy.einsum().

  • out, order, and casting options are not supported.

  • If CUPY_ACCELERATORS includes cutensornet, the einsum calculation will be performed by the cuTensorNet backend if possible.

    • The support of the optimize option is limited (currently, only False, ‘cutensornet’, or a custom path for pairwise contraction is supported, and the maximum intermediate size is ignored). If you need finer control for path optimization, consider replacing cupy.einsum() by cuquantum.contract() instead.

    • Requires cuQuantum Python (v22.03+).

  • If CUPY_ACCELERATORS includes cutensor, einsum will be accelerated by the cuTENSOR backend whenever possible.

Parameters:

  • subscripts (str) – Specifies the subscripts for summation.

  • operands (sequence of arrays) – These are the arrays for the operation.

  • dtype – If provided, forces the calculation to use the data type specified. Default is None.

  • optimize – Valid options include {False, True, ‘greedy’, ‘optimal’}. Controls if intermediate optimization should occur. No optimization will occur if False, and True will default to the ‘greedy’ algorithm. Also accepts an explicit contraction list from numpy.einsum_path(). Defaults to False. If a pair is supplied, the second argument is assumed to be the maximum intermediate size created.

Returns:

The calculation based on the Einstein summation convention.

Return type:

cupy.ndarray

See also

numpy.einsum()