
layout: blog_detail
title: 'The torch.fft module: Accelerated Fast Fourier Transforms with Autograd in PyTorch'
author: Mike Ruberry, Peter Bell, and Joe Spisak 

The Fast Fourier Transform (FFT) calculates the Discrete Fourier Transform in O(n log n) time. It is foundational to a wide variety of numerical algorithms and signal processing techniques since it makes working in signals’ “frequency domains” as tractable as working in their spatial or temporal domains.
As part of PyTorch’s goal to support hardware-accelerated deep learning and scientific computing, we have invested in improving our FFT support, and with PyTorch 1.8, we are releasing the torch.fft module. This module implements the same functions as NumPy’s np.fft module, but with support for accelerators, like GPUs, and autograd. 
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