keras/src/backend/torch/numpy.py/ceil
def ceil(x):
    x = convert_to_tensor(x)
    ori_dtype = standardize_dtype(x.dtype)

    # TODO: torch.ceil doesn't support bool
    if ori_dtype == "bool":
        x = cast(x, "uint8")
    # TODO: torch.ceil doesn't support float16 with cpu
    elif get_device() == "cpu" and ori_dtype == "float16":
        x = cast(x, config.floatx())

    if ori_dtype == "int64":
        dtype = config.floatx()
    else:
        dtype = dtypes.result_type(ori_dtype, float)
    return cast(torch.ceil(x), dtype=dtype)