1- During model load, are the module layers packed again to a format like in torch::nn::Linear and torch::nn::Conv1d … etc? how can I access them?

what is torch::nn::Linear? are you talking about the pytorch c++ API? the weights are packed in linear modules, you can use https://github.com/pytorch/pytorch/blob/master/torch/nn/quantized/modules/linear.py#L34 6 to get the unpacked weights.

Are the pointers printed in the dump (like the line marked with “(Here->)” ) for Python objects and methods or they are C++ objects and methods? are they cast-able to the formats in torch::nn:* ?

These are TorchScript objects I think. I’m not sure about the relationship between the pytorch c++ API and TorchScript, cc @Michael_Suo could you comment on this?

What is the recommended procedure to structure the model again in terms of the number of layers , the attributes\configuration of each layer and the corresponding trained weights from the jitted\torchscript format ?

Not sure I understand the question, could you be more concrete?