What is HRank? An Overview of this Filter Pruning Method
Have you ever wondered how computers are able to recognize objects in images, like faces or animals? The answer lies in convolutional neural networks (CNNs), a type of artificial intelligence technology. CNNs use filters to analyze different aspects of an image, such as edges or colors, and combine them to form a final prediction. However, with so many filters in a single CNN, the computational power required can become overwhelming. That
Movement pruning is a pruning method used for simplifying the structure of deep neural networks by removing some of the connections between neurons. This technique is more adaptive to fine-tuning of pre-trained models and is a first-order weight pruning method. Unlike magnitude pruning, movement pruning methods derive importance from first-order information. Instead of selecting weights that are far from zero, movement pruning retains connections that are moving away from zero during the trainin
Spectral-Normalized Identity Priors, also known as SNIP, is a pruning technique that helps improve the efficiency of artificial intelligence models. This method penalizes an entire residual module in a Transformer model towards an identity mapping, which means the model adjusts the function to keep it as close to the original as possible. SNIP can be applied to structured modules like an attention head, an entire attention block, or a feed-forward subnetwork.
What is SNIP?
Spectral-Normalized