Source code for diffsptk.modules.mpir2c

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

from ..misc.utils import check_size
from ..misc.utils import clog




class MinimumPhaseImpulseResponseToCepstrum(nn.Module):
    """See `this page <https://sp-nitech.github.io/sptk/latest/main/mpir2c.html>`_
    for details.

    Parameters
    ----------
    cep_order : int >= 0
        Order of cepstrum, :math:`M`.

    ir_length : int >= 1
        Length of impulse response, :math:`N`.

    n_fft : int >> N
        Number of FFT bins. Accurate conversion requires the large value.

    """

    def __init__(self, cep_order, ir_length, n_fft=512):
        super().__init__()

        assert 0 <= cep_order
        assert 1 <= ir_length
        assert max(cep_order + 1, ir_length) <= n_fft

        self.cep_order = cep_order
        self.ir_length = ir_length
        self.n_fft = n_fft



    def forward(self, h):
        """Convert minimum phase impulse response to cepstrum.

        Parameters
        ----------
        h : Tensor [shape=(..., N)]
            Truncated minimum phase impulse response.

        Returns
        -------
        out : Tensor [shape=(..., M+1)]
            Cepstral coefficients.

        Examples
        --------
        >>> h = diffsptk.ramp(4, 0, -1)
        >>> mpir2c = diffsptk.MinimumPhaseImpulseResponseToCepstrum(3, 5)
        >>> c = mpir2c(h)
        >>> c
        tensor([1.3863, 0.7500, 0.2188, 0.0156])

        """
        check_size(h.size(-1), self.ir_length, "impulse response length")
        return self._forward(h, self.cep_order, self.n_fft)


    @staticmethod
    def _forward(h, cep_order, n_fft):
        H = torch.fft.fft(h, n=n_fft)
        c = torch.fft.ifft(clog(H))[..., : cep_order + 1].real
        c[..., 1:] *= 2
        return c

    _func = _forward