2 """Extracts trainable parameters from Caffe models and stores them in numpy arrays. 4 python caffe_data_extractor -m path_to_caffe_model_file -n path_to_caffe_netlist 6 Saves each variable to a {variable_name}.npy binary file. 8 Tested with Caffe 1.0 on Python 2.7 16 if __name__ ==
"__main__":
18 parser = argparse.ArgumentParser(
'Extract Caffe net parameters')
19 parser.add_argument(
'-m', dest=
'modelFile', type=str, required=
True, help=
'Path to Caffe model file')
20 parser.add_argument(
'-n', dest=
'netFile', type=str, required=
True, help=
'Path to Caffe netlist')
21 args = parser.parse_args()
24 net = caffe.Net(args.netFile, 1, weights=args.modelFile)
27 for name, blobs
in net.params.iteritems():
28 print(
'Name: {0}, Blobs: {1}'.format(name, len(blobs)))
29 for i
in range(len(blobs)):
40 if os.path.sep
in varname:
41 varname = varname.replace(os.path.sep,
'_')
42 print(
"Renaming variable {0} to {1}".format(outname, varname))
43 print(
"Saving variable {0} with shape {1} ...".format(varname, blobs[i].data.shape))
45 np.save(varname, blobs[i].data)
SimpleTensor< T > range(SimpleTensor< T > &dst, float start, const size_t num_of_elements, float step)