  We introduce a high-dimensional quantum encoding based on coherent
mode-dependent single-photon subtraction from multimode squeezed states. This
encoding can be seen as a generalization to the case of non-zero squeezing of
the standard single-photon multi-rail encoding. The advantage is that the
presence of squeezing enables the use of common tools in continuous-variable
quantum processing, which in turn allows to show that arbitrary $d$-level
quantum states can be generated and detected via simply tuning the classical
fields that gates the photon-subtraction scheme. Therefore, the scheme is
suitable for mapping arbitrary classical data in quantum mechanical form.
Regardless the dimension of the data set alphabet, the mapping is conditioned
on the subtraction of a single photon only, making it nearly unconditional. We
prove that this encoding can be used to calculate vector distances, a pivotal
primitive in various quantum machine learning algorithms.
