toolbox/torchaudio/models/dfnet3/utils.py

#!/usr/bin/python3
# -*- coding: utf-8 -*-
import torch


def as_complex(x: torch.Tensor):
    if torch.is_complex(x):
        return x
    if x.shape[-1] != 2:
        raise ValueError(f"Last dimension need to be of length 2 (re + im), but got {x.shape}")
    if x.stride(-1) != 1:
        x = x.contiguous()
    return torch.view_as_complex(x)


if __name__ == '__main__':
    pass