Function compute_lpips

utils/metrics.py:28–33

(
    ground_truth: Float[Tensor, "batch channel height width"],
    predicted: Float[Tensor, "batch channel height width"],
)

@torch.no_grad()
def compute_lpips(
    ground_truth: Float[Tensor, "batch channel height width"],
    predicted: Float[Tensor, "batch channel height width"],
) -> Float[Tensor, " batch"]:
    value = get_lpips(predicted.device).forward(ground_truth, predicted, normalize=True)
    return value[:, 0, 0, 0]


@torch.no_grad()