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| # File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details. | |
| # Author: adefossez, 2020 | |
| # flake8: noqa | |
| """ | |
| .. image:: ../logo.png | |
| Julius contains different Digital Signal Processing algorithms implemented | |
| with PyTorch, so that they are differentiable and available on CUDA. | |
| Note that all the modules implemented here can be used with TorchScript. | |
| For now, I have implemented: | |
| - `julius.resample`: fast sinc resampling. | |
| - `julius.fftconv`: FFT based convolutions. | |
| - `julius.lowpass`: FIR low pass filter banks. | |
| - `julius.filters`: FIR high pass and band pass filters. | |
| - `julius.bands`: Decomposition of a waveform signal over mel-scale frequency bands. | |
| Along that, you might found useful utilities in: | |
| - `julius.core`: DSP related functions. | |
| - `julius.utils`: Generic utilities. | |
| Please checkout [the Github repository](https://github.com/adefossez/julius) for other informations. | |
| For a verification of the speed and correctness of Julius, check the benchmark module `bench`. | |
| This package is named in this honor of | |
| [Julius O. Smith](https://ccrma.stanford.edu/~jos/), | |
| whose books and website were a gold mine of information for me to learn about DSP. Go checkout his website if you want | |
| to learn more about DSP. | |
| """ | |
| from .bands import SplitBands, split_bands | |
| from .fftconv import fft_conv1d, FFTConv1d | |
| from .filters import bandpass_filter, BandPassFilter | |
| from .filters import highpass_filter, highpass_filters, HighPassFilter, HighPassFilters | |
| from .lowpass import lowpass_filter, lowpass_filters, LowPassFilters, LowPassFilter | |
| from .resample import resample_frac, ResampleFrac | |