Abstract: This disclosure discloses a method for training a neural network and a related device. The method includes: inputting a first sample subset into a first neural network, to generate first feature information and a first prediction result of a first query sample; generating a second prediction result of the first query sample based on second feature information corresponding to M groups of support samples included in a sample set, first labeling results corresponding to the M groups of support samples, and the first feature information, and training the first neural network. A first loss function indicates a similarity between the first prediction result and a second labeling result, and a second loss function indicates a similarity between the first prediction result and the second prediction result, or indicates a similarity between the second prediction result and the second labeling result.

Abstract: An illuminating apparatus is provided. The illuminating apparatus comprises a lower plate, an upper plate opposing to the lower plate to form a containing space therebetween, a supporting structure mounted within the containing space and connected with the lower plate and the upper plate, and a buffer material connected with at least one of the lower plate, the upper plate and the supporting structure.