deep learning - Reload weights into fc layer after converting to csr_matrix -


i trying store weights in fc layers in compressed sparse row format. when retrieve weights , convert them csr matrix format, size in memory reduces drastically when load caffe model size remains same. i'm doing:

temp2 = net.params['ip1'][0].data.shape sparse_csr1 = sparse.scr_matrix(temp2, shape) net.params['ip1'][0].data[...] = sparse_csr1 net.save('compressed.caffemodel')

any suggestions appreciated.

looks these repos both inner-product , conv layers:


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