Hi. I was trying to plot the weight distribution of the full precision model and its quantized counterpart and encountered the following issue: although “.named_modules()” has all existing modules in the full precision model, the .named_parameters() does not have all weights matching the existing modules—namely, only the nn.BatchNorm3D have parameters.
An extract of a print from q_model.named_parameters() (q_model is a MobileNet3D, post training quantized and saved with torch.jit.save(torch.jit.script(model)…):

features.0.1.weight
features.0.1.bias
features.1.conv.1.weight
features.1.conv.1.bias
features.1.conv.4.weight
features.1.conv.4.bias
features.2.conv.1.weight
features.2.conv.1.bias
features.2.conv.4.weight
features.2.conv.4.bias
features.2.conv.7.weight
features.2.conv.7.bias
Notice layers 0 (Convolution), 2 (ReLU), 3 (Convolution), 5 (ReLU) and 6 (Convolution) are not present (have no weights or biases?).
The modules were not fused for this model, which otherwise could explain the behaviour. Unless fusion is done under the rug. Does anyone have some insights on this?