With the help of the deep learning model applied in the inverse design of the metagrating beam splitter, good uniformity and high diffraction efficiency can be obtained. The structure design, diffraction efficiency and uniformity of the metagrating beam splitter was studied by using the global topology optimization neural networks. Under the working wavelength of 900 nm, the beam splitter with splitting angle of 120° and 150° designed based on the global topology optimization networks had high diffraction efficiencies of 95% for 120° and 85% for 150°.