src/transformers/models/deta/modeling_deta.py/dice_loss
def dice_loss(inputs, targets, num_boxes):
    """
    Compute the DICE loss, similar to generalized IOU for masks

    Args:
        inputs: A float tensor of arbitrary shape.
                The predictions for each example.
        targets: A float tensor with the same shape as inputs. Stores the binary
                 classification label for each element in inputs (0 for the negative class and 1 for the positive
                 class).
    """
    inputs = inputs.sigmoid()
    inputs = inputs.flatten(1)
    numerator = 2 * (inputs * targets).sum(1)
    denominator = inputs.sum(-1) + targets.sum(-1)
    loss = 1 - (numerator + 1) / (denominator + 1)
    return loss.sum() / num_boxes