4e97213b48e152344b7429c7d1067e7525bfa4b9,examples/source_separation/utils/metrics.py,,sdr,#,7

Before Change

    reference = scale * reference
    error = estimate - reference

    reference_pow = reference.pow(2).mean(axis=2)
    error_pow = error.pow(2).mean(axis=2)

    return 10 * torch.log10(reference_pow) - 10 * torch.log10(error_pow)

After Change

    reference = scale * reference
    error = estimate - reference

    reference_pow = reference.pow(2)
    error_pow = error.pow(2)

    if mask is None:
        reference_pow = reference_pow.mean(axis=2)
        error_pow = error_pow.mean(axis=2)
    else:
        denom = mask.sum(axis=2)
        reference_pow = (mask * reference_pow).sum(axis=2) / denom
        error_pow = (mask * error_pow).sum(axis=2) / denom

    return 10 * torch.log10(reference_pow) - 10 * torch.log10(error_pow)

Instances