In　this　paper,　we　propose　a　deep　learning　based　detection　for　multiple　input　multiple　output　(MIMO)　physical-layer　network　coding　(DeepPNC)　over　two　way　relay　channels　(TWRC).　In　MIMO-PNC,　the　relay　node　receives　the　signals　superimposed　from　the　two　end　nodes.　The　relay　node　aims　to　obtain　the　network-coded　(NC)　form　of　the　two　end　nodes＇　signals.　By　training　suitable　deep　neural　networks　(DNNs)　with　a　limited　set　of　training　samples.　DeepPNC　can　extract　the　NC　symbols　from　the　superimposed　signals　received　while　the　output　of　each　layer　in　DNNs　converges.　Compared　with　the　traditional　detection　algorithms,　DeepPNC　has　higher　mapping　accuracy　and　does　not　require　channel　information.　The　simulation　results　show　that　the　DNNs　based　DeepPNC　can　achieve　significant　gain　over　the　DeepNC　scheme　and　the　other　traditional　schemes,　especially　when　the　channel　matrix　changes　unexpectedly.