Source code for diffsptk.modules.rmse

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# Copyright 2022 SPTK Working Group                                        #
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import torch
from torch import nn




class RootMeanSquareError(nn.Module):
    """See `this page <https://sp-nitech.github.io/sptk/latest/main/rmse.html>`_
    for details.

    Parameters
    ----------
    reduction : ['none', 'mean', 'sum']
        Reduction type.

    eps : float >= 0
        A small value to prevent NaN.

    """

    def __init__(self, reduction="mean", eps=1e-8):
        super().__init__()

        assert reduction in ("none", "mean", "sum")
        assert 0 <= eps

        self.reduction = reduction
        self.eps = eps



    def forward(self, x, y):
        """Calculate RMSE.

        Parameters
        ----------
        x : Tensor [shape=(...,)]
            Input.

        y : Tensor [shape=(...,)]
            Target.

        Returns
        -------
        out : Tensor [shape=(...,) or scalar]
            RMSE.

        Examples
        --------
        >>> x = diffsptk.nrand(4)
        >>> x
        tensor([-0.5945, -0.2401,  0.8633, -0.6464,  0.4515])
        >>> y = diffsptk.nrand(4)
        >>> y
        tensor([-0.4025,  0.9367,  1.1299,  3.1986, -0.2832])
        >>> rmse = diffsptk.RootMeanSquaredError()
        >>> e = rmse(x, y)
        >>> e
        tensor(1.8340)

        """
        return self._forward(x, y, self.reduction, self.eps)


    @staticmethod
    def _forward(x, y, reduction, eps):
        error = torch.sqrt(torch.square(x - y).mean(-1) + eps)
        if reduction == "none":
            pass
        elif reduction == "sum":
            error = error.sum()
        elif reduction == "mean":
            error = error.mean()
        else:
            raise ValueError(f"reduction {reduction} is not supported.")
        return error

    _func = _forward