coreai_opt.inspection.bits_per_weight

coreai_opt.inspection.bits_per_weight(model)

Compute the average bits-per-weight of a prepared coreai-opt model.

Walks the module tree once. For each parametrized weight, the dense original tensor is counted at its effective compressed cost (eager mode quantization or palettization). Every other directly-owned parameter (biases, norms) and every buffer (BatchNorm running stats, RoPE caches, etc.) are counted at their full-precision dtype cost, regardless of persistent=.

Parameters:

model (torch.nn.Module) – A full-precision, eager-mode quantized, or palettized prepared model.

Returns:

Overall bpw, per-module breakdown, and the total number of bits and weights used to derive them.

Return type:

BitsPerWeightResult

Raises:

NotImplementedError – If model is a graph-mode prepared model (a torch.fx.GraphModule) or a torch.export.ExportedProgram, or if it contains a weight compression whose storage cost this utility cannot compute.