Source code for compressai.losses.rate_distortion

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import math

import torch
import torch.nn as nn

from pytorch_msssim import ms_ssim

from compressai.registry import register_criterion




@register_criterion("RateDistortionLoss")
class RateDistortionLoss(nn.Module):
    """Custom rate distortion loss with a Lagrangian parameter."""

    def __init__(self, lmbda=0.01, metric="mse", return_type="all"):
        super().__init__()
        if metric == "mse":
            self.metric = nn.MSELoss()
        elif metric == "ms-ssim":
            self.metric = ms_ssim
        else:
            raise NotImplementedError(f"{metric} is not implemented!")
        self.lmbda = lmbda
        self.return_type = return_type



    def forward(self, output, target):
        N, _, H, W = target.size()
        out = {}
        num_pixels = N * H * W

        out["bpp_loss"] = sum(
            (torch.log(likelihoods).sum() / (-math.log(2) * num_pixels))
            for likelihoods in output["likelihoods"].values()
        )
        if self.metric == ms_ssim:
            out["ms_ssim_loss"] = self.metric(output["x_hat"], target, data_range=1)
            distortion = 1 - out["ms_ssim_loss"]
        else:
            out["mse_loss"] = self.metric(output["x_hat"], target)
            distortion = 255**2 * out["mse_loss"]

        out["loss"] = self.lmbda * distortion + out["bpp_loss"]
        if self.return_type == "all":
            return out
        else:
            return out[self.return_type]