layer attention
时间: 2023-09-21 07:05:06 浏览: 29
Layer attention is a type of attention mechanism used in neural networks, particularly in the field of natural language processing (NLP). It involves computing attention weights between different layers of a neural network to determine how much importance should be given to each layer during the computation of the final output.
In NLP tasks, layer attention can be used in models such as the transformer architecture to capture dependencies between different parts of the input sequence. This allows the model to selectively focus on relevant information and ignore irrelevant information during the encoding and decoding stages.
Overall, layer attention helps to improve the performance of NLP models by allowing them to better understand the relationships between different parts of the input sequence.