Intelligent reflecting surface (IRS) is an effective technology to improve the energy and spectral efficiency of wireless powered communication network (WPCN). Under user cooperation, we propose an IRS-assisted WPCN system where the wireless devices (WDs) collect wireless energy in the downlink (DL) and then share data. The adjacent single-antenna WDs cooperate to form a virtual antenna array so that their information can be simultaneously transmitted to the multi-antenna common hybrid access point (HAP) through the uplink (UL) using multiple-input multiple-output (MIMO) technology. By jointly optimizing the passive beamforming at the IRS, the active beamforming in the DL and the UL, the energy consumed by data sharing, and the time allocation of each phase, we formulate an UL throughput maximization problem. However, this optimization problem is non-convex since the optimization variables are highly coupled. In this study, we apply the alternating optimization (AO) technology to decouple the optimization variables and propose an efficient algorithm to avoid the difficulty of directly solving the problem. Numerical results indicate that the joint optimization method significantly improves the UL throughput performance in multi-user WPCN compared with various baseline methods.