cupyx.scipy.signal.fftconvolve(in1, in2, mode='full', axes=None)[source]#

Convolve two N-dimensional arrays using FFT.

Convolve in1 and in2 using the fast Fourier transform method, with the output size determined by the mode argument.

This is generally much faster than the 'direct' method of convolve for large arrays, but can be slower when only a few output values are needed, and can only output float arrays (int or object array inputs will be cast to float).

  • in1 (cupy.ndarray) – First input.

  • in2 (cupy.ndarray) – Second input. Should have the same number of dimensions as in1.

  • mode (str) –

    Indicates the size of the output:

    • 'full': output is the full discrete linear cross-correlation (default)

    • 'valid': output consists only of those elements that do not rely on the zero-padding. Either in1 or in2 must be at least as large as the other in every dimension.

    • 'same': output is the same size as in1, centered with respect to the ‘full’ output

  • axes (scalar or tuple of scalar or None) – Axes over which to compute the convolution. The default is over all axes.


the result of convolution

Return type:


See also


See also