import torch


def mse(image_pred, image_gt, valid_mask=None, reduction='mean'):
    value = (image_pred-image_gt)**2
    if valid_mask is not None:
        value = value[valid_mask]
    if reduction == 'mean':
        return torch.mean(value)
    return value


@torch.no_grad()
def psnr(image_pred, image_gt, valid_mask=None, reduction='mean'):
    return -10*torch.log10(mse(image_pred, image_gt, valid_mask, reduction))