Deep Learning, Artificial Intelligence, Mathematics, Convolutional Network, Gpt.
Performer. 2. Memory Footprint ConvNets: Due to weight sharing, the memory required is: Where D_in​ and D_out​ are the input and output depths. ViTs: The memory cost is: Again, with efficient variants and optimizations, the memory footprints align closely for large-scale classification tasks. As we