Uses manually created .idx files to store data in a format that their search components can index.
In the MNIST context, the IDX format proves highly efficient for read-heavy workloads. Because the file is memory-mappable, operating systems can load specific portions of the dataset into RAM without parsing the entire file structure, providing low-latency access during neural network training. The absence of compression allows for immediate byte-offset calculations, enabling random access to any specific image or label without decompressing a container. idx file type