Inside Quantization Aware Training

Real-world applications of Deep Neural Networks are increasing by the day as we are learning to make use of Artificial Intelligence to accomplish various simple and complex tasks. However, the problem with Deep Neural Networks is that they involve too many parameters due to which they require powerful computation devices and large memory storage. This makes it almost impossible to run on devices with lower computation power such as Android and other low-power edge devices. Optimization techniques such as Quantization can be utilized to solve this problem. With the help of different quantization techniques, we can reduce the precision of our parameters from float to lower precision such as int8, resulting in efficient computation and less amount of storage.