% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/lap_solve.R
\name{.assignment_lazy}
\alias{.assignment_lazy}
\title{Solve a lazy_cost_spec (memory_mode = "lazy" backend for assignment())}
\usage{
.assignment_lazy(cost, maximize = FALSE, method = "auto", auction_eps = NULL)
}
\description{
Mirrors assignment()'s contract (same result shape) but computes costs
on demand from the underlying feature data instead of a materialized
matrix. Only "jv" and "auction" are supported -- every other method is
fundamentally dense (repeated full-matrix scans, or an algorithm not yet
templated for a lazy cost source) and gets a clear error here rather than
a silent dense fallback that would defeat the point of \code{memory_mode = "lazy"}.
}
\keyword{internal}
