Model Footprint

Definition

A measure of the memory footprint, in bytes, required to represent a model, which reflects quantization, parameters, and buffering requirements. The metric summarizes (and can be further broken down into) synaptic weight count, weight precision, trainable neuron parameters, data buffers, etc. Zero weights are included, as they are addressed in the connection sparsity metric.

Implementation Notes

This sums the Torch model’s buffers and parameters. If the model uses explicit memory buffering, the buffering must be implemented as a Torch buffer.