scale_methods = ["nearest-exact", "bilinear", "bicubic", "bislerp", "area", "lanczos"]


def get_latent_size(LATENT, ORIGINAL_VALUES=False) -> tuple[int, int]:
    lc = LATENT.copy()
    size = lc["samples"].shape[3], lc["samples"].shape[2]
    if ORIGINAL_VALUES == False:
        size = size[0] * 8, size[1] * 8
    return size


def get_image_size(IMAGE) -> tuple[int, int]:
    samples = IMAGE.movedim(-1, 1)
    size = samples.shape[3], samples.shape[2]
    # size = size.movedim(1, -1)
    return size


def get_conditioning_size(CONDITIONING) -> tuple[dict[int, int], dict[int, int]]:
    size = CONDITIONING["area"]
    width = size[1]
    height = size[0]
    x_offs = size[3]
    y_offs = size[2]
    return ({"width": width, "height": height}, {"x_offset": x_offs, "y_offset":y_offs})