We present Chook, an open-source Python-based tool to generate discrete optimization problems of tunable complexity with a priori known solutions. Chook provides a cross-platform unified environment for solution planting using a number of techniques, such as tile planting, Wishart planting, equation planting, and deceptive cluster loop planting. Chook also incorporates planted solutions for higher-order (beyond quadratic) binary optimization problems. The support for various planting schemes and the tunable hardness allows the user to generate problems with a wide range of complexity on different graph topologies ranging from hypercubic lattices to fully-connected graphs.
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